ROADMAP FOR FLEXIBILITY SERVICES TO
2030
A report to the Committee on Climate Change
May 2017
ROADMAP FOR FLEXIBILITY SERVICES TO 2030
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Contact details
Name
Email
Telephone
Anser Shakoor
anser.shakoor@poyry.com
+44 (0)1865 812 267
Gareth Davies
gareth.davi[email protected]
+44 (0)1865 812 204
Goran Strbac
goran.strbac@imperial.ac.uk
+44 (0)7973 658 976
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Authors
Pöyry Management Consulting
Imperial College London
Anser A Shakoor and Gareth Davies
Goran Strbac, Danny Pudjianto,
Fei Teng, Dimitrios Papadaskalopoulos
and Marko Aunedi
Pöyry Management Consulting
Pöyry is an international consulting and engineering company. We serve clients globally across
the energy and industrial sectors and provide local services in our core markets. We deliver
management consulting and engineering services, underpinned by strong project implementation
capability and expertise. Our focus sectors are power generation, transmission & distribution,
forest industry, chemicals & biorefining, mining & metals, transportation and water. Pöyry has an
extensive local office network employing about 5,000 experts. Pöyry’s net sales in 2016 were
EUR 530 million and the company’s shares are quoted on Nasdaq Helsinki (Pöyry PLC: POY1V).
Pöyry Management Consulting provides leading-edge consulting and advisory services covering
the whole value chain in energy, forest and other process industries. Our energy practice is the
leading provider of strategic, commercial, regulatory and policy advice to Europe's energy
markets. Our energy team of 200 specialists offer unparalleled expertise in the rapidly changing
energy sector.
Imperial College London
The Imperial College team conducted dedicated modelling of the UK’s electricity system for this
report. This team has led the development of novel advanced analysis approaches and
methodologies that have been extensively used to inform industry, governments and regulatory
bodies about the role and value of new technologies and systems in supporting cost effective
evolution to smart low carbon future. The authors would like to express their gratitude to the
Engineering and Physical Sciences Research Council for the support obtained through the Whole
Systems Energy Modelling Consortium and Energy Storage for Low Carbon Grids programmes.
This support enabled the fundamental research that led to the development of modelling
frameworks used in this study.
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TABLE OF CONTENTS
EXECUTIVE SUMMARY 1
1. INTRODUCTION 7
1.1 Overall approach 8
1.2 System flexibility 9
1.3 Flexibility providing technologies 9
1.4 Flexibility services and technologies 10
1.5 Structure of this report 12
1.6 Sources 13
2. MODELLING THE NEED FOR FLEXIBILITY 15
2.1 Modelling assessment of future flexibility requirements 15
2.2 Future flexibility requirements 16
2.3 Impact of alternative generation mixes on flexibility requirements 21
2.4 Potential benefits of alternative system flexibility options 22
2.5 Uncertainties related to the portfolio of flexibility services 24
2.6 Main requirements of the future electricity systems 25
3. ENSURING EFFICIENT FLEXIBILITY INVESTMENT DECISIONS 27
3.1 Availability and accessibility of revenue streams 28
3.2 Efficiency of pricing signals 30
3.3 Improved understanding of long-term requirements 38
4. DEVELOPING CAPABILITY TO MANAGE GREATER COMPLEXITY IN
THE SYSTEM 41
4.1 System operators will need to have clear roles and responsibilities
besides developing capability to manage greater complexity of the
future smart electricity system 41
4.2 Development of energy and smart-enabling infrastructure needs to be
well-coordinated 47
5. ENSURING INNOVATION SUPPORT 49
5.1 Continued support is required to ensure learning in developing
innovative flexibility solutions 49
5.2 Action to ensure innovation 53
6. ENSURING EFFECTIVE CONSUMER PARTICIPATION 55
6.1 Consumers need to be better informed about the benefits that a smart
system offers them 55
6.2 Consumers protection will need to be ensured to build trust for DSR
participation 57
7. SUMMARY OF THE FLEXIBILITY ROADMAP AND INDICATOR
FRAMEWORK 59
7.1 Flexibility roadmap actions 59
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7.2 Progress monitoring framework 61
ANNEX A SYSTEM EVOLUTION PATHWAYS TO MEET THE CARBON
INTENSITY TARGETS 65
A.1 Carbon targets 65
A.2 Modelled scenarios 66
A.3 Modelling inputs and assumptions 67
A.4 Overview of the methodology for whole-system analysis of electricity
systems 74
ANNEX B FLEXIBILITY SERVICES AND TECHNOLOGIES 77
B.1 Flexibility services procured under current arrangements 77
B.2 Mapping flexibility technologies to existing flexibility services 78
ANNEX C FIRST STAKEHOLDER WORKSHOP 81
C.1 Introduction 81
C.2 Workshop participants 81
ANNEX D SECOND STAKEHOLDER WORKSHOP 83
D.1 Introduction 83
D.2 Workshop participants 83
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EXECUTIVE SUMMARY
The GB electricity system is expected to undergo a fundamental transformation over the
next few decades in response to tightening energy sector decarbonisation targets. In its
advice to Government on future carbon budgets, the Committee on Climate Change
(CCC) has emphasised the importance of decarbonising the power sector and
recommended that the aim should be to reduce the carbon intensity of power generation
from current levels of around 350 gCO
2
/kWh to around 100 gCO
2
/kWh in 2030.
Delivering on such a target will require investment in a portfolio of low-carbon
technologies and an increase in the provision of flexibility services to enable the cost
effective integration of the new system. Growth in required flexibility will facilitate
development and deployment of innovative technologies and emergence of new business
models and service offerings.
While there are several possible configurations of demand and supply, in any future low-
carbon electricity system we should anticipate:
a much higher penetration of low-carbon generation with a significant increase in
variable renewable sources including wind and solar and demand growth driven by
electrification of segments of heat and transport sectors;
growth in the capacity of distribution connected flexibility resource;
an increased ‘flexibility’ requirement to ensure the system can efficiently maintain
secure and stable operation in a lower carbon system;
opportunities to deploy energy storage facilities at both transmission and distribution
levels; and
an expansion in the provision and use of demand-side response across all sectors of
the economy.
System flexibility, by which we mean the ability to adjust generation or consumption in the
presence of network constraints to maintain a secure system operation for reliable service
to consumers, will be the key enabler of this transformation to a cost-effective low-carbon
electricity system. There are several flexibility resource options available including highly
flexible thermal generation, energy storage, demand side response and cross-border
interconnection to other systems.
Scenario analysis undertaken by Imperial College as part of this study demonstrates that
the system wide benefits of integrating new sources of flexibility relative to the use of
conventional thermal generation based sources of flexibility, as shown in Figure 1, are
potentially very significant between £3.2bn and £4.7bn per year in a system meeting a
carbon emissions target of 100gCO
2
/kWh in 2030.
Key categories of system cost savings achievable by accessing the new sources of
flexibility include:
reduced investment in low-carbon generation (between 25% and 60% of the total
savings depending on the scenario), as the available renewable resource and nuclear
generation can be utilised more efficiently enabling the system to reach the carbon
target with less low carbon generation capacity;
reduced system operation cost (between 25% and 40% of the total savings), as
various reserve services are provided by new, cheaper, flexibility sources rather than
by conventional generation; and
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reduced requirement for distribution network reinforcement (between 10% and 20% of
the total savings) and backup capacity.
Figure 1 Potential benefits of efficient integration of new system flexibility
resource
Source: Imperial’s modelling analysis of the CCC scenarios
However, due to uncertainties around future cost and technical performance of different
options, the relative contribution of each flexibility technology may vary greatly, as shown
in Figure 2, and it is therefore important that the future market and regulatory environment
does not distort decisions but delivers clear signals on which participants can base their
investment choices.
Figure 2 Indication of uncertainty in the deployment of flexibility resource
based on modelling analysis
Source: Imperial’s modelling analysis of the CCC scenarios
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From the analysis and stakeholder engagement undertaken as part of this study, we have
identified four key requirements of a future GB electricity system.
Investment decisions should be made on the basis of the full system value
offered by providers this means that the market design must effectively price and
reward energy, capacity and flexibility.
Appropriate systems and interfaces should be in place to manage greater
complexity in system operation and control this implies a shift in the resource of
system control from the transmission to the distribution level and a capability of the
system to deal with more interactions between distribution and transmission
networks, and to promote and utilise more active demand management.
Ongoing support for innovation in technology, services and operating models
it will be important that, as the institutional and market framework evolves, the drive
for innovation across the value chain is not dampened.
Enhanced framework to achieve greater consumer participation in addition to
establishing the technical infrastructure for demand-side response, legal and
regulatory frameworks around consumer protection and data protection will be
necessary to achieve widespread consumer acceptance.
Flexibility roadmap
To deliver these requirements, action will need to be taken to enhance the market and
regulatory framework and in the course of this study we have developed a roadmap to
facilitate low-carbon flexibility. The roadmap is intended to create a technology neutral
investment environment supported by an innovation programme that facilitates uptake of
the most efficient and cost effective flexibility technologies.
The roadmap, which was informed by a series of stakeholder workshops, defines specific
enabling actions aimed at improving access for flexibility. For each action, we describe
(a) the primary responsible party; (b) the timeframe over which action is required; and (c)
the priority of the action.
Table 1 presents the recommended high priority actions included in the flexibility
roadmap. Lower priority actions, together with a detailed description of the rationale for
the proposed actions and a high-level overview of the relevant ongoing activities is
provided in the main report (Chapter 3 to Chapter 6).
Table 1 High priority actions of the flexibility roadmap
Action
Responsible
Time
frame
Review characteristics of current procurement processes (e.g.
threshold capacity level to participate, contract terms / obligations)
and the procurement route (e.g. open market, auctioning or
competitive tendering) that enable more efficient procurement of
services without unduly restricting the provision of multiple services
by flexibility providers.
Ofgem in
conjunction
with SO, TOs
and DSOs
By 2020
Assess the materiality of distortions to investment decisions in the
current network charging methodology (e.g. lack of locational
charging, double-charging for stored electricity), and reform charging
methodology where appropriate.
SO, DSOs,
and Ofgem
By 2020
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Action
Responsible
Time
frame
Assess the materiality of distortions to investment decisions in the
absence of non-network system integration charging (i.e. back up
capacity and ancillary services) and implement charging where
appropriate.
SO, DSOs,
and Ofgem
By 2020
Publish annual projections (in each year) of longer-term future
procurement requirements across all flexibility services including
indication of the level of uncertainty involved and where possible
location specific requirements, to provide greater visibility over future
demand of flexibility services.
SO and
DSOs
2020
onwards
Publish a strategy for developing the longer-term roles and
responsibilities of system operators (including transitional
arrangements) that incentivises system operators to access all
flexibility resource by making investments and operational decisions
that maximise total system benefits.
Ofgem in
conjunction
with industry
2018
Periodical review of existing system planning and operational
standards for networks and generation, assessing whether they
provide level-playing field to all technologies including active network
management and non-build solutions (e.g. storage and DSR), and
revise these standards as appropriate.
Industry
codes
governance
and Ofgem
Initial
review
by 2019
A number of initiatives led variously by Government, Ofgem, National Grid and wider
industry, are already underway which support our proposed actions. Some of the key
initiatives include:
BEIS and Ofgem’s work on flexibility in 2016 (i.e. BEIS and Ofgem’s position papers
on flexibility) which led to their combined call for evidence for a smart, flexible energy
system. It is a wide scope activity intended to collate stakeholder’s views and
evidence on system flexibility aspects such as; policy and regulatory barriers, price
signals and consumers participation. It also presents alternative future models for
system and network operator roles and responsibilities for stakeholder feedback.
Power Responsive is a stakeholder-led programme, facilitated by National Grid, to
stimulate increased participation in the different forms of flexible technology such as
DSR and storage. National Grid is also working on rationalising the portfolio of the
flexibility services it procures.
The network companies have initiated a case to carry out a thorough review of
Engineering Recommendation (ER P2) for the planning of distribution networks.
Ofgem has supported this initiative as well as the public engagement process
assessing the P2 review on the design of the electricity distribution networks and
changes to SQSS (GRS 022) in relation to the integration of new technologies in the
networks.
The combination of the ongoing work and the proposed roadmap actions will create a
more robust and supportive environment for efficiently meeting the future flexibility
requirements in the system.
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Progress monitoring framework
In order to monitor progress in development of low-carbon flexibility, we have developed
indicators that can be used by the CCC. The indicators and monitoring framework serve
the following two main purposes:
monitor whether the proposed actions are being implemented in line with the
roadmap; and
to assess the impact of actions i.e. actual progress in the market around
assimilating ‘smart’ flexible solutions.
Performance against specific actions
In relation to specific actions recommended in the roadmap we have, where appropriate,
defined a time frame for completion of the action. Where actions are ongoing, this is
noted separately.
Any delay in the completion of actions will need investigation to understand the reasons
for such delay and its knock-on effect (if any) on other actions and wider achievement of
decarbonisation objectives.
For the ongoing actions, a periodical monitoring will be required to check that progress is
in line with the requirements and objectives set out in the roadmap.
Performance of the market in general
Performance in this area will be linked to the assessment of measureable impacts of
actions on delivering enhanced and efficient volumes of flexibility in the GB system.
However, the challenge with developing any quantitative metrics is that there is no precise
target for particular forms of flexibility provision. This is driven by the uncertainties around
costs and technical development of different types of flexibility sources as well as the
long-term evolution of supply mix and market and regulatory frameworks.
In the above context and considering the practicality of collecting and processing
information to determine an indicator, we propose that a broad measure of the
deployment of additional capacity of flexible technologies should be used as the key
indicator to measure the impact of roadmap action.
Based on the modelling analysis undertaken as part of this study for alternative future
generation scenarios, we have assessed the required range of additional capacity of
different flexible technologies to efficiently meet 2030 carbon intensity targets. Figure 3
shows these additional capacity requirements based on the modelling analysis
undertaken as part of this study. The low and high levels for a given flexibility technology
are based on its range of penetration across the four main future scenarios investigated in
this study (see Section A.2 for scenario details) whereas the central level shows the mid-
point of the range.
The central levels of additional capacity of flexible technologies are to be used to track
progress on deployment of technologies in a given period. It is expected that a trade-off
between various technologies will also take place. For example, lower deployment of
additional storage may be compensated by higher uptake of another technology thus
meeting the system’s overall flexibility requirements.
However, a consistent low deployment of one or more technologies across several years
could be seen as a flag for further investigation e.g. to identify if there is a specific
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barrier that is hindering the deployment of the technology or affecting its competitiveness
against other flexibility technologies.
Figure 3 Potential levels of flexibility providing capacity (GW)
Source: Imperial’s modelling analysis
Considering the value and scalability of DSR we also propose that the following two
indicators should be used to assess the progress for this particular flexibility resource:
growth in number and size (i.e. total contracted volume, MW) of aggregators
providing DSR-based flexibility in the market; and
growth in the share of smart appliances as a percentage of total appliances sold each
year.
Low Central High Low Central High Low Central High
New flexible generation 1 3 5 2 6 10 3 9 15
Storage 0.8 2.9 5 3.2 11.6 20 5.6 20.3 35
DSR 2.1 6.3 10.5 2.76 8.28 13.8 3.42 10.26 17.1
Interconnection 3.4 3.4 3.4 4.45 5.825 7.2 5.5 8.25 11
By 2030
Flexible technology
By 2020
By 2025
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1. INTRODUCTION
The GB electricity system is expected to undergo a fundamental transformation over the
next few decades in response to tightening energy sector decarbonisation targets,
development and deployment of innovative technologies and emergence of new business
models and service offerings. While there are several possible configurations of future
demand and supply, we should anticipate:
a much higher penetration of low-carbon generation with a significant increase in
variable renewable sources including wind and solar;
an increased ‘flexibility’ requirement to ensure the system can efficiently maintain
secure and stable operation;
growth in the capacity of distribution connected flexibility resource;
opportunities to deploy energy storage facilities at both transmission and distribution
levels; and
an expansion in the provision and use of demand-side response across all sectors of
the economy.
This paradigm shift in the GB electricity system is depicted in Figure 4 below.
Figure 4 Potential evolution of power system in GB
Source: Imperial College
System flexibility will be the key enabler in delivering this transformation. It is important
not only in the context of maintaining secure and efficient system operation but also for
maximising the utilisation of the assets thus reducing the need for investment in new
generation and network capacity. However, the volume of increased flexibility in the
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system is uncertain, and how and through which technologies these additional flexibility
requirements will be served is also not clear.
The Committee on Climate Change, therefore, is looking to develop a roadmap for
flexibility services out to 2030. The Committee have engaged Pöyry and Imperial College
to develop the roadmap for the provision of flexibility services that would facilitate meeting
the CO
2
emission reduction target of below 100gCO
2
/kWh for the UK electricity sector by
2030.
1.1 Overall approach
In order to develop the roadmap we have applied the approach shown in Figure 5. Our
approach includes research, review and analysis of the flexibility landscape (required
flexibility services, flexibility providing technologies and relevant procurement processes),
primarily focused on Great Britain and supplemented by knowledge and understanding of
the same issues in other systems. Furthermore, a detailed quantitative assessment of the
CCC scenarios
1
was also carried out by Imperial College to evaluate future flexibility
requirements under alternative generation and demand projections of the GB electricity
system.
Figure 5 Roadmap development approach
1
Power sector scenarios for the fifth carbon budget, The Committee on Climate Change (UK),
October 2015
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In addition to Pöyry and Imperial’s research and analysis, the project also benefitted from
stakeholder input through two workshops:
Stakeholder Workshop 1 was focused on identifying the barriers to deployment of
different types of flexibility options and developing ideas on actions to address these
barriers.
Stakeholder Workshop 2 tested the draft flexibility roadmap with stakeholders by
presenting the future flexibility requirements and discussing the actions for facilitating
provision of enhanced flexibility out to 2030.
The list of participating organisations and their representatives in the first and second
workshops are provided in Annex C and Annex D respectively.
The project work and findings were overseen by a Steering Committee comprising
members from the Committee on Climate Change, BEIS and Ofgem. The project Steering
Committee provided highly valuable feedback and guidance during three meetings at key
milestones during the project.
While stakeholder and Steering Committee inputs have greatly contributed to the
development of the roadmap, we (Pöyry and Imperial) have maintained our independent
analysis in defining the actions necessary to enable an efficient provision of flexibility in
the future GB electricity system.
We acknowledge that a number of enabling activities are already being progressed by
Government, Ofgem, National Grid and the wider industry. Our proposed actions are
intended to build upon or complement these ongoing activities and they are explicitly
referred to in the relevant sections of the report.
1.2 System flexibility
In this report system flexibility is defined as the ability to adjust generation or consumption
in the presence of network constraints to maintain a secure system operation for reliable
service to consumers. It has the following two components:
Operational flexibility i.e. the use of resources, both energy and ancillary services,
to ensure efficient and secure system operation; and
System adequacy i.e. maintaining the long-term capacity requirement of the
system.
The two forms of flexibility are complementary to each for example, the energy storage
supports maintaining demand-supply balance during system operation and it can also
reduce system’s peak demand lowering the need for generation and network capacity in
the long-term. Imperial’s modelling based assessments presented in this report take
account of the synergies and complementarities between the two forms of flexibility as
well as across different flexibility providing technologies.
1.3 Flexibility providing technologies
In response to the flexibility challenge, novel flexible technologies that can make more
efficient use of the existing infrastructure are emerging.
The analysis in this report focused on the following types of flexibility providing
technologies.
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Flexible generation: advances in conventional generation technologies are allowing
them to provide enhanced flexibility to the system. This is due to their ability to start
more quickly, operate at lower levels of power output (minimum stable generation),
and achieve faster changes in output (see Table 5 for technical parameters of flexible
generation as applied in our modelling work).
Cross-border interconnection: interconnectors to other systems enable large-scale
sharing of energy, ancillary service and back-up resources.
Demand Side Response (DSR): DSR schemes can re-distribute consumption and
engage demand-side resources for system balancing to enhance system flexibility
without compromising the service quality delivered to end customers. These
schemes have a significant potential to provide different types of flexibility services
across multiple time frames and system sectors, from providing primary frequency
response to facilitating network congestion management.
Energy storage: energy storage technologies have the ability to act as both demand
and generation sources. They can contribute substantially to services such as
system balancing, various ancillary services and network management.
In addition to the above mentioned flexibility providing technologies, there is significant
potential for the power sector to access the flexibility embedded in other energy sectors
particularly the heat and gas sectors. However, understanding the effectiveness and
implications of exploiting this flexibility resource needs further research and analysis. This
flexibility resource is discussed further in Section 5.1.3.
1.4 Flexibility services and technologies
In order to ensure that generation and demand are balanced at all times and in all
locations, GB System Operator (i.e. National Grid) employs a range of measures (i.e.
Flexibility Services) across various time horizons. These services are secured under
various procurement mechanisms (e.g. markets, bilateral agreements, competitive
tendering, etc.) and can be broadly broken down as follows:
Capacity market: the aim of the Capacity Market (CM) is to deliver generation
adequacy. Capacity contracts are allocated to providers through auctions intended to
secure a capacity requirement in order to meet the reliability standard set by the UK
government.
Wholesale energy market: this market allows generators to sell their electricity to
suppliers from several years ahead up until Gate Closure.
2
Balancing Market (energy): its purpose is to maintain demand and supply balance
post Gate Closure as Generators and suppliers will most likely generate or consume
more or less than they have sold or bought in the Wholesale market. The System
Operator accepts offers and bids for electricity to enable it to balance the
transmission system during the post Gate Closure period.
Ancillary (Balancing) services: these are used by the System Operator to ensure that
supply meets demand at all times and that the system frequency remains within
statutory limits around the target level of 50Hz. Main balancing services are:
Short Term Operating Reserve (STOR) to retain spare generation capacity (or
demand reduction) on stand-by during certain hours of the day (typically during
2
Gate Closure is the time by which all notifications must be given; currently it is set at 1 hour
prior to the start of the traded period.
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periods of rapid change in demand or generator loading) for dealing with actual
demand being greater than forecast demand and/or plant unavailability.
Fast Reserve provides a rapid and reliable delivery of active power through an
increased output from generation or a demand reduction, following receipt of an
electronic despatch instruction from National Grid. This service operates in
quicker timeframes than STOR.
Frequency Response is the automatic provision of increased/reduced
generation or demand reduction/increase in response to a drop or increase in
system frequency. It can be delivered through either Dynamic Response (a
continuous service used to manage second by second changes on the system)
or Static Response (a discrete service usually triggered by a defined frequency
deviation).
Enhanced Frequency Response achieves 100% active power output at 1
second (or less) of registering a frequency deviation. This is a new service that is
being developed to improve management of the system frequency pre-fault, i.e.
to maintain the system frequency closer to 50Hz under normal operation.
In addition to the above mentioned main flexibility services, a range of other services are
also used by the System Operator which are defined in Annex B.
A number of technologies are capable of providing the various types of flexibility services
required in the system. Table 2 summarises technologies which are currently providing
the key flexibility services in the GB electricity systems (see green dots) and those that
are technically capable of providing the services based on their existing technical
characteristics or with some technical improvements (see red dots). The lack of current
service provision may be for several reasons including commercial constraints, market
limitations or lack of incentives. For example, DSR can provide Enhanced Frequency
Response (EFR) but no DSR aggregator was successful in securing a contract in the
recent EFR auctions because bids were out of merit.
It is also worth noting that in some cases, although a technology is providing a given
service, its market share for the service could be very small. For example, wind
generation provided only 0.03% of total frequency response (FR) in 2015. It could
potentially provide significant volumes of additional FR in the form of synthetic inertia if
appropriate regulatory requirements or incentives were in place and this was considered
efficient.
Therefore, there is a need for: (a) innovation support to improve technical characteristics
of such technologies; and (b) improvements in existing flexibility markets, including
procurement processes, in order to enable and facilitate access of such technologies in
providing a wider range of flexibility services.
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Table 2 Flexibility services and technologies
Source: Pöyry analysis
1.5 Structure of this report
The rest of this report is organised as follows:
Chapter 2 provides the findings of the modelling analysis carried out as part of this
study. It highlights the higher flexibility demands in the future system and identifies
portfolios of technologies to meet this.
Chapter 3 to Chapter 6 provide our analysis on each of the four identified components
of an effective low-carbon flexibility system:
ensure efficient investment decisions in providing increased flexibility services;
develop capability to manage greater complexity in future smart electricity
systems;
ensure innovation support; and
ensure effective consumer participation for exploiting demand flexibility potential.
and the actions required to achieve them.
Chapter 7 summarises the roadmap actions and describes the progress monitoring
framework.
There are four annexes to the report.
Annex A contains key modelling assumptions and methodology as applied by
Imperial College in quantifying the need and benefits of system flexibility.
STOR
FAST
reserve
Frequency
response
Enhanced
Frequency
Response
Coal
Nuclear
Gas-CCGT
Gas-OCGT
CHP (Thermal / RES)
Biomass
Engines (gas / diesel)
Wind (onshore / offshore)
Solar - PV
Solar - CSP
Hydro (reservoir)
Marine (wave, tidal, etc.)
Hydro (pump storage)
Storage (batteries)
Demand Side response
Technology is able to provide and is currently providing the relevant service
Blank cells indicate absence of any evidence or information to map technologies onto flexibility services
Technology that can potentially provide the service but is currently restricted due to economic or market limitations, or
requires some technical improvements for providing the releavnt service
Main balancing services
Wholesale
energy
market
Capacity
market
Balancing
market
(Energy)
Technology
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Annex B provides an overview of the flexibility services currently procured by the
system operator, and mapping of flexible technologies to various flexibility services in
the future.
Annex C and Annex D list the participants who joined the two stakeholder
workshops.
1.6 Sources
Unless otherwise attributed the source for all tables, figures and charts presented in this
report is Pöyry Management Consulting.
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2. MODELLING THE NEED FOR FLEXIBILITY
System flexibility will be the key enabler for an efficient transformation to the future smart
electricity system. There is a general acknowledgement that a low-carbon power sector
will need greater system flexibility to maintain stable and secure operation because of the
nature of the generation technologies. However, the scale of growth and the mix of
flexibility services required will depend on the way in which the decarbonisation of the
power sector is achieved.
2.1 Modelling assessment of future flexibility requirements
As part of this study, a detailed modelling based assessment was carried out by Imperial
College to investigate how flexibility requirements change in a system that meets the CO
2
emissions intensity target for the power sector (i.e. 100gCO
2
/kWh by 2030 and
10gCO
2
/kWh by 2050). The modelling investigated how flexibility needs changed across
four alternative future scenarios of low-carbon generation.
Balanced scenario: assumes balanced development across different low-carbon
technologies (i.e. nuclear, CCS and renewables). The scenario is based on the
extrapolation of the CCC power sector scenarios.
3
High PV scenario: assumes a large deployment of PV which significantly exceeds
the development of other low-carbon technologies. This would be facilitated by a
rapid decrease in the cost of solar cells, massive technology development in this
area, and incentives given to the PV industry to stimulate significant growth.
High offshore wind scenario: as the UK has one of the best wind sources in the
world, this scenario reflects extensive exploitation of this large energy potential for
decarbonisation of the UK electricity industry.
High nuclear and CCS scenario: assumes that the future decarbonisation of the
system will depend on the energy production primarily from nuclear and CCS.
The modelling provides a range of insights into the challenges of managing a low-carbon
generation system and the potential benefits from access to a wider set of flexibility
providers and technologies. In particular, it highlights that:
regardless of the composition of the future energy mix, any low-carbon system will
have a materially higher demand for system flexibility;
because of the different technical characteristics of the low-carbon generation
technologies, the balance of additional flexibility services can be very different to
today;
flexibility can be provided by a variety of new sources (including DSR, energy storage
and additional interconnection) and deliver savings compared to relying on
conventional sources of flexibility (e.g. conventional thermal plants like combined
cycle gas turbines or open cycle gas turbines);
savings can be made in investment and operating costs across the value chain
if decisions are based on the full system value; and
3
Power sector scenarios for the fifth carbon budget, The Committee on Climate Change (UK),
October 2015
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the future flexibility portfolio is uncertain and will need to be responsive to a
range of external factors including policy and market initiatives, technology costs
and efficiency improvements.
These insights have helped inform the focus of actions in the flexibility roadmap.
Importantly, they have demonstrated the need for any future market to encourage access
from as wide a set of flexibility resource as possible, and not to be unduly restrictive given
the various uncertainties around new technologies. In addition, they have emphasised the
importance of continued support for innovation and clear, transparent signals of value for
all flexibility services.
The remainder of this Chapter presents the key modelling insights in each area. An
overview of the modelling methodology applied by Imperial College in this analysis and
the key modelling assumptions are provided in Annex A.
2.2 Future flexibility requirements
Any future low-carbon power system will potentially have a large penetration of
intermittent generation, or less flexible nuclear / CCS plants, or a combination of these low
carbon sources. This generation setup drives the need for significant additional flexibility
over shorter time scales (i.e. between few hours ahead to the real-time) necessary to
maintain safe and efficient operation of the system as described in the following sections.
Figure 6 shows an illustrative
4
snapshot of the hourly net demand profile (i.e. system
demand minus intermittent generation) in a single winter week in 2030. A key observation
is that the net demand turns more volatile and often peakier with shorter duration of peak
demand in the future than today. This leads to a need for a very steep ramping
requirement i.e. increase as well as decrease in generation or demand from
dispatchable resources (demand or generation) in the system.
In this case, the steepest ramp requirement is found when the morning pick-up coincides
with a large drop of renewable output. For safe operation of the system, a large number
of dispatchable generators will need to be synchronised to be able to meet this ramping
requirement in order to maintain demand-supply balance in the system.
Figure 6 also shows that the minimum net demand levels which occur during a low
demand period coincide with high renewable output. The minimum net demand
approaches zero indicating that the entire system demand is supplied by renewables
during such periods. However, such conditions create a challenge in power system
operation since renewables such as wind and solar PV do not contribute to the system
inertia and are not the main providers of frequency response or regulation.
In order to mitigate the risk to safe operation of the system, a sufficient number of
conventional plants need to be synchronised operating at least at the minimum stable
generation level. This will lead to surplus generation in the system resulting in curtailment
of renewable generation unless demand can be increased or energy is exported to other
systems in order to accommodate the surplus energy.
4
The week is drawn from the modelled scenarios to demonstrate the potential volatility in net
demand to be managed by the system operator through its range of flexibility services.
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Figure 6 An illustrative example indicating higher requirement for operational
flexibility in the future (Balanced scenario)
Source: Imperial’s modelling analysis
2.2.1.1 Ramping requirements
Based on the modelling of scenarios analysed in this study, it is estimated that there will
be an increase of up to 100% in the maximum ramping requirements over a one-hour time
horizon in 2030 relative to the current situation. This is primarily driven by the increased
renewable energy capacity. The maximum ramping up and ramping down requirements
for different time scales (1 up to 8 hours) are shown in Figure 7.
In general, the ramping requirements increase over all time horizons (i.e. across 1-8
hours). This requires the system operator to plan a larger volume of ramping capability of
the synchronised generators or other dispatchable demand/supply resource in the system
within the respective time frame to meet the demand-supply balancing challenge.
Meeting the increased ramping requirements by fossil based generation is expensive due
to (a) efficiency losses as some plants will be required to run part-loaded; (b) increased
number of start-ups; and c) increase in CO
2
emissions driven by efficiency losses. On the
other hand, lack of adequate ramping capability in the system can jeopardise the safe
operation of the system and potentially increases the need and cost of other (more
expensive) flexibility services by several folds that are required over shorter term frames.
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Figure 7 Increase in ramping requirement (Balanced scenario)
Source: Imperial’s modelling analysis
2.2.1.2 Reserve requirements
Operating reserve includes the provision of increased generation or demand reduction
over a period of minutes to hours in response to an instruction from the system operator.
Increased share of variable intermittent generation in the system also increases the
uncertainty in demand and supply balance which increases the minimum operating
reserves held by the SO to maintain sufficient system balancing capability. The amount of
operating reserves depends on the level of uncertainty in supply and demand; so it is
assessed dynamically and changed according the system conditions.
Figure 8 shows two implications of the low-carbon system:
a) a higher maximum requirement e.g. the maximum reserve requirement across the
year increase from 5.2 GW in 2020 to 7.3 GW in 2030; and
b) a more frequent need of higher reserve levels e.g. the number of hours during
which a reserve volume of 4.5GW will be required increase from about 300 in 2020
to 700 in 2030.
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Figure 8 Future GB operating reserves requirement (Balanced scenario)
Source: Imperial’s modelling analysis
Today, the operating reserves mainly come from mid-merit (Combined Cycle Gas Turbine
plants and Coal plants) and peaking plants (Open Cycle Gas Turbine). The available
capacity of these technologies is expected to decrease in future in line with tighter
decarbonisation targets and reduced economic viability. Therefore, the system will need
to source alternative operating reserves.
2.2.1.3 Frequency response requirements
Frequency response (FR) refers to the automatic provision of increased generation or
demand reduction in order to contain a drop in system frequency. Increased share of
renewables (i.e. inverter based power generation) in the capacity mix reduces the system
inertia which is provided by the stored kinetic energy of the rotating mass of the power
generator’s turbines. With this reduction in system inertia, any imbalance between supply
and demand will change system frequency more rapidly making the system unstable.
Therefore, a sufficient level of frequency response is needed to deal with sudden loss of
supply to the system (e.g. as a result of a failure of a large generator / interconnector or
rapid demand turn up) in order to keep the system frequency within its statutory limits.
Figure 9 (right box) shows the FR requirement as a function of net demand (demand
minus wind output). It demonstrates that the FR requirement increases significantly when
the net demand is low e.g. when a low demand condition coincides with high output
from intermittent renewables. On the other hand, the system will require less FR during
high demand conditions coinciding with low output from intermittent generators
considering there are many synchronised plants in the system. As the frequency of
having low net demand is higher in future, it is expected that the requirement for
frequency services by 2030 will also be higher as shown in the Figure 9 (left chart) for
50% renewables penetration.
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Figure 9 Impact of intermittent generation on frequency response requirements
in the future system (illustrative)
Source: Imperial’s modelling analysis
To date, the frequency response service can only be provided by synchronised
conventional plants which need to operate part-loaded and produce at least at the
minimum stable generation level (MSG). This reduces the ability of the system to absorb
electricity production from renewables or other low-carbon technologies. Moreover,
running at a suboptimal level of production (i.e. at MSG level) also reduces the fuel
efficiency of the conventional generation and increases the emissions. This opens
opportunities to alternative FR providing sources such as fast storage or DSR that can
provide the required services potentially at lower cost and without increasing emissions.
2.2.1.4 Potential increase in the value of flexibility services
The large increase in flexibility requirements will result in a significant growth of the overall
value of such services in the future GB system.
Figure 10 shows the potential change in system operation costs in order to efficiently meet
the CO
2
reduction target of 100gCO
2
/kWh in the power sector in 2030 relative to the 2015
system. Although the overall system operation costs are expected to reduce due to high
penetration of low marginal cost low-carbon generation (wind, solar and nuclear), the cost
of ancillary services costs will potentially increase by about 10 times relative to the 2015
levels.
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Figure 10 Change in overall value of ancillary services (illustrative)
Source: Imperial’s modelling analysis
2.3 Impact of alternative generation mixes on flexibility
requirements
The system flexibility requirements depend on many factors such as the characteristics of
the generation system (capacity mix, locations, dynamic parameters, availability, output
profiles of energy sources), demand characteristics (customer types, locations, profiles,
peak demand) and network characteristics (e.g. AC vs. DC links to other systems).
Figure 11 (left chart) compares the frequency distribution of the net demand profiles of the
four modelled scenarios. It can be observed that under the High Wind scenario there are
more periods where the net demand is low or even negative (i.e. total wind output
exceeds system demand).
Figure 11 (right chart) compares the frequency distribution of the operating reserve
requirements across the scenarios, while all low-carbon options result in a rising
(additional) demand for operating reserve, this is most strongly required in the case of
High Wind scenario.
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Figure 11 Evolution of net demand and operating reserve requirements in the
modelled scenarios by 2030
Source: Imperial modelling analysis of the CCC scenarios
2.4 Potential benefits of alternative system flexibility options
Across the modelled scenarios, there are several alternative options for delivering the
necessary flexibility in a decarbonised energy system. To a greater or lesser extent, by
exploiting new sources of flexibility, there is the potential to realise cost savings relative to
a system that continues to rely on conventional generation to deliver flexibility. These
savings are associated with:
Avoidance of energy curtailment from low-carbon generation sources: a lack of
operational flexibility limits the system’s ability to accommodate output from
intermittent renewable technologies, particularly during periods when low demand
conditions coincide with high output from wind and solar sources. Presence of
system flexibility sources such as energy storage facilities, demand side response or
interconnectors can absorb/export surplus generation in the system thus avoiding
energy curtailment and associated costs.
Efficient provision of operating reserve and response facilities: the provision of
operating reserve to the system by non-thermal flexibility technologies (i.e. Storage,
DSR and interconnection) increases the ability of the system to absorb low-carbon
electricity and reduces the need to maintain thermal plant at minimum stable
generation with associated impacts on carbon emissions and operating costs due to
efficiency losses.
Potential savings in generation capacity: new service providers may reduce
overall generation capacity on the system due to:
Reduced need for low-carbon capacity in the system: reductions in energy
curtailment will result in increased utilisation hence lower capacity of low-carbon
generation to meet the decarbonisation targets.
Peak reduction: electrification of heat and transport will disproportionally
increase peak electricity demand however, system flexibility in the form of energy
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storage or demand side response can reduce system peak by redistributing
demand from high demand to low demand periods. This results in reducing the
amount of required generation capacity in the system (particularly, the peaking
plant capacity).
Reduced need for back-up capacity: energy storage, DSR and interconnection,
can reduce the need for back-up generation capacity required to support the
intermittent generation.
Deferral or avoidance of the network reinforcement/addition: in addition to the
network capacity savings driven by lower generation capacity requirements (as
described above), additional network capacity savings are possible by deploying
flexibility to manage network constraints and reassessing the need for network
reinforcement in conjunction with innovative network planning and operation
standards as discussed in Section 4.1.2.
The results of Imperial’s modelling analysis demonstrate that alternative system flexibility
solutions for meeting the CCC’s 2030 carbon intensity target (100gCO
2
/kWh) can save up
to £4.7 bn/year. The savings are obtained from the reduction in system capacity
requirement (low-carbon generation, conventional generation, transmission,
interconnection, distribution assets) and lower operating cost (due to energy curtailment
avoidance, CO
2
cost savings, and reduced fuel usage) as shown in Figure 12 for different
scenarios.
The results also show that the savings due to increased system flexibility are higher in
scenarios with large penetration of intermittent generation (High Wind or High PV
scenarios). This is because the volume of additional system flexibility becomes more
pronounced in such systems compared to a system that also contains non-intermittent
low-carbon, nuclear and CCS, generation (e.g. the Balanced scenario). Presence of
higher flexibility services, from energy storage and/or DSR, enables more efficient
management of demand-supply balance by time shifting the surplus intermittent
generation or demand. This avoids curtailment of solar and/or wind energy as well as
reducing the need for their generation capacity resulting in higher savings in operational
expenditure (Opex) and capital expenditure (capex) respectively.
Moreover, more ambitious carbon reduction target (50gCO
2
/kWh) would see a further
increase the value of flexibility (up to £7.8 bn/year) as the system would need to
accommodate more low-carbon generation.
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Figure 12 System cost savings due to alternative flexibility provision across
scenarios
Source: Imperial’s modelling analysis of the CCC scenarios
2.5 Uncertainties related to the portfolio of flexibility services
As mentioned earlier the required level of additional flexibility is dependent on the
characteristics of the generation capacity mix in the system as multiple generation mixes
can deliver the decarbonisation targets. For a given level of additional flexibility there are
multiple other factors that will define the uptake of different flexibility resource in the future
system, such as:
relative costs, scalability, locational distribution, availability of the control infrastructure
and technical performance of different types of flexibility sources;
the adopted energy policies, market and regulatory framework; and
the social (e.g. consumer acceptance) and cultural (e.g. maintaining status quo)
aspects associated with effective participation of demand side flexibility.
There are uncertainties associated with the aforementioned factors introducing the
uncertainty around the cost of demand side response and/or expected drop in cost of
storage. Similarly, there is lack of clarity as well as diverging views on the level of
consumer acceptance of DSR technologies.
Taking account of the technology cost and deployment rate uncertainties, Imperial College
has analysed the range of possible penetration of different flexibility technologies in their
modelling assessment. Figure 13 shows the modelling based potentials of different
flexibility technologies such as DSR, storage, interconnection and flexible generation in
2030 across different scenarios to meet the 100gCO
2
/kWh carbon intensity target.
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Figure 13 Indication of uncertainty in the deployment of different types of
additional flexibility resource based on scenario modelling
Source: Imperial’s modelling analysis of the CCC scenarios
Given the level of uncertainty over individual flexibility technologies that can be deployed
to the system in future, it is important for the policy, market and regulatory framework
should provide a technology neutral environment to facilitate the development and
deployment of all flexibility technologies.
Earlier analysis by Imperial College
5
also supports the above argument that a ‘balanced’
strategy of deployment across different sources of flexibility is the ‘least worst-regret’
pathway for the UK energy system. Facilitating the ‘balanced’ deployment pathway, with
some deployment of DSR, storage and flexible CCGT by 2020, and deployment of the
current interconnector pipeline
6
, is an effective way to avoid worst regret outcomes and
technological lock-in.
2.6 Main requirements of the future electricity systems
Enabling the transformation to an efficient GB electricity system will not be without its own
challenges. From the analysis and stakeholder engagement undertaken as part of this
study, we have identified four key requirements of any future electricity system.
5
An analysis of electricity system flexibility for Great Britain, D. Sanders, A. Hart, M.
Ravishankar, G. Strbac, M. Aunedi, D. Pudjianto, and J. Brunert, Report by Carbon Trust
and Imperial College London, November 2016, available at:
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/568982/
An_analysis_of_electricity_flexibility_for_Great_Britain.pdf
6
Electricity interconnectors. Ofgem, available at:
https://www.ofgem.gov.uk/electricity/transmission-networks/electricityinterconnectors
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Investment decisions should be made on the basis of the full system value offered by
providers this means that the market design must effectively price and reward
energy, capacity and flexibility.
Appropriate systems and interfaces should be in place to manage greater complexity
in the system this implies a capability of the system to deal with more interactions
between distribution and transmission networks and to promote and utilise more
active demand management.
Enhanced framework to achieve greater consumer participation in addition to
establishing the technical infrastructure for demand-side response, legal and
regulatory frameworks around data protection and consumer protection will be
necessary to achieve widespread consumer acceptance.
Ongoing support for innovation in technology, services and operating models it will
be important that, as the institutional and market framework evolves, the drive for
innovation across the value chain is not dampened.
In the following chapters, we outline in more detail the importance of each requirement,
the current challenges to realising the objective and the specific actions that will help to
realise the objective. A high-level overview of the ongoing activities relevant to the
proposed actions, where information is available in the public domain, is also described.
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3. ENSURING EFFICIENT FLEXIBILITY INVESTMENT
DECISIONS
The shift to a low-carbon electricity system will require major investment, so it is important
that the system makes adequate and timely investment in the most effective technologies
and services. Investment decisions should be made taking account of the value to the
system of the full range of services that the provider is offering. Since more flexibility will
be required, the value of the flexibility offered by technologies should be a key
consideration in any new investments, as should the costs they impose on system
operation. If the value of flexibility is not transparently signalled in the market and
available to all technologies, then the cost to consumers will be higher than it needs to be.
In theory, there are multiple potential revenue streams available to the market players
(both demand and supply sources). These revenues reflect different ‘products’ or
‘services’ and are accessed from a variety of separate market platforms. The main forms
of revenue relate to:
capacity i.e. provision of system security during system stress conditions through
offers on the capacity market;
wholesale energy provision i.e. sale of electricity through standard wholesale
markets;
balancing i.e. actions in the system balancing market;
ancillary services i.e. provision of specific services to the system operator such as
frequency regulation services; and
network support i.e. provision of services to reduce the need for network
reinforcement.
These services are not mutually exclusive and for commercial investment decisions to
deliver efficient system development it is important that:
all potential revenue streams exist and are available to a service or technology; and
the value of the service to the system is accurately reflected in the market or
procurement platforms in operation.
This is particularly important for the emerging technologies and services around flexibility
provision as, in contrast to conventional generation investment, a higher proportion of their
value will be dependent on ancillary service and network support revenue streams.
For example, Imperial College has modelled the business case of battery storage facilities
which can provide a range of system services across multiple revenue streams while
taking account of the physical interactions between the different system support services.
Figure 14 shows the results for a 6MW battery storage connected in the HV distribution
grid supporting connection of 20MW of PV generation. This demonstrates how the value
of the asset increases several-fold with access to a wider set of revenue streams.
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Figure 14 A business case for energy storage facilities (illustrative case)
Source: Imperial’s modelling analysis of benefits of full market access
From the analysis and stakeholder engagement undertaken as part of this study, it is clear
that the GB electricity system needs to ensure that:
value streams are available for all forms of system service and that they are
accessible to all potential providers;
the price signals for these services are efficient and reflect the value to the system at
the time; and
there is some transparency for providers over the longer-term requirements for these
services in the market.
The following sections expand on these observations and identify appropriate actions to
address current challenges.
3.1 Availability and accessibility of revenue streams
3.1.1 Availability of flexibility services
In order to ensure future investments in the power system take account of the flexibility
requirements of the system, all types of flexibility services need to be valued. Under the
current arrangements, this is not always the case, with the main gap identified in the
valuing of system inertia.
One of the key challenges associated with integration of renewable generation is the
reduction of system inertia. This may be provided through conventional generators
manufactured with a higher inertia constant or from wind generators providing “synthetic
inertia” (SI). However, the current flexibility market does not reward the provision of
inertia and this has contributed to a lack of interest by investors to develop alternative
ways for enhanced inertia provision. Without a remuneration mechanism for inertia, there
will be higher cost to the system.
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3.1.2 Access to revenue streams
Even where revenue streams exist, flexibility providers do not always have access to all of
the services that they can technically offer. This means they may not be able to be
rewarded for the full value they offer to the system, leading either to insufficient flexibility
being available to the system or, more likely, to a higher cost of delivering flexibility due to
inefficient investment and operational decisions.
Examples of limitations to some flexibility providers include:
Independent aggregators need to be a Balancing Mechanism Unit (BMU) or need to
reply on third parties to have access to the balancing mechanism (BM) as they do not
have a defined role in the Balancing and Settlement Code (BSC). This involves
administrative costs and sharing of some revenues with third parties which
discourages small scale aggregators from accessing value in the BM as well as in the
wholesale market.
Enhanced Frequency Response (EFR) providers, which includes all storage facilities,
are excluded from participation in the Capacity Market (CM).
Holders of long-term STOR contracts are ineligible for participation in the Capacity
Market.
Low-carbon capacity sources that receive support payments such as the Renewables
Obligation (RO), Contracts for Difference (CfD) or Feed-in-tariffs (FITs) have no
incentive to provide flexibility even if they are capable of providing.
Ofgem has recently taken several initiatives to assess and improve the flexibility
procurement process in order to provide a more level-playing field for different flexibility
providers. These include identifying barriers and proposing changes in the current
Capacity Market rules for participation of small generators and DSR capacity by initiating
consultations with the relevant stakeholders.
7
,
8
3.1.3 Recommended action on availability and accessibility of revenue streams
Our recommended actions in these areas are outlined below.
Periodical assessment of existing portfolio of flexibility services to identify services that
may be procured more efficiently through transparent and technology-neutral processes
in the future and reform their procurement processes accordingly.
Responsible: SO/DSOs
Initial assessment by 2020
Medium priority
7
Electricity Market Reform: Open letter and consultation on changes to the Capacity Market
Rules, September 2016
https://www.ofgem.gov.uk/system/files/docs/2016/09/open_letter_cm_rules_150916.pdf
8
Capacity Market Rules change proposal submissions, November 2016
https://www.ofgem.gov.uk/electricity/wholesale-market/market-efficiency-review-and-reform/electricity-market-reform/change-proposals
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3.2 Efficiency of pricing signals
In order to deliver the full benefits of flexibility, price signals should reflect the overall value
of smart technologies to the electricity system. In this section we discuss the enablers for
improving the efficiency of price signals to encourage deployment of flexibility in the future
system.
3.2.1 Provision of dynamic pricing signals
The need and value of flexibility is time dependent it varies across different seasons as
well as across different times of the day, driven by system demand conditions. With
significant growth in intermittent generation, variation in supply is becoming more
pronounced. At the same, the nature of demand variability is changing as new sources of
demand (e.g. heat pumps and electric vehicles) bring additional variability in demand-
supply balance from the demand side.
In GB, the dynamic value of required flexibility services e.g. the Firm Frequency
Response (FFR) is procured through a monthly tender based on the demand for this
service which is assessed up to several weeks ahead of real time. This can result in a
risk of over/under procurement of services and a lack of availability of flexibility resource
for other services. Although the balance (i.e. in case of under procurement) can be
procured through mandatory frequency response, it has cost implications. In case of over
procurement, depending on the contract terms, at least the availability fees will be paid to
the providers whose services were not required by the system.
In the future with growing need of flexibility, dynamic price signals (i.e. time dependent
cost of energy and value of flexibility) can potentially incentivise availability of flexibility
during periods when it is most needed by the system. This will also encourage
consumers to change their energy consumption behaviour (i.e. reduce consumption when
the system is under stress or the electricity cost is high and vice versa) in order to lower
overall system costs as well as their bills. In the energy market this is likely to improve as
a result of developments such as half-hourly settlement and reserve scarcity pricing
schedule
9
.
Imperial has investigated the value and need for EFR across days with different system
conditions
10
. As shown in Figure 15 and Figure 16, during high system demand and low
wind days, the benefit of EFR saturates at £350k after 300 MW of EFR become available,
suggesting low demand for EFR. However, during low system demand and high wind
days, more than 600 MW is needed and saves £9000K in operating cost. It is clear that
the value and need for EFR vary significantly across different days and times within a day
depending on the system conditions. This informs that there is a significant uncertainty in
the required volume of EFR and PFR at any time and if procured over longer timeframes
then there is a risk of over-procurement and increase costs associated with these
services. Therefore, these should be procuring over shorter timeframes taking account of
their mutual trade-off more efficiently reflect the variation in their value in the system.
9
Electricity Balancing Significant Code Review (EBSCR) - Draft Business Rules, Ofgem, 2015
10
An advanced stochastic unit commitment (ASUC) model was applied to
simultaneously optimise scheduling energy production, standing/spinning reserves and
inertia-dependent frequency response in the light of uncertainties associated with wind
production and generation outages. All key dynamic frequency requirements, (a) ROCOF,
(b) frequency nadir and (c) quasi-steady-state frequency, are explicitly considered in the
optimisation model. This model is therefore capable to maintain the post-fault system
frequency within the limits, while optimising the portfolio of EFR and PFR.
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Figure 15 Operating cost saving from enhanced frequency response in the day
with high demand and low wind
(a) System condition (b) Operating cost saving from EFR
Source: Imperial’s modelling analysis
Figure 16 Operating cost saving from enhanced frequency response in the day
with low demand and high wind
(a) System condition (b) Operating cost saving from EFR
Source: Imperial’s modelling analysis
Similarly, the marginal value of inertia for different demand-wind conditions is shown in
Figure 17. It varies from almost zero under the high demand low wind condition to more
than 140 £/h/ MW-sec
2
under the low demand and high wind condition. This is due to the
fact that under the high demand and low wind condition, the overall system inertia is high
as conventional generators are the main source of supply and hence the requirement for
frequency response is driven by the steady-state frequency requirement and vice versa.
0
10
20
30
40
50
60
1 2 3 4 5 6 7 8 9 10 11 12 13 1 4 15 16 17 18 19 20 21 22 23 24
Power(GW)
Time(hour)
WindPower Demand
0
50
100
150
200
250
300
350
400
0 200 400 600 800 1000
OperatingCostSaving(K£)
AmountofEFR(MW)
0
10
20
30
40
50
60
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Power(GW)
Time(hour)
WindPower Demand
0
1000
2000
3000
4000
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6000
7000
8000
9000
10000
0 200 400 600 800 1000
OperatingCostSaving(K£)
AmountofEFR(MW)
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Figure 17 Growing need for remuneration of inertia
Source: Imperial’s modelling analysis
With greater variability in system conditions in the future, there will be a corresponding
variability in the value of the associated flexibility services, meaning that more dynamic
pricing (e.g. half hourly prices), reflecting more accurately the value to the system at
different times, will become more important for effective investment and system operation
decisions.
Ofgem has recently announced its plans and a timetable
11
on moving to mandated half-
hourly settlement to sharpen short-term signals in order to better reflect the cost to the
system and enabling smart technologies to realise more value and suppliers to develop
innovative dynamic retail offerings.
3.2.2 Improvements in network charging
For more efficient investment decisions, cost impacts of alternative flexibility solutions will
need to be addressed alongside revenue and pricing signals.
The proliferation of distribution-connected generation, the increase in intermittent
renewable generation, the recent growth of storage assets and the potential for demand
side management means that the old network charging regime is increasingly becoming
less cost-reflective. The nature of flows is changing radically and the peaks on individual
parts of the network (which drive losses and the network investment needs) are becoming
increasingly disconnected from overall system peak demand. Therefore, the underlying
objective of cost-reflective charges cannot easily be fulfilled without considering both time
and location, reflecting the actual flows on the network at the time.
11
Mandatory Half-Hourly Settlement: aims and timetable for reform, Ofgem, November 2016
https://www.ofgem.gov.uk/ofgem-publications/106472
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The current allocation of network charges has been frequently challenged
12
to be over-
compensating some network users and/or penalising others affecting both consumers and
flexibility investors. Typical issues include:
Representation of location specific element in TNUoS charges: currently the
location specific part of the overall Transmission Network Use of System (TNUoS)
charges is very small, see Figure 18. As a consequence it does not allocate charges
to parties responsible for incurring network reinforcement and addition affecting
locational incentives for generation, demand and storage.
Under-charging of rooftop solar: currently unit charge for distribution costs is
based on net usage (i.e. energy consumed minus energy produced). Without
adequate onsite storage, consumers with rooftop solar panels rely on electricity from
the distribution system. Therefore, they do not necessarily reduce the costs of the
distribution system and are therefore under-charged at the expense of the remaining
consumers.
13
Double-charging to storage: at present there is a lack of guidance on the treatment
of storage in the network charging methodologies. This creates difficulties and
uncertainty for storage developers in estimating their network charges.
14
For
example, the transmission and distribution tariffs are levied twice on storage as it is
treated as both an electricity consumer and generator. These doubled charges
arguably do not reflect the complementary benefits of energy storage to the
transmission network in balancing the wider electricity system.
15
Figure 18 TNUoS charges
Source: Imperial’s modelling analysis
12
Ofgem has recognised these issues in their July 2016 and December 2016 open letters:
Open letter: Charging arrangements for embedded generation, 29 July 2016
Open letter: Update on charging arrangements for Embedded Generation, December 2016
13
A response to BEIS’ and Ofgem’s call for evidence ‘A Smart Flexible Energy System’,
Citizens Advice Bureau, January 2017
14
BEIS and Ofgem Call for evidence ‘A Smart Flexible Energy System’, November 2016
15
http://www.restless.org.uk/documents/briefing-paper-1
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Imperial’s analysis of the impact of a fully cost-reflective Distribution Use of System
(DUoS) charges, as shown in Figure 19, indicates that on the average flexible consumers
would have a 4 times lower share of DUoS charges in their annual electricity bills
compared to inflexible consumers.
Figure 19 Potential Impact of customer’s flexibility on their bills
Source: Imperial’s modelling analysis
If an increasing proportion of electricity demand is supplied by embedded generation,
there is a concern that the burden of system costs could be spread over a declining
residual demand. Therefore, Ofgem has been proposing several changes in the current
network charging arrangements, based on the argument that the current charges have the
potential of distorting the investment decisions due to the additional burden of costs to the
residual generators in order to compensate the cost avoidance (i.e. benefits) of the
embedded generation. Some of these proposals include:
the reduction of the demand residual charge that the embedded generators are
currently receiving as a benefit
16
; and
a more structural change in the current network charging methodology related to
the forward-looking and sunk (residual) costs, with a focus on the current benefits and
cost avoidances that behind the meter generation receives
17
.
Both of the above proposals aim to eliminate market distortions due to the current network
charging structure and to encourage investment in flexible resource such as storage and
DSR (e.g. removal of double network charging for storage facilities).
16
Minded to decision and draft Impact Assessment of industry’s proposals (CMP264 and
CMP265) to change electricity transmission charging arrangements for Embedded
Generators, Ofgem, March 2017
https://www.ofgem.gov.uk/system/files/docs/2017/03/minded_to_decision_and_draft_impact_assessment_of_industrys_proposals.pdf
17
Targeted Charging Review: a consultation, Ofgem, March 2017
https://www.ofgem.gov.uk/system/files/docs/2017/03/tcr-consultation-final-13-march-2017.pdf
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3.2.3 Improvements in other system integration costs
We have also identified issues with the allocation of other system integration costs /
charges of some technologies. For example:
the magnitude (and corresponding cost) of Frequency Response (FR) required in the
system is predominantly influenced by the largest unit (typically a nuclear power plant
or interconnection to a connected system), however, it is currently being socialised;
and
some technologies such as solar power on their own offer no capacity value and wind
power offers only limited capacity contribution, however, both of these technologies
need back-up capacity but are not charged for that.
We recognise that the assessment and allocation of system integration costs is a
challenging task however, it is important for establishing a level playing field for all users
of the system. Therefore, a review of the allocation of all system costs i.e. network
charges, back up capacity costs and cost of ancillary services to the parties that are
responsible for causing these costs is required.
3.2.4 Improvements in balancing services procurement
Currently, a wide range of flexibility system balancing services is procured by the system
operator. Table 3 shows the technical requirements and the type of contract for
procurement of frequency response and reserve services by the SO.
The procurement of these services differ in terms of technical requirements, validation
processes
18
, contract type and procurement platform, increasing complexity and reducing
transparency. Three of the nine services reported (i.e. FFR bridging, FCDM and STOR
Runway) are procured under bilateral contracts of different lengths with limited visibility to
the rest of the market players. There is a significant range of minimum size (MW)
requirements among the various services with lack of transparency on the sizing rationale.
Another key issue is the limitation in offering bundled services as these different services
are procured at different times in isolation without full consideration of their mutual
interactions, particularly from the provider’s perspective.
18
These include the requirements and the processes involved in qualifying the eligibility criteria
for providing a specific flexibility service to the system.
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Table 3 Technical requirements and types of contracts for Frequency response
and reserve services
Source: National Grid (UK)
The procurement of services should take account of interactions or trade-offs between
services. Under the current arrangements the volumes of various operating reserve are
procured separately and do not comprehensively take account of the interactions (e.g.
temporal, technical and cost interactions) between the procured products. For example,
as both PFR and EFR share the same goal to limit the system frequency nadir above the
standard, these two services should, in fact, be procured together based on their mutual
interactions to minimise their overall cost. With rise in the amount of flexibility
requirement, the optimisation of the portfolio of various flexibility services required by the
system becomes more important.
Furthermore, some forms of flexibility sources create additional demand for flexibility at
other times which need to be included in the decision process while procuring flexibility.
For example, DSR based provision of ancillary services generally redistributes demand
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across different time. This means that reduction in demand at a point in time aimed at
providing reserve services, will be followed by an increase in demand during a
subsequent period e.g. use of Thermostatic Loads to provide frequency response will
increase the need for secondary reserve, which should be accounted for, otherwise the
value of this flexibility source would be overestimated as depicted in Figure 20.
Figure 20 Impact of interactions between flexibility products on the accrued
value
Source: Imperial’s modelling analysis
In New Zealand, the system operator (Transpower) applies a Reserve Management Tool
(RMT) to continually identify risk to the demand-supply balance in the system. It then
determines an optimised portfolio of flexibility services (grouped into Fast Instantaneous
and Sustained Instantaneous reserves) and ensures its provision for each 30 minute
trading period through the ancillary services market. This reserve management
framework provides a simple and transparent procurement process, where providers are
able to bid in reserve products right up to the gate closure time meaning that the costs
are more reflective of the system conditions at that time.
The GB system operator (National Grid, UK) has recognised the complexity and low
transparency
19
of the existing flexibility procurement processes such as the following:
there exist too many markets with differing technical requirements expected from the
same provider;
the criteria for validation of a provider has not been transparent to the market players;
and
SO’s requirements of various flexibility products and how they interact with each other
has not being transparent.
Consequently, some markets are over- and some under-subscribed.
The SO is currently consulting on simplification and rationalisation of the balancing
services and potentially reducing the number of products. This is intended to reduce
19
http://powerresponsive.com/wp-content/uploads/2017/03/SNAPS-SWG-Slide-Deck-13-3-2017.pdf?mc_cid=bc29dbffc5&mc_eid=bcfef9e0be
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complexity in the procurement process of these flexibility services. Furthermore, it is also
exploring alternative structures of the future market to procure flexibility services.
In the future, significantly more flexibility activity will potentially occur at the distribution
level. At present the level of transparency in Distribution Network Operator’s (DNO)
actions is much less than for the SO. The information on currently procured flexibility
services by the DNOs and the future projection of the demand of such services is not
openly available to flexibility providers. Therefore, it is expected that the issues National
Grid has identified at the transmission level are likely to be replicated at the distribution
level. Therefore, earlier actions to pre-empt these issues at the distributed level will be
required.
3.2.5 Recommended actions on improving efficiency of pricing signals
Our recommended actions in this area are outlined below.
Review characteristics of current procurement processes (e.g. threshold capacity level
to participate, contract terms / obligations) and the procurement route (e.g. open
market, auctioning or competitive tendering) that enable more efficient procurement of
services without unduly restricting the provision of multiple services by flexibility
providers.
Responsible: Ofgem in
conjunction with SO, TOs and
DSOs
By 2020
High priority
Assess the materiality of distortions to investment decisions in the current network
charging methodology (e.g. lack of locational charging, double-charging for stored
electricity), and reform charging methodology where appropriate.
Responsible: SO, DSOs and
Ofgem
2020
High priority
Assess the materiality of distortions to investment decisions in the absence of non-
network related system integration charging (i.e. back up capacity and ancillary
services) and implement charging where appropriate.
Responsible: SO, DSOs and
Ofgem
Post 2020
Medium priority
3.3 Improved understanding of long-term requirements
Investors and providers of flexibility need clarity and information on how the different types
of system flexibility requirements will evolve in the future in order to have confidence
regarding ‘demand security’ of their services and reasonable predictability of potential
revenues based on provision of all flexibility services offered to the system.
Currently there is a lack of public understanding and information on how system flexibility
requirements will grow in the future. National Grid (UK) annually publishes a forecast of a
limited number of flexibility services (frequency response and reserve) for the next five
year time horizon.
20
However, given investment cycles are typically longer than five years
20
National grid (UK), Future Requirements for Balancing Services, 2017
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(e.g. 8-10 years for battery storage systems, 12-15 years for gas based peaking plants)
stakeholders have highlighted a benefit from availability of information for particular
flexibility services over longer time horizons. This can be addressed through projection of
a longer-term outlook of flexibility requirements including an indication of the uncertainty
involved.
Our recommended action in this area is outlined below.
Publish annual projections (for each future year) of longer-term future procurement
requirements across all flexibility services including indication of the level of uncertainty
involved and where possible location specific requirements, to provide greater visibility
over future demand of flexibility services.
Responsible: SO/DSOs
2020 onwards
High priority
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4. DEVELOPING CAPABILITY TO MANAGE GREATER
COMPLEXITY IN THE SYSTEM
Future electricity systems will be much more complex than their current counterparts, as a
consequence of a range of factors including:
access for system operators to multiple types of resource to maintain system security;
manifold increase in the number of active (i.e. responsive) demand sources,
generation sources and intermediaries;
dynamic consumer usage patterns and presence of potentially large variable supply
sources in the system;
the availability and growth of distributed flexibility resource;
the need for location specific flexibility services leading to conflicts/synergies between
distribution and transmission level flexibility requirements; and
large volumes of multidimensional (e.g. electricity prices, consumption and their
forecasts) and dynamic data flows involving both technical data as well as monetary
transactions.
Accounting for these factors will require:
system operators and other key market players being prepared to embrace the
growing complexity challenge for safe and efficient operation and control of the future
smart system; and
the energy as well as associated Information and Communication (ICT) infrastructure,
to be in place for enabling various functions of the future system.
4.1 System operators will need to have clear roles and
responsibilities besides developing capability to manage
greater complexity of the future smart electricity system
Future smart electricity systems will have interactions in many different ways with a range
of loads, generation sources and virtual entities (e.g. aggregators and virtual power
plants) as depicted earlier in Figure 4. One key implication will be a more complex and
frequent interaction between system operation at the transmission and distribution levels,
demanding better coordination. In addition, the wider set of operational choices available
to networks will need to be adequately reflected in network planning and management
decisions.
4.1.1 Need for increased coordination in network management
Traditionally the Distribution Network Operators (DNOs) own, build, maintain and operate
the distribution networks to be able to deliver power to consumers all year round. On the
other hand, the responsibility of the transmission network is split between Transmission
Owners (TOs) and System Operator (SO). TOs own, build and maintain the transmission
network while the SO maintains the demand-supply balance by coordinating activities of
market participants such that the safe operation of the system and network is maintained.
A sizeable share of distributed energy resource (DER), particularly the new flexibility
resource (e.g. DSR, storage, onsite generation and combined storage & generation
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facilities) are being connected at distribution networks.
21
As a consequence, there is a
need to have stronger coordination between transmission and distribution network
operators to enable use of all available flexibility resource to its full effect.
Imperial has analysed three types of network models to assess their relative benefits:
a) Coordinated operation and design of the transmission and distribution networks,
which would enable DER to be used to maximise the whole-system benefits by
managing the synergies and conflicts between local and national level objectives
(e.g. maximising the value of combined benefits delivered through energy arbitrage,
providing support to local and national network infrastructure, delivering various
ancillary services to optimise system operation, while reducing the investment in
conventional and low carbon generation).
b) Transmission centric model, which focuses on the use of available flexibility
resource for deferring transmission/interconnection investment and reducing system
operating costs, while ignoring the benefits of DER to the distribution network.
c) Distribution centric model, which focuses on managing local distribution network
operation and investment through applying DER for peak demand reduction at the
local network.
The savings due to integrating new sources of flexibility relative to the use of conventional
thermal generation based sources of flexibility, in all three models are shown in Figure 21.
It demonstrates that the coordinated (i.e. whole-system) approach may result in significant
additional savings in system operation and investment costs, i.e. between £1.1bn/yr and
£2.3bn/yr, relative to transmission or distribution network centric models.
Figure 21 Potential benefits of alternative operation and design models of the
network
Source: Imperial’s modelling analysis
21
Energy Network Association (ENA) is estimating 27.8GW of distributed generation currently
connected to the system.
http://www.energynetworks.org/assets/files/news/publications/Reports/TDI%20Report%20v1.0.pdf
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However, to realise these whole-system benefits, it will be critical to establish strong
coordination between distribution and transmission network operators by clearly defining
their future roles and responsibilities and through establishing appropriate regulatory and
incentives framework.
Some recent activities have attempted to clarify the future roles and responsibilities of
system operators. Ofgem and BEIS have recently proposed alternative models for the
future roles of system operators (at both transmission and distribution levels).
22
Ofgem
has also proposed
23
several changes
in the SO’s current role with the aim of creating an
independent SO where its role will be separated from the remaining functions of the
National Grid.
In this context, Transmission and Distribution Interface Steering Group of Energy Network
Association’s (ENA), also aims at providing the strategic direction and to identify
upcoming issues.
24
4.1.2 Complex system operation under updated network design standards to
facilitate efficient integration of flexibility resource
Network Capex avoidance is one of the main areas where potential savings have been
identified from deployment of alternative forms of flexibility. The replacement of network
asset-based (build) solutions with alternative commercial (non-build) solutions can reduce
the overall cost of developing, as well as operating, the system.
However, existing planning and operational standards for both networks and generation
systems were primarily developed around asset-based (build) solutions and did not
incorporate alternative solutions to meeting system operational requirements. With the
emergence of cost effective non-build solutions, an update of these planning and
operational standards is needed to establish a level playing field between traditional
network infrastructure and emerging flexible technologies.
For example, as shown in Figure 22, in order to meet a rise in demand in a given
distribution area, conventional network planning standards (e.g. N-1 or N-2) would
typically trigger the need to build an additional line with associated network infrastructure.
However, depending on the characteristics of demand in the area (e.g. if peak demand
turns up for a limited time per year), the use of distributed flexibility resource in network
operation (e.g. DSR, distributed generation and storage) can substitute the need for
network reinforcement. These flexibility sources can support network flows and voltage
management equivalently to the functions of network reinforcement and should be
considered where they are a more cost-effective solution.
22
BEIS and Ofgem Call for evidence ‘A Smart Flexible Energy System’, November 2016
23
Future arrangements for the electricity system operator: its role and structure, January 2017,
https://www.ofgem.gov.uk/system/files/docs/2017/01/future_arrangements_for_the_electricity_system_operator.pdf
24
Transmission and Distribution Interface Steering Group Report, ENA, December 2016
http://www.energynetworks.org/assets/files/electricity/regulation/TDI%20Report%20Dec%2016_final%20v0%2010%20211216.pdf
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Figure 22 Growing complexity in the future systems
Build solution following
conventional planning standard
Smart solutions (i.e. use of flexibility resource) that efficiently serve the same objective
as of the traditional planning standard
Another example of the potential for change in operational standards is the relaxation of
Rate of Change of Frequency (RoCoF) constraints. This will make the system more
flexible in accommodating relatively larger variations in system frequency driven by
imbalances in demand and supply.
A relaxation in the RoCoF standard from 0.25Hz/s to 0.5 Hz/s would, according to
Imperial’s modelling analysis, lower required frequency response and overall costs of
operating the system (as shown in Figure 23).
With rising penetration of wind capacity in the system, the savings driven by relaxing the
RoCoF constraint increase significantly. This suggests that a review of standards may be
appropriate given the changing nature of the electricity system to which they apply.
Figure 23 Potential benefits of RoCoF constraints
Source: Imperial’s modelling analysis
The network companies have initiated a case to carry out a thorough review of
Engineering Recommendation (ER P2). ER P2 has acted as the foundation stone for the
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planning of distribution networks for many decades. It is essentially unchanged from ER
P2/5 which was introduced in 1978. It therefore pre-dates the development of smart grids,
widespread distributed generation and active customers. Ofgem has fully supported this
initiative and the public engagement process assessing the P2 review
25
on the design of
the electricity distribution networks and changes to SQSS (GRS 022). Both of these are
considering changes related to new technologies like storage.
4.1.3 Growth in system complexity driven by cross-border flexibility sharing
With large increase in flexibility requirements in the future de-carbonised electricity
systems there is a need to explore all available flexibility sources including cross-border
flexibility resource.
Currently, interconnectors to the GB electricity system offer some flexibility on both sides
of the interconnectors based on energy arbitrage. However, system balancing services
are not shared across the border with the connected systems. This was mainly due to
lower need for flexibility requirements in the past and absence of a mechanism for GB to
participate in exchange of cross-border flexibility services. Recently, a pilot project
(Trans-European Replacement Reserve Exchange, TERRE
26
) has been initiated for
cross-national exchange of operating reserve between GB, France, Spain, Portugal, Italy,
Switzerland and Greece.
The cross-border sharing of flexibility, particularly of ancillary services, brings additional
complexity in system operation as the utilisation of diverse national flexibility resource
(available at both transmission and distribution connected) will need to be optimised
alongside the cross-border flexibility resource. This will also need another layer of
coordination between GB system operators and cross-border system operators.
Therefore, system operators will need to be prepared to utilise this resource and the
required coordination functions should be defined in their new roles and responsibilities
27
.
Imperial’s analysis of sharing balancing services with other systems through
interconnectors is shown in Figure 24 for two targets of CO
2
intensities in 2030
(100gCO
2
/kWh and 50gCO
2
/kWh). This indicates significant benefits for the GB system
from accessing cross-border flexibility. These benefits are driven by savings in low-
carbon generation capacity and system operation costs while meeting the 2030 carbon
intensity target for the power sector. The net savings are higher for a tighter
decarbonisation target case. These are driven by avoidance of energy curtailment
produced by renewables thus allowing meeting CO
2
targets with relatively lower installed
capacity of low-carbon technologies and back-up capacity (i.e. savings in generation
capex) and reduced requirements of interconnection capacity to export high volumes of
surplus intermittent generation during low demand periods in GB.
25
The Design of Electricity Distribution Networks Looking to the Future, Ofgem, May 2015
https://www.ofgem.gov.uk/publications-and-updates/design-electricity-distribution-networks-looking-future
26
TERRE is about setting up and operating a multi-TSO platform capable of gathering all the
offers for Operating Reserves and to optimise the allocation of these reserves across the
systems of the different TSOs involved.
27
Proposals on required modifications in the GB Balancing and Settlement Code (BSC) are
being developed for implementing TERRE in the BSC. (Elexon, Implementing TERRE in the
BSC, October 2016)
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Figure 24 Potential benefits of sharing balancing services via interconnection
Source: Imperial’s modelling analysis
4.1.4 Actions on roles and responsibilities of system operators
To manage the complexity in the future systems and, indeed, to enable some of the
innovative new flexibility solutions to emerge, the system operator role will need to be
significantly more proactive. While a core aspect of this will be the interactions between
transmission and distribution systems, it also encompasses the linkages with and between
consumers, suppliers and third party intermediaries, and increased coordination with
cross-border system operators. An efficient operation of the smart system will therefore
need a clear outline of the roles, responsibilities and interfaces between the various
actors. In addition, there is a need to ensure that the regulatory framework adapts to
facilitate the growing diversity of choices open to system operators in managing and
controlling their systems.
The following action is proposed regarding the future role and responsibilities of system
operators in GB.
Publish a strategy for developing the longer-term roles and responsibilities of system
operators (including transitional arrangements) that incentivises system operators to
access all flexibility resource and be prepared to handle additional complexity in the
system, by making investments and operational decisions that maximise total system
benefits.
Responsible: Ofgem in
coordination with industry
2018
High priority
A separate action to support innovation and test new flexibility solutions (e.g. to develop
new network design standards, coordination platforms for system operators, etc.) is
proposed in Section 5.2.
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4.2 Development of energy and smart-enabling infrastructure needs
to be well-coordinated
The investment in the enabling infrastructure for future smart energy systems is being
undertaken by a number of independent players including not only the energy network
operators but providers of complementary ICT infrastructure. Having a strategy that
enables coordination of all smart infrastructure will provide:
a transparent way to map individual investment programmes for identify critical
interdependencies and/or misalignments; and
the risks associated with delays in one area and how those would limit the realisation
of the full capability of a smart system and potentially wider implications (including
costs) for the energy system and consumers.
Our recommendation for a coordinated strategy could be similar to the National
Infrastructure Commission’s (NIC) current approach for initiation of coordination in
infrastructure developments
28
,
29
for which the NIC plans to publish a Vision and Priorities
document in summer 2017.
Smart metering is an enabling technology that will help to address a number of challenges
in the move towards smart energy systems. However, a number of issues have been
identified with the smart meter roll-out programme which may potentially affect the
expected benefits and objectives of the programme. Some of the identified include:
Effect of programme delays on economic benefits the updated cost-benefit
modelling of government’s smart meter roll-out programme
30
that takes account of the
new evidence on actual smart meters deployment progress, reduces the Net Present
Value (NPV) of the programme by around £1,013m (due to a £534m reduction in
costs and a £1,548m reduction in benefits. This reduction of benefits is primarily
driven by delays in installations of smart meters in comparison to the expectations
reflected at the start of programme in 2014.
Lack of interoperability of first-generation of SMETS1 meters (with over 5 million
SMETS1 meters or earlier smart meter versions already installed) impact of this
installation on the market is also not well understood (e.g. risk of stranded costs and
customers being deterred to seek best deals).
Optimistic predictions regarding the ease and cost of installations between 10-15
percent of properties may require more than one visit (compared to government’s
expectation of 5 percent of properties) in order to complete installations pushing up
the cost by as much £1 billion.
31
The central communication system for smart meters is still lacking in a number of
core areas. These include a 12 months delay in the major ‘go-live’ event of the
28
Cambridge Milton Keynes Oxford: 'growth corridor' call for evidence, NIC, May 2016
https://www.gov.uk/government/consultations/cambridge-milton-keynes-oxford-growth-corridor-call-for-evidence/cambridge-milton-keynes-
oxford-growth-corridor-call-for-evidence
29
National Infrastructure Assessment Call for Evidence, NIC, November 2016
https://www.gov.uk/government/publications/national-infrastructure-assessment-call-for-evidence
30
Smart meter roll-out cost-benefit analysis, BEIS, August 2016
31
Warning by The Big Deal (a collective switching enterprise), and Utility Week’s research
showing that currently 13% of properties are requiring more than one visit for completion of
installation
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system and communication issues with SMETS2 meters, prepay meters and meters
in multiple occupancy dwellings with a knock on effect to the deployment of SMETS2
meters.
The heavy cost burden imposed of the roll-out programme to suppliers investing (in £
billions) in IT systems, regulatory compliance and installation contracts is potentially
resulting in resource squeeze for innovation via new products such as Time of Use
(ToU) tariffs and connected home services.
32
The action to enhance coordination of energy and energy-related infrastructure plans is
proposed below.
Publish a smart infrastructure strategy to integrate existing plans relating to energy
technologies (e.g. smart meter, public EV charging and interconnectors) and associated
ICT infrastructure (e.g. broadband roll-out) to ensure coordination of actions based on
identifying and managing risks to delivery of a smart electricity system.
Responsible: BEIS and NIC
By end 2018
Medium priority
32
EY expert view reported in Utility Week, 12-18 May 2017
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5. ENSURING INNOVATION SUPPORT
Innovation will be at the heart of the low-carbon transition affecting the whole value chain,
with anticipated developments in:
network management models (e.g. dynamic network operation and control);
supplier/aggregator models to facilitate provision of flexibility to system operators;
emerging and new flexibility providing technical solutions (e.g. DSR, Storage, inertia
provision from intermittent generators and highly flexible conventional thermal
generators); and
accessing flexibility from other energy sectors (e.g. heat and has sectors).
Future market and regulatory arrangements should aim to continue to support innovation
not only through clear signals and low entry barriers but also, where appropriate, through
ongoing support for research and development. This is especially true where solutions
are at early stages of commercialisation due to the immaturity of the technology or limited
market scope until higher penetration of renewable generation is realised.
5.1 Continued support is required to ensure learning in developing
innovative flexibility solutions
As flexibility requirements are growing and technologies emerging, the scope for
alternative solutions will also increase. These solutions will need to be investigated to
better understand where they can add most value and what the specific costs and risks
associated with their use are for users and network operators. Without direct support the
development of some of these options may be slow and the adoption by wider industry
hindered due to lack of shared knowledge. In the short-term, therefore, we see the need
for ongoing support to:
test and develop new system planning and operational approaches incorporating non-
build solutions. This will allow the system operators to assess and manage the risks
associated with innovative approaches to network operation & control; and
encourage development of pre-commercial technologies. Support now should be
targeted on continuing technical learning to improve efficiency, reduce costs and to
improve understanding and demonstration of the services that can be provided while
preventing lock-in to less efficient technologies.
This will also allow the developers of flexibility solutions in GB to export the developed
technologies, operational models and knowledge to other countries.
5.1.1 Developing new planning and operational approaches
As discussed in the last chapter (Section 4.1) the smart electricity system will need new
planning and operational standards in order to efficiently use non-build solutions.
However, in the shift from an asset led conventional system to a smart future system,
research and development support as well as appropriate incentivisation will be required
for testing new (generation and network) standards. This should address trade-offs
between the build and non-build solutions and focus on improving understanding of:
risks to safe operation of the system;
the implications to security of supply; and
costs and benefits of a range of alternatives.
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Ofgem reviewed the level of funding and criteria of the projects under the Network
Innovation Allowance (NIA) and the Network Innovation Competition (NIC) arrangements
with an aim of delivering more value to the consumer from the use of smart technologies.
The changes have been proposed in the associated consultation
33
process and the
development of an industry innovation strategy.
The current RIIO price control framework is designed with an intention that it would lead to
a more innovative approach to managing the transmission and distribution networks. The
TOTEX approach is intended to facilitate smart and non-build solutions for network
management and system operation. However, we are still in the first price-control cycle
under RIIO and much of the innovation is being driven through explicit innovation funding
mechanisms such as the NIA and NIC. When networks start to prepare their business
plans for the second RIIO controls (commencing in 2021 for transmission and 2023 for
distribution) we would expect to see a much stronger role for smart solutions in TSO/DSO
network development and operational plans.
In order to support and incentivise innovation in testing and developing new planning and
operational approaches and standards the relevant actions are proposed below.
Periodical review of existing system planning and operational standards for networks
and generation, assessing whether they provide level-playing field to all technologies
including active network management and non-build solutions (e.g. storage and DSR),
and revise these standards as appropriate.
Responsible: Industry codes
governance and Ofgem
Initial review by 2019
Priority: High
Ensure that the second RIIO price-control framework provides a transparent process
that incentivises efficient investment and trade-off between build and non-build (e.g.
storage and DSR) solutions in future network investment programmes.
Responsible: Ofgem
2020
Priority: Medium
5.1.2 Improving technical and cost performance of emerging flexibility resource
The benefits of smart technologies for the system depend on early deployment to realise
technical reliability and economies of scale and learning by doing. In this context, the UK
can possibly lead innovation in the area of:
system integration, IT platforms and infrastructure,
novel commercial arrangements and business models;
risk identification and their mitigation associated with technologies such as storage
and DSR; and
implementation of promising new operational and planning concepts such as virtual
power plants.
Research and development in this area will allow future technological improvements and
avoid technological lock-in.
33
The network innovation review: our consultation proposals, Ofgem, December 2016
https://www.ofgem.gov.uk/system/files/docs/2016/12/innovation_review_consultation_final.pdf
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The potential and implications of intermittent generators (wind and solar) in providing
flexibility services is not fully understood and there are limited incentives on renewable
generators to provide system flexibility in GB. Since the growth in renewable generation
drives the need for more flexibility while at the same time displacing conventional thermal
plant that traditionally has been the source of this flexibility, enhancements in the
capability of renewable generation to offer some of these services would be beneficial.
There is evidence that wind farms can provide some of these services and hence lower
the costs associated with provision of flexibility. Studies on provision of synthetic inertia
(SI) by wind generation show that at 60GW wind capacity installed, the annual costs
associated with frequency response provision can be halved if wind provides SI, as shown
in Figure 25.
34
Figure 25 Benefits of providing Synthetic Inertia by wind
Source: Imperial’s modelling analysis
There are different ways in which SI from intermittent renewable sources can be exploited.
For example, through changes in the industry codes as in 2005, Hydro-Québec (North
American utility, 40GW peak load) amended its grid code that new wind turbines be
capable of delivering a power boost equal to six percent of their rated capacity during low-
frequency events. Manufacturers responded with synthetic inertia designs, and the first
were installed in 2011. Today, inertia-compliant turbines account for two-thirds of
Quebec’s wind capacity.
35
However, this may not be the best solution for the GB system
as a large amount of wind capacity is already installed and the ease and cost of
retrospectively applying the new requirements to existing generators is unknown.
Furthermore, we may not need all plant to be able to provide this.
Another approach to exploit the flexibility resource embedded in intermittent generation
sources is market incentivisation for example, through remuneration of inertia provided
by generators (i.e. synthetic inertia in case of wind generation).
34
This study assumes 1800MW as the biggest outage in the system.
35
Can Synthetic Inertia from Wind Power Stabilize Grids?, IEEE, Peter Fairly, 2015
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5.1.3 Investigating provision of flexibility from other energy sectors
In addition to the flexibility available from technologies within the power sector, there is
significant potential to access flexibility embedded in other energy sectors, particularly the
heat and gas sectors. However, understanding the effectiveness and implications of
exploiting this flexibility resource needs further research and analysis.
Imperial College has conducted an initial analysis to quantify the potential benefits of
exploiting the flexibility potential from the heat and gas sectors. This analysis
demonstrates that coordination of design and operation of different energy vectors can
potentially bring significant benefits and that coordinated policy, regulation and market
measures will be important for cost effective decarbonisation of the energy system.
5.1.3.1 Interaction between electricity and heat sectors
A higher degree of integration between electricity and heat sectors presents unique
opportunities to make use of cross-vector flexibility to support the integration of low-
carbon generation technologies and to significantly reduce the cost of decarbonisation.
A modelling based analysis of coordinated design and operation of low carbon heat and
electricity systems, which assumed heat demand is met by heat networks in which
Combined Heat and Power (CHP), industrial network heat pumps (NHP) and thermal
energy storage (TES) are used, was carried out by Imperial. Where the heat system was
decoupled from the electricity system (i.e. it did not provide flexibility services like reserve
and response service), costs of operating the overall system were higher than the case
when they were integrated (as shown in Figure 26).
Figure 26 Savings from integrated heat and electricity system operation
paradigm (High wind scenario)
Source: Imperial’s modelling analysis
The net benefits of coordinated operation of the heat and electricity system were between
£2.4bn/year and £5.4bn/year for 100gCO
2
/kWh and 50gCO
2
/kWh scenarios (by 2030)
respectively. Given that CHP can provide ancillary service to the electricity system
besides providing heat, which enhances the overall generation efficiency, CCGT plant
would be replaced by CHP in the integrated system, delivering fuel cost savings.
Furthermore, increase in efficiency achieved through coordinated operation of heat and
electricity sectors can achieve carbon targets with reduced amount of low carbon
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generation. It can also be observed that a higher penetration of CHP leads to the
reduction in the amount of industrial NHP capacity, which also reduces high-voltage
distribution network reinforcement requirements.
5.1.3.2 Interaction between gas and electricity system
The future growth of intermittent generation will also increase the complexity of gas
network management as gas plant is expected to play a significant role in providing
flexibility. Unlike electrical energy, it takes a significant amount of time to transport gas
from supply sources (terminals and storage facilities) to gas demand centres. One of the
cost effective solutions to deal with this would be to enhance the flexibility of gas network
infrastructure by installing multi-directional compressors that can deal with the growing
variability in the gas demand across the system.
A high-level modelling analysis was carried out by Imperial for assessing the value of
flexibility in the gas system for supporting the electricity system. Figure 27 shows that
enhancing the flexibility of gas infrastructure (improves the operability of gas generation
and reduces more costly coal generation and interconnection imports. This would deliver
annual reduction in operating cost of £612m and does not account for the reduced amount
of low carbon generation needed to meet the carbon target.
Figure 27 Change in energy production facilitated by enhanced flexibility of gas
network through multi-directional compressors (illustrative example)
Source: Imperial’s modelling analysis
5.2 Action to ensure innovation
We have proposed the following action to ensure that innovation is supported in improving
technical performance and costs of emerging technologies and in developing novel
system operation and control approaches, and commercial models.
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Ensure a supporting environment (e.g. research, development and innovation funding
support, price control frameworks, etc.) for continued innovation and learning in the
following key areas:
improvements in the flexibility of conventional technologies and in the reliability and
efficiency of emerging technologies;
managing risks associated with the application of the new system operation
model(s) based on emerging technologies and control systems;
building evidence base on costs associated with DSR in different consumer
sectors;
managing synergies and conflicts in the operation of transmission, distribution and
cross-border interconnection functions of the system;
understanding consumer responses to new tariff offerings (e.g. HH tariffs) by
suppliers;
understand current and future potential and implications (e.g. levels of renewable
energy curtailment, impact on CO
2
emissions, etc.) of providing flexibility from
intermittent renewables; and
investigating the provision of flexibility from other energy sectors (e.g. heat and gas
sectors).
Responsible: BEIS, Ofgem
Ongoing
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6. ENSURING EFFECTIVE CONSUMER PARTICIPATION
Demand Side Response (DSR) is already an established flexibility option. There is a lot
of latent DSR resource available across different demand sectors (i.e. industrial,
commercial, public sector and domestic sectors) but currently it does not form a significant
share of any flexibility service in GB. Access to this potential flexibility source will require:
educating and informing consumers about the ongoing changes in the system and the
opportunities these bring as a result of their ability to provide flexibility to the system;
and
ensuring that the consumers are protected i.e. not exposed to undue risks such as
those associated with their security of supply, cyber security and affordability.
6.1 Consumers need to be better informed about the benefits that a
smart system offers them
The potential flexibility provision through DSR, the nature of the service, the terms on
which it would be available and the necessary investment to access it varies across
consumer groups. Especially for domestic consumers, the absence or limited information
on the implications of DSR provision is seen as a potential barrier to future uptake of
DSR-related offerings as technology and market conditions make such opportunities more
prevalent in the market
Potential issues that would hinder the uptake of DSR include:
lack of value as the service is not remunerated for all benefits delivered to the system;
limited availability of simple and practical offerings by market players to customers
enabling them to participate;
perceived complexity (e.g. managing the DSR/smart enabling kits or devices
particularly in case of domestic consumers);
a culture of maintaining status quo, for example, in the public and industrial sectors;
perceived loss of control/comfort and autonomy in energy use when it is required;
lack of trust between consumers and market players, partially due to poor consumer
understanding and lack of communication between the two parties; and
the perception of risk that bills will be higher if consumers are unable to adapt
behaviour as anticipated.
Many of the above discussed barriers can be removed through transparent and consumer
focused awareness programmes. However, as discussed earlier in Chapter 4, it is critical
that DSR providers can access the full range of revenue streams.
According to research by DECC (now BEIS)
36
, 76% of British consumers reported
knowing either nothing or very little about smart meters
37
which is a fundamental enabler
of residential DSR. Similarly, according to another analysis on public perception of the UK
36
The British public’s perception of the UK smart metering initiative: Threats and opportunities,
Kathryn Buchanan, Nick Banks, Ian Preston, Riccardo Russo, Energy Policy, Elsevier, 2016
37
Quantitative Research into Public Awareness, Attitudes and Experience of Smart Meters:
Wave 4, DECC (now BEIS), 2014
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smart metering initiative
38
, consumers are sceptical about the motivation of suppliers to
promote smart meters and the services to be offered through these meters.
This demonstrates a need to educate domestic consumers as to how smart meters can
widen the types of tariff offering they can choose between and the wider opportunities for
active engagement with the market through provision of DSR for the system.
There are also some other natural barriers to large scale uptake of DSR. In particular,
since much DSR is linked to the deployment of smart appliances, slow roll-out of smart
appliances in line with natural product replacement cycles will prevent the full potential of
domestic DSR being accessed quickly. According to a review by Deloitte on internet-
connected appliances for households
39
, two-thirds of consumers were not intending to buy
any such appliances in the next 12 months, as shown in Figure 28. This not only limits
the uptake of domestic DSR but also has knock-on implications for incentives amongst
manufacturers to increase production of smart appliances.
Figure 28 Consumer Choice of Connected Devices
Source: Switch on to the connected home, The Deloitte Consumer Review”, July 2016
The ‘Smart Energy GB’ organisation is building consumer awareness related to smart
meters and the benefits it offers. National Grid has been facilitating a campaign
40
, which
aims to encourage participation in several forms of flexibility technology in the electricity
market by raising the awareness on the benefits of smart technologies.
In order to raise consumer trust and awareness regarding opportunities offered by DSR as
well as brining transparency and clarity on risks (often perceived) we have proposed the
38
The British public’s perception of the UK smart metering initiative: Threats and opportunities,
Kathryn Buchanan, Nick Banks, Ian Preston, Riccardo Russo, Energy Policy, Elsevier, 2016
39
Switch on to the connected home, The Deloitte Consumer Review, July 2016
40
Power Responsive Campaign
http://powerresponsive.com/
Consumer ownership of connected devices
Intent to purchase within 12 months
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first action as proposed in the below given below. The second and third actions in the box
are related to monitoring the progress on DSR.
Introduce an education / awareness programme to inform industrial, commercial, public
sector and domestic consumers of the opportunities (e.g. remuneration for provision of
flexibility services and/or reduction in electricity bills), and clarify the materiality of
perceived risks.
Responsible: System operators,
Suppliers, CAB, BEIS
Ongoing, linked to
implementation
programmes
n/a
Assess uptake of DSR and any constraints thereof, and if required take action to
encourage effective DSR participation (e.g. product standardisation and fiscal
incentives).
Responsible: BEIS and suppliers
2020 onwards
Low priority
Review minimum standards of all smart related equipment (appliances and ICT kits) to
ensure their cyber security, interoperability, user friendliness and high energy efficiency
performance.
Responsible: BEIS,SO, DSOs
and OEMs
2020 onwards
Low priority
6.2 Consumers protection will need to be ensured to build trust for
DSR participation
In order to facilitate effective participation of consumers in DSR, a critical requirement is to
ensure that consumers have trust in the following two aspects:
security of equipment and software; and
upholding privacy and appropriate use of data.
These concerns are linked to each other for example, a cyber-attack can also lead to
leakage of data to parties who are not allowed to have access to such information.
6.2.1 Security of equipment and software
Smart technologies are based on information, communication and online data transfer
technologies which are being continuously evolved and are vulnerable to cyber-attacks.
41
Therefore, consumers are concerned about the protection of their smart equipment (i.e.
smart devices, appliances, kits and the data processing and communication programmes)
against cyber-attacks.
41
The internet of things: how your TV, car and toys could spy on you, The Guardian, February
2016
https://www.theguardian.com/world/2016/feb/10/internet-of-things-surveillance-smart-tv-cars-toys,
https://www.theguardian.com/technology/2015/nov/30/vtech-toys-hack-private-data-parents-children
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At present, the Government’s National Cyber Security Strategy
42
covers the necessary
steps for maintaining cyber security of the energy industry covering the increasing usage
of smart appliances in the power grid.
6.2.2 Upholding privacy and appropriate use of data
Consumers also see risks around sharing data via the internet that was collected from
their smart appliances and smart meters. These concerns have been intensified by
reported incidents that smart appliances were spying on people. This requires placement
of robust systems to mitigate the risk.
The data privacy framework (for consumption data from smart meters) is set out in the
licences of suppliers and DNOs and the Smart Energy Code
43
, which sets out the rules on
the ownership, access and usage rights of customer data collected from smart meters.
6.2.3 Recommended actions on building consumer trust for DSR participation
BEIS has commissioned a study
44
to build understanding on the motivating factors and
barriers that drive small energy users’ decision making around demand side response.
The study is also expected to propose products, services, policies and engagement
strategies that could be most effective at achieving DSR at scale amongst these users.
In order to protect customers and build their trust we have proposed the following actions
for their effective participation in provision of DSR.
Ensure that an effective system remains is in place to comprehensively and continuously
assess, monitor and mitigate cyber security risks to the operation of future smart
electricity system and integrity of related smart infrastructure.
Responsible: BEIS and DCC in
coordination with SO/DSO,
NCSC and CAB
Ongoing
Keep under review the ownership, access and usage rights of customer data collected
from smart meters and other smart devices, and if necessary amend these rights to strike
appropriate balance between data access by market participants and consumer privacy.
Responsible: BEIS in
coordination with industry
Ongoing
42
National Cyber Security Strategy 2016-2021, HM Government
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/567242/national_cyber_security_strategy_2016.pdf
43
Smart Energy Code, March 2017
https://www.smartenergycodecompany.co.uk/docs/default-source/sec-documents/smart-energy-code-5.5/sec-5-5---15th-march-
2017.pdf?sfvrsn=6
44
Realising the Potential of Demand-Side Response to 2025 A focus on Small Energy Users,
(work in progress), BEIS, October 2016
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7. SUMMARY OF THE FLEXIBILITY ROADMAP AND
INDICATOR FRAMEWORK
This chapter provides a summary of the recommended actions that will be required to
facilitate provision of increased levels of flexibility in the future GB system.
In addition to the roadmap actions we have also proposed a set of indicators in order to
assess the progress on the roadmap.
7.1 Flexibility roadmap actions
All actions in the roadmap are grouped in the following four key areas:
ensure efficient investment decisions in providing increased flexibility services;
develop capability to manage greater complexity in future smart electricity
systems;
ensure innovation support for improvement in technology, testing new
operating/business models and to develop understanding of consumer response to
alternative offerings by market players; and
ensure effective consumer participation for exploiting demand flexibility potential.
For each action, we describe (a) the primary responsible party; (b) the timeframe over
which action is required; and (c) the priority of the action, as set out in Table 4.
Table 4 Flexibility roadmap
Action
Responsible
Time
frame
Priority
Actions to ensure efficient investment
Publish annual projections (in each year) of longer-term future
procurement requirements across all flexibility services including
indication of the level of uncertainty involved and where possible
location specific requirements, to provide greater visibility over future
demand of flexibility services.
SO and DSOs
2020
onwards
High
Periodical assessment of existing flexibility services to identify services
that may be procured more efficiently through transparent and
technology-neutral processes in the future and reform their
procurement processes accordingly.
SO and DSOs
Initial
assessment
by 2020
Medium
Review characteristics of current procurement processes (e.g.
threshold capacity level to participate, contract terms / obligations) and
the procurement route (e.g. open market, auctioning or competitive
tendering) that enable more efficient procurement of services without
unduly restricting the provision of multiple services by flexibility
providers.
Ofgem in
conjunction with
SO, TOs and
DSOs
By 2020
High
Assess the materiality of distortions to investment decisions in the
current network charging methodology (e.g. lack of locational charging,
double-charging for stored electricity), and reform charging
methodology where appropriate.
SO, DSOs, and
Ofgem
By 2020
High
Assess the materiality of distortions to investment decisions in the
absence of non-network related system integration charging (i.e. back
up capacity and ancillary services) and implement charging where
appropriate.
SO, DSOs, and
Ofgem
By 2020
High
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Action
Responsible
Time
frame
Priority
Actions to develop capability to manage greater complexity
Publish a strategy for developing the longer-term roles and
responsibilities of system operators (including transitional
arrangements) that incentivises system operators to access all
flexibility resource by making investments and operational decisions
that maximise total system benefits.
Ofgem in
conjunction with
industry
2018
High
Publish a smart infrastructure strategy to integrate existing plans
relating to energy technologies (e.g. smart meter, public EV charging
and interconnectors) and associated ICT infrastructure (e.g.
broadband roll-out) to ensure coordination of actions based on
identifying and managing risks to delivery of a smart electricity system.
BEIS and NIC
By end 2018
Medium
Actions to ensure innovation support
Periodical review of existing system planning and operational
standards for networks and generation, assessing whether they
provide level-playing field to all technologies including active network
management and non-build solutions (e.g. storage and DSR), and
revise these standards as appropriate.
Industry codes
governance and
Ofgem
Initial review
by 2019
High
Ensure that the second RIIO price-control framework provides a
transparent process that incentivises efficient investment and trade-off
between build and non-build (e.g. storage and DSR) solutions in future
network investment programmes.
Ofgem
2020
Medium
Ensure a supporting environment (e.g. research, development and
innovation funding support, price control frameworks, etc.) for
continued innovation and learning in the following key areas:
- improvements in the flexibility of conventional technologies and in the
reliability and efficiency of emerging technologies;
- managing risks associated with the application of the new system
operation model(s) based on emerging technologies and control
systems;
- building evidence base on costs associated with DSR in different
consumer sectors;
- managing synergies and conflicts in the operation of transmission,
distribution and cross-border interconnection functions of the system;
- understanding consumer responses to new tariff offerings (e.g. HH
tariffs) by suppliers;
- understand current and future potential and implications (e.g. levels of
renewable energy curtailment, impact on CO2 emissions, etc.) of
providing flexibility from intermittent renewables; and
- investigating the provision of flexibility from other energy sectors (e.g.
heat and gas sectors).
BEIS and Ofgem
Ongoing
Actions to ensure effective consumer participation
Introduce an education / awareness programme to inform industrial,
commercial, public sector and domestic consumers of the
opportunities (e.g. remuneration for provision of flexibility services
and/or reduction in electricity bills), and clarify the materiality of
perceived risks.
System
operators,
Suppliers, CAB,
BEIS
Ongoing,
linked to
implementati
on
programmes
Assess uptake of DSR and any constraints thereof, and if required
take action to encourage effective DSR participation (e.g. product
standardisation and fiscal incentives).
BEIS and
suppliers
2020
onwards
Low
Review minimum standards of all smart related equipment (appliances
and ICT kits) to ensure their cyber security, interoperability, user
friendliness and high energy efficiency performance.
BEIS,SO, DSOs
and OEMs
2020
onwards
Low
Ensure that an effective system remains in place to comprehensively
and continuously assess, monitor and mitigate cyber security risks to
the operation of future smart electricity system and integrity of related
smart infrastructure.
BEIS and DCC
in conjunction
with SO/DSO,
NCSC and CAB
Ongoing
Keep under review the ownership, access and usage rights of
customer data collected from smart meters and other smart devices,
and if necessary amend these rights to strike appropriate balance
between data access by market participants and consumer privacy.
BEIS in
conjunction with
industry
Ongoing
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7.2 Progress monitoring framework
This section describes the indicators that can be used by the CCC in order to monitor
progress on the flexibility roadmap.
The indicators and monitoring framework serve the following two main purposes:
monitor whether the proposed actions are being implemented in line with the
roadmap; and
to assess the impact of actions i.e. actual progress in the market around
assimilating ‘smart’, flexible solutions.
7.2.1 Performance against specific actions
In relation to specific actions recommended in the roadmap we have, where appropriate,
defined a time frame for completion of the action. Where actions are ongoing, this is
noted separately.
Any delay in the completion of actions will need investigation to understand the reasons
for such delay and its knock-on effect (if any) on other actions and wider achievement of
decarbonisation objectives.
For the ongoing actions, a periodical monitoring will be required to check that progress is
in line with the requirements and objectives set out in the roadmap.
7.2.2 Performance of the market in general
The challenge with developing any quantitative metrics is that there is no precise target for
particular forms of flexibility provision. This is driven by the uncertainties around:
relative costs and technical performance of different types and distribution of flexibility
sources;
long-term evolution of supply mix as multiple generation mixes can deliver the
decarbonisation targets;
the development of market and regulatory framework; and
the social and cultural aspects associated with effective participation of DSR.
Considering this uncertainty, the roadmap is developed with the aim that it would provide
a technology neutral environment that facilitates optimal uptake of most efficient and cost
effective flexibility technologies. Therefore, the focus of actions has been around creating
unbiased incentives, improving fair access terms and minimising the risk of lock-in to
existing or inefficient technologies.
In the above context, we first identified a range of key metrics that can provide information
on market entry and participation of new technologies alongside ongoing changes to
realise maximum flexibility potential. These include:
overall deployed volume of low-carbon flexibility resource ((e.g. storage/DSR capacity
(MW)) and their impact (e.g. peak demand reduction (MW) due to storage /DSR);
growth in market penetration of low-carbon flexibility resource (e.g. volume/capacity
of DSR and storage participating in relevant market platforms, proportion (%) of DSR
and storage operators providing system balancing services, etc.); and
other progress indicators (e.g. number and size of aggregators in the market, growth
in roll-out rate of smart appliances, etc.).
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The use of the above metrics as indicators to monitor progress will potentially require:
a significant amount of underlying data which should be readily available to the CCC
in order to quantify the relevant indicator; and
benchmarks to compare the quantified values of indicators to gauge progress.
Considering difficulties in meeting these requirements e.g. absence of any established
benchmarks of the identified indicators there is a need for simple and easy to apply
indicators. Therefore, we propose that the deployment of additional capacity of flexible
technologies should be used as the key indicator to measure the impact of roadmap
actions.
Based on the modelling analysis undertaken as part of this study for alternative future
generation scenarios, we have assessed the required range of additional capacity of
different flexible technologies to efficiently meet 2030 carbon intensity targets. The central
levels of additional capacity of flexible technologies are to be used to track progress on
deployment of technologies in a given period. It is expected that a trade-off between
various technologies will also take place. For example, lower deployment of additional
storage may be compensated by higher uptake of another technology thus meeting the
system’s overall flexibility requirements. However, a consistent low deployment of one or
more technologies across several years could be seen as a flag for further investigation
e.g. to identify if there is a specific barrier that is hindering the deployment of the
technology or affecting its competitiveness against other flexibility technologies
Figure 29 shows these additional capacity requirements based on the modelling analysis
undertaken as part of this study. The low and high levels for a given flexibility technology
are based on its range of penetration across the four main future scenarios investigated in
this study (see Section A.2 for scenario details) whereas the central level shows the
middle point of the range.
The central levels of additional capacity of flexible technologies are to be used to track
progress on deployment of technologies in a given period. It is expected that a trade-off
between various technologies will also take place. For example, lower deployment of
additional storage may be compensated by higher uptake of another technology thus
meeting the system’s overall flexibility requirements. However, a consistent low
deployment of one or more technologies across several years could be seen as a flag for
further investigation e.g. to identify if there is a specific barrier that is hindering the
deployment of the technology or affecting its competitiveness against other flexibility
technologies.
Figure 29 Potential levels of flexibility providing capacity (GW)
Source: Imperial’s modelling analysis
Low Central High Low Central High Low Central High
New flexible generation 1 3 5 2 6 10 3 9 15
Storage 0.8 2.9 5 3.2 11.6 20 5.6 20.3 35
DSR 2.1 6.3 10.5 2.76 8.28 13.8 3.42 10.26 17.1
Interconnection 3.4 3.4 3.4 4.45 5.825 7.2 5.5 8.25 11
By 2030
Flexible technology
By 2020
By 2025
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Considering the value and scalability of DSR we also propose that the following two
indicators can also be used to assess the progress for this particular flexibility resource.
growth in number and size (i.e. total contracted volume, MW) of aggregators
providing DSR-based flexibility in the market; and
growth in the share of smart appliances as a percentage of total appliances sold each
year.
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ANNEX A SYSTEM EVOLUTION PATHWAYS TO MEET
THE CARBON INTENSITY TARGETS
This annex provides further details on the scenarios modelled in this study. These
scenarios are described in terms of the future demand and supply backgrounds. In
addition to the scenario description, a high-level overview of Imperial’s modelling
methodology and key modelling assumptions are also provided.
A.1 Carbon targets
The core scenarios postulate that by 2030, the carbon intensity of the UK power sector
should reach 100gCO
2
/kWh and by 2050, it will be reduced substantially to 10gCO
2
/kWh.
In order to understand the importance and the implications of having more ambitious
target, as part of the sensitivity analysis, a second carbon reduction trajectory is also
analysed with 50gCO
2
/kWh as the target in 2030. The two trajectories of the carbon
intensity targets per 5 year period assumed in the study are shown in Figure 30.
Figure 30 Carbon intensity targets for the GB power sector (gCO
2
/kWh)
Source: Imperial’s modelling assumptions
In order to reduce carbon intensity, the share of electricity production from low-carbon
generation needs to increase. The sharp reduction of carbon emissions from 2020 to 2030
suggests a significant shift from fossil fuel based power generation towards sustainable
and low-carbon generation technologies.
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A.2 Modelled scenarios
Four scenarios have been developed and analysed in this study include:
Balanced scenario: assumes balanced development across different low-carbon
technologies (i.e. nuclear, CCS and renewables). The scenario is based on the
extrapolation of the CCC power sector scenarios.
45
High PV scenario: assumes a large deployment of PV which significantly exceeds
the development of other low-carbon technologies. This would be facilitated by a
rapid decrease in the cost of solar cells, massive technology development in this
area, and incentives given to the PV industry to stimulate significant growth.
High offshore wind scenario: as the UK has one of the best wind sources in the
world, this scenario reflects extensive exploitation of this large energy potential for
decarbonisation of the UK electricity industry.
High nuclear and CCS scenario: assumes that the future decarbonisation of the
system will depend on the energy production primarily from nuclear and CCS.
Figure 31 shows the projected installed capacity of different low-carbon technologies
between 2020 and 2050 in each scenario.
Figure 31 Capacity of low-carbon generation technologies in different scenarios
45
Power sector scenarios for the fifth carbon budget, The Committee on Climate Change (UK),
October 2015
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A.3 Modelling inputs and assumptions
A.3.1 Electricity demand
It is envisaged that heat and transport sector decarbonisation by electrification will
substantially increase electricity demand in the future. Through our bottom-up modelling
of heat and transport demand, the projected growth of the overall annual electricity
demand is determined as shown in Figure 32. Our demand projection has considered the
increased energy efficiency in all sectors. During this 30 years period, the load will grow
almost double from around 340 TWh to 640 TWh.
The net increase in the future electricity demand is primarily driven by the electrification of
heat and transport sectors; while the net demand growth in other types of loads is
relatively limited. By 2050, electricity demand attributed to heat and transport sectors will
reach about 35% of the overall annual electricity demand.
Figure 32 Electricity demand growth
Source: Imperial’s analysis of the CCC scenarios
The projected growth in peak electricity demand between 2020 and 2030 is shown in
Figure 33. Since the load factor of electric vehicles and heat pumps are relatively low
compared to the other demand types, and the peak load of these technologies potentially
coincides with the UK peak demand periods, the inclusion of those technologies will
increase the peak of electricity load significantly.
The peak demand, without demand side response, will increase about three times from 60
GW today to around 180 GW in 2050. As the rate of growth in peak demand (without
DSR) is higher than the rate of growth in annual electricity demand, the average load
factor will decrease. Therefore, the utilisation factor of the assets (generation and
networks) will reduce indicating a reduction in the investment efficiency.
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Figure 33 Increased peak of electricity demand (without DSR)
Source: Imperial’s analysis of the CCC scenarios
A.3.2 Demand side response
It is expected that new electricity demand categories such as electrified heating or
transport will play an increasingly important role in decarbonising the energy sector.
Based on our understanding of specific features of these demand sectors, and have
developed detailed bottom-up models to produce hourly demand profiles employing large
databases of transport behaviour and building stock data.
Understanding characteristics of the flexible demand and quantifying the flexibility they
can potentially offer to the system is vital to establishing its economic value of DSR.
46
In
order to offer flexibility, controlled devices (or appliances) must have access to some form
of storage when rescheduling their operation (e.g. thermal, chemical or mechanical
energy, or storage of intermediate products). Load reduction periods are followed or
preceded by load recovery, which is a function of the type of interrupted process and the
type of storage. This, in turn, requires bottom-up modelling of each individual demand
side technology to simulate actual service functions while exploiting their flexibility without
compromising the service that it delivers. In our analysis, we consider various types of
flexible demand.
47
,
48
,
49
,
50
,
51
,
52
,
53
,
54
46
Demand side management: Benefits and challenges, G. Strbac, Energy Policy, Vol: 36, pp.
4419-4426, Dec 2008
47
Efficient System Integration of Wind Generation through Smart Charging of Electric Vehicles,
M. Aunedi, G. Strbac, 8
th
International Conference and Exhibition on Ecological Vehicles and
Renewable Energies (EVER), Monte Carlo, March 2013
48
Benefits of Advanced Smart Metering for Demand Response based Control of Distribution
Networks”, ENA, SEDG, Imperial College, April 2010. Available at:
http://www.energynetworks.org/modx/assets/files/electricity/futures/smart_meters/Smart_Metering_Benerfits_Summary_ENASEDGImperial_1
00409.pdf
.
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The following assumptions regarding demand side flexibility are made in the system
modelling analysis:
55
electric vehicles: up to 80% of EV demand could be shifted away from a given hour to
other times of day;
heat pumps: heat storage enables that the 35% of HP demand can be shifted from a
given hour to other times of day;
smart appliances: demand attributed to white appliances (washing machines,
dishwashers, tumble dryers) participating in smart operation can be fully shifted away
from peak;
industrial and commercial (I&C) demand: 10% of the demand of I&C customers
participating in DSR schemes can be redistributed; and
daily consumption: the modelling assumes that the demand side response will not
change the daily energy consumption.
In addition to improving energy management and potentially reducing generation and
network capacity requirements due to reduced peak demand, these flexible demand
sources are also assumed to be capable of providing ancillary services for example:
smart fridges can provide frequency regulation as it detects the frequency deviation and
reduces the load when the frequency is low as long as the temperature in the fridge is still
within the permissible limits. Electric vehicles can also temporarily interrupt their charging
if the system frequency is low. This simple control mechanism can provide substantial
frequency response services to the system at low costs. As the frequency of the events
that trigger the utilisation of this service is relatively low, and the duration of having low
frequency is relatively short because the system operator will restore the system
frequency back to nominal levels within minutes, this will not substantially change the daily
operation of the flexible load devices.
49
Investigation of the Impact of Electrifying Transport and Heat Sectors on the UK Distribution
Networks, C.K. Gan, M. Aunedi, V. Stanojevic, G. Strbac and D. Openshaw, 21
st
International Conference on Electricity Distribution (CIRED), Frankfurt, Germany, 6-9 June
2011
50
Smart control for minimizing distribution network reinforcement cost due to electrification”, D.
Pudjianto, P. Djapic, M. Aunedi, C. K. Gan, G. Strbac, S. Huang, D. Infield, Energy Policy,
Vol. 52, pp. 76-84, January 2013
51
Value of Smart Appliances in System Balancing, Part I of Deliverable 4.4 of Smart-A project
(No. EIE/06/185//SI2.447477), Imperial College London, September 2009
52
Economic and Environmental Benefits of Dynamic Demand in Providing Frequency
Regulation, M. Aunedi, P. A. Kountouriotis, J. E. Ortega Calderon, D. Angeli, G. Strbac,
IEEE Transactions on Smart Grid, vol. 4, pp. 2036-2048, December 2013
53
Distributed generation and demand response services for the smart distribution network, M.
Woolf, T. Ustinova, E. Ortega, H. O’Brien, P. Djapic, G. Strbac, Report A7 for the “Low
Carbon London” LCNF project, Imperial College London, 2014.
54
Understanding the Balancing Challenge, analysis commissioned by DECC, Imperial College
and NERA Consulting, 2012
https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/48553/5767-understanding-the-balancing-challenge.pdf
55
An overview of the rationale and evidence behind these assumptions is provided in Carbon
impact of smart distribution networks’, M. Aunedi, F. Teng, G. Strbac, Report D6 for the “Low
Carbon London” LCNF project, December 2014
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The magnitude of demand (and therefore the amount of demand that can be shifted) in
each of the above categories changes over time (i.e. it is time-specific). In our analysis
the demand shifting is modelled to occur within the timeframe of one day, i.e. no demand
shifting over longer time horizons.
There is a large uncertainty in the future cost of demand side response especially for the
residential customers. For example, the low cost projection in 2030 for the residential
DSR is around £6/kW, while the high cost projections reach to £107/kW. For the I&C
sector DSR, the low to high cost estimates vary between £19 and £40/kW of contracted
capacity. This uncertainty is primarily driven by the customer acceptance for allowing
their electricity load profiles to be adjusted to support the system needs. For this study,
we use the projected cost of DSR, as depicted in Figure 34, developed by Carbon Trust;
the same data were used in the recent work by Imperial College for the BEIS report.
56
Figure 34 Cost of demand side response assumed in the modelling analysis
Source: Imperial’s modelling analysis
The cost of the residential DSR is applied to the DSR capacity contracted from the
residential loads, i.e. smart appliances, electric vehicles, and flexible heating systems.
While the cost of I&C sector DSR is applied to the (generic) capacity procured from the
industrial and commercial customers.
56
An analysis of electricity system flexibility for Great Britain, D. Sanders, A. Hart, M.
Ravishankar, G. Strbac, M. Aunedi, D. Pudjianto, and J. Brunert, Carbon Trust and Imperial
College London, 2016
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A.3.3 GB network system and cross-border interconnection
The system used for the study consists of Great Britain (GB) electricity system
interconnected with Ireland, Norway and few other regions in the continental Europe. The
GB electricity system was modelled using five following regions
57
:
Scotland;
Northern England and Wales;
Midlands;
South England and Wales; and
London (embedded within South England in terms of transmission grid).
Given that the GB transmission network is characterised by North-South power flows, it
was considered appropriate to represent the GB system using the above mentioned five
key regions and their boundaries, while considering London as a separate zone.
The two neighbouring systems, Ireland, and Continental Europe (CE)
58
are considered.
ENTSO-E
59
data and other publicly available data were used to construct the generation
and demand backgrounds for the CE and Ireland systems. It is important to note that the
approach used in the WeSIM model optimises the operation of the entire European
system, including seasonal optimisation of hydro energy in Scandinavia, pump storage
schemes across CE and DSR across CE.
Currently, there exists 4GW of interconnector capacity listed as below:
2GW to France (IFA);
1GW to the Netherlands (BritNed);
500MW to Northern Ireland (Moyle); and
500MW to the Republic of Ireland (East West).
The study also considers the planned development of the GB interconnectors, e.g.
additional 1 GW capacity between GB and France (IFA2) by 2020, 1GW new link to
Belgium (NEMO) by 2019 and the 1.4 GW GB-Norway(NSN) by 2020. Other potential
interconnector developments are captured as part of the optimisation process in the
model.
A.3.4 Technical and cost characteristics of modelled technologies
Flexibility related technical characteristics of thermal generation technologies as applied in
this modelling analysis are provided in Table 5. These include Minimum Stable
Generation (MSG), the response slope, the maximum response capability, ramping up
and down capability, and minimum up and down time of different generating technologies.
57
Value of Flexibility in a Decarbonised Grid and System Externalities of Low-Carbon
Generation Technologies, G. Strbac, M. Aunedi, D. Pudjianto, F. Teng, P. Djapic, R. Druce,
A. Carmel and K. Borkowski, Imperial College and NERA Economic Consulting, 2015
58
CE is an equivalent representation of the entire interconnected European system.
59
ENTSO-E Ten Year Network Development Plan 2016: 2020 scenario Expected Progress
and the 2030 Vision 3 scenario (National Green Transition).
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Higher flexibility can be achieved by having a lower MSG, higher response slope, higher
response max, higher ramping capability and a lower minimum up and down time of the
generator.
The response slope of a generator represents the ratio of the frequency response that can
be delivered to the capacity being unloaded. For example, for low flexible gas, the
response slope value of 0.4 means that by unloading 1 MW, the generator can deliver 0.4
MW frequency response. There is a maximum bound for the frequency response is
determined by the “Response max” parameter.
Table 5 Dynamic parameters of thermal generators
Technology
MSG
(% of
rating)
Response
slope
Respon
se max
(% of
rating)
Ramp
up
(% of
rating/h)
Ramp
down (%
of
rating/h)
Min up
time (h)
Min
down
time (h)
Coal
35%
1.00
5%
60%
60%
4
4
CCGT (LF)
50%
0.40
17%
60%
60%
4
4
CCGT (HF)
50%
0.85
17%
60%
60%
4
4
Coal based
CCS
40%
1.00
5%
50%
50%
4
4
Gas based
CCS
50%
0.50
10%
50%
50%
4
4
Nuclear (LF)
80%
-
0%
10%
10%
24
24
Nuclear(HF)
60%
-
0%
10%
10%
24
24
Peaking(gas)
40%
1.00
40%
100%
100%
0
0
Peaking(oil)
40%
1.00
40%
100%
100%
0
0
LF = low flexible, HF = high flexible
In addition to the technical parameters, the investment costs of different thermal
generation technologies as applied in this study are provided in Table 6.
Table 6 Thermal generation investment costs (real 2015 money)
Technology
CAPEX (£/kW)
Annuitised
CAPEX(£/kW/yr)
Annual fixed cost
(£/kW/yr)
Coal
2,139.63
168.53
58.55
CCGT (LF)
701.66
58.55
30.79
CCGT (HF)
736.74
61.48
32.33
Coal CCS
4,109.25
510.29
79.81
Gas CCS
1,794.99
226.62
34.09
Nuclear (LF)
7,327.85
638.51
82.76
Nuclear (HF)
7,694.24
670.43
86.9
Peaking(gas)
372.69
31.1
14.28
Peaking(oil)
1,904.77
144.38
41.91
Source: Imperial’s modelling analysis
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We assume that the Capex of high flexible generation is 5% higher than the Capex of low
flexible generation. The capacity of the thermal generators including CCS technologies is
optimised, i.e. minimisation of the overall system costs subject to system security and
carbon target constraints. The capacity of other generation technologies such as
renewables is pre-defined according to the CCC scenarios.
60
Two types of generic storage facilities, bulk and distributed, were considered in the
modelling analysis. Table 7 and Table 8 provide the technical and cost parameters for the
bulk and distributed storage systems respectively as applied in this study.
Table 7 Summary of modelling assumptions for bulk storage
Component
Unit
2015
2030
Capex (high)
£/kW
1,727
1,879
Capex (low)
£/kW
673
673
Fixed Opex
£/kW/year
6.1
6.1
Variable Opex
£/MWh
0.7
0.7
Cycle efficiency
%
81
81
Duration
Hours
12
12
Lifetime*
Years
N/A
N/A
*The annual fixed Opex is assumed to maintain the asset in perpetuity
All monetary values are in real 2015 money
Table 8 Summary of modelling assumptions for distributed storage*
Component
Unit
2015
2030
Capex (high)
£/kW
1,318
1,130
Capex (low)
£/kW
897
616
Fixed Opex
£/kW/year
4.3
4.3
Variable Opex
£/MWh
0.8
0.8
Cycle efficiency
%
90
90
Duration
Hours
2
2
Lifetime**
Years
5
5
*Based on a basket of lithium ion battery technology
**The annual fixed Opex is assumed to maintain the asset in perpetuity
All monetary values are in real 2015 money
60
Power sector scenarios for the fifth carbon budget, The Committee on Climate Change (UK),
October 2015
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All technical and cost data applied in this study is sourced from a recent study conducted
by Imperial College and Carbon Trust.
61
A.3.5 Other key assumptions
In this study the following assumptions regarding the GB electricity system were modelled
as specific constraints in the model.
System reliability standard: a reliability criterion of Loss of Load Expectation (LOLE)
being less than 3 hours per year is applied.
A self-sufficient system: i.e. there is no contribution from other regions to the capacity
margin in the UK and vice versa in order to maintain the LOLE criterion.
An energy-neutral system: this means that the net annual energy import / export is
zero. This allows UK to import power from and export to Europe / Ireland as long as
the annual net balance is zero. In other words, the UK is still able to export power
when there is excess in energy available, for example when high wind conditions
coincide with low demand, and import energy from Europe when economically
efficient e.g. during low-wind conditions in UK.
A.4 Overview of the methodology for whole-system analysis of
electricity systems
In order to carry out this study, we use the Whole-electricity System Investment Model
(WeSIM) developed by Imperial College, which is specifically designed to perform this
type of analysis. WeSIM has been extensively tested in previous projects studying the
interconnected electricity systems of the UK and the rest of Europe.
62
WeSIM simultaneously optimises system operation decisions and capacity additions to
the system, while taking account of the trade-offs of using alternative measures, such as
DSR and storage, for real-time balancing and transmission and distribution network and/or
generation reinforcement. For example, the model captures potential conflicts and
synergies between different applications of distributed storage in supporting intermittency
management at the national level and reducing necessary reinforcements in the local
distribution network.
The optimal decisions for investing into generation, network and/or storage capacity (both
in terms of volume and location) are based on modelling the real-time supply-demand
balance in an economically optimal way while ensuring security of supply. Capturing the
interactions across different time scales and across different asset types is essential for
the analysis of future low-carbon electricity systems that include alternative balancing
technologies such as storage and demand side response. Applications of these
technologies may improve the economics of real time system operation as well as reduce
61
An analysis of electricity system flexibility for Great Britain, Carbon Trust and Imperial
College, November 2016
62
WeSIM model, in various forms, has been used in a number of recent European projects to
quantify the system infrastructure requirements and operation cost of integrating large
amounts of renewable electricity in Europe. The projects include: (i) “Roadmap 2050: A
Practical Guide to a Prosperous, Low Carbon Europe” and (ii)“Power Perspective 2030: On
the Road to a Decarbonised Power Sector”, both funded by European Climate Foundation
(ECF); (iii) “The revision of the Trans-European Energy Network Policy (TEN-E)” funded by
the European Commission; and (iv) “Infrastructure Roadmap for Energy Networks in Europe
(IRENE-40)” funded by the European Commission within the FP7 programme.
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the investment into generation and network capacity in the long-run, as captured in the
integrated modelling framework of WeSIM.
Our approach to quantifying the value of flexible balancing technologies considers total
system costs (including both investment and operation) for a given generation and
demand scenario. It compares various types of system costs between two cases: (a) the
case when the model is allowed to add new capacity of alternative flexibility technologies
(such as interconnection, flexible generation, storage or DSR) in a cost-optimal manner;
and (b) the case where no such addition is allowed in the system i.e. only conventional
flexibility solutions (fossil fuel based generation) is allowed. The difference (i.e. reduction)
in the total system cost between the two cases, as a result of deploying flexible balancing
technologies, is interpreted as the value generated by these technologies.
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ANNEX B FLEXIBILITY SERVICES AND
TECHNOLOGIES
This annex provides a review of the flexibility services that are currently utilised by the
system operator in GB. We have also analysed how improvements in various
technologies in the future can change this services-technology mapping.
B.1 Flexibility services procured under current arrangements
Table 9 summarises the balancing services managed by the GB system operator
(National Grid)
63
. These balancing services are procured from the independent power
producers or other flexibility service providers in order to balance demand and supply
while maintaining the security and quality of electricity supply across the system.
At the distribution level, the commercial framework for distributed generation, storage, and
DSR to support the operation of the distribution system under Active Network
Management scheme has not been developed as complex as at the transmission level.
The commercial agreement is still largely in the form of bilateral contract between the
utility and the service providers or the aggregators. In the distribution system, the focus of
the services is normally on the voltage and flow management by adjusting the output of
Distributed Energy Resources to minimise the requirement to increase distribution system
capacity.
Table 9 System balancing services
Abbreviation
Balancing services
Definition
BMSU
BM Start-up
Access to additional generation BMUs that would not
otherwise have run, and which could not be made
available in Balancing Mechanism timescales.
BS
Black Start
The capability to recover from a total or partial shutdown of
the GB Transmission System which has caused an
extensive loss of supplies.
CBR
Contingency Balancing
Reserve
DSBR is targeted at large energy users who volunteer to
reduce their demand. SBR is targeted at keeping power
stations in reserve that would otherwise be closed or
mothballed.
DTU
Demand Turn Up
Enable demand side providers to increase demand (either
through shifting consumption or reducing embedded
generation) as an economic solution to managing excess
renewable generation when demand is low.
EFR
Enhanced Frequency
Response
A new service to achieve 100% active power output at 1
second (or less) of registering a frequency deviation.
EOSTOR
Enhanced Optional
STOR
Additional STOR Service from non-BM Providers on a trial
basis for this winter.
ERPS
Enhanced Reactive
Power Services
A market based provision of voltage support which
exceeds the minimum technical requirement of the
Obligatory Reactive Power Service.
FCDM
Frequency Control by
Frequency response provision through interruption of
63
Source: National Grid, available at:
http://www2.nationalgrid.com/uk/services/balancing-services/
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Abbreviation
Balancing services
Definition
Demand Management
demand customers
FFR
Firm Frequency
Response
The firm provision of Dynamic or Non-Dynamic Response
to changes in Frequency.
FFR-BC
FFR Bridging Contract
Enabling smaller parties a route to access the FFR
tendered market.
FR
Fast Reserve
Fast Reserve provides the rapid and reliable delivery of
active power through an increased output from generation
or demand reduction, following receipt of an electronic
despatch instruction from National Grid.
Ittr
Intertrips
Automatic control arrangement where generation may be
reduced or completely disconnected following a system
fault event.
MFR
Mandatory Frequency
Response
An automatic change in active power output in response to
a frequency change and is a Grid Code requirement.
MG
Maximum Generation
Access to capacity which is outside of Generators normal
operating range during emergency circumstances.
ORPS
Obligatory Reactive
Power Service
The provision of mandatory variation in Reactive Power
output.
SO-SO
SO to SO
Services that are provided mutually with other
Transmission System Operators connected to the GB
Transmission System via interconnectors.
STOR
Short Term Operating
Reserve
Short Term Operating Reserve (STOR) is a service for the
provision of additional active power from generation and/or
demand reduction.
STORR
STOR Runway
A contracting opportunity for Demand Side Response
providers to support additional reserve volume in to the
STOR market.
TCM
Transmission
Constraint
Management
Management of power flow across the network due to
thermal, voltage constraints taking to maintain network
security.
B.2 Mapping flexibility technologies to existing flexibility services
We have analysed the improvements in the technical characteristics of flexibility providing
technologies that will enable them to provide significantly more services in the future.
Table 10 summarises the types of potential improvement across technologies and maps
them to the various relevant balancing services.
Table 10 Potential flexibility improvement mapped to the relevant balancing
services
Sources of
flexibility
Potential improvement in the
flexibility
Flexibility
services
Current status of
technology
Thermal generation
- gas fired CCGT
and coal/gas fired
CCGT with CCS
Lower minimum stable generation
BMSU,
EFR,ERPS,FF
R,FR,MG,ORP
S,STOR,TCM
Under development
and demonstration
of highly flexible
plant
Shorter minimum up and down time
Faster start-up and shorter
synchronisation time
Enhanced reactive power capability
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Sources of
flexibility
Potential improvement in the
flexibility
Flexibility
services
Current status of
technology
Wind power
Provision of synthetic inertia
FFR, MFR,
STOR (when
curtailed),
ORPS, Ittr
Early
commercialisation
Voltage control and reactive
power sources
Early
commercialisation
Fault-ride through capability
Fully commercialised
Intertripping scheme
Fully commercialised
Solar PV
Smart PV inverter
FFR, MFR,
STOR (when
curtailed),
ORPS, Ittr (at
transmission
and distribution)
Fully commercialised
Voltage control and reactive
power management
Early
commercialisation
Intertripping scheme
Fully commercialised
Demand Side Response
Industrial and
Commercial Load
(HVAC,
interruptible load,
back-up DG)
A combined load management with
ancillary services to provide multiple
services which include:
- Interuptible load
- Load-shifting
- Back-up capacity
BMSU,
CBR,
DTU,FCDM
,FR, STOR,
STORR,
TCM
Fully commercialised
Electric vehicles
Load-shifting, interruptible load (in
charging mode),
DTU,
FCDM,
STOR
Early
commercialisation
Vehicle to Grid (V2G)
Demonstration
Smart fridges
Frequency sensitive operation
MFR
Early
commercialisation
Washing machine,
tumble dryer,
dishwasher
Load-shifting
DTU
Early
commercialisation
Heat pump with
heat storage
Load-shifting, interruptible load
DTU,
FCDM
Demonstration
Energy storage
Bulk storage, e.g.
Pumped Hydro
Energy Storage
(PHES), CAES,
batteries, flywheels
Energy arbitrage as well as multiple
types of ancillary services.
EFR,
ERPS,
FFR, Fast
Reserve,
MFR,
ORPS,STO
R,TCM
Early to full
commercialisation
Distributed storage,
e.g. CAES,
batteries, hybrid
storage (heat and
electricity)
- Primary and secondary frequency
response (in both charging and
discharging modes).
Early to full
commercialisation
(hybrid storage at
demonstration level)
- Reserves
- Services for network congestion
management and network security
- Back-up capacity
- Voltage control and reactive power
management
Source: Imperial’s analysis
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ANNEX C FIRST STAKEHOLDER WORKSHOP
(09 January 2017, London)
C.1 Introduction
This first stakeholder workshop was focused on identifying the barriers to deployment of
different types of flexibility options and developing ideas on actions to address these
barriers.
The workshop participants identified a number of barriers to the full deployment of
flexibility services in the GB electricity system. This was followed by prioritising the
identified barriers and developing actions to address the prioritised barriers. The barriers
identified in the workshop are grouped into the following four categories:
policy and regulatory barriers;
market and commercial barriers;
consumers related barriers; and
technical barriers.
Some of the identified barriers fall into one or other category therefore, some overlap or
repetition of barriers exists in the below provided details on the identified barriers.
C.2 Workshop participants
The following table provides names of the participating organisations and their
representatives in the first workshop.
Organisation
Representative
Organisation
Representative
AES Energy
Storage
Claire Addison
National Grid (UK)
Paul Lowbridge
Committee on
Climate Change
Eric Ling
Pöyry Management
Consulting
Gareth Davies
Committee on
Climate Change
Mike Thompson
Pöyry Management
Consulting
Anser Shakoor
Committee on
Climate Change
Mike Hemsley
Pöyry Management
Consulting
Benedikt Unger
EDF Energy
Guy
Buckenham
Renewables UK
Gordon Edge
EDF Energy
Andrew Jones
Renewable Energy
Systems
John Prendergast
Electricity Storage
Network
Zoltan Zavody
Scottish power
Stuart Noble
Energy UK
Rosie McGlynn
SP Energy
Networks
Geoff Murphy
Eon UK
Laurence
Barrett
UK Power Network
Sotiris
Georgiopoulos
Imperial College
London
Goran Strbac
UK Power Reserve
Ltd
Janine Freeman
Infinis Limited
Jon Crouch
Western Power
Roger D. Hey
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ANNEX D SECOND STAKEHOLDER WORKSHOP
(08 February 2017, London)
D.1 Introduction
The second stakeholder workshop tested the draft flexibility roadmap with stakeholders by
presenting the future flexibility requirements and discussing the actions for facilitating
provision of enhanced flexibility out to 2030.
D.2 Workshop participants
The following table provides names of the participating organisations and their
representatives in the second workshop.
Organisation
Representative
Organisation
Representative
AES Energy
Storage
Claire Addison
National
Infrastructure
Commission
Katie Black
Committee on
Climate Change
Eric Ling
Origami Energy
Limited
Alex Howard
Committee on
Climate Change
Mike Thompson
Pöyry Management
Consulting
Gareth Davies
Committee on
Climate Change
Mike Hemsley
Pöyry Management
Consulting
Anser Shakoor
Drax Power Limited
Ian Foy
Renewables UK
Caroline Bragg
EDF Energy
Guy
Buckenham
Renewable Energy
Association (RES)
Frank Gordon
Electricity Storage
Network
Zoltan Zavody
RWE/Npower UK
Ben Willis
Energy UK
Rosie McGlynn
Tempus Energy
Sara Bell
Flextricity
Jill Cox
UK Power Network
Sotiris
Georgiopoulos
Imperial College
London
Goran Strbac
Upside Energy
Graham Oakes
National Grid (UK)
Paul Lowbridge
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QUALITY AND DOCUMENT CONTROL
Quality control Report’s unique identifier: 2017/379
Role
Name
Date
Author(s):
Anser A Shakoor (Pöyry)
Gareth Davies (Pöyry)
Goran Strbac (Imperial College)
Danny Pudjianto (Imperial College)
Fei Teng (Imperial College)
Dimitrios Papadaskalopoulos (Imperial
College)
Marko Aunedi (Imperial College)
May 2017
Approved by:
Gareth Davies
May 2017
QC review by:
Jonathan Harnett
May 2017
Document control
Version no.
Unique id.
Principal changes
Date
v100
N/A
Draft release to the client
10 April 2017
V200
2017/379
Final release to the client
18 May 2017
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