Analytical techniques and tools for power balancing assessments

648
Analytical techniques and tools for power
balancing assessments
Working Group
C4.603
February 2016

ANALYTICAL
TECHNIQUES AND
TOOLS FOR POWER
BALANCING
ASSESSMENTS
WG C4.603
Members
K. UHLEN, Convenor (NO), S. JAEHNERT, Secretary (NO), C. HAMON, Secretary (NO),
C. BRUNO, (IT), H. FARAHMAND (NO), T. INOUE (JP), J. MATEVOSJANA (US), F. NOBEL (NL), P.
SØRENSEN (DK),
Copyright © 2016
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ISBN : 978-2-85873-351-4

Analytical techniques and tools for power balancing assessments
Page 2
Analytical techniques and tools for
power balancing assessments
Table of Contents
EXECUTIVE SUMMARY.........................................................................................................4
Chapter 1. Introduction...........................................................................................................................8
Background and motivation ................................................................................................................8
Scope of work........................................................................................................................................8
Report outline.........................................................................................................................................9
Chapter 2. Power balancing assessments.........................................................................................11
Terms and Definitions.......................................................................................................................11
The Nordic power system..................................................................................................................11
Types of reserves.............................................................................................................................12
Reserve procurement.......................................................................................................................12
Reserve requirements ......................................................................................................................14
Japan.....................................................................................................................................................15
Comments...........................................................................................................................................17
National Electricity Market in Australia..........................................................................................17
Types of reserve...............................................................................................................................17
Texas .....................................................................................................................................................19
Types of reserve...............................................................................................................................19
Procedures to determine the reserve requirements...................................................................20
Reserve activation............................................................................................................................20
Chapter 3. Analytical techniques and tools......................................................................................21
Models and Tools................................................................................................................................21
Power market model chain ............................................................................................................21
Kermit ................................................................................................................................................21
Advance dispatching ......................................................................................................................21
Balancing market model ................................................................................................................22
Assessment of modelling tools...........................................................................................................22
Chapter 4. Recommendations..............................................................................................................24
Summary of observations ...............................................................................................................24
Analytical techniques and tools available...................................................................................25
Conclusion................................................................................................................................................26
Recommendations for further development ................................................................................26
References...............................................................................................................................................28

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Annexes....................................................................................................................................................29
MODEL NAME: "Power market model chain"................................................................................29
MODEL NAME: "KERMIT"...................................................................................................................32
MODEL NAME: "Advance Dispatching" ..........................................................................................35
MODEL NAME: "Balancing market model" ....................................................................................38

Page 4
EXECUTIVE SUMMARY
This report is written based on work performed in CIGRE working group WG C4.603 “Analytical Techniques and
Tools for Power Balancing Assessments”. In this context, power balancing is defined to include all aspects of
maintaining the active and reactive power balance in the power system at various timescales. This working group
has only focused on the active power balancing, and the scope is limited to include power system control and
operational aspects ranging from what is commonly referred to as primary and secondary power control up to
management of reserves and intra-hour power (balancing) markets.
The main objective is to perform a critical assessment of existing analytical techniques and tools for the analysis of
power balancing and reserves management in order to provide recommendations for future developments. The
assessment aims to identify whether there is a lack of methods or tools to properly analyse certain power balancing
problems. More specifically, the application of the tools are related to:
 Primary frequency control and inertia.
 Secondary and tertiary control (active power balance).
 Reserves management (how to assess the need for reserves).
 Benefits and challenges with larger control areas.
 Balancing markets.
The need for new methods and tools will form a basis for recommending further research and developments in this
field.
Two main drivers are influencing operation of the transmission systems. The first is the rapid development and
integration of variable renewable energy resources, in particular wind power and photovoltaics. Second is the ongoing
development of high capacity HVDC interconnections in and between synchronous power grids. Both developments
stimulate the integration of power markets and opening to competition of regional electricity markets as a part of
larger power markets across national borders and interconnections. These drivers create new challenges in
predicting power flows and managing imbalances and congestions in the transmission networks. There are also
indications that the quality of system frequency (measured in term of deviations from the nominal 50 or 60 Hz) is
deteriorating in some synchronous power systems. A regulatory challenge is the expectation that on European
markets the imbalance settlement periods will be reduced to 15 minutes, allowing for shorter market time units than
the present 1 hour trading schedules.
As a consequence there will be increasing challenges related to balancing control and management of fast reserves.
Few tools and analytical techniques are readily available for the analysis of power balancing issues, ranging from
secondary and tertiary control to the organisation of markets for balancing and management of reserves. Therefore,
new methods and analysis tools are needed to address the future challenges in transmission system operation.
Examples of questions that need to be addressed are:
 How to analyse and design controls and solutions to deal with higher ramp rates as a consequence of larger
variability in generation and demand?
 How to compute the need for reserves?
 Do we have adequate models for representation of loads and turbine dynamics covering the time frames of
interest?
In this report, an overview of the main challenges and tasks related to balancing control is presented. The purpose
is to assess how the characteristics of the future power systems will challenge the way systems are operated and
controlled, and hence help to identify the areas where there is a need to develop new methods and tools.
From a technical point of view, power systems around the world are operated and controlled in very similar ways.
However, the definition of balancing tasks and their organisation into different services, markets and types of reserves
can vary considerably. Therefore, a short overview of the main definitions and differences in selected power systems
is provided to explain these issues in the power systems around the world.

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In general, the criteria for dimensioning and procurement of reserves must be related to the size of probable
disturbances, and take into account the uncertainties related to expected deviations in demand and generation
forecasts. Moving from traditional system to a system with high penetration of wind and photovoltaic entails changing
these criteria for dimensioning and procurement of reserves. The challenges as well as the solutions will depend on
the nature and size of the control areas in questions, and the possibilities for exchanging balancing services across
control areas.
This calls for new technical solutions as well as cost-benefit assessments. Market design and incentive schemes
also play important roles when new solutions are studied. The need for new analytical techniques and tools must
therefore be viewed on the basis of technical possibilities and challenges, as well as taking into account the
constraints related to costs and regulatory frameworks.
The main focus of this report is to describe the state of the art with respect to the availability of analytical techniques
and tools to address the challenges identified. The focus will be on the description of methods and tools that can be
used to analyse the present and future challenges, and where the established methods and commercial software
tools have shortcomings.
Analytical techniques and tools available
An assessment of available tools and methods is summarised in this report. Very broadly the tools can be classified
either as time series simulation models with representation of the slow dynamics (possibly including the electro-
mechanical phenomena), or as optimization models that include a combination of market modelling and power flow
representation of the power grid. The models are often designed to analyse a specific problem area, and this is
naturally reflected in the choice of methods that are implemented.
Four different modelling tools are presented in the report. These are chosen as examples that address different
challenges within the topic of balancing power.
Power market model chain – Simulation tool
The advantage of this tool (model chain) is that it accounts for the volumes and prices of power as it is traded and
controlled at different points of time: The power is first traded on the spot market based on day-ahead bids and load
prognoses. Then, the day-ahead forecast error is balanced based on hour-ahead prognoses and bids in the relevant
balancing market1 . Finally, the real-time power balance is obtained using automatic (secondary and primary)
reserves. The typical time resolution with this model is 5 minutes.
Kermit – Simulation tool
KERMIT allows analysis of dynamic grid performance in future scenarios or during events such as generator trips,
sudden load rejections, and volatile renewable resource (wind, solar) ramping events. KERMIT is designed for the
study of power-system frequency behaviour and fills a critical gap in power system modelling by addressing the one
second to 24 hour timeframe.
The model allows studying system dynamics related to frequency and active power flows for longer time horizons
than traditional power system models. This allows simulating and analysing the utilisation of the different kinds of
balancing reserves. Voltage and reactive power are not considered, therefore the computational time is reduced
compared to traditional dynamic power system simulators.
Advance dispatching – Optimisation tool
The fundamental objective of the “Advance Dispatching” tool is to analyse the future state of the power system
relative to expected weather and load and to make considerations on the adequacy degree associated with the
scheduled Unit Commitment. In the case that the adequacy conditions are considered insufficient, the Advance
Dispatching process has to be able to propose, well in advance, to the Control Room Operators, corrective
1 Normally this is the Nordic Balancing Power Market: http://www.statnett.no/en/Market-and-operations/Market-
information/The-balancing-power-market/

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manoeuvres (e.g. Unit Commitment) with minimum cost for the restoration of acceptable conditions. The typical time
resolution with this model is 1 hour.
Balancing market model – Optimisation tool
This method enables the quantification of the potential benefits of implementing balancing market integration in the
northern European power system. The balancing market model is implemented from the super transmission system
owner’s (TSOs') viewpoint of balancing regions to procure and employ resources in the balancing areas. In the
modelling approach, the reserve procurement is limited to the northern European area and is done simultaneously
with the day-ahead dispatch. The reserve in the model represents resources necessary for load-following, or rather
"net-load following'', where "net-load'' indicates demand minus non-regulating production. The model addresses the
transmission grid constraints through power flow equations. This fundamental model of the balancing market could
also be suitable for the wider European power market with its highly meshed transmission grid. The typical time frame
of analysis is one year with hourly resolution.
Conclusions and Recommendations
The limited number of tools that are assessed and described in this report are categorised in three groups based on
the timescale of their analysis.
 Shorter timescales; Inertia, primary and secondary frequency control (Kermit)
 Medium timescales: primary and secondary control (Power Market Model Chain)
 Longer timescales: secondary and tertiary control (Advance Dispatching & Balancing Market Model)
In shorter timescale, the use of time series simulation models is dominating, and to a large extent commercial power
system simulators for dynamic analysis are applied. Under these models, the fault or disturbance in question still
seems to be the loss of largest unit, and not so much the variability and ramp rates of generation and loads. Proper
modelling of primary control functions and capabilities of frequency converter based generation, loads and HVDC
converters will be increasingly important. For example, the possibility of these components to provide "synthetic
inertia" may have significant effect on system dynamic performance.
In medium timescale, time series simulation models are still the most important tools. This implies that the analyses
are very much based on trial and error. Very often tailor-made simulators are used that are able to represent the
variability in generation and loads from seconds to hours. A main challenge is to represent the dispatch (unit
commitment) of generators. A representative simulation of frequency control implies that the starting and
synchronising of generators must be properly represented. There seems to be no tools that actually analyse or
optimise the need for primary reserves.
In longer timescales, the optimisation tools start to become relevant and are applied in several ways. The main focus
is on the variability and forecast uncertainty, and the impact of the variability on reserve requirement. Analyses are
performed in the time range up to a year with a time resolution typically from minutes to hours. The tools typically
implement optimization methods for solving the dispatch and reserve procurement problem, and some form of time
series simulations (step-wise power flow or similar) to evaluate the grid impacts.
The recommendations for further development refer to the different timescales. A main recommendation for the
shorter timescale tools is to ensure proper modelling of primary frequency control capability that can be provided by
frequency converter based components, such as wind generation, photovoltaic systems and HVDC converters. The
possibility of these components to provide “synthetic inertia” is a part of this. The recommendation for medium
timescale tools is to include the uncertainties related to the procurement of reserves, the market design to provide
these reserves at the right costs and the technical performance of the different alternatives. To address the
challenges at longer timescales, improved analytical tools are needed that combine market models with a sufficiently
detailed representation of the power grid and power flows.
A limited number of analytical techniques and tools for power balancing assessments have been described in this
report. It gives an overview of the wide range of models and methods that are needed for the analysis of balancing
control challenges now and in the future. However, there is a lot of research and development going on globally in

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this field, and certainly there are many other techniques and tools that could have been included, and many more
examples and case studies that could have been described. The developments towards a renewable and sustainable
electric power systems suggest that the balancing issues will become increasingly important.
In the last few years, since the inception of this WG, the subject of power balancing with the growing deployment of
renewable generation worldwide has become a greater point of focus in more regions around the world. Therefore,
a final recommendation is to continue this work, and perhaps take an even broader look at tools, algorithms and
techniques for modeling and analysis of frequency response and balancing across a wider range of countries and
regions. A follow up of this work should be done in collaboration with Study Committees C5 to look at the market
implications in more detail, and C2 to look more into the operational aspects.

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Chapter 1. Introduction
This brochure documents the work of WG C4.603. The aim of this working group has been to perform a critical
assessment of existing modelling methods and tools for analysing power balancing issues in order to provide
recommendations for future developments. The overall scope of work is related to:
 Primary frequency control and inertia.
 Secondary and tertiary control (active power balance).
 Reserves management (how to assess the need for reserves – amount and location).
 Procurement of reserves, including benefits and challenges with larger control areas.
 Balancing markets.
Background and motivation
Two main drivers are influencing operation of the transmission systems:
 Rapid development and integration of variable renewable energy resources, in particular wind power and
photovoltaics.
 Integration of power markets and opening to competition of regional electricity markets as part of larger power
markets across national borders and interconnections.
This creates new challenges in predicting power flows and managing imbalances and congestions in the transmission
networks. There are also indications that the quality of system frequency (measured in term of deviations from the
nominal 50 or 60 Hz) is deteriorating in some synchronous interconnections. As a consequence there will be
increasing challenges related to balancing control and management of fast reserves. A regulatory challenge is the
expectation that on European markets the imbalance settlement periods will be reduced to 15 minutes, allowing for
shorter market time units than the present 1 hour trading schedules2.
Few tools and analytical techniques are readily available for the analysis of power balancing issues, ranging from
secondary and tertiary generation control to the organisation of markets for balancing and reserves management.
New methods and analysis tools are therefore needed to address the new challenges in transmission system
operation. Some of the main questions that need to be addressed are:
 How to analyse and design controls and solutions to deal with higher ramp rates as a consequence of larger
variability in generation and demand?
 How to compute the need for reserves?
 Do we have adequate models for representation of loads and turbine dynamics covering the time frames of
interest?
Scope of work
Power balancing can be defined to include all aspects of maintaining the active and reactive power balance in the
power system at various timescales, including automatic voltage and frequency control. This working group has only
focused on the active power balance, and the scope is limited to include power system control and operational
aspects ranging from what is commonly referred to as primary and secondary power control up to management of
reserves and intra-hour power (balancing) markets. The main tasks and timescales in operation related to active
power balancing are indicated in Figure 1.
The main objective is to perform a critical assessment of existing analytical techniques and tools for the analysis of
power balancing and reserves management. The assessment aims to identify if there is a lack of methods or tools
to properly analyse certain power balancing problems. The need for new methods and tools will form a basis for
recommending further research and developments in this field.
2
http://www.acer.europa.eu/Official_documents/Acts_of_the_Agency/Recommendations/ACER%20Recommendatio
n%2003-2015.pdf

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There is also a need to critically assess and partly define the terms that are used to describe the balancing issues of
interest in this context. We will in this report use definitions and terms following a process oriented approach (as used
by ENTSO-E3) rather than a product oriented approach.
Figure 1: Example and rather general illustration of possible tasks and timescales in operation
related to power balancing.
The relevant application areas include:
 Frequency containment (primary control) and frequency containment reserves (FCR)
 Frequency restoration (secondary control) and frequency restoration reserves (FRR)
 Reserve replacement (tertiary control)
 Reserve management (how to assess the need for reserves)
 Tools to assess benefits and challenges with larger control areas and multi-national balancing markets.
Tools and techniques for analysis of electro-mechanical dynamics and related power system controls are well
established. Primary control is therefore largely considered out of scope, but there are still some issues related to
the coordination and interaction between primary and secondary controls that should be considered. This can for
example be related to the control and damping of slow frequency variations and the corresponding responsibilities.
Another interesting issue is related to the fact that renewable energy sources like photovoltaics and new wind power
plants are mainly interfaced to the grid through power electronics converters. A consequence of this is that there will
be larger uncertainties and variability regarding what is the actual inertia in the future power systems. Methods will
be needed to estimate the actual inertia on-line, as well as tools to design and assess controls to provide 'synthetic'
inertia.
Coordination between the different processes, responsibilities and organisational issues are of interest. For example,
which processes should be managed and organised through markets and which should be managed and coordinated
by the TSOs as a mandatory or auction based services.
Report outline
3 ENTSO-E is the European Network of Transmission System Operators for Electricity
Increasingly market
based -Long term markets
and contracts
-Day-ahead markets
- Primary
frequency
control
- Inertia
- Intra-day markets
- Real-time balancing
markets (tertiary contr
- AGC (secondary
control)
Degree of
automation
sec. min. hour day week month/year
Main challenge due to
increased variability (wind
power in particular)

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Chapter 2 provides an overview of the main challenges and tasks related to balancing control. The purpose of this is
mainly to assess how the characteristics of the future power systems will challenge the way systems are operated
and controlled today, and thereby help to identify the areas where there is a need to develop new methods and tools.
From a technical point of view power systems around the world are operated and controlled in very similar ways.
However, the definition of balancing tasks and their organisation into different services, markets, types of reserves,
etc. can vary considerably. Therefore, a short overview of the main definitions and differences in selected power
systems is provided.
Chapter 3 aims to describe the state of the art with respect to the availability of analytical techniques and tools to
address the challenges identified. The focus will be on the description of methods and tools that can be used to
analyse the present and future challenges, and where the established methods and commercial software tools have
shortcomings.
Attempts will be made to present the challenges, methods and tools in a structured way, and thus making it easier
to identify the gaps.
Chapter 4 summarises the findings and provides some recommendations for further research and developments
based on the gaps identified. This could be related to research and development into methods for analysis and design
of controls and markets as well as development and demonstration of new tools.

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Chapter 2. Power balancing assessments
The purpose of this chapter is to provide a brief overview of balancing control practices and balancing markets in
different power systems around the world. This chapter discusses the following points.
 The main balancing control challenges in the different regions.
 Balance management practices such as procurement and activation of reserves.
 Main definitions, timescales and distribution of responsibilities (e.g. TSO vs. markets).
Power balancing concerns all activities in planning and operation to maintain at all times the balance between electric
power generation and consumption. In an AC grid interconnection this is essentially about keeping the system
frequency (i.e. the fundamental frequency of the AC voltage) at its nominal value, 50 or 60 Hz. The balancing control
tasks are performed partly through automatic control systems, but on the longer timescales by management and
scheduling of generation and demand through power market arrangements. An essential condition in order to
manage the balancing tasks is the availability of reserves. Congestion management and power system reliability, in
terms of generation adequacy and security of operation, relies heavily on the availability and utilization of reserves.
Thus power balancing, reserves and frequency control are all very closely related.
The way power balancing control and management of reserves are implemented may vary considerably from one
system to another. In order to assess and discuss analytical techniques and tools it is necessary to have some
knowledge of the specific power systems and how they are operated. The purpose of this chapter is therefore to
provide a brief overview of balancing control practices and balancing markets in different power systems around the
world. It is not the aim to perform an in-depth assessment of balance management as such, but merely to describe
the practices and challenges in some power systems as an introduction and motivation to the assessment of methods
and tools.
TERMS AND DEFINITIONS
When appropriate the report will use the terms and definitions now used in ENTSO-E (Network Code on Electricity
Balancing), which distinguishes between the generic processes and the actual products (services) related to
balancing control and reserves.
This is to reflect that there is a need to have a set of definitions and terms that is generally understood and has the
same meaning for all power systems.
To briefly explain the idea behind this, consider three of the main processes that are relevant for large power systems:
Frequency Containment, Frequency Restoration, and Reserve Replacement. These correspond loosely to what are
often denoted primary, secondary and tertiary controls/reserves. Common products related to these processes would
be e.g. primary control on generators (for frequency containment), secondary control like load frequency control
(LFC) and automatic generation control (AGC) (for frequency restoration) and e.g. services organized through a
"balancing market" for reserve replacement.
The Nordic power system
This section is based on [1-8] to which the reader is referred for further detail.
The Nordic power system comprises the synchronously interconnected power systems in Norway, Sweden, Finland
and Eastern Denmark. Western Denmark is also part of the common Nordic power market, although not
synchronously interconnected with the other members.
The Nordic power system is characterized by a large share of flexible hydropower. As a consequence, historically
there have been very few challenges regarding balancing. A more important issue has been the optimal utilization
and dispatch of hydro resource on a longer term basis. Partly, this also motivated the establishment of the common
Nordic power market and an early deregulation.

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However, recent developments such as strong interconnections, more trade and more wind and variable generation
(very much in Western Denmark and Northern Germany) have led to increasingly stronger variations in generation
and power flows throughout the system. Consequently, the challenges with respect to balancing the system have
increased. This is underlined by observations that the system frequency in the Nordic synchronous area grid shows
increasingly larger variations and more frequent deviations from the nominal 50.0 Hz as depicted in Figure 2.
Figure 2: HISTORICAL DEVELOPMENT OF THE FREQUENCY QUALITY IN THE NORDIC SYSTEM IN
TERMS OF MINUTES DURING WHIch THE FREQUENCY WAS OUTSIDE THE 49.9-50.1 HZ BAND,
from [1].
There are also observations that the system frequency exhibits slow periodic variations (typical period is 60-90
seconds) that are not fully understood. The analysis of frequency control and variations in the minute range requires
modelling techniques and tools that may not be readily available.
TYPES OF RESERVES
The following types of reserves exist in the Nordic system. The terminology follows ENTSO-E’s network code [2].
 Frequency containment reserves for normal operation (FCR-N)
 Frequency containment reserves for disturbances (FCR-D)
 Automatic frequency restoration reserves (FRR-A)
 Manual frequency restoration reserves (FRR-M)
RESERVE PROCUREMENT
Table 1 gives, for some of the countries in the Nordic system, some details about the timescale, the activation method
and the procurement mechanism for each type of reserve. In addition to these reserves, some transmission system
operators have additional mechanisms to deal with power balancing. In Sweden, for example, the start of production
plans can be shifted up to 15 minutes before or after the start of the hour.

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Name of reserve
product
Activation time Activation
method
Procurement
Frequency containment
reserves for normal
operation (FCR-N)
Full activation after
3 minutes for
frequency changes
within 49.9 to 50.1
Hz.
Automatic Sweden: Auctions at D-2 and D-1.
Finland: Yearly and D-1 auctions.
Norway: Weekly and D-1 auctions.
Frequency containment
reserves for
disturbances (FCR-D)
30 seconds if
frequency between
49.9 to 49.5 Hz
Automatic Sweden: Auctions at D-2 and D-1.
Finland: Yearly and D-1 auctions.
Norway: Weekly and D-1 auctions.
Automatic frequency
restoration reserves
(FRR-A)
120 seconds. (up to
210 seconds in
Norway)
Automatic Sweden: Auctions on Thursdays for
coming Saturday to Friday period.
Norway: Weekly auctions.
Finland: Hourly auctions.
Manual frequency
restoration reserves
(FRR-M)
Full activation
within 15 minutes
Manual Common regulating market: Bids can be
given and adjusted up to 45 minutes
before the actual hour of operation. After
that, they are binding and can be called
upon during operation.
Table 1: reserve types in the Nordic system
As an example, Figure 3 illustrates, for Sweden, the four different time instants at which reserves are procured before
the actual operating hour:
 At point 1, on the previous Thursday, the market for FRR-A is settled.
 At point 2, two days before the operating hour, the first market for FCR-N and FCR-D is settled.
 At point 3, one day before the operating hour, the second market for FCR-N and FCR-D is settled. Note
that it is settled after the day-ahead power market, Elspot, is cleared.
 At point 4, up to 45 minutes before the operating hour, regulating bids can be handed in for FRR-M
Figure 3: Reserve procurement in Sweden

Page 14
RESERVE REQUIREMENTS
The reserve requirements are determined jointly for the whole Nordic system and then divided between each country
according to the national consumptions. Requirements for the different types of reserves amount to
 600 MW for FCR-N
 For FCR-D, it depends on the largest individual fault in the Nordic system. In normal conditions, it amounts
to 1200 MW.
 300 MW for FRR-A
 Requirements for FRR-M should cover the dimensioning fault in each individual price area. The Nordic
transmission system operators have different ways of ensuring that enough capacity will be available in the
regulating market. For example, Norway resorts to seasonal and weekly capacity markets while Sweden and
Finland have long-term bilateral agreements with some power plants. These mechanisms ensure that
enough capacity will be available in FRR-M to cover the dimensioning faults in each price area and are
mainly used during the winter time.

Page 15
Japan
The definition of the reserve capability required for power system supply-demand balance operations in Japan is
shown in Table 2.
Category Type of reserve capability Facilities or functions
Cold reserve
(supplemental
reserve)
Reserve capability that can achieve maximum
power output from start-up within a few hours
Standby thermal turbines
Hot reserve
(operating
reserve)
Reserve capability that can start-up within 10
minutes and continue power output until cold
reserve is available
Standby hydro turbines
Thermal turbines in partial load
operations
Spinning
reserve
(synchronized
reserve)
Reserve capability that can increase power
output within 10 seconds (especially for
frequency drop due to generator tripping) and
continue increase in power output until hot
reserve is available
Hydro and thermal turbines in governor
droop operations
Table 2: Reserve capability required for power system operations in Japan
The timescale of the reserve application is shown in Figure 4.
Time
About 10s A Few Min A Few Hours
Application of
Spinning Reserve
Increase in Power Output Level
Demanded by Automatic Generation
Control or Dispatching Operator with
Respect to Synchronized Generators
Start-up of
Standby
Hydro
Turbindes
Start-up of
Standby
Thermal
Turbines
Application of
Cold Reserve
Application of Operating Reserve
SpinningReserve
PowerOutput
Figure 4: Timescale of reserves
Because the structure of electricity system in Japan is vertically-integrated at present, the electric power companies
have responsibilities in securing the necessary amount of reserve capability from their generators. The general
concept in securing the necessary amount of reserve capability is summarized in Table 3.

Page 16
Category
Sub-
category
Necessary
amount
Specification Current reserves
Spinning
reserve
(synchronized
reserve)
Turbine
governor
droop
operation
About 3% of
total system
capacity*
 Hydro and
thermal turbines
in governor
droop operation
 Hydro turbines enable to use minimum power
output through maximum power output as
spinning reserve.
 Thermal turbines enable to use 5% of
maximum power output as spinning reserve.
 It can be considered that current spinning
reserves described above sufficiently meet
with reserve requirement.
Misc.
 Emergency control by FC (frequency
converter stations between 50Hz system and
60Hz system) is available.
Hot reserve
(operating
reserve)
Thermal
turbines
3-5% of total
system
capacity*
 Generators
controlled by
system
operators at
dispatch centre
online
 Ramp speed in
power output
change varies
from one
generator to
another. The
generators to be
controlled are
selected by
system
operators based
on their
knowledge and
experience.
 Margin of thermal turbines between current
power output and maximum power output
Hydro
turbines
 Margin of synchronized hydro turbines
between current power output and maximum
power output
 Standby pumped storage units
Misc
 Generators which can provide reactive power support and voltage control are required.
Generators which help system recovery after large-scale blackouts are also required.
 Specified facilities for specified purpose, e.g. reactive power compensation for voltage drop at
a specified area, start-up pumped storage units after the entire system is collapsed, etc.
*: The relationship between the necessary amount of the spinning reserve and the necessary amount of the operating reserve is not sufficiently
clarified at present. However, the sufficient reserve capability has been experimentally verified because the weekly operating plan on generation
with respect to the daily load curves is developed considering the reserve in parallel with the weekly plan on supply and demand.
Table 3: General concept in securing the necessary amount of reserve capability from generators
in Japan
The ancillary service cost related to the balancing issues is defined as a part of fixed cost of hydro power plants and
thermal power plants which are responsible for the frequency regulation4. The cost is estimated based on the amount
of power output utilized for power balancing from those power plants.
4 In the case of Tokyo Electric Power Company, 5% of the peak electricity demand.

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COMMENTS
 All the information above is referred from the materials submitted to the third meeting (on Oct. 21, 2013) of
the system design working group of the electricity system reform subcommittee in METI (Ministry of
Economy, Trade and Industry) of Japan.
 Japan has not yet introduced full retail deregulation at present. It is scheduled that electricity market reforms
including retail liberalization will start after 2018 at the initiative of the Japanese government (refer to
http://www.meti.go.jp/english/press/2013/pdf/0402_01a.pdf). To cope with it, the system design working
group was established to extract the technical challenges and to update the grid code which includes the
requirement for covering sufficient operating reserves for future power system in terms of the technical point
of view.
National Electricity Market in Australia
This section is based on [9-12], to which the reader is referred for further detail.
The National Electricity Market (NEM) includes five interconnected transmission networks: Queensland, New South
Wales, Tasmania, Victoria and South Australia. These five transmission networks are owned by their respective
transmission network service providers (TNSP). The Australian Energy Market Operator (AEMO) is responsible for
ensuring that these five interconnected transmission networks are commonly operated in a safe, secure and reliable
manner. The NEM is organized in five-minute dispatch intervals.
TYPES OF RESERVE
Among market ancillary services, a distinction is made between three types of products that are used for different
purposes: Frequency Control Ancillary Services (FCAS), Network Control Ancillary Services (NCAS) and System
Restart Ancillary Services (RCAS). The latter two ancillary services, NCAS and SRAS, are procured with long-term
contracts.
For frequency control purposes, the FCAS are procured through markets for regulation and contingency services.
Regulation services are provided by automatic generation control (AGC) and are used to maintain the frequency in
the normal operating band 49.9-50.1 Hz. Contingency services are provided by generator governor response, load
shedding and frequency relays installed at fast generators. Contingency services are used to both contain frequency
excursions and restore the frequency to the normal operating band within five minutes.
RESERVE PROCUREMENT
Two markets exist for regulation: one for services aiming at raising the frequency (regulation raise) and one for
services aiming at lowering the frequency (regulation lower). As for contingency services, six markets exist
characterized by whether they are aimed at raising or lowering the frequency, containing the frequency excursion or
restoring the frequency and the time length of the response. An overview is given in Table 4.
Name of reserve Activation time Procurement
Regulation raise/lower Day-ahead auction*
Contingency fast raise/fast lower Six seconds Day-ahead auction*
Contingency slow raise/fast lower Sixty seconds Day-ahead auction*
Contingency delayed raise/delayed
lower
Five minutes Day-ahead auction*
(*) All markets are cleared jointly with the day-ahead energy market.
TABLE 4: types of reserve in Australia

Page 18
The eight markets are cleared jointly with the energy market during the dispatch process, for five-minute dispatch
intervals, to meet requirements on the amount of each type of reserves in MW. In addition to the five-minute dispatch
process, a pre-dispatch is run every 30 minutes to give indication of half hourly pre-dispatch from the coming 30
minutes up to the end of the day after.
The bids to the eight markets take the form of a trapezium that “indicates the maximum amount of FCAS that can be
provided for a given MW output level for a generator, or given MW consumption level for a scheduled load”, see [9].
The bids are therefore described by this trapezium, some parameters of which must be set on the day before the
actual operating period while the other parameters can be altered up to dispatch at the beginning of the operating
period.
Figure 5 illustrates the procurement of the reserves for FCAS. The eight different markets for the eight different types
of reserves for FCAS follow the same procedure.
 At point 1, on the day prior to the five-minute dispatch period, some parameters of the bids must be set.
 At point 2, just before the five-minute dispatch period, the rest of the parameters of the bid must be set. The
dispatch engine then co-optimizes the eight reserve markets with the energy market for the coming five-
minute dispatch in order to meet the reserve requirements that ensure that the frequency standards are
fulfilled, see [12].
Figure 5: Reserve procurement in Australia
For controlling power flows across interconnectors, AEMO can use network loading ancillary services which are
part of network control ancillary services (NCAS). Similarly as for regulation, AGC signals are sent to participating
generators. Load shedding can also be used.

Page 19
Texas
The section is based on [13-18], to which the reader is referred for further detail.
TYPES OF RESERVE
The following types of reserve are used in Texas:
 Responsive reserves: Arrest frequency decay (primary control and interruptible load) and help restore the
frequency back to normal.
 Regulation service (up/down): Reserves that must respond within 5 seconds. A subset of these reserves is
called fast-responding regulation service (up/down) which must respond within 60 cycles.
 Non-spinning reserve: Reserves that must respond within 30 minutes.
RESERVE PROCUREMENT
Ancillary services and energy offers are first co-optimized on the day-ahead market (DAM). The dispatch period on
the day-ahead market is one hour. The requirements for each ancillary service for all hours of the coming day are
specified in an Ancillary Service Plan which is posted before the day-ahead market is cleared.
Following the dispatch obtained from the day-ahead markets, a day-ahead reliability unit commitment (DRUC) is run.
This process assumes a future state of the power system based on the results from the day-ahead markets and
forecasts and adjusts the accepted offers to meet the reliability criteria which consider, among other things, some
selected N-1 and N-2 contingencies as well as transmission constraints accounting for weather-adjusted MVA limits
for the transmission lines and other stability constraints. The DRUC is typically not used to alter the ancillary service
offers that were accepted on the day-ahead market.
An hourly reliability unit commitment (HRUC) is then performed at the latest one hour prior to the operation period,
following a procedure similar to the DRUC, but using updated information.
During the actual operation, a security-constrained economic dispatch (SCED) is run every five minutes for energy
dispatch and signals are sent to each generation or load resource. SCED considers capacity that must be available
for ancillary services when resolving the dispatch.
Figure 6 illustrate the important times during the procurement of reserves:
 At time 1, ERCOT publishes the day-ahead ancillary service plan that sets the MW requirements for each
type of reserves that will be procured on the day-ahead market.
 At time 2, all day-head offers for energy and ancillary services have been received and the day-ahead market
co-optimizes energy and ancillary services for all operating hours of the coming day. Note that although the
day-ahead gives hourly schedule, during real-time operation, five-minute dispatch is performed.
 During period 3, from the clearing of the day-ahead market up to one hour before the operating hour, ERCOT
continuously assesses, based on updated information, whether ancillary services procured on the day-ahead
market are sufficient to meet the requirements. If not, supplementary ancillary service markets (SASM) can
be organized up to one hour before the actual operating hour to procure additional amounts of ancillary
services
Figure 6: Reserve procurement in Ercot

Page 20
ERCOT can resort to supplemental ancillary service markets (SASM) after the day-ahead decisions and before the
operating period if it deemed necessary to procure larger quantity of reserves.
PROCEDURES TO DETERMINE THE RESERVE REQUIREMENTS
Different procedures exist for the different types of reserves. For regulation services and non-spinning reserves, they
are partly based on net load variations and net load forecast errors. More detail is given below for each type of
reserve.
 Regulation service:
o Compute the 98.8 percentile of the five-minute net load variations from the previous month and the
same month from the previous year.
o Compute the 98.8 percentile of the up and down regulation services deployed from the previous
month and the same month from the previous year.
o To consider new installations of wind generation, tabulated additional MWs of regulation
requirements per 1000 MWs additional wind generation are added.
o In addition, additional MWs of regulation requirements can be added if the frequency control
performance indicator CSP1 defined by the North American Electrical Reliability Corporation (NERC)
during the previous month was less than 100%.
 Non-spinning reserve
o Hourly net load (load minus wind generation) accuracy due to forecast error is assessed by
comparing historical net load with the wind generation and load forecasts. Forecasts made six hours
before each operating hour are considered.
o Non-spinning reserve requirements are set such that 95 percent of the hourly net load uncertainty
resulting from the forecast errors can be covered by the average regulation up reserves and the non-
spinning reserves. The loss of the largest unit is also considered.
 Responsive reserves: At least 2300 MW will be procured. In addition, requirements are set to cover 70 % of
the historic system inertia conditions for all four-hour blocks of each month. These requirements are the
minimal quantities that will be procured in the day-ahead market for each hour of the year. These minimal
requirements are published once a year for the coming year.
This methodology is updated once a year. During day-ahead operations, the needed quantity, in MW, of each of the
three types of ancillary services is determined for each hour of the following day based on net load forecasts and
outage information and posted in the form of a day-ahead ancillary plan. During real-time operations, an ancillary
service capacity monitor is run every ten seconds to assess whether enough reserves are available to meet the
requirements.
RESERVE ACTIVATION
Regulation services and responsive reserves are controlled by load-frequency control (LFC) signals sent every four
second by ERCOT’s dispatch center. Non-spinning reserves are deployed by dispatch instructions sent by ERCOT.

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Chapter 3. Analytical techniques and tools
The purpose of this chapter is to review existing analytical techniques and tools for the assessment and analysis
of balancing control problems. This chapter discusses the following points.
 Collection and description of available tools and analytical techniques.
 Collection and description of some relevant application examples to illustrate the use of the tools.
 Overview and classification of the tools
Models and Tools
Four different modelling tools are chosen and presented in the following. These represent examples for addressing
challenges within the topic of balancing power.
POWER MARKET MODEL CHAIN [19-22]
DTU Wind Energy has developed a power market model chain in cooperation with Energinet.dk. The model chain
supports wind integration studies, mainly as part of the EU TWENTIES project, Energinet.dk’s Simba project and a
PhD under the Sino-Danish Center for Education and Research (SDC).
The advantage of using this model chain is that it accounts for the volumes and prices of power as it is traded and
controlled at different points of time: The power is first traded on the spot market based on day-ahead prognoses,
and then the day-ahead forecast error is balanced based on hour-ahead prognoses of bids and capacity in the
relevant balancing market5. Finally, the real-time power balance is obtained using automatic (secondary and primary)
reserves. The typical time resolution with this model is 5 minutes.
KERMIT [23]
sudden load rejection, and volatile renewable resource (wind, solar) ramping events. KERMIT is designed for the
study of power-system frequency behaviour and fills a critical gap in power system modelling by addressing the one
second to 24 hour timeframe.
The model allows studying system dynamics and frequency development for longer time horizons than traditional
power system models. This allows simulating and analysing the utilisation of the different kinds of balancing reserves.
Voltage and reactive power are not considered, and therefore the computational time can be considerably reduced
compared to traditional dynamic power system simulators.
ADVANCE DISPATCHING [24]
manoeuvres (e.g. Unit Commitment) with minimum cost for the restoration of acceptable conditions.
As a matter of fact, the "Advance Dispatching" tool has the aim of restructuring the production plans and reserves
under the current system configuration, the available ex-post data and the very short-term forecasting results. In fact,
very short-term congestions, generator faults, or load increases have the effect of reducing the tertiary reserve below
unacceptable levels, so it becomes necessary to reprogram the Unit Commitment (UC) of generating assets, which
consists in starting units or changing their production configuration in case of combined cycles.
5 Normally this is the Nordic Balancing Power Market: http://www.statnett.no/en/Market-and-operations/Market-
information/The-balancing-power-market/

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The common practice is fundamentally based on “deterministic sizing” criteria of the reserve, required to bear a load
demand foreseen the day ahead D-1 for the day D. This information feeds the D-1 deterministic procedures for Unit
Commitment and Dispatching. The uncertainties inherent in the processes of operational planning and dispatching
are usually faced in D-1 by establishing deterministic operating margins and carrying out a probabilistic verification.
“Advance Dispatching” reverses this approach for day D. Given an acceptable and ideally constant level of risk in all
the operating situations, “Advance Dispatching” provides to the real-time control environment an indication of
"deterministic synthesis" of the possible amount of reserves (present or allocated) which is missing or in excess with
respect of the theoretically associated level of risk accepted.
BALANCING MARKET MODEL [25]
This method enables the quantification of the potential benefits of implementing balancing market integration in the
northern European power system. The balancing market model is implemented from the super TSOs' viewpoint of
balancing regions to procure and employ resources in the balancing areas. The super TSOs act as single buyers in
the regulating reserve capacity market. In the modelling approach, the reserve procurement is limited to the northern
European area and is done simultaneously with the day-ahead dispatch. The reserve in the model represents
resources necessary for load-following, or rather "net-load following'', where "net-load'' indicates demand minus non-
regulating production.
In contrast to the analyses that have been done on the integration of northern European balancing markets thus far,
the model addresses the transmission grid constraints through power flow equations. This fundamental model of the
balancing market could also be suitable for the wider European power market with its highly meshed transmission
grid. The typical time frame of analysis is one year with hourly resolution.
Assessment of modelling tools
An attempt has been made to provide a classification and categorisation of the chosen modelling tools.
Table 5 outlines an overview and classification of each methods and tools. The first group classifies the tools
according to their main application area, including optimisation tools, simulation tools or combination of both
optimisation and simulation tools. The next category comprises the different "balancing" problems that each method
can address. This category encompasses consecutive markets, activation balancing reserves, exchange of
balancing reserves, intra-hour balancing, dynamic grid analysis, short-term system adequacy, short-term reserve
dimensioning, real time dispatch and forecast errors. The users of each method are categorised in transmission
system operators (TSO), producers, balance responsible parties (BRP), balance service providers (BSP) and
research.
The "Power Market Model Chain" method has been developed to study the balancing market in the Danish power
system based on the current market arrangements and to study possible control contribution from wind power in
Western Denmark. The model deals with simulation of consecutive markets beginning with day-ahead market with
one hour resolution and followed by balancing market with 5 minutes resolution. The balancing market model
simulates the intra-hour balancing performed by TSO and the dynamics of the load frequency control at the Danish
border to Germany. The output of the model includes the volume and activated balancing power to balance out hour-
ahead prognosis with 5 minutes resolution. The model is very much suitable to be used by both TSO and research
institutes.
The "Kermit model" deals with simulation of system dynamics and frequency development. The model allows
analysing intra-hour activation of balancing reserve, real-time area interchange and energy dispatch. It is suitable for
TSOs to study system inertia and governor response in short, medium and long term planning processes.
The "Advance Dispatching" method uses an optimisation algorithm to find a balance between production plan and
the latest forecast load for the hour ahead in order to meet system adequacy. The model deals with consecutive
markets including day-ahead and market for ancillary services. The focus of the model is on analysing short term
system adequacy and reserve dimensioning with respect to the latest load forecast information. The approach is
suitable for producers and both BRPs and BSPs to study their position in the market for ancillary services.

Page 23
"Balancing Market model" can estimate the benefit of integrating balancing market in Northern Europe. The model
optimises the procurement and activation of balancing services in an integrated balancing market. The model
incorporates a common clearing of day-ahead and reserve capacity market and real-time market. The aim of real-
time market is to activate the necessary reserve to re-establish the system balance while minimising balancing cost.
The simulation is based on flow-based power market simulation, which considers a detailed grid model and takes
into account grid constraints during allocation and activation of reserves. The model is suitable both for TSOs and
research institutes and gives holistic view of reserves procurement and activation between two synchronous systems.
Tool
Power market
model chain
Kermit
Advance
Dispatching
Balancing
market model
Classification
Optimisation tool X X
Simulation tool X X
Combination
Problems
Consecutive
markets
X X X
Activation of
balancing reserves
X X
Exchange of
balancing resources
X
Intra-hour balancing X
Dynamic grid
analysis
X
Short-term system
adequacy
X
Short-term reserve
dimensioning
X
Real-time
dispatching
X X
Forecast errors
(Demand and RES)
X X X
User
TSO X X X
Producer X
BRP X
BSP X
Research X X
Table 5: Overview of methods and tools

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Chapter 4. Recommendations
This chapter:
 Summarises the main findings and observations by the working group.
 Identifies and describes the need for new models and tools based on the findings.
 Recommends areas for further research and development to gain new knowledge.
SUMMARY OF OBSERVATIONS
In general, the criteria for dimensioning and procurement of operating reserves are related to the size of probable
disturbances and uncertainties related to expected deviations in demand and generation forecasts. Traditionally, the
common criterion for determining the need for spinning reserves has been to manage the loss of the largest
generation unit. This is the worst (N-1 criterion) contingency in terms of unbalance, and traditionally this has been
larger than the expected unbalance resulting from forecast errors in generation and demand. The uncertainty in
generation due to larger amounts of renewable energy sources is becoming a larger challenge than to manage
generation outages. Some system operators, such as in Texas, have started to consider both a measure for net load
uncertainty and the size of the largest generating unit to determine the required amount of reserves.
Rapid growth in distributed generation (photovoltaics in particular) and more complex demand patterns, e.g. due to
new types of loads such as electric transport will add to the total uncertainty in forecasts. This sets the need for
balancing control and calls for new criteria and new ways of thinking when dimensioning and procuring reserves. The
procurement of reserves must be assessed based on the needs in different time frames and spatial (geographical)
perspectives.
The balancing and reserve problem in time needs to be based on the following considerations:
 The expected variability in generation as well as in demand must be accounted for, that is: how large
deviations can be expected over the planning period?
 Adding to this is the uncertainty of generation availability. This is particularly relevant for weather dependent
sources like wind and photovoltaics. Although there can be good estimates of the expected uncertainty
energy-wise, the additional uncertainty is related to the variability in power, i.e. when the capacity is available.
This challenge is related to weather forecast and the difficulty of e.g. predicting cloud patterns and when
storm fronts are passing.
 Higher ramp rates as a consequence of increasing variability in generation and demand is a particular
concern [26]. This calls for new types of reserves with flexibility to handle steeper ramp rates.
Similarly, the balancing and reserve problem in a spatial perspective needs to be considered. This is more related to
the size of the control areas in question, and what the possibilities for exchanging balancing services across control
areas are.
 Netting of unbalances: Several studies [27, 28] have shown that the geographical spread of wind farms
creates a smoothing effect on the total power generation due to the natural variability in weather. The relative
variability is therefore reduced over a larger geographical area. This is referred to as netting of unbalances
and can be utilized either by creating larger control areas or by effectively exchanging balancing reserves.
The potential benefit is that each area needs to procure less reserve and can access to cheaper resources
than if no exchange was possible.
 Grid capacity and congestion management: Exchanging balancing services is only possible if there are no
congestions that inhibit the use of available reserves. Therefore, the available transmission capacity
becomes an important factor, and thus also how congestions are managed. Effective congestion
management reduces the total need for reserves.
On the more technical level, the main questions are very much related to the choice and design of balancing controls:
 Are the present turbine/governor systems on conventional generators able to respond to faster changes and
ramp rates?

Page 25
 How does the more intermittent operation of power plants affect wear and tear of turbines and generators?
 Is there a need for more contributions from wind farms and HVDC converters to provide primary frequency
control and synthetic inertia?
 When will there be a need for energy storage to manage short term fluctuations?
 Will intelligent demand side response schemes solve many of these problems in the end?
Many of these questions deal with technical solutions as well as cost-benefit assessments. Market design and
incentive schemes also play important roles when new solutions are studied. The need for new analytical techniques
and tools must therefore be viewed on the basis of technical possibilities and challenges, while taking into account
the constraints related to costs and regulatory frameworks.
ANALYTICAL TECHNIQUES AND TOOLS AVAILABLE
An assessment of available tools and methods was summarised in the previous chapter. Very broadly the tools can
be classified either as time series simulation models with representation of the slow dynamics (possibly including the
electro-mechanical phenomena), or as optimization models that include a combination of market modelling and
power flow representation of the power grid. The models are often designed to analyse specific problems, and this
is naturally reflected in the choice of methods that are implemented.
Overall conclusions based on the limited number of models that are assessed and described in this report can be
summarised as follows.
Problems on the shorter timescales; primary frequency control and inertia
The use of time series simulation models is dominating, and to a large extent commercial power system simulators
for dynamic analysis are applied. Very often this implies that analysis and control design are carried out by trial and
error. Dynamic simulations assess for example whether the generators can remain in synchronism after a large
sudden and discrete event (loss of units, loss of line) and how inertial response and primary controls act to stabilize
(contain) system frequency. Typically, the ”dimensioning fault” or disturbance in question is the loss of largest unit,
and not so much the variability and ramp rates of generation and loads. This may still be sufficient as the variability
and ramp rate issues are rather continuous event with power imbalance accumulating over time. A more important
challenge is related to the fact that more and more generation, as well as load, is interfaced through power electronics
converters, which means that the dynamic response is essentially determined by the converter controls. Although
this opens new possibilities to improve short term dynamics, and that the modelling task as such may not be difficult,
the uncertainty remains how the variety of controls are actually implemented.
At medium timescales: primary and secondary control
Time series simulation models are still the most important tool, which implies that the analyses are very much based
on trial and error. Very often tailor-made simulators are used that are able to represent the variability in generation
and loads from seconds to hours. Probably, this reflects the lack of good commercial software tools that address this
particular time range. A main challenge is to represent the dispatch (unit commitment) of generators. A representative
simulation of frequency control implies that the starting and synchronising of generators must be properly
represented. The modelling of turbines and governors are particularly important, as well as the representation of
short-term demand variation. There seems to be no tools that analyse or optimise the need primary reserves.
At longer timescales: secondary and tertiary control
Here the optimization tools start to become relevant and applied in several ways. The main focus is on the variability
and forecast uncertainty, and their impact on the need for reserves. Analyses are performed in the time range up to
a year with a time resolution typically from minutes to hours. The tools typically implement optimization methods for
solving the dispatch and reserve procurement problem, and some form of time series simulations (step-wise power
flow or similar) to evaluate the grid impacts. Different versions of security-constrained optimal power flow (SCOPF)
algorithms are used for this purpose. The software available for this are mostly "research-grade".

Page 26
Conclusion
Additional supply side variability by increasing penetration of renewables poses new challenges related to balancing
control and management of fast reserves in power systems. Moreover, the opening to competition of new power
markets has created larger variations and uncertainties in power flows that need to be managed. It is also a fact that
presently there are few tools and analytical techniques readily available for the analysis of power balancing issues.
In this report, a brief overview of balancing control practices in different power systems around the world has been
presented. The chapter gave a holistic view of different balancing market mechanism in the Nordic, Japan, Australia
and Texas in the US. We have presented the existing analytical techniques and tools for the assessment and analysis
of balancing control problems. The available tools were characterised either as time series simulators or as
optimisation methods. The assessment of the tools focused on the various challenges to be analysed at different
timescales, including the shorter timescales, i.e., primary frequency control and inertia, medium timescales, i.e.,
primary and secondary control and longer timescales, i.e., secondary and tertiary control.
RECOMMENDATIONS FOR FURTHER DEVELOPMENT
Below is a summary of the main recommendations for further development, addressing the challenges at different
timescales, ranging from primary frequency control and inertia to longer timescales including secondary and tertiary
control and balancing markets.
At the shorter timescales: primary frequency control and inertia
More generation connected through frequency converters and increased numbers of HVDC connections between
synchronised areas are seen to potentially challenge the frequency containment process even in larger power
systems. This motivates new studies related to the performance of power/frequency control from generators and the
amount of inertial response in the system. Although modelling tools do exist for this purpose (dynamic power system
simulators like Siemens PTI PSS®E, GE PSLFTM, Eurostag®, DIgSILENT PowerFactory, ) there are still uncertainties
regarding modelling and model validations that need to be addressed, e.g.:
- Modelling of primary control functions and capabilities of frequency converter based wind generation,
photovoltaic systems and HVDC converters.
- The possibility of these components to provide "synthetic inertia" and its effect on the system performance.
- The focus on frequency control over a wider time frame motivates to revisit the modelling and model
validation of turbine dynamics and governors on "conventional" power plants (hydro and thermal). A greater
confidence in the actual control response from generators is needed in order to design the grid codes and
system services that minimise the costs of operation.
At medium timescales: primary and secondary control
Increasing ramp rates is a main concern. The challenge is to maintain power balance, required frequency quality and
security of operation in periods (minutes to hours) of extreme ramp rates. The technical solutions are available,
ranging from improved turbine controls, automatic demand side response to deployment of short term energy storage
systems. However, there are still uncertainties related to the procurement of reserves, the market design to provide
these reserves at the right costs and the technical performance of the different alternatives.
Analytical tools are needed to analyse, design and verify the technical solutions as well as their economic impacts.
At longer timescales: secondary and tertiary control
Here the challenges are more on the economical side. How should the electricity markets (for energy and capacity)
be designed, to on one hand stimulate the development and deployment of a sustainable energy system, and on the
other hand ensure the necessary flexibility and capacity to manage the variability and uncertainties resulting from the
weather dependence of renewable sources?

Page 27
Analytical tools that combine market models with a sufficiently detailed representation of the power grid and power
flows are needed to address this challenge.
Final recommendation
A limited number of analytical techniques and tools for power balancing assessments have been described in this
report. It gives an overview of the wide range of models and methods that are needed for the analysis of balancing
control challenges now and in the future. However, there is a lot of research and development going on globally in
this field, and certainly there are many other techniques and tools that could have been included, and many more
examples and case studies that could have been described. The developments towards a renewable and sustainable
electric power systems suggest that the balancing issues will become increasingly important.
Given that since the inception of this WG the subject has become in the last year or two a greater point of focus in
more regions around the world, a final recommendation is to continue this work, and perhaps take an even broader
look at tools, algorithms and techniques for modeling and analysis of frequency response and balancing across a
wider range of countries and regions. A follow up of this work should be done in collaboration with Study Committees
C5 to look at the market implications in more detail, and C2 to look more into the operational aspects.

Page 28
References
[1] E-bridge, "Analysis & review of requirements for automatic reserves in the Nordic synchronous system,"
2011.
[2] ENTSO-E, "Network Code on Load-Frequency Control and Reserves," 2013.
[3] ENTSO-E, "Principles for determining the transfer capacities in the Nordic power market," 2015.
[4] Fingrid, "Fingrid – Reserves," 2015. Available:
http://www.fingrid.fi/en/powersystem/reserves/Pages/default.aspx
[5] Statnett, "Vilkår for tilbud, aksept, rapportering og avregning i marked for primærreserver til Statnett," 2014.
[6] Statnett, "Vilkår - anmelding, håndtering av bud og prissetting I sekundærreservemarkedet til Statnett," 2014.
[7] Statnett, "Vilkår for tilbud, aksept/prissetting og håndtering av bud I regulerkraftopsjonsmarkedet (RKOM),"
2014.
[8] Svenska Kraftnät. (2015). Balansansvarsavtal.
[9] Australian Energy Market Operator, "Guide to ancillary services in the national electricity market," 2010.
[10] Australian Energy Market Operator, "Constraint formulation guidelines," 2010.
[11] Australian Energy Market Operator, "Constraint implementation guidelines," 2010.
[12] Australian Energy Market Operator, "ESOPP guide FCAS constraint equations," 2009.
[13] NERC, "Real Power Balancing Control Performance," 2010.
[14] ERCOT, "ERCOT Methodologies for Determining Ancillary Service Requirements," 2015.
[15] ERCOT, "ERCOT Nodal Protocols, Section 3: Management activities for the ERCOT system," 2015.
[16] ERCOT, "ERCOT Nodal Protocols, Section 4: Day-Ahead Operations," 2015.
[17] ERCOT, "ERCOT Nodal Protocols, Section 5: Transmission security analysis and reliability unit
commitment," 2015.
[18] ERCOT, "ERCOT Nodal Protocols, Section 6: Adjustment period and real-time operations," 2015.
[19] H. Ravn et al., "Balmorel: A model for analyses of the electricity and CHP markets in the Baltic Sea region,"
Project report, ISBN 87-986969-3-9, Mar. 2001. Available: www.balmorel.com
[20] P. Sørensen, A. D. Hansen, and P. A. C. Rosas, "Wind models for simulation of power fluctuations from wind
farms," Journal of Wind Engineering and Industrial Aerodynamics, vol. 90, pp. 1381-1402, 2002.
[21] L. Söder, "Simulation of wind speed forecast errors for operation planning of multiarea power systems," in
Probabilistic Methods Applied to Power Systems, 2004 International Conference on, 2004, pp. 723-728.
[22] M. Marinelli, et al., "Wind and Photovoltaic Large-Scale Regional Models for Hourly Production Evaluation,"
Sustainable Energy, IEEE Transactions on, vol. 6, pp. 916-923, 2015.
[23] J. Matevosyan, “Big Wind in the Big Oil State”, In Public utilities FORTNIGHTLY, May 2014, page 12.
Available: http://mag.fortnightly.com/publication/?i=207172&p=14
[24] C. Sabelli et al., "Very short-term optimal dispatching: An integrated solution for the advance dispatching,"
presented at the CIGRE Conference, Paris, France, 2012.
[25] Hossein Farahmand, "Integrated Power System Balancing in Northern Europe-Models and Case Studies,"
PhD, ISSN 1503-8181; 2012:150, Department of Electric Power Engineering, NTNU, Trondheim, 2012.
[26] W. W. Hogan, "A Cleaner Energy System: Renewable Energy and Electricity Market Design [In My View],"
Power and Energy Magazine, IEEE, vol. 13, pp. 112-109, 2015.
[27] K. Veum, L. Cameron, D. Huerta Hernandes, and M. Korpås, "Roadmap to the deployment of offshore wind
energy in the Central and Southern North Sea (2020-2030)," July 2011. Available:
http://www.seanergy2020.eu/wp-content/uploads/2011/08/WINDSPEED_Roadmap_110719_final.pdf
[28] Hannele Holttinen, et al., "Summary of experiences and studies for Wind Integration – IEA Wind Task 25,"
presented at the WIW2013 workshop, London, 22-24 Oct, 2013.

Page 29
Annexes
MODEL NAME: "Power market model chain"[19-22]
Model Category:
☐Market Model
☒ Technical Issues and Balancing Control
☐Institutional Issues
The Objectives of the Model
DTU Wind Energy has developed the model chain illustrated in Figure 7 in cooperation with Energinet.dk. The
model chain has been developed to support wind integration studies, mainly as part of the EU TWENTIES project,
Energinet.dk’s Simba project and a PhD under the Sino-Danish Center for Education and Research (SDC).
Model Contribution
The advantage of using this model chain is that it accounts for the volumes and prices of power as it is traded and
controlled at different points of time: The power is first traded on the spot market based on day-ahead prognoses,
then the power is balanced based on hour-ahead prognoses using the regulating power market like NOIS, and
finally the power is balanced using automatic (secondary and primary) control.
Figure 7. The model chain which has been used in wind integration studies
Spot
market
model
Wind generation patterns model (CorWind)
Balancing
model
(Simba)
PWind,DA[1h] PW,Wind,HA[5m] PWind,real[5m]
Psched,DA[1h] Automatic
control
model
Pplan,HA[5m]
Power system scenario

Page 30
In the present applications of the model chain, the spot market model has included unit commitment and dispatch in
a system of interconnected areas including the Danish power system and the neighbouring power system.
Subsequently, Simba is only simulating the balancing of the two main areas in the Danish power system, but the
Simba balancing is done with the internal Danish reserves as well as reserves in neighbouring countries if the is
sufficient interconnection capacity. Thus, the balancing model has focus on the Danish system, but the spot market
model has a wider focus.
It should be noticed that the present version of the model chain only takes wind uncertainties into account because
this is the main uncertainty in the present Danish power system, but the wind uncertainties will be supplemented by
the additional PV uncertainties which will be important in the long term scenarios studied in the NSON-DK project.
It should also be noticed that the intra-day balancing is not included explicitly in the model chain at this stage, which
is because the intra-day balancing markets are used to a lesser extent today, so this marked function is aggregated
into the balancing model. It should also be mentioned that the hour-ahead horizon is used for the balancing because
the vast majority of the balancing in the Danish power system is presently done with this horizon.
Spot market model
So far, two different market models (WILMAR and SIVAEL) have been used the modelling chain Figure 7, but in the
NSON-DK project, Balmorel will be used. Balmorel is a model for analysing the energy system with emphasis on
electricity and heat. It is a multi-period model with representation of years and detailed time resolution within the year.
It has geographical entities representing district heating areas, electricity price regions linked by transmission
interconnectors and countries for representing e.g. taxation and incentive schemes. The Balmorel model is
optimisation-based with the possibility to minimise production cost and to maximise social welfare. The base version
is linear with options for applying integers for e.g. unit commitment. The production system for electricity and heat
includes a number of technologies, including wind, hydro and thermal production units and also storage possibilities
for i.a. heat in district heating system and water for hydro power production. Further description of the model can be
found in Ravn et al.[19].
The Balmorel model is coded in the GAMS model language, and the source code is open source and thus readily
available (www.balmorel.com). The Balmorel model has been applied in projects in Europe (e.g. Denmark, Norway,
Estonia, Latvia, Lithuania, Poland, Germany, Austria), Africa (e.g. Ghana, Mauritius), America (Canada) and Asia
(China), and it is in regular use in a number of countries by e.g. energy companies and TSOs. It has been used for
analyses of i.a. security of supply, the role of flexible demand, wind power development, development of international
electricity markets and markets for green certificates and emission trading, expansion of transmission infrastructure,
and evaluation of energy policy and renewable support schemes.
Balmorel will be used for generating spot prices. The Balmorel version used will include stochastic elements from i.a.
wind power production to provide a more robust yet economical spot market solution. This will build on the on-going
research project ENSYMORA (www.ensymora.dk) where i.a. relevant elements from WILMAR will be adapted to
Balmorel. Additionally, Balmorel will be extended with an enhanced representation of electrical transmission system
in the form of a DC approximation.
Balancing model
Simba is developed by Energinet.dk in cooperation with DTU as a tool to simulate the balancing of the Danish power
system, which is performed by Energinet.dk before the hour of operation, based on hour-ahead schedules.
The main driver for the development of Simba is to be able to quantify the intra-hour balancing performed by
Energinet.dk as a supplement to conventional unit commitment and dispatch models, which are mainly accounting
for the power traded by independent power producers. Such a tool can be used by Energinet.dk for assessment of
cost and value of reserves, assessment of needs for reserve capacities, economic optimisation of system services,
assessment of flexible demand support to system balancing, and assessment of new market designs (e.g. towards
real time).

Page 31
Simba simulates the balancing in the Danish power system based on the current market rules and practices using
day-ahead schedules with one hour resolution and hour-ahead prognoses with 5 minutes resolution as input. The
output from the balancing is hour-ahead power plans for generation and power exchange with neighbouring power
systems using 5 minutes resolution. Another output is the volume and price of activated balancing power.
Simba has so far been used in the EU TWENTIES6 project with spot market inputs from WILMAR and in internal
Energinet.dk studies with spot market inputs from SIVAEL. The input and output interface to Simba is described in
sufficient detail in an Energinet.dk document, which makes it possible to use Simba with other tools like Balmorel,
which will be used in NSON-DK.
The present version of Simba includes coded web access to CorWind, which automatically provides Simba with the
wind power inputs generated by CorWind online. This web access can be extended to include PV power inputs.
Automatic control model
A model for automatic power and frequency control in the Danish power system has been developed and
implemented in the power system simulation software Power Factory as part of a PhD study in DTU Wind Energy. It
includes secondary and primary control. Figure 8 shows and overview of the model. It is an aggregated “cupper plate”
model of the Danish power system with one busbar for the western system and one for the eastern system. Thus,
the model is suitable for frequency control studies, but not for voltage control studies.
Figure 8. Overview of power flow in automatic control model.
The model has been developed to study possible secondary control contribution from wind power. It uses Simba
power plans (5 minute resolution) as input, and simulates the dynamics of the Load Frequency Control (LFC) at the
Danish boarder to Germany. The state-of-the-art of the model includes the following components:
 aggregated dynamic models for the large Combined Heat and Power (CHP) plants
 aggregated dynamic models for the Decentralised Combined Heat and Power (DCHP) plants
 aggregated dynamic models for wind generation with power control
 inputs (from Simba) of scheduled production for CHP, DCHP and interconnectors to neighbouring countries and
between the areas
 a model for the Load Frequency Control (LFC) at the border between western Denmark and Germany
6 http://www.twenties-project.eu/

Page 32
MODEL NAME: "KERMIT"
Model Category:
☐Market Model
☐Institutional Issues
sudden load rejection, and volatile renewable resource (wind, solar) ramping events. KERMIT is designed for the
study of power-system frequency behaviour and fills a critical gap in power system modelling by addressing the
one second to 24 hour timeframe.
Model Contribution
The model allows studying system dynamics and frequency development for longer time horizons than traditional
power system models. This allows simulating and analysing the utilisation of the different kinds of balancing
reserves.
Brief Description of Modelling Approach
DNV GL’s proprietary simulation tool KERMIT was originally designed to study the impact of variable non-
dispatchable resources on electric-power systems yet it is finding a variety of new applications with grid operators
across the U.S. and Europe. These applications range from assessment of long term expansion plans to installation
as a control room tool. Related topics were presented to the forum by researchers.
sudden load rejection, and volatile renewable resource (wind, solar) ramping events. The software runs on a Matlab®
platform and incorporates inertial, governor and regulation response as well as Automatic Generation Control (AGC),
balancing market logic and control of new technologies such as energy storage. Model input includes data on power
plants, wind and solar production, daily load profile and generation and interchange schedules. The outputs include
power plant output, area interchange and frequency deviation, real‐time dispatch requirements, and numerous other
dynamic variables on a second-by-second timescale. Figure 9 outlines the KERMIT model concept, its inputs and
outputs. KERMIT is designed for the study of power-system frequency behaviour and fills a critical gap in power
system modelling by addressing the one second to 24 hour timeframe.

Page 33
Figure 9: KERMIT model concept
A sample output from KERMIT, from a 2013 study evaluating the benefits and performance of energy storage
technologies, is shown in Figure 10. Here, the ACE performance for a 24 hour period is shown, contrasting the ACE
when no storage is deployed (blue) to the ACE of a system with 6 hours of storage available to smooth a large portion
of the renewable capacity on-line (red). The reduced ACE indicates a reduced need for regulation capacity, which
can be a significant cost saving.
Figure 10: Sample KERMIT Output: ACE

Page 34
1.1 Real-time estimation of inertia and governor response
Electric grid system inertia has historically been supplied by the rotating machinery of conventional generation. Inertia
is a fundamental component for system stability because it determines how fast the system frequency changes in
response to mismatches between system generation and demand. Inertia declines in systems with higher penetration
in variable renewable energy and distributed resources because the renewable and distributed generation production
erodes the share of power produced by conventional generation. Typically, the power electronic devices associated
with most renewable energy technologies limit the amount of inertia being provided by those resources.
A system with fewer conventional resources on-line, also has a reduced amount of primary frequency response, also
commonly referred to as governor response. Governor response is the capability of a generator to automatically
increase its output when system frequency falls below a given threshold. As systems become less flexible, the
amount of available governor response decreases and increases a system’s risk of cascading blackouts if a large
contingency event were to occur. Figure 11 depicts a typical frequency response associated with a generation unit
trip, depicting NERC defined A, B & C points and time windows for Inertial Frequency Response (1), Primary
Frequency Response (2) and Secondary Frequency Response (3).
Figure 11: Typical Frequency Response associated with generation unit trip
Today the boundaries of the problem are not known, i.e. how much inertial and governor response is needed, nor do
any usable tools exist to accurately determine the physical characteristics of the grid at a precise moment in time,
i.e., how much inertia and governor response is currently online. Lastly, tools to address the problem are lacking.
To that end, DNV GL is currently conducting a Research and Development project looking to create a framework of
methods to incorporate system inertia and governor response in short, medium, and long term planning processes.
This framework will also form the basis for a control room tool that system operators can use to estimate the total
inertia and governor response online in their system in real time.

Page 35
MODEL NAME: "Advance Dispatching"[23]
Model Category:
☒ Market Model
☐ Institutional Issues
manoeuvres (e.g. Unit Commitment) with minimum cost for the restoration of acceptable conditions.
As a matter of fact, the "Advance Dispatching" tool has the aim of restructuring the production plans and reserves
under the current system configuration, the available ex-post data and the very short-term forecasting results. In
fact, very short-term congestions, generator faults, or load increases have the effect of reducing the tertiary reserve
below unacceptable levels, so it becomes necessary the reprogramming of the Unit Commitment (UC) of
generating assets, which consists in starting units or changing their production configuration in case of combined
cycles.
Model Contribution
The common practice is fundamentally based on “deterministic sizing” criteria of the reserve, required to bear a
load demand foreseen the day ahead D-1 for the day D. This information feeds the D-1 deterministic procedures
for Unit Commitment and Dispatching. The uncertainties inherent the processes of operational planning and
dispatching are usually faced in D-1 by establishing deterministic operating margins and carrying out a probabilistic
verification.
“Advance Dispatching” reverses this approach for day D. Given an acceptable and ideally constant level of risk in
all the operating situations, “Advance Dispatching” provides to the real-time control environment an indication of
"deterministic synthesis" of the possible amount of reserves (present or allocated) which is missing or in excess
with respect of the theoretically associated level of risk accepted.
Brief Description of Modelling Approach
The “Advance Dispatching” solution (designed and developed by Terna and CESI) aims to formalise the execution
of very short-term adequacy tests according to the needs of managing the power system at a minimum and constant
risk in terms of load coverage. This analysis is carried out periodically with reference to the extended time period that
goes from the current hour to the end of the day, every time starting from the latest weather and load information, as
well as, in general, from the most detailed available situation of the network.
From the algorithmic point of view, the “Advance Dispatching” process makes predictive adequacy assessments
based on a probabilistic modelling of both the generators set and the load needs, respectively based on a reduced
combinatorial approach (making use of the failure rates of the individual production units) and a normal

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