Electricity Markets: Balancing Mechanisms and Congestion ...609988/FULLTEXT01.pdf · Master Thesis Report Mathilde Dupuy - 2 - ABSTRACT During the last few years, several European

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Electricity Markets:

Balancing Mechanisms and Congestion Management

Master Thesis Report

Mathilde Dupuy

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ABSTRACT

During the last few years, several European countries have opened their electricity

markets. Power exchanges have been created, and market based rules have been settled to

handle most of the existing mechanisms. The main goal is to improve the competition by

increasing the number of actors. More and more coordination between the different European

markets is now needed, and the trend is to go from juxtaposed regional markets to a unique

European market. Indeed, in February 2006 was launched the Electricity Regional Initiative,

where directives were given in order to foster market integration within several European

countries. In this context, two main points have to be focused on: the settlement of market

based rules for each mechanism and the integration of the different existing markets.

This master thesis is a part of a Research and Development project, and has been done

at EDF Research & Development, in the department “Economie, Fonctionnement et Etudes

des Systèmes Electriques”. It is divided in two parts.

The first part explains the main principles of the balancing mechanisms in Great-

Britain and Germany, in order to see to which extend these mechanisms are “markets”. The

study is a part of a larger project at EDF, resulting in a benchmark of the different European

Balancing Markets.

The second part deals with a key to the integration of electricity markets: the

congestion management methods. Indeed, cross border congestions are a main hindrance to

the elaboration of a European market, and new mechanisms are developed to allocate the

cross border capacities. One of them is the Market Coupling, which is a way to maximize the

market value. This thesis aims at giving a basic understanding of the method as it is carried

out today between France, Belgium and the Netherlands through the Trilateral Market

Coupling. In the frame of an Open Market Coupling including more countries, this thesis

gives an introduction to two different approaches: the “commercial” approach and the “flow-

based” approach. Simulations aim at stressing the main differences between the two methods.

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ACKNOWLEDGMENTS

Firstly, I would like to thank Jeremy Louyrette, who has accepted to be my supervisor

at EDF. I would like to thank all the people with whom I had the occasion to work at EDF for

their cooperation and for the great working environment they have provided to me.

This master thesis has allowed me to learn a lot on very interesting and challenging topics,

and I am very grateful for that.

Besides, I would like to thank Lennart Söder and Mikael Amelin for reviewing my

thesis and being my examiners.

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CONTENTS

Chapter I. Introduction ................................................................................................................................. 10

I.A. Background................................................................................................................................................ 10

I.B. Thesis work: Scope and Contents .............................................................................................................. 11

Chapter II. Balancing Markets: The examples of Great Britain and Germany ................................... 12

II.A. Background .............................................................................................................................................. 12 II.A.1 The different actors ........................................................................................................................... 12 II.A.2 The main principles........................................................................................................................... 13 II.A.3 Aim of the study................................................................................................................................ 13

II.B. Balancing mechanism in Great-Britain.................................................................................................... 15 I.A.1 Description of balancing services....................................................................................................... 15

II.B.1.1. Frequency response .................................................................................................................. 15 II.B.1.2. Reserve services ....................................................................................................................... 16

II.B.2 The Balancing Mechanism and the “market” aspect ......................................................................... 17 II.B.2.1. How the market works.............................................................................................................. 18 II.B.2.2. Imbalance Settlement ............................................................................................................... 21

II.C. Balancing mechanism in Germany .......................................................................................................... 23 II.C.1 Description of the services ................................................................................................................ 23

II.C.1.1. Primary control ......................................................................................................................... 23 II.C.1.2. Secondary control ..................................................................................................................... 23 II.C.1.3. Tertiary control: Minutenreserve .............................................................................................. 23 II.C.1.4. Time frame of control energy ................................................................................................... 24

II.C.2 The Balancing mechanism and the “market” aspect ......................................................................... 25 II.C.2.1. How the market works.............................................................................................................. 25 II.C.2.2. Imbalance settlement ................................................................................................................ 28 II.C.2.3. The particular case of wind power............................................................................................ 29

II.D. Conclusions.............................................................................................................................................. 30

Chapter III. Congestion Management: The Market Coupling Mechanism............................................ 32

III.A. Background............................................................................................................................................. 32

III.B. Market Coupling: Analysis of the mechanism principles........................................................................ 33 III.B.1 Some basic principles....................................................................................................................... 34

III.B.1.1. Aggregated supply and demand curves ................................................................................... 34 III.B.1.2. Net exportation curves ............................................................................................................ 35 III.B.1.3. Block offers............................................................................................................................. 37

III.B.2 Trilateral Market Coupling: how does it work? ............................................................................... 37 III.B.2.1. Overview of the mechanism as it is carried out today............................................................. 37 III.B.2.2. Algorithm of the coordination module: Coupling three markets............................................. 39

III.C. Simulation of Market Coupling............................................................................................................... 43 III.C.1 Simulation on three markets using a sequential algorithm............................................................... 43

III.C.1.1. Inputs and Outputs of the simulation....................................................................................... 43 III.C.1.2. Prices calculation..................................................................................................................... 44 III.C.1.3. Algorithm principles ............................................................................................................... 44 III.C.1.4. Steps of the algorithm ............................................................................................................. 45 III.C.1.5. Particularities of the model...................................................................................................... 51 III.C.1.6. Conclusion regarding the sequential model ............................................................................ 51

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III.C.2 Market Coupling as a system-wide optimisation problem............................................................... 52 III.C.2.1. Definition of the parameters and variables.............................................................................. 52 III.C.2.2. Definition of the objective function ........................................................................................ 53 III.C.2.3. Formulation of the constraints................................................................................................. 55 III.C.2.4. Particularities of the simulation............................................................................................... 56 III.C.2.5. Calculation of the market prices and surplus........................................................................... 57

III.C.3 Results of the simulation: Sequential model versus optimisation .................................................... 58 III.C.4 Conclusions regarding the results .................................................................................................... 64 III.C.5 Perspectives ..................................................................................................................................... 64

III.D. Towards an Open Market Coupling ....................................................................................................... 66 III.D.1 Elaboration of the scenarios............................................................................................................. 66 III.D.2 Result of the simulations.................................................................................................................. 67

III.E. Towards a flow-based market coupling .................................................................................................. 75 III.E.1 Formulation of the problem with the Power Transfer Distribution Factors ..................................... 75 III.E.2 Data used in the model ..................................................................................................................... 76 III.E.3 Simulation on the scenarios.............................................................................................................. 79

III.F. The commercial approach versus the flow based approach ................................................................... 85

Chapter IV. Conclusions ............................................................................................................................. 86

IV.A. Main aspects of the study ........................................................................................................................ 86

IV.B. Perspectives ............................................................................................................................................ 87

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FIGURES

Figure 1: Timescales of electricity markets ............................................................................. 10

Figure 2: Timescales of the balancing services ....................................................................... 17

Figure 3: Timescales of the British electricity market ............................................................. 18

Figure 4: Bid/Offer Data [5] ................................................................................................... 19

Figure 5: Representations of the bid/offer data ....................................................................... 19

Figure 6:Bid/offer acceptance (BOA) [6] ................................................................................ 20

Figure 7: Main Price calculation in case of a short system .................................................... 22

Figure 8: Timescales of the different kinds of reserve [2] ....................................................... 24

Figure 9: The different timescales of the German market ....................................................... 25

Figure 10: Example of bid data [3] ......................................................................................... 26

Figure 11:Extract of tender results for downwards regulation for tertiary reserves

(10.07.2007, 12:00-16:00) [16] ............................................................................................... 27

Figure 12:Extract of tender results for upwards regulation for tertiary reserves

(10.07.2007, 00:00-4:00) [16] ................................................................................................. 28

Figure 13 : The different congestion management methods in Europe [26] ........................... 32

Figure 14: Coupling of two markets when there is no congestion........................................... 35

Figure 15: Coupling of two markets when there is a congestion............................................. 35

Figure 16: Construction of the Net Exportation Curve ........................................................... 36

Figure 17: Bilateral Coupling using the NECs........................................................................ 36

Figure 18: Overview of different steps in the Market Coupling process [25] ......................... 38

Figure 19: First step of the TLC .............................................................................................. 39

Figure 20: Second step of the TLC, non-congested case ......................................................... 40

Figure 21: Second step of the TLC, non-congested case ......................................................... 40

Figure 22: TLC results, congested case................................................................................... 41



Figure 25: System studied ........................................................................................................ 43

Figure 26: Effect of an import or an export on the NEC ......................................................... 44

Figure 27: Coupling three markets with no constraints – incremental process ...................... 47

Figure 28: Coupling three markets with constraints – incremental process ........................... 49

Figure 29: Calculation of the consumers’ and producers’ surplus, ........................................ 50

Figure 30: Effect of an import/export on the supply an demand curves.................................. 50

Figure 31: Definition of the parameters .................................................................................. 52

Figure 32: Global surplus of the three markets aggregated, in case of no congestion ........... 54

Figure 33: Definition of the variables...................................................................................... 56

Figure 34: Particularities with linear curves .......................................................................... 56

Figure 35: Price and Volume indeterminations....................................................................... 57

Figure 36: Results of the simulation, scenario 1 ..................................................................... 59



Figure 39: Results of the simulation, scenario 4 .................................................................... 62


Figure 41: Calculation of the surplus using the NECs ............................................................ 65

Figure 42: Increase of the surplus resulting from the coupling............................................... 65

Figure 43: Results from the base scenario using the ATC model ............................................ 67

Figure 44: Results from the scenario 1 using the ATC model ................................................. 68


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Figure 50 : Power flow distribution of a 1000 MW trnasport from Northern France to Italy 75

Figure 51:Results from the base scenario using the PTDF model .......................................... 79

Figure 52: Comparison of the results from the base scenario................................................. 80

Figure 53: Comparison of the results from the scenario 1 ...................................................... 81






Figure 59: Metered Imbalance ................................................................................................ 88

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TABLES

Table 1: The different actors .................................................................................................... 17

Table 2: Imbalance settlement prices....................................................................................... 22

Table 3: The different kinds of reserve in Germany................................................................. 24

Table 4: Main aspects of the British and German Balancing Markets.................................... 31

Table 5: Results of the simulation, scenario 1 ......................................................................... 59



Table 8: : Results of the simulation, scenario 4....................................................................... 62

Table 9: Results of the simulation, scenario 5 ........................................................................ 63

Table 10: Prices of the futures for the second semester 2008 ................................................. 66

Table 11: Volumes on the spot market in 2006........................................................................ 66

Table 12: Day-ahead market volumes ..................................................................................... 66

Table 13: ATC matrix (in MW) ................................................................................................ 67

Table 14: Average balances in MW ......................................................................................... 76

Table 15: Initial Balances in MW ............................................................................................ 77

Table 16: Data used for PTDF and T0 .................................................................................... 77

Table 17 : Prices in €/MWh ..................................................................................................... 79

Table 18: Physical power flows, Base scenario....................................................................... 80

Table 19: Constraints on the pysical power flows ................................................................... 80

Table 20: Physical power flows and their limitations.............................................................. 83

Table 21: Physical power flows and their limitations.............................................................. 84

Table 22: Activation of minute reserve .................................................................................... 88

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LIST OF ABREVIATIONS

• EDF: Electricité de France (main company of electricity production and distribution in

France)

• RTE: Réseau de Transport d’Electricité (French TSO)

• TSO: Transmission System Operator

• UCTE: Union for the Coordination of Transmission of Electricity

• ETSO: Association of the European Transmission Operators

• CWE: Central Western Europe

• E&W: England and Wales

• TLC: Trilateral Market Coupling

• OMC: Open Market Coupling

• NEC: Net Exportation Curve

• NIC: Net Importation Curve

• ATC: Available Transfer Capacity

• NTC: Net Transfer Capacity

• PTDF: Power Transfer Distribution Factor

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Chapter I. Introduction

I.A. Background

In 1989, England opened its market, and Sweden followed in 1995. The first

international power pool, NordPool, was founded in the Scandinavian countries.

In the current context of opening energy markets, new objectives have become a priority.

The main goal is to allow a better competition, by increasing the number of actors. The trend

is nowadays to abolish the situations of monopoly, and base the new mechanisms on a

reduction of the overall costs. Market-based rules are laid down, in order to create a fair and

non-discriminatory market for every mechanism.

Therefore, each country in Europe has developed their own energy market, and by a better

coordination of these markets, the final goal is to integrate all of them in a unique European

market. Hereby, it would not only ensure a better economical stability, but a better physical

stability as well through a wider power system.

New methods are created for trading energy, planning production, keeping the balance

between production and consumption and managing the energy transactions on cross border

transmission lines. All of these activities are done on different timescales, corresponding to

the general description below:

Time

Years, Months, Weeks

Futures & Forward

Markets

Bilateral Market

D-1

Spot

Market

D

Intraday

Market

Real Time

Balancing

Market

Program

redeclarations

• Bids & Offers

Submission

• Initial Planning

• After the Gate closure:

Bids & Offers selection,

Pricing

Real time energy

balancing

operated by the

TSO

D+1

Imbalance

SettlementLong term contracts

D+n

Figure 1: Timescales of electricity markets

On the Futures and Forwards market, long term contracts are decided: a certain amount of

energy for a defined period of time and on an agreed price is contracted. A forward is a

bilateral contract, whereas the future is contracted on an organized market and is a

standardized product.

On the day-ahead spot market, the actors submit their bids and offers, and units submit

their production planning before the gate closure. The time of the gate closure depends on the

country. After closure of the bilateral market and the spot market, bids and offers are selected,

and the spot price is set up, through a price clearing.

Then during the day, in the so-called intra-day market, generation programs can be re-

declared and market players can modify existing bilateral contracts or create new ones.

Besides, in real time, the Transmission System Operator must keep the balance between

production and consumption, through the balancing market. Finally, the imbalance metered

between contractual and physical positions of actors is financially settled after the day of

delivery.

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I.B. Thesis work: Scope and Contents

The thesis is divided in two parts: the first one focuses on the balancing mechanism,

corresponding to the real time in the different timescales of the market. The second one

presents a study of a congestion management method, the market coupling, which takes place

in the day-ahead market, and will probably be adopted in the intra-day market as well.

The first part of the project consists of studying the balancing mechanisms in Germany

and Great-Britain, based on literature. This was in fact a participation to a larger project,

aiming at describing and analysing the different balancing mechanisms in Europe. This

project has been carried out by EDF in order to have a benchmark of the different European

balancing markets, focusing on the format of the bids and offers. Indeed, the orders submitted

on the French balancing market are implicit, but they are to become explicit orders.

In this frame, two countries have been studied. Even if it does not give a general view

upon the existing mechanisms in Europe, it was interesting to study in detail two countries, so

that differences and likenesses could be pointed out. In this report, a summary of the study is

given, in order to give concise information regarding the two mechanisms.

If the trend is to integrate the different markets in a unique one, an increasing part of

energy transaction between the different European markets will be necessary and especially

balancing energy. To fulfil these objectives, new congestion management methods are

adopted, in order to make an optimal use of the cross border transmission lines.

Among them, the Market Coupling mechanism has been implemented in Central Western

Europe. Trilateral Market Coupling was launched between France, Belgium and the

Netherlands in November 2006. The mechanism is about to be extended to other border

countries like Germany.

In this report, we will first study the theoretical approach of market coupling and how it is

handled between France, Belgium and the Netherlands. Then, we will try to formulate the

problem in different ways and simulate the mechanism using theoretical data.

Finally, a small study will explain the differences between a commercial approach and a

flow-based approach.

In this frame, two models have been developed:

� The first one simulates the mechanism for three countries, and has been implemented

using Excel and its programming language Visual Basic for Application. It calculates

the final prices and energy transactions between the markets, starting with the net

exportation curves of the isolated markets, and the cross-border transmission

capacities.

� The second one is an optimisation under constraints using GAMS, and can be used

with N markets. Two approaches have been implemented:

• The commercial approach, where transmission constraints take into account

commercial limitations of the energy transactions.

• The flow-based approach, where transmission constraint takes into account

physical limitations of the power flows.

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Chapter II.

Balancing Markets: the examples of Great Britain and

Germany

II.A. Background

The main specificity of electric energy is that it cannot be stored. Moreover, in order to

ensure the security of the electricity network, the balance between production and

consumption must be kept all the time.

In the day-ahead market, supply and demand curves are submitted for each settlement

period of the following day. According to these data, the balance between production and

consumption is respected, since the energy price and the traded volume are defined by the

intersection of the two curves. Nevertheless, these data are only forecasts, and the real time

situation might be different. Indeed, the demand can vary compared to the forecast, and the

production planning can fluctuate, in case of a problem in a power plant for example.

To handle those variations, a mechanism is needed to balance in real time the

consumption and the production; it is the so-called balancing mechanism.

From a country to another, the balancing mechanisms may be different, depending on the

timescales of the market, the technical differences, the means of generation or the national

rules. Nevertheless, the common trend in deregulated market is to build a market with the

balancing mechanism, based on market rules.

Though differences between countries, some common principles define the general scope

of the balancing mechanism, when it is based on market rules:

� Production plan and load forecast, which takes into account bilateral contracts, and

bidding on the day-ahead spot market.

� Balancing generation and consumption in real-time by the means of re-declarations of

generation planning and bidding on the short term balancing market, which is an intra-

day market where bids are selected and activated in real time.

� Financial imbalance settlement between physical and contractual positions. It

generally takes place the following day and spreads fairly the incomes and costs

among the actors.

II.A.1 The different actors

� The balancing mechanism is carried out in real time by the Transmission System

Operator, who is required to maintain the permanent balance between generation and

demand.

� The units which are qualified can participate to the balancing market by submitting

bids1 and offers

2.

1 Downwards regulation order

2 Upwards regulation order

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� The Balance Responsible Entity, who is in charge of a balancing perimeter, is

responsible for the financial settlement of imbalances within its perimeter. Every

market player has to belong to a balancing perimeter and choose a balancing

responsible.

II.A.2 The main principles

To handle real time deviations between injection and withdrawals in the electrical grid,

the TSO dispose of three different kinds of reserve power, which can be used for upwards or

downwards regulations:

� Primary Reserve

This kind of reserve is automatically activated. It is usually compulsory and never

constitutes the object of a market. The cost of this control are recovered through the

networks tariffs, based on the metered quantities of generators and consumers.

� Secondary Reserve (only for the UCTE network)

This kind of reserve is automatically activated in most cases. Depending on the country, it

can be part of a balancing market. The aim of the reserve is to reconstitute the primary

reserve when it has been used.

� Tertiary Reserve

This reserve is a complementary reserve, and is often the core of the balancing market. It

is usually manually activated, and split into rapid reserve (available in less than 10-15

minutes) and cold reserve (available after a longer time). However, in some countries, the

boundaries between secondary and tertiary reserve and between the two types of tertiary

reserve are blurred.

According to the ETSO [9], three groups are identified having different services for

frequency control:

� UCTE (Union for the Coordination of Transmission of Electricity), where the three

kinds if services described above are available

� E&W (England and Wales), where the secondary control does not exist and is in

fact a part of the primary control

� The Nordel (common power system of the Nordic countries), where the so-called

“Secondary Regulation” is referred to as tertiary control, since it is manually

activated.

The object of balancing mechanism is mainly tertiary reserves, and sometimes secondary

reserves as well. This can vary from a country to another.

II.A.3 Aim of the study

The aim of the first study is to analyse the balancing mechanisms in two countries, Great-

Britain and Germany. This will allow us to see to which extent the mechanism can differ

between two countries. In order to stress the important differences and define the changes to

set up to reach a better harmonisation in Europe, it would be necessary to study the

mechanisms in all the European countries. However, it is not the aim of this master thesis.

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This study has been carried out in a frame of a project, which aims at focusing on the

format of the orders and the type of services they are related to.

Indeed, on balancing markets, there are two types of orders: offers for upwards regulation

and bids for downwards regulation. The format of an order might be different from a country

to another. In France, the current orders are implicit, which means that a producer must offer

on the balancing market the available capacity remaining after the submission of its planning.

However, this situation might change, and let the actors submit explicit offers, with a chosen

quantity and price.

Studying two countries will not give a general European scope of the situation, but it will

nevertheless show important aspects of the balancing mechanisms, and point out some aspects

that should be harmonised.

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II.B. Balancing mechanism in Great-Britain

National Grid Company (NGC) owns and manages the electricity transmission system in

England and Wales (E&W). By supplying Balancing Services, it maintains the balance

between injections and withdrawals on the grid. Therefore, it uses available reserves in order

to keep the system frequent at 50 ± 0.5 Hz. The allowed deviation from the nominal

frequency 50 Hz is higher than the one allowed by the UCTE, which is 50 ± 0.2 Hz. The

British synchronous network has a lower inertia than the UCTE network, due to the nature of

its generation power plant. Therefore, its network is more often prone to frequency deviation,

and needs balancing power.

Since the Great Britain is not connected to the rest of Europe, the system services are

carried out in a different way [1]. Secondary control does not exist in Great Britain.

We can distinguish three different types of balancing services [8]:

� Ancillary services, which are the system services procured by electricity producers.

There can be either mandatory or commercialised, and are detailed in the first

section

� Offers and Bids, submitted to the Balancing Mechanism. These are commercial

services offered by suppliers willing to increase or decrease the production in a

Balancing Mechanism Unit (BMU). These services are detailed in the second

section

� Other services, which are commercialised services. They are classified neither as

ancillary services nor as balancing market offers and bids.

The actors of the British balancing mechanism are:

� The TSO National Grid Company

� The BMU, which are units signatories of the Balancing and Settlement Code

� Actors not registered as BMU in some cases

II.A.1 Description of balancing services

II.B.1.1. Frequency response

Frequency response services are equivalent to the primary and secondary control in the

UCTE zone. They are part of system services, but can be remunerated.[1,2]. Dynamic

providers are in charge of handling changes second by second, whereas the non dynamic

providers change their production only from a certain level of frequency deviation.

NGC maintains the system frequency through three separate balancing services:

� Mandatory Frequency Response

The service is compulsory and automatic, guaranteed by BMUs. The bids contain an

availability fee (in £/h) and an energy fee (£/MWh). The aspect “market” is introduced

thanks to a system which allows the participant to modify the prices on a monthly basis, in

order to set a greater competition.

� Firm Frequency Response (FFR)

This service is commercialised by BMU or non-BMU actors, and act as a complement

of the other sources of Frequency Response, through dynamic and non-dynamic reserves.

FFR is procured through a monthly tender; the submitted orders can be valid for a single

month or several months. A provider submits several prices in its bid: an availability fee

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(in £/h), an energy fee (£/h) and fees related the nomination or the revision of the offer on

a particular settlement period3 of the day.

� Frequency Control Demand Management (FCDM)

This service provides frequency response through interruption of the demand

customers; it is a way for demand-side provider to access to the market. However, the

service is conclude on a bilateral basis, and the remuneration is based on an availability

fee (£/MWh).

II.B.1.2. Reserve services

The remaining services correspond more to the tertiary reserves of the UCTE. It

contains the additional power sources which are available to NGC, and comprised

synchronised and non-synchronised sources, with different response times. [3]

� Fast start

It is a non compulsory system ancillary service, commercialised by BMU units. It is

provided by power plants which can start in a very short time (5-7 minutes), and is

concluded through bilateral contracts.

The bids contain an availability fee (£/h), an energy fee (£/MWh) and a start-up payment

(£/start).

� Fast reserve

The service is provided by BMU and non BMU, both from the production and demand

sides. The aim is to rapidly handle the frequency deviations, in less than 2 minutes. The

service is procured through a monthly tender. A provider submit several prices in its bid:

an availability fee (in £/h), an energy fee (£/MWh) and fees related the nomination or the

revision of the offer on a particular settlement period of the day.

� Short Term Operating Reserve (STOR)

The service is provided by BUM and non BMU, both from the production and demand

sides, with longer response time (240minutes).

The utilisation of this service is done through the balancing mechanism only for the BMU.

The bids contains an availability fee (£/h) and an energy fee (£/MWh).

� Demand management

The service provides reserve via a reduction of the demand. It is concluded through

bilateral agreements; there is only an energy fee (£/MWh).

� BM start-up

The service is provided by BMU only, and allows NGC to use in the balancing

mechanism additional units that would not otherwise have ran. The remuneration is based

on a start-up payment and a hot standby payment (£/h) to cover the cost of sustaining a

BMU in a state of readiness.

3 In the British system, the day is divided into 48 “windows”, or settlement period, of ½ hour each.

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Finally, this summary of the balancing services offers in Great Britain show the

complexity of the system. The pictures below show the different timescales and actors

involved in each type of service.

Demand

Management

STOR

BM Start-up

Fast Start

Fast reserve Frequency

Response

< 240 min

< 85 min

< 5 min

< 2 min

< 1 sec

T-24 h T

FCDM

< 2 sec

Time

Figure 2: Timescales of the balancing services

Services BMU participation Non-BMU Participation

Mandatory Frequency

response

Suppliers

Firm Frequency response Suppliers & Consumers Suppliers & Consumers

FCDM Consumers

Fast Reserve Suppliers & Consumers Suppliers & Consumers

Fast Start Suppliers

STOR Suppliers & Consumers Suppliers & Consumers

Demand Management Consumers

BM Start-up Suppliers

Table 1: The different actors

II.B.2 The Balancing Mechanism and the “market” aspect

In 2001, The New Electricity Trading Arrangement (NETA) is introduced and then

extended to Scotland. The aim of this system is to allow a greater competition in the

wholesale market, while ensuring the security of the system.[6]

The new arrangements include:

• Forwards and Futures markets

• A Balancing mechanism, by which the TSO can accept offers and bids to

maintain the balance between production and consumption

• An imbalance settlement process, a financial settlement of the observed

imbalances

Through the Balancing Mechanism, NGC can buy and sell energy close to real time,

using the offers4 and bids

5 submitted by the actors. The acceptance of a bid or an offer is

managed by the Balancing and Settlement Company Elexon .

4 Upwards regulation

5 Downwards regulation

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NGC provides the balancing services through the balancing mechanisms or other means

(bilateral contracts, specific tender for certain system services)[7].

The volumes and costs of balancing services concluded outside of the Balancing Mechanism

are integrated afterwards in the calculation of the prices for the imbalance settlement.

II.B.2.1. How the market works

Only the bids and offers belong to the balancing mechanism, which will work on

market based rules.

II.B.2.1.a. The different timescales

One of a feature of the British market is that there is a gate closure every half hour

during the whole day. Indeed, for each settlement period, the gate closure is one hour before

the beginning of this period. By this time, producers should have submitted their final

production plan, called the Final Physical Notification, and the BMUs should have submitted

their offers and bids as well.

Forward/Futures Markets

Bilateral Market

Balancing Mechanism

(on behalf of NGC)

Imbalance Settlement

(on behalf of Elexon)

T –1h

Gate Closure

T T+1/2h

-Bilateral & Forward contracts

-NGC contracts primary reserve and

other reserve contracts

NGC accepts offers & bids

for system energy

balancing

Settlement of cash flows

arising from the balancing

process

-FPN Submission

-Bids & Offers Submission

Figure 3: Timescales of the British electricity market

II.B.2.1.b. Format of the Bids & Offers

Each order are under the form of a “Bid-Offer pair”, which means that the provider

offers an interval of available capacity (a deviation from the FPN level) which can be used for

upwards or downwards regulation, depending on the level of production. Therefore, for each

submitted pair Bid/Offer, the unit defines a power level (number of MW, positive or

negative); which represents a variation from the planned level of production.

Each pair has a number, positive if the level is higher than the FPN, negative if it is

lower. The minimum order is 1 MW, and each one contain an energy price for the offer and

an energy price for the bid (£/MWh).

- 19 -

An example is given below:

Figure 4: Bid/Offer Data [5]

Each BMU can submit 10 pairs; the level of MW must be constant on each settlement period

[6]. The number of the pair increases with the proposed price.

To put it in a nutshell, the BMU offers an capacity interval, in which it can vary its

production depending on the need. It cannot offer only an upwards regulation; or only a

downwards regulation. The energy price depends on the level of the production compared to

the FPN level.

For example, considering the former bid/offer data and a FPN at 200 MW, then:

- If NGC wants to increase the production with 50 MW, starting from the FPN at 200 MW,

the energy price will be 30£/MWh

- If NGC needs afterwards a downward regulation of 80 MW, the BMU will pay 25£/MW

between 250 MW and 200 MW (pair 1), and then 20£/MW (pair –1)

The process is shown in the picture below:

Price

(€/MWh)

Puissance (MW)FPN(200 MW)

10

20

30

40

Offer Price

Bid Price

250 290 310 340160130

(-2)(-1)

(1)(2)

(3)(4)

Figure 5: Representations of the bid/offer data

- 20 -

If three positive pairs have been used for upwards regulation, the TSO must use the bid part of

those pairs before using a negative pair.

Furthermore, each BMU must submit a list of technical parameters with the order, to

allow NGC to compare it with the available system services and make the best choice. [5]

Those information concern especially the dynamic parameters, the generator specificities, the

limitation of injection and withdrawal at the network connection point…

Those parameters and the proposed prices are essential in the decision of using a bid/offer

pair instead of another reserve service.

II.B.2.1.c. Bids and Offers selection

The selection takes place right after the gate closure, based upon technical and economical

criteria.

Though the ancillary services are mainly considered as outside the Balancing Mechanism [8],

there can be used in the following case:

- NGC considers there will not be sufficient bids and offers to ensure the

security of the system

- NGC considers that they are an economical alternative to bids and offers

- The technical parameters of the offers and bids do not fit the requirements

The offers and bids, though explicit when they are submitted, are more implicit when they

are selected. Indeed, NGC can choose the quantity, and can thus accept an pair bid/offer

partly, as shown in the following example:

Figure 6: Bid/offer acceptance (BOA) [6]

The points A, B, C and D represent the accepted level, function of the time. The blue area

represents the acceptance energy volume. The picture above is called a Bid offer Acceptance.

A BMU can reject it only for security or technical reasons.

II.B.2.1.d. Remuneration

The services are paid at the bid or offer price, and not the marginal price: it is a pay-as-bid

system [6, 9]. It is important to notice that the capacity of the bids and offers are not paid for.

- 21 -

II.B.2.2. Imbalance Settlement

II.B.2.2.a. Imbalance definition

After each settlement period, the volume of the overall system energy imbalance is

calculated, in order to see if the system is globally long or short. It is the net of all systems

and energy balancing actions (including the ancillary services used outside of the balancing

mechanism) taken by the TSO for the considered period. [6]

It is called the Net Imbalance Volume (NIV):

- If NIV<0, the system is long (NGC must sell energy)

- If NIV>0, the system is short (NGC must buy energy)

Each BMU belongs to a Trading Unit, which is balance responsible. Therefore, a

Trading Unit contains several BMUs, regrouping the production on one side and the

consumption on the other. When the imbalance is calculated, only the imbalance of the whole

Trading Unit is considered, and not each BMU separately. This allows a compensation effect

between the different physical imbalances among the BMU.

Concerning the financial imbalance settlement, it is important to notice that the

imbalance is separated in two parts. Indeed, each balance responsible has two energy

accounts: one generation energy account and one production energy account.[10, 12]

Therefore, financially speaking, and there is no compensation between deviation registered on

the production side and deviation registered on the consumption side.

For example, let us consider a system where the deviations metered (compare to the

forecasts) are the following:

- An excess of 50 MWh in the production

- An excess of 50 MWh in the consumption

The overall imbalance is equal to zero, but the balance responsible must pay for a deviation of

100 MWh.

II.B.2.2.b. Financial Settlement

For each settlement period of a day, two prices are calculated:

- SSP, the System Sell Price, paid to the Trading Units, in case of a long

position

- SBP, the System Buy Price, paid by the Trading Units, in case of a

short position

These prices take into account the volume and prices of the accepted bids and offers.

The costs from the use of other system services contracted outside the balancing mechanism

appear also in the calculation, in the Balancing Services Adjustment Data (BSAD).

Indeed, for economical or technical reasons, NGC can use a balancing service outside the BM

instead of an offer or bid, and then its cost appears in the imbalance settlement prices, through

the BSAD. [6,14]

If the balancing service is provided by a BMU, the payment of the energy used is done

via the BM, and the availability fee (payment for the capacity) is integrated to the BSAD.

The services included in the BSAD are a priori the following: STOR, fast reserve, BM Start-

up. [13] NGC submits these data for each hour, the day before at 17:00 PM.

- 22 -

The imbalance settlement is based on two prices:

� The main price, paid for the imbalance which are in the same direction as the

Transmission Operator (ie the overall system): the referred balance responsible

contributes to the system deviation

� The reverse price, paid for the imbalance which are in the opposite direction to

the Transmission Operator : the referred balance responsible counters to the

system deviation

Before 2006, the SBP and the SSP were respectively equal to the average price of the

accepted offers and bids.

Since 2006, the calculation depends on the position of the system, and is more

penalizing. Indeed, the main price is calculated based on the marginal 500 MWh of accepted

offers and bids. For example, if the system is short, SBP is calculated as the volume weighted

average of 500 MWh of the most expensive offers which have been used.

The defined volume (500 MWh here) is called the Price Average Reference Volume.

Price

(€/MWh)

Price

(€/MWh)

Volume of

accepted

Offers

Volume of

accepted

Offers

marginal

500 MWhVolume

weighted

average

price

Volume

weighted

average

price

Figure 7: Main Price calculation in case of a short system

The reverse price is based on the volume weighted average of the purchase and sale

done before the Gate Closure. It is the Market Index Data (MID), which is the price of the

wholesale electricity in the short term market, related to the referred half hour. [6]

Finally, this system with two energy imbalance prices is an incentive for a better

forecast of the production and demand. Indeed, a producer with a deviation from its planning

can cannot make a benefit, but, on the contrary, often looses money.

Balance Resp.

ImbalanceSystem

positionlong

long

short

short

MID (SBP)

(main price)

MID (SSP)

(main price)

SSP

(reverse price)

SBP

(reverse price)

Table 2: Imbalance settlement prices

- 23 -

II.C. Balancing mechanism in Germany

Germany is divided four zones, each one controlled by a different TSO: RWE, EnBW,

E-ON and Vattenfall Europe Transmission6.

The TSOs are required to maintain the permanent balance between production and demand,

and provide balancing energy to the balancing groups.

Verband der Netzbetreiber (VDN) is an independent association, founded in 2001, which

represents the four TSOs. The Bundesnetzegentur (Federal Network Agency) is the common

regulator for the German networks, and in particular the electricity network. [18]

Concerning the frequency regulation, the three main kinds of services are conformed

to the definition of the UCTE:

- Primärregelung, which corresponds to the primary control

- Sekundärregelung, which corresponds to the secondary control

- Minutenreserve, which corresponds to a fast tertiary reserve

As a part of the UCTE Network, Germany must keep the frequency level at 50 ± 0.2 Hz.

Since 2001, the three kinds of services are procured through a competitive bidding,

each service having its own market. All the balancing services are therefore commercialised

and remunerated.[9] These markets appeared gradually: in February 2001 for RWE, in August

2001 for E-ON, in August 2002 for EnBW and in September 2002 for Vattenfall Europe

Transmission.

On these markets, about 7 000 MW are contracted every day for upwards regulation,

of which 3 000 MW of minute reserve, and about 5 500 MW for downwards regulation, of

which 2 000 MW of minute reserve.

II.C.1 Description of the services

II.C.1.1. Primary control

This service in provided by all synchronously connected power system inside the

UCTE area. It is automatic, must be delivered within 30 seconds, and for an incident of less

than 15 minutes.

II.C.1.2. Secondary control

This service is provided by the concerned TSO. It is semi-automatic, and must be

delivered within 5 minutes, and for an incident which lasts between 30 seconds and 15

minutes.

II.C.1.3. Tertiary control: Minutenreserve

This service reconstitutes the secondary reserves and acts as a complement to the

secondary control. The TSO uses this kind of reserve in case of a large imbalance between

production and demand. The service is manually activated by the affected TSO; it must be

provided within 15 minutes, and for an incident which lasts up to an hour. The duration of the

settlement period in Germany, which is fifteen minutes, gives a special role to this kind of

6 RWE Transportnetz Strom GmbHNET, EnBW Transportnetze AG, EON Netz GmtH, Vattenfall Europe

Transmission GmbH

- 24 -

reserve. In case the TSO is not able to meet its needs in minute reserve, it must set up

transactions with other TSOs to face the problem.

II.C.1.4. Time frame of control energy

According to the German market rules, the TSOs are responsible for supplying reserve

energy during the first hour of the incident. Then it becomes the affected balance responsible

who is in charge of the compensation via bilateral contracts.[15,21]

Figure 8: Timescales of the different kinds of reserve [2]

This last information might refer to another kind of reserve, the Stundenreserve, which

is provided within an hour. This slower reserve depends upon the balance responsible, and is a

way for the TSO to constitute a operating margin.[1]

In case of a major problem, the Stundenreserve is completed by the Notereserve, which is a

special reserve contracted by the TSO on the market. If there is an emergency, the balance

responsible can ask the TSO for this reserve.

Finally, the Kurtzeitreserve (primary, secondary and minute reserve) are the

responsibility of the TSOs, whereas the Stundenreserve and the Noterserve depends upon the

balance responsible.

The different reserves are summarized in the table hereafter:

Type of reserve Response time Who is responsible for the

reserve ?

Primary control ≤ 30 secondes All the TSO (in the UCTE)

Secondary control ≤ 5 minutes The TSO of the affected zone

Minutenreserve ≤ 15 minutes The TSO of the affected zone

Stundenreserve ≤ 1 heure The balance responsible of the

affected balancing group

Tertiary control

Notreserve variable The balance responsible of the

affected balancing group

Table 3: The different kinds of reserve in Germany

- 25 -

II.C.2 The Balancing mechanism and the “market” aspect

Procurement of primary, secondary and minute reserve is done through a tendering

process. Therefore, we can speak of a balancing “market”. Each TSOs has its owns “reserve

markets”. Primary and secondary reserves are based on a semi-annual tender, whereas minute

reserve is based on a daily tender. Recently, a common platform has been set up for the

minute reserve, so that the four TSOs can organise a common tender [16].

Many actors participate to the tender, even small ones via pooling systems. Due to an

important cooperation between the TSOs, a supplier can provide control power to any zone;

since 2004, even the suppliers from the Austrian control zones TWAG and VKW can

participate in the minute reserve market.

A pre-qualification process is performed by the TSOs, based on technical and dynamical

criteria.

Since 2005, several changes occurred in order to improve the cooperation among the

TSOs and decrease the need of balancing energy. Among them, the most important are the

creation of a common regulator and a common tender for minute reserve. A common tender

for primary and secondary reserve should be organized soon.

II.C.2.1. How the market works

II.C.2.1.a. The different timescales

The time frame of the market, available for all the zones, is described in the following picture:

Time

Primary reserve market

Secondary reserve market

Minute reserve

market

Spot market Programs submission

Programs

rectifications

Wind reserve market

D-1 D

Forward market Intra-day market

Every

6 months

Every

month

10:00

12:00 14:30

15:30

Figure 9: The different timescales of the German market

The offered minute reserve should be submitted by 10:00 AM the day before, Two

hours before the gate closure of the spot market. At 11:00 the selection of the reserve minute

offers is published. The balancing group managers submit their programs to the TSO at 2:30

PM the day before. Concerning the intra-day modifications of the generation program, they

can happen for each settlement period (15 minutes), with an advance warning 45 minutes

before.

- 26 -

II.C.2.1.b. Format of the bids and offers

� Primary and Secondary reserves

All the plants with a capacity of 100 MW or more must participate to the primary control,

but they are paid for that.

The offers are available for six months and the providers give the following information:

- Offered capacity (MW), which can be used for upwards or downwards regulation

- Price for the capacity (€/MW)

- The energy is not paid

Concerning the secondary control, the offers for upwards regulations and the bids for

downwards regulations are separated. The participation is not compulsory. The following

information is given:

- Upwards or downwards regulation

- Offered capacity (MW)


- Price for the energy actually used (€/MWh)

� Minute reserve

The tender is common to the four TSOs, which is a progress towards the integration of the

four zones. However, the qualification process is done with the TSO of the zone where the

offer is submitted.

The format of the offers and bids is the following:

- Upwards or downwards regulation

- Duration of the offer: the day is divided into six periods of four consecutive hours

(starting from midnight). Therefore, an offer must be available for at least one block of

four hours.

- Offered capacity (MW), it should be at least 15 MW


- Price for the energy actually used (€/MWh)

- The zone where the unit is located (Anschlussregelzone)

Example:

Product Name

Capacity

Price [€/MW]

Energy

Price [€/MWh]

Offered

Capacity [MW] Zone

NEG_00_04 55,400 0,000 50 EON

Figure 10: Example of bid data [3]

The offers seem to be explicit regarding the amount of MW given; it is interesting to

notice that the capacity is remunerated, for all services.

Before the changes occurred in 2006 , the minimal quantity to offer was 30 MW; the

decreasing of this amount allows a better competition, since more offers are now submitted.

- 27 -

II.C.2.1.c. Bids and offers selection

Once the technical and dynamical criteria respected, the selection is done based on

economical criteria.

Regarding the primary control, the offers are ordered by ascending capacity price, and

a forecast of the need defines the last accepted offer.

Regarding the secondary control, the merit order is done with the same method, but

when two capacity prices are equal, the energy price is considered. The orders are then sorted

out by ascending energy prices for upwards regulation, and descending energy prices for

downwards regulation. [19, 22]

Regarding the minute reserve, the TSOs select a certain quantity of offers and bids

after their submission, the day before. In order to guarantee the system security, a minimal

amount is required in each zone. This amount is called Kernanteile (core portion); it

represents between 1 and 15% of the total contracted amount, and is not constant. It does not

seem to affect the competition between the offers from different zones.

The merit order is done the same way as for secondary reserve.

This merit order for tertiary reserves, listing the offers and bids, and the result of the selection

is published on Internet:

Product Name Capacity

Price[€/MW]

Energy

Price [€/MWh]

Offered

Capacity [MW] Zone

Acceptance

[ja/nein]

NEG_12_16 0,670 5,000 20 RWE ja

NEG_12_16 0,672 5,000 15 RWE ja

NEG_12_16 0,674 5,000 15 RWE ja

… … … … … …

NEG_12_16 0,770 2,000 15 EON ja

NEG_12_16 0,780 0,000 15 Vattenfall ja

NEG_12_16 0,780 0,000 50 ENBW ja

NEG_12_16 0,780 0,000 46 RWE ja



NEG_12_16 0,790 0,000 50 ENBW ja

NEG_12_16 0,800 0,000 100 ENBW ja


NEG_12_16 0,800 2,000 15 EON ja


NEG_12_16 0,810 0,000 50 ENBW ja


NEG_12_16 0,820 0,000 50 ENBW ja

NEG_12_16 0,820 0,000 15 Vattenfall nein

NEG_12_16 0,820 0,000 15 Vattenfall nein

Figure 11: Extract of tender results for downwards regulation for tertiary reserves

(10.07.2007, 12:00-16:00) [16]

- 28 -

Product Name

Capacity

Price [€/MW]

Energy

Price [€/MWh]

Offered

Energy [MW] Zone

Acceptance

[ja/nein]

POS_00_04 1,136 200,000 15 RWE ja

POS_00_04 1,137 200,000 15 RWE ja

POS_00_04 1,137 493,201 24 EON ja

POS_00_04 1,138 200,000 15 RWE nein

POS_00_04 1,139 200,000 15 RWE nein

Figure 12:Extract of tender results for upwards regulation for tertiary reserves

(10.07.2007, 00:00-4:00) [16]

Concerning the utilisation of the orders, once the selection done, it is based on the

energy prices and dynamic parameters. It is important to notice that the selected orders are

paid for the capacity, even if they are not activated afterwards.

The quantities of energy from the minute reserve orders which have been activated and

the imbalances for each settlement period are published on each TSO’s website. As described

in the Appendix 1, it is surprising to see that very few minute reserve orders are actually

activated, even if the imbalance is important. In fact, it seems to be the secondary reserve that

is used instead, and very rarely some minute reserve.

Nevertheless, the amount of contracted minute reserve each day (which is remunerated

by the TSO) is quite important (about 3000 MW of offers, 2000 MW of bids). The reason for

the choice of this quantity remains a bit blurry, but it might be due to some imposed rules (in

the UCTE maybe).

II.C.2.1.d. Remuneration

The system is a pay-as-bid system for the three kinds of reserve. [19] We can notice

than before 2005, E-ON was the only TSO who paid the orders at the marginal price.

Specificity here is that the capacity is always paid for by the TSO. These costs are then

integrated to the network tariff [16]. However, the energy costs are integrated in the

imbalance settlement.

II.C.2.2. Imbalance settlement

A balancing perimeter (Bilanzkreis) contains several points of injection and

withdrawal of energy, and is under the responsibility of a manager who is balance responsible

(Bilanzkreisverantwortlichen, BkV). Inside a perimeter, the different deviations can

compensate each other; during each settlement period, the balancing perimeter manager is

responsible for the balance between production and demand. The balancing perimeters are

confined in a single zone, in order to be able to settle the imbalance TSO by TSO. If a

balancing group is present on several zones, it must be divided. In its zone, the TSO

compensate the deviation from the forecast by activating the reserves; afterwards, the balance

responsible must pay for the regulation of energy done by the TSO.

For each balancing perimeter and each ¼ hour, the imbalance is calculated. Here, there

is one single imbalance, regrouping producers and consumers [20]:

∑∑ ∑∑ −+−= ExportsImportDemandSupplyImbalance

- 29 -

The imbalance settlement is based on a single price system: the imbalance price is the

same, regardless the position of the balance responsible compared to the system position

[15,16].

The prices are calculated for each settlement period of ¼ hour. The price is the volume

weighted average cost of the secondary and minute reserve which has been actually used

(only the energy, since the cost due to the capacity payment are integrated to the network

tariffs). The price is the same for positive and negative imbalances.

The balance responsibles who are in a long position get paid by the TSO (they sell the

surplus of energy); on the contrary, the ones who are in a short position pay the TSO (they

buy energy to cover their deficit).

II.C.2.3. The particular case of wind power

Regarding the fluctuating nature of this production, the balancing costs are quite high.

The additional costs due to balancing is estimated at 7 €/MWh. In 2006, the total production

of energy from the wind was around 30 millions of MWh, which amounts to a balancing cost

of 210 millions euros (while the overall cost of the balancing mechanism is about 800

millions euros) [23,24].

Since the new regulation of 2004 concerning renewable energy, wind power is

grouped in the same balancing perimeter, called EEG-Bilanzkreis, and the four TSOs are

balance responsible for this special perimeter. Therefore, a compensation effect is allowed

between the productions of the different zones, and the balancing costs are spread among the

four TSOs. There is a specific reserve for wind power, called Windreserve, which is provided

through a monthly tendering process. [21]

Concerning the imbalance settlement, the balancing costs of wind power are

incorporated to the network tariffs of the four TSOs, on a pro-rata basis of the wind power

capacity installed in their zone. Therefore, there is no incentive to reduce the imbalance

caused by wind power, since the costs are comprised in the network tariffs.

If a wider balancing perimeter regrouping all the wind power of the UCTE was

created, this could reduce the costs, thanks to the variation of winds depending on the location

and the compensation effect between different deviations.

- 30 -

II.D. Conclusions

In this part, we will try to point out the main likenesses and differences of the two

markets. We can see that, just from the study of two countries, a lot of changes are necessary

in order to improve the harmonisation and coordination between different balancing

mechanisms. The table hereafter summarizes the main points of the study:

Great-Britain Germany One TSO: National Grid Company Four TSOs: EnBW, RWE, E-ON, Vattenfall.

Each one is responsible for its own zone

- Many balancing services

- The limit between system services and

balancing market is blurred

- Three types of reserve services,

according to the definition of the

UCTE

- Secondary and tertiary power in the

balancing market

- Settlement period of ½ hour

- Gate closure for the submission of

bids and offers one hour before every

settlement period

- Settlement period of ¼ hour

- Gate closure at 10:00 on the day-ahead

spot market

Format of the Offers & Bids inside the

Balancing Market:

- Pairs

- Energy Price only (£/MWh)

- Chosen duration

Format of the Offers & Bids (for secondary

and minute reserve):

- Separation Upwards/Downwards

- Capacity Price (€/MW)

- Energy Price (€/MWh)

- Standard duration (6 months for

secondary reserve, 4 hours for minute

reserve)

Offers & Bids Acceptance:

- Selection upon economical (energy

price) and technical criteria

- The TSO chooses the quantity

- Remuneration of the used energy

only7

- Pay-as-Bid system

Offers & Bids Acceptance:

- Selection upon economical (capacity

price) and technical criteria

- The TSO must accept the whole offer

in capacity, and choose the quantity in

energy

- Remuneration of the capacity and the

used energy

- Pay-as-Bid system

For each balancing perimeter, two energy

accounts:

- One for the consumption

- One for the generation

For each balancing perimeter, one global

imbalance is calculated.

For each settlement period, two prices are

calculated:

- The main price

- The reverse price

- Income for the TSO

For each settlement period, one price is

calculated:

- Volume weighted average cost of the

secondary and minute reserve actually

used

- No income for the TSO

7 Except for specific reserve services which could be contracted inside the Balancing Market

- 31 -

Table 4: Main aspects of the British and German Balancing Markets

In conclusion, the orders inside the Balancing Market seem to be explicit in their

submission; however in Great-Britain, the orders are more implicit in their acceptance when

there is no remuneration of the capacity.

The imbalance settlement system is less penalizing in Germany, since the actors

cannot make a loss with their imbalances. Therefore, compare to Great-Britain, there are less

incentives to minimize the deviations from the contractual position and to make better

forecasts. Besides, the German market has a special system for wind power.

From this study, we could roughly stress some important points which would need to be more

harmonised:

- The type of services included in the balancing mechanism, and the limit between

system services and the balancing mechanism:

- The format of the submitted offers and bids, regarding the prices given (for capacity,

energy…) and of course regarding the quantity given (explicit/implicit offer)

- The criteria on which the TSO accepts the offers and bids, and the format of the

acceptance (whether the TSO must accept the whole offer, or if it can accept it

partially)

- The remuneration: it can be at the bid price or at the marginal clearing price, it can pay

the capacity and/or the energy

- The timescales of the market, particularly the gate closure time and the settlement

period duration

- The imbalance settlement: it can be based on a dual price or a single price system

- The definition of the imbalance for a balance responsible (potential separation

between consumers and suppliers, in order to be more penalizing)

- The specific case of wind power generation or other fluctuating production

Furthermore, if the trend is to harmonise the balancing markets and allow a better

competition between actors, there would be more exchange of balancing energy on the cross-

border transmission lines between the European countries.

Therefore, congestion management methods should improve the integration of the

different markets and allow an optimal use of the cross-border transmission capacities.

Several important changes concerning congestion management occurred lately, but mainly

concerning the day-ahead cross border capacity allocation mechanisms. But the new

mechanisms settled will probably be developed and applied in the intra-day market as well.

- 32 -

Chapter III.

Congestion Management: The Market Coupling

Mechanism

III.A. Background

At the present time, the European Commission supports every market mechanism

which increases the level of integration of the existing electricity markets in Europe.

Bottlenecks on the interconnections are the main hindrance to the integration of the different

markets. Therefore, the allocation of cross border capacity must be done in a fair and non-

discriminatory manner, using market-based mechanisms which will improve the global

economical efficiency.

Currently, there are two main kinds of market-based mechanisms:

• Explicit auctions: the product is a right to use a certain amount of capacity on a

transmission line. A tendering process is organized by the two concerned

TSOs, in order to allocate the commercial capacity. Therefore, the capacities

are allocated using market based mechanism, but their use is not optimized.

• Implicit auctions: actors submit offers and bids for electrical energy on the

power exchanges, and a special market mechanism determines the allocation

which will lead to the most efficient situation of power exchanges between the

market zones. Nowadays, the two existing implicit auctioning mechanisms are

the market splitting and the market coupling; we will explain them further on.

In the picture below, the different existing mechanisms in Europe are represented:

Explicit Auctions

Market Splitting

Market Coupling

Other Mechanisms

Outside the EUFr

UKIE

ESPT IT

CH

Be

NL

DK

(W)

De

AT

Cz

PL

SK

HR

SL

Gr

No

SeFi

DK(E)

Figure 13 : The different congestion management methods in Europe [26]

- 33 -

In 2003, the European Commission laid down preliminary principles for the

implementation of cross border congestion management methods. Through the given

guidelines, a regional approach has been taken in order to allow faster progress, but the final

goal still remains the realisation of an Internal Electricity Market in Europe. Therefore,

Electricity Regional Initiatives (ERI) has been launched in 2006 but the European regulators

Group for Electricity and Gas.

The aim of the project is to focus on the Central West Region8, consisting of the

Netherlands, Belgium, France, Luxembourg and Germany. On November 21st 2006, an

implicit auctioning process to handle day-ahead cross border capacity allocation was

implemented between the Netherlands, Belgium and France, which is the so-called “Trilateral

Market Coupling9”. It complements the existing process of explicit auctioning to handle year-

ahead and month ahead cross border capacity allocation.

Market Coupling aims at optimising the use of the D-1 available transmission capacity

on cross-border lines, by a coupling between the three Power Exchanges (APX10

, Belpex11

and Powernext12

), in cooperation with the relevant TSOs TenneT, Elia and RTE.

The TLC enables different power exchanges to be coupled in the day-ahead market, without

any change to their market structure and rules. The three power exchanges are still legally

separated markets, the coupling is done without a common order book nor a common clearing

for example.

Therefore, the Market Coupling mechanism is to be extended in order to integrate more

markets. The next step is the extension of Market Coupling to Germany and Luxembourg in

an Open Market Coupling, and then to Scandinavian countries.

III.B. Market Coupling: Analysis of the mechanism principles

Market coupling is both an implicit cross-border capacity allocation mechanism and a

mechanism for matching orders. The aim is to improve the economic surplus by a better use

of the interconnections: cheaper generation in a country may be used to cover more valuable

demand in another country. Indeed, by coupling the power exchanges, the highest bids and the

lowest offers of the coupled markets are matched, without considering the area it belongs to.

Nevertheless, the matching depends on the transmission capacity between the coupled hubs.

The daily cross-border transmission capacity

The mechanism involves handling simultaneously their supply and demand curves, but

there is no common order book. Therefore, it does not require any significant change in the

structure of the power exchanges, except the harmonisation of the day-ahead gate closure

time. The three power exchanges still exist as legally separate markets. [25]

Market Coupling allows a wider market to be created, and a more efficient use of the daily

capacity of the interconnections between the different networks, compared to explicit auctions

mechanisms.

This method for integrating electricity markets in several areas can be considered as an

alternative to another method already established in the Nordic area, the Market Splitting.

8 Also Called CWE

9 Also called TLC

10 Dutch energy exchange

11 Belgian energy exchange

12 French energy exchange

- 34 -

Market splitting is carried out by the market place operator, the NordPool, based on an

agreement between the different TSOs. As market coupling, market splitting is a system wide

optimisation, in order to make a better use of the cross-border transmission lines. The actors

notify their bids and offers in the same market place, specifying the concerned area. The

exchange capacity is integrated as a part of the day-ahead spot price calculation. The main

principle is the following: there is one single market which can be split into separated virtual

markets (with different prices) when a congestion occurs on a cross-border transmission line.

Using the same hypothesis, market coupling and market splitting should lead to the

same results. However, it is interesting to see the differences between the algorithm used and

the reason why market splitting is not used in Central Western Europe.

Indeed, the market coupling consist of coupling N markets, which results in a unique

virtual market in case of no congestions, while market splitting starts with one single market,

which is split in several different markets in case of congestions. Market coupling allows an

integration of several markets, even if they have different designs.

The main difference is that market coupling is organized with two or more power

exchanges. Therefore, according to the decentralized approach in Central Western Europe,

market coupling is more suitable since each area has its own market operator. Moreover,

market splitting remains hard to carry out in Europe, since there are too many

interconnections between the different TSOs, which means that congestions observed on a

line might not come from bilateral exchanges

Market coupling let the national markets stay independent, without sharing their bids and

offers, so it might be easier to extend to other countries.

III.B.1 Some basic principles

We will first explain the basic principles of coupling markets and how it is applied to the

Netherlands, France and Belgium.

Coupling markets involves handling simultaneously their supply and demand curves, in

order to make the highest bid (purchase) match with the lowest offer (sale).

The market coupling mechanism relies on the principles that the market with the lowest price

exports to the market with the highest price.

Let us consider two markets A and B, linked with a cross-border transmission line. If the

isolated market price in A is lower than the one in B, the market A exports to the market B.

We can reach two situations:

- The two prices become equal, if the capacity of the line is large enough

- A congestion occurs on the line, and the two prices remains different.

III.B.1.1. Aggregated supply and demand curves

On the day-ahead spot market, aggregated supply and demand curves are submitted at

the power exchange for each hour of the following day. The price of an isolated market is

given by the intersection of these two curves.

The energy transaction due to the coupling between two markets has the following

impact on the supply and demand curves:

- 35 -

Price

(€/MWh)

Price

(€/MWh)

Volume (MWh) Volume (MWh)

Market A Market B

isolated

AP

isolated

BP

*

AP*

BP

Purchase

Sale

Purchase

Sale

Figure 14: Coupling of two markets when there is no congestion

As it is shown in the picture above, when a market exports a certain quantity of

energy, it is equivalent to translate its demand curve to the right (add the value of the export).

Similarly, If a market imports a certain quantity of energy, it is equivalent to translate its

supply curve to the right (add the value of the import). The new market price is given by the

intersection of the aggregated curves, shifted with respect to the export and import. In the case

represented in the picture, there is no congestion on the line between A and B, so the two

markets have the same final price ( **

BA PP = ).

When the transmission capacity is not sufficient to reach two equal prices, the exchange

between the two markets will be equal to this transmission capacity:

Price

(€/MWh)

Price

(€/MWh)

Volume (MWh) Volume (MWh)

Market A Market B

isolated

AP

isolated

BP

*

AP *

BP

Purchase

Sale

Purchase

Sale

P∆

Figure 15: Coupling of two markets when there is a congestion

Transmission constraints limit the necessary cross-border flow. There is no complete price

convergence, but the differential between the two prices decreases.

III.B.1.2. Net exportation curves

Another concept which will be used in the algorithm to describe a market is the Net

Exportation Curve (NEC), which is also submitted on the day-ahead spot market, for each

hour of the following day.

The NEC represent the price at which the market is ready to export or to import: it represents

the net position of the market as a function of the marginal cost price. The NEC is calculated

- 36 -

by determining the volume differences between the hourly offers (supply curve) and the

hourly bids (demand curve). Therefore, it contains less information than the supply and

demand curves.

Price

(€/MWh)

Volume (MWh)

AP

Purchase

Sale

Import (MWh) Export (MWh)

Price

(€/MWh)

NEC

Figure 16: Construction of the Net Exportation Curve

If the considered market exports, the NEC will be shifted to the left; if the market imports, the

NEC will be shifted to the right. The marginal price of the isolated market is given by the

intersection of the NEC and the price axis (it is the price when the net position is equal to

zero).

Depending on the market, two types of NEC are possible: either a stepwise curve or a

linear curve. In the first type of market, the offers and bids are defined with price-quantity

range pairs (for each price, a range of quantity is defined); in the second type of market, offers

and bids are defined with price-quantity couples, and the NEC is obtained by joining the

segments.

In the TLC algorithm, there is one linear NEC, to represent the French market Powernext,

and two stepwise NECs, to represent the Dutch market APX and the Belgian market Belpex.

[28]

Coupling two markets is done easily using the NECs. The market with the lowest isolated

marginal price exports to the market with the market with the highest isolated marginal price

The export of one market is equal to the import of the other, thus the equilibrium is found at

the intersection of the net exporting curve of a market, and the net importing curve of the

other (the inverted NEC). [27]

Price

(€/MWh)


Market A

Market B

Price

(€/MWh)


Market A

Market B

**

BA PP = *

AP

*

BP

BAATCQ→

=*

Uncongested Case Congested Case

*Q

Figure 17: Bilateral Coupling using the NECs

- 37 -

As we can see on the example above, the representations with the NEC make the

coupling quite easy to realize. If the ATC is large enough, the equilibrium and net position is

given by the intersection of the two curves. However, if congestion occurs, the energy

transaction is equal to the ATC; the net positions are equal to the ATC and the price of a

market is given by the point on its NEC corresponding to the ATC.

III.B.1.3. Block offers

The NEC obtained when considering only simple orders is called a simple NEC. It is a

particular case; the real NEC will also consider the selected block orders. The selected block

orders are represented by price-inelastic hourly divisible orders.

When considering block orders, the supply demand and supply curves shift to the

right. The difference between the shift of the supply curve and the shift of the demand curve

(the net colume) is called the Net Block Volume (NBV). For each hour, the NEC is a

horizontal translation of the block-free NEC by the NBV[25]. We will see afterwards how

these NEC are constructed.

III.B.2 Trilateral Market Coupling: how does it work?

III.B.2.1. Overview of the mechanism as it is carried out today

III.B.2.1.a. Data used as inputs

� In the trilateral market coupling, the cross-border transmission capacity is represented

by the Available Transmission Capacity. The ATC represent the commercial capacity

for energy transactions between two markets, taking into account the yearly and

monthly explicit auctions and their nominations. The definition and calculation of the

ATC is detailed in the Appendix 2. The ATCs are submitted by the TSOs, in each

market.

� For each market and each hour of the following day, the hourly orders are collected in

a simple NEC.

� The block orders are submitted for each market. Several NECs may be constructed for

a settlement period, considering all the possible set of accepted block offers.

III.B.2.1.b. The overall process

The Trilateral market coupling process adopts a decentralised technical approach. The

three power exchanges and the three TSOs act separately, and the data submitted are not put

in common.

Using the NECs and the ATC, the algorithm determines the price of each market, and

its net position (which corresponds to a point on the NEC). The net position of a market

represents commercial transactions, and not physical power flows. We will see further on how

to make the link between those transactions and the real flows on the line.

In each power exchange, block orders are submitted to a block selector, and divisible

orders to a NEC creator. A NEC is build on the basis of n hypothetical set of accepted block

orders (which is called Winning Subset).

- 38 -

Then the resulting set of NEC is used to determine the price and the net position of

each market. The set of prices obtained might not be compatible with the assumed Winning

Subset, thus the winning subset is updated and the prices calculated again. These calculations

are iterated until the looping process reaches a stable solution.

Consequently, because of the block offers, the algorithm involves iterations between

two modules [25]:

- The block selector of each power exchange, in charge of the decentralized

selection of block offers (returns the NBV)

- The coordination module, in charge of the centralized calculation of the prices and

net positions, using the NECs and the ATCs

The following picture summarizes the different actors and modules of the algorithm.

Figure 18: Overview of different steps in the Market Coupling process [25]

Once a convergence of the solutions is observed, the coordination module returns a

price and a net position to each power exchange, which then uses these data to determine the

schedule of its participant and the portfolio allocations according to its own rules.

- 39 -

III.B.2.2. Algorithm of the coordination module: Coupling three markets

The general idea of the algorithm is to realize successively two bilateral coupling.

The first step is order the three markets regarding to their isolated marginal cost price.

Let us assume that the market A has the lowest isolated price, the market C the highest. Thus,

the market A is going to export to the market C (potentially via the market B if market B is

Belgium), which will raise the price in market A and reduce the price in market C. Two

situations can then occur:

- If a market uses all its ATC, it becomes isolated and cannot export or import

anymore. Then a bilateral coupling takes place between the two other markets

- The price of market A or C reaches the price of market B, and we aggregate the

two markets together (the two NECs are added together). Then a bilateral market

coupling takes place between the market resulting from the merging and the other

one.

We consider the following example, where we can observe an aggregation of France

and Belgium. Here, we do not consider any transmission limitation.

Regarding the price of the isolated markets, the two markets which get the closest price will

merge together. France and Belgium are aggregated, and a common NEC is constructed (by

adding the two NECs of the separated markets).

Price

(€/MWh)

Net Export (MWh)Net Export (MWh)Net Export (MWh)

Price

(€/MWh)

Price

(€/MWh)

10

20

30

40

10

20

30

40

Belgium

Netherlands

10

20

30

40

Price

(€/MWh)

Net Export (MWh)

France + Belgium

BeP

NLP

10

20

30

40

EquP

Figure 19: First step of the TLC

Then a coupling takes place between the exporting market { }BelgiumFrance + and the

importing Dutch market.

- 40 -

10

20

30

40

Net Export (MWh)

Price

(€/MWh)

FrBeNL PPP ==

Import NL

Fr+BeNL

Figure 20: Second step of the TLC, non-congested case

Without limitation on ATC, the three markets get the same price, which is given by

the intersection of the two curves.

The import made by the Netherlands and the common price can be read on the

intersection of its inverted NEC and the aggregated NEC of France and Belgium.

Since we have the market price, we can then read on the individual NEC of France and

Belgium their net positions.

Price

(€/MWh)

Net Export (MWh)Net Export (MWh)

Price

(€/MWh)

10

20

30

40

10

20

30

40

France Belgium

Export Fr Export Be

FrBeNL PPP ==

Figure 21: Second step of the TLC, non-congested case

The situation may be more complicated when there are transmission limitations. We

will now consider the three possible scenarios concerning ATC limitations, using the same

example as before.

- 41 -

� Scenario 1: Constraint on NlBeATC →

In case the ATC between Belgium and the Netherlands limit the importation, the Dutch

market becomes isolated, with a higher price. Since there is no congestion between France

and Belgium, both markets are merged and get the same price.

The import made by the Dutch market is equal to the NlBeATC → ; the net position of the French

and Belgian market can be read on their respective NECs.

10

20

30

40

Net Export (MWh)

Price

(€/MWh)Fr+BeNL

NlBeATC→

FrBe PP =

NLP

Figure 22: TLC results, congested case

Here it is interesting to notice the fact that the three considered countries are ligned up,

which will sometimes simplify the problems due to ATC limitations. Indeed, once there is a

congestion, one market gets isolated and a bilateral coupling takes place between the two

other one.

For example, in this scenario, if the ATC between Belgium and the Netherlands is not

sufficient, the Netherlands will be isolated. This is due to the absence of interconnection

between the Netherlands and France; otherwise we would have to consider an import from

France as well.

� Scenario 2: Constraint on BeFrATC →

The ATC between France and Belgium limits the export, and make its price remains at a

lower level. Belgium continues to export, and without other restriction the Belgian and Dutch

prices become equal.

10

20

30

40

Net Export (MWh)

Price

(€/MWh)

NEC Fr+Be

NL

BeFrATC →

FrP

BeNL PP =

NEC Be


- 42 -

� Scenario 3: Constraint on NlBeATC → and BeFrATC →

When all ATCs are limited, we get three different prices.

10

20

30

40

Net Export (MWh)

Price

(€/MWh)

NEC Fr+Be

NL

BeFrATC→

FrPBeP

NEC Be

NlBeATC→

NLP


Finally, the algorithm applied in the coordination module of the TLC appeared quite

clearly through the example above. Using the NECs of the three isolated markets and the

ATCs between them, one can calculate the final prices and the net position of the countries.

One important aspect in the TLC algorithm is that the input data are NECs and not supply and

demand curve. This is more a strategic way for the local power exchanges of giving less

information to the coordination module.

The first aim of this study is to establish a model of the mechanism (except the block

selector module).

- 43 -

III.C. Simulation of Market Coupling

III.C.1 Simulation on three markets using a sequential algorithm

The aim here is to simulate the coupling of three markets, all interconnected. It is important to

notice that the transmission capacity and the transaction are commercial; there is no

calculation of physical power flows here.

The first simulation has been implemented with Excel and its language Visual Basic

for Application. The aim of this small simulation is to develop a simple market coupling

sequential algorithm, working on three countries (M1, M2, M3), all interconnected with one

another. The simulation is done with theoretical data.

M1

M2M3

Figure 25: System studied

This model can be used to simulate the functioning of the actual “Trilateral Market

Coupling”, which is a particular case of a coupling of three markets. Indeed, we shall assume

that M1 stands for France, M2 for Belgium and M3 for the Netherlands. The Available

Transfer Capacity of the commercial line between M1 and M3 is then set to zero.

As we have already noticed before, the algorithm is slightly different in case of three

countries all interconnected and not ordered on a line. Thereby, the method would have to be

changed compared to the mechanism explained before.

III.C.1.1. Inputs and Outputs of the simulation

Inputs (available for the considered hour):

- Available Transfer Capacity (ATC) for each line, in each direction

- Net Exportation Curves for each market, without considering any block offer. Indeed,

we work here with single offers only.

Outputs (available for the considered hour):

- Accepted offers and bids in each market

- Use of the commercial power capacity on each line

- Market price for each market

Optionally, the economic surplus is computed, also called overall Social, provided we have

the global supply and demand curves on each market. In that case, it is not necessary to have

both NECs and supply and demand curves as the NECs can be deduced from the curves.

- 44 -

III.C.1.2. Prices calculation

The marginal price of each market is calculated as the intersection of the Net Export curve of

the considered market with the price axis (price of the market when the net position is equal to

zero)13

.

In the program, the prices are calculated at each step of the algorithm on every market, using

the NEC and taking into account the exchanges that take place with the neighbouring markets:

- When the market M exports 1 MWh, the NEC is translated to the left (1 MWh is

subtracted from the values of the NEC), and therefore the market price increases

- When the market M imports 1 MWh, the NEC is translated to the right (1 MWh is

added to the values of the NEC), and therefore the market price decreases.

Price

(€/MWh)

Price

(€/MWh)

Net Export (MWh)Net Export (MWh)

Effect of an import Effect of an export

Figure 26: Effect of an import or an export on the NEC

III.C.1.3. Algorithm principles

The Market Coupling mechanism relies on the following principle between two markets:

the market with the lowest price shall export to the market with the highest price. This is

equivalent to make the highest bid match with the lowest offer, regardless the market where

the order is submitted.

This is done using loops. Indeed, when a market A exports to a market B, the condition that

must be observed to increment the amount of exported power from A to B with 1 more MW is

the following:

While Price(A)<Price(B) and QAB<QAB_Max

(Where QAB is the transaction on the line between A and B).

We implement this principle in an algorithm, which treats the problem by differentiating all

the possible cases. Therefore, the method is sequential.

13

This equilibrium can also be deduced as the intersection of supply and demand curves when the whole

supply/demande curves are given as an input data

- 45 -

III.C.1.4. Steps of the algorithm

III.C.1.4.a. Calculation of the isolated market prices: Identification of the

export zone and the import zone

The three markets M1, M2 and M3 are sorted out by price, from the lowest (market A) to the

highest price (market C).

Then we distinguish two base cases:

� Base case 1:

BCAB PPPP −≤− , which means that the markets A and B export to the market C

� Base case 2:

ABBC PPPP −<− , which means that the markets B and C import from the market A.

The two markets with the closest prices will be treated together. In the base case 1,

markets A and B are the exporting area, and market C the importing one. In case 2, market A

is the exporting area, and markets B and C the importing area.

Here it is interesting to notice that the two markets with the closest prices are not merged

as they were in the TLC algorithm described before, which means that we do not exactly

aggregate their NECs. Indeed, the transmission limitations are a bit more complicated to

handle, since the three countries are not necessarily aligned.

Therefore, we choose to handle the NECs separately, using a loop that select the cheapest

offer of both NEC in the first case, or the highest offer in the second case, as explained below.

This is equivalent to an aggregation, but the result is not calculated by intersecting two curves.

III.C.1.4.b. Modification of the NECs, according to the accepted

transactions

In a two zones model, the lowest offer of the exporting area will be matched with the highest

bid of the importing area, using the commercial capacity between these two areas. By this

way, the price of the exporting area will increase, while the price of the importing area will

decrease. Then either a congestion occurs between the two zones or the prices of both markets

become equal.

As already explained above, with a three zones model, we come down to a two zones model

by handling together the two markets which prices are the closest.

� Case 1: BCAB PPPP −≤−

The markets A and B export towards the market C, so we will skim through the NECs

of A and B (at each price, in increasing order, we consider the offers made by both markets),

taking the less expensive offer, until a congestion appears or the price of the market A or B

reaches the price of the market C. At each accepted MWh, we report the modification on the

NECs of both importing and exporting countries (by shifting them to the right or the left), and

calculate the new marginal prices of the relevant markets. We also increment the resulting

amount of energy transacted on the concerned transmission line (if the offer is in A, the

transmission CAP → is incremented; if the offer is in B, the transmission CBP → is incremented).

- 46 -

� Case 2: ABBC PPPP −<−

The markets B and C import from the market A. Therefore, we will skim through the

inverted NEC (the net importation curves) of B and C, taking the most expensive importation

offer from B or C, until a congestion appears or the price of market B or C reaches the price

of the market A. At each MWh accepted, we report the modification on the NECs of both

importing and exporting countries and calculate the new marginal prices of the relevant

markets. The transaction on the concerned line is incremented (if the bid is in C, the

transmission CAP → is incremented; if the bid is in B, the transmission BAP → is incremented).

An example of the functioning of the algorithm in the case 1 is illustrated,step by step, in the

following table. A large amount of ATCs is assumed.

NEC A

NEC B

NEC C

Net Export (MWh)

Price

(€/MWh)

Net Export (MWh)

Price

(€/MWh)

C

ATC (MWh)

A�C

B�C

A�B

Net Export (MWh)

Price

(€/MWh)

Net Export (MWh)

Price

(€/MWh)

ATC (MWh)

A�C

B�C

A�B

Price

(€/MWh)

Net Export (MWh) Net Export (MWh)

Price

(€/MWh)

ATC (MWh)

B�C

A�C

A�B

- 47 -

Price

(€/MWh

)


Price

(€/MWh)

ATC (MWh)

B�C

A�C

A�B

Net Export (MWh)

Price

(€/MWh)

Net Export (MWh)

Price

(€/MWh)

ATC (MWh)

B�C

A�C

A�B

Price

(€/MWh)


Price

(€/MWh)

ATC (MWh)

B�C

A�C

A�B

Figure 27: Coupling three markets with no constraints – incremental process

Without any congestion, we reach the same final price in the three markets. The process

described in the picture is explained in detail in appendix 4.

In the case 2, the process is the same, excepting that the Net Importation Curves are used by

the program, instead of the Net Exportation Curve.

III.C.1.4.c. Congestions

Once a transmission capacity is reached, the algorithm is still the same, except the fact

that the congested line cannot be used anymore. The transaction underway is done via other

lines if it is possible; if there is no other available path, the transaction is stopped and the

concerned market is isolated. For example, if A exports to C and the line A-C becomes

congested, the market A keeps on exporting to C, but using the line A-B and B-C.

When the two lines connected to a market are congested, the market is isolated from

the others, and the price is then determined by its NEC when the congestion occurred.

The detail of the different steps of the algorithm is described in an algorithm tree in appendix

3.

An example of the functioning of the algorithm in the case 1 with congestions is illustrated,

step by step, in the following table.

- 48 -

NEC A

NEC B

NEC C

Net Export (MWh)

Price

(€/MWh)

Net Export (MWh)

Price

(€/MWh)

ATC (MWh)

B�C

A�B

A�C

Net Export (MWh)

Price

(€/MWh)

Net Export (MWh)

Price

(€/MWh)

ATC (MWh)

B�C

A�B

A�C

Net Export (MWh)

Price

(€/MWh)

Net Export (MWh)

Price

(€/MWh)

ATC (MWh)

B�C

A�B

A�C

- 49 -

Net Export (MWh)

Price

(€/MWh)

Net Export (MWh)

Price

(€/MWh)

ATC (MWh)

B�C

A�B

A�C

Net Export (MWh)

Price

(€/MWh)

Net Export (MWh)

Price

(€/MWh)

ATC (MWh)

A�B

A�C

B�C

Net Export (MWh)

Price

(€/MWh)

Net Export (MWh)

Price

(€/MWh)

ATC (MWh)

A�B

A�C

B�C

Figure 28: Coupling three markets with constraints – incremental process

In this example, the capacity available from A towards C is firstly fully used. Then the energy

transaction from A to C is done via the ATC from A towards B and from B towards C.

However, the line from A to B gets congested, which isolates the market A at a lower

marginal price. Both markets B and C get the same final price. The process described in the

picture above is detailed in appendix 5.

All the possible cases of congestions and prices configurations are handled by the sequential

algorithm, as it is shown in the algorithm tree.

III.C.1.4.d. Calculation of the consumers and producers surplus for each

market, before and after the coupling

The global surplus (called Social Welfare) is a way to measure the effect of market

coupling. The term “consumers’ surplus” describes the difference between the price a

consumer is willing to pay to get a certain quantity of energy and the price the consumer

actually pays for it (the marginal price). On the other hand, the term “producers surplus”

describes the difference between the price a producer get paid for a certain quantity of energy

and the price the producer was first ready to get for it (which is equal to the marginal

production cost).

- 50 -

The global surplus is the sum of these two quantities, and is represented by the coloured

area below:

Figure 29: Calculation of the consumers’ and producers’ surplus,

In order to compute those values, we need the supply and demand curves, as well as

the importation and exportation of the considered market.

If a market exports a certain quantity of energy, it is equivalent to shift its demand curve

to the right (add the value of the export):

- the price of this market increases

- the consumers’ surplus decreases

- the producers’ surplus increases

If a market imports a certain quantity of energy, it is equivalent to shift its supply curve to

the right (add the value of the import) :

- the price of this market decreases

- the consumers’ surplus increases

- the producers’ surplus decreases

Import

Export

Price

(€/MWh)

Volume (MWh)

Price

(€/MWh)

Volume (MWh)

Figure 30: Effect of an import/export on the supply and demand curves

Therefore, knowing the import and export for each market, we can calculate the global

surplus resulting from the coupling.

- 51 -

III.C.1.5. Particularities of the model

� When A exports to B, the condition that must be observed to increment the export

with 1 more MWh is the following:

While Price (A) <Price (B) and BAP → < MAX

BAP →

Where BAP → is the energy transaction on the line BA → .

Therefore, the last accepted MWh might sometimes make the price of market A higher

than the price of the market B, if we are at the edge of a step on a stepwise NEC.

� The model is defined for three markets: one with a linear NEC (France) and two with

a stepwise NECs (Netherlands and Belgium)

� The NECs of the three markets must have the same number of points

III.C.1.6. Conclusion regarding the sequential model

Constructing this model allows a better understanding of how the mechanism works,

and of all the conceivable cases with three interconnected markets. In particular, the

sequential model allows modeling the actual Open Market Coupling that came into force

between France, Belgium and the Netherlands in November 2006. The main particularity here

is that only the NECs are used as input data, the full supply and demand curves are not

required.

Nevertheless, the more countries the more possible cases to handle. Besides, there

would be a problem of capacity definition if an aggregation of markets occurs: how would we

define the capacity on the hub between an aggregation of several markets and the rest of the

system?

For those two reasons, the algorithm becomes really complicated to implement in this way

when there are more than three countries, all interconnected together.

In order to study the extension of Market Coupling, we will try to formulate the problem

in a different way. This will also give a way to validate the first model, by checking if the

global surplus is indeed maximized.

- 52 -

III.C.2 Market Coupling as a system-wide optimisation problem

The aim of the market coupling mechanism is to maximize the global surplus (or

“social welfare”). Therefore, the mechanism will be studied as an optimisation problem,

which maximizes a function under constraints. This is a way to integrate the transmission

limits easily in our problem.

The relevant components of an open market coupling will be mathematically

modelled. Firstly, the solver Excel was used, in order to validate the results obtained with the

sequential algorithm on small example. However, the solver Excel is limited to two hundreds

variables, and is not competitive enough. Thus, the problem has been implemented with the

optimisation software GAMS. Obviously, we get the same results for the small example

treated by the solver Excel or GAMS.

III.C.2.1. Definition of the parameters and variables

The different component of the mechanism must be modelled. Each market involved

has a power exchange, where offers and bids are submitted, and a transmission system

connect these markets. The model consists of nodes and lines. The nodes represent the

markets (each country has one market) and transmission lines with limited commercial

capacity connect them together. [29]

As a consequence of the formulation, we consider there is no congestion within a

market zone, each injection or withdrawal refers to a market, and each market forms a

homogeneous price zone. We do not take into account the block orders. We consider a market

with stepwise supply and demand curves, and the following denominations:

- A “step” of the supply curve is defined by a quantity jSQ , of energy and a price jSP , to

be received for this amount of energy

- A “step” of the demand curve is defined by a quantity iDQ , of energy and a price iDP ,

to be paid for this amount of energy

- nP , the price of the isolated market n, defined by the intersection of its demand and

supply curves

The parameters are described in the picture below: Price

Volume

iDP ,

jSP ,

iDQ ,

jSQ ,

nP

Figure 31: Definition of the parameters

- 53 -

The variables named jSX , and iDX , represent the accepted volume of a bid i or an

offer j. For the orders fully accepted, jSX , and iDX , are respectively equal to jSQ , and iDQ , . For

the marginal offers and bids, jSX , and iDX , might be lower than jSQ , and iDQ , .

We add variables to represent the exports. It is redundant to introduce variables for the

imports as well, since an energy transaction from A to B is an export from A to B, which is

equal to an import towards B from A. Therefore, we introduce the following variables:

mnExp → , where mn ≠ , which represents the energy transfer from the markets n to m.

Finally, the inputs of our model are:

Ps (j,n) Price of the offer j on the market n Pd (i,n) Price of the bid j on the market n

Qs (j,n) Offered volume in the corresponding offer

Qd (i,n) Offered volume in the corresponding bid

ATC (n,m) Available Transmission Capacity n->m

The variables are defined by:

Xs (j,n) Accepted Volume of the offer j on market n

Xd (i,n) Accepted Volume of the bid i on market n Exp (n,m) Transaction from n to m

III.C.2.2. Definition of the objective function

In a market n, with nI bids in the demand curve, the consumers’ surplus can be

formulated as below:

In a market n, with nJ offers in the supply curve, the producers’ surplus can be

formulated as below:

The global surplus for this market is equal to the sum of these two functions:

−+⋅−⋅=

⋅−+⋅−=+

∑∑∑∑

∑∑

====

==

nnnn

nn

I

i

iD

J

j

jSn

J

j

jSjS

I

i

iDiD

J

j

jSjSn

I

i

iDniD

XXPXPXP

XPPXPPPSCS

1

,

1

,

1

,,

1

,,

1

,,

1

,, )()(

Since ∑ ∑= =

=−n nJ

j

I

i

iDjS XX1 1

,, 0 in a market at the equilibrium, the global surplus is independent

of the market price nP .

∑=

⋅−=nI

i

iDniD XPPCS1

,, )(

∑=

⋅−=nJ

j

jSjSn XPPPS1

,, )(

- 54 -

Finally, when considering N markets, the objective function is the following:

Where the jSP , , iDP , are parameters of the problem, and the jSX , and iDX , are variables which

must be optimised. The optimisation problem is linear.

Using GAMS, we need to add a term to avoid loop flows. Indeed, when running the

program, we notice that the transmission capacities are used at their maximum. This is due to

the fact that it does not represent physical flows but commercial transactions, so the

constraints allows GAMS to make the transactions as large as possible.

To avoid these loop transactions, it is necessary to add to the objective function a term

proportional to the sum of the transactions. Thus, the objective function becomes:

In fact, this formulation of the problem is the equivalent to aggregate the demand and

supply curves of all the considered markets, and then find the optimum.

Prix (€/MWh)

Volume (MWh)

Supply Curve A+B+C

Demand Curve A+B+C

Figure 32: Global surplus of the three markets aggregated, in case of no congestion

∑ ∑∑= ==

⋅−⋅

N J

j

jSjS

I

i

iDiD

nn

XPXPM1n 1

,,

1

,, AX

∑∑ ∑∑ ⋅−

⋅−⋅

= == mn

N

n

J

j

jSjS

I

i

iDiD mnFluxXPXPnn

,1 1

,,

1

,, ),(00001.0

- 55 -

III.C.2.3. Formulation of the constraints

� Equilibrium condition

In an isolated market, the sum of the demand must be equal to the sum of the supply, as

we saw before:

However, this formulation does not take into account any coupling of the markets.

Indeed, we have to add the energy transactions between the different markets. For a market n,

the sum of the supply plus the importations must be equal to the sum of the demand plus the

exportations. The equilibrium condition becomes:

∑ ∑= =

=+−n nJ

j

I

i

iDjS XX1 1

,, 0n fromExport -n Import to

which is equivalent to: ∑ ∑ ∑∑= = ≠

→

≠

→ =+−n nJ

j

I

i nmnm

iDjS XX1 1

mnnm,, 0 Exp - Exp

Furthermore, we add a global equilibrium condition, which states that the total quantity

consumed in all the zones is equal to the total quantity produced:

0 1 1 1

,, =

−∑ ∑ ∑

= = =

N

n

J

j

I

i

iDjS

n n

XX

� Transmission constraints

The commercial energy transactions on the lines are limited by the ATC of each line.

Moreover, the variables mnExp → are all positive, since it is defined for each way on a line.

� Constraints on the volume of each offer

Considering an offer, the volume X accepted on this offer is limited by the volume effectively

offered:

≤≤

≤≤

≠∀

→→

→→

AB

BA

ATC

ATC

AB

BA

Exp0

Exp0

BA zones,market B andA

≤≤

≤≤

∀

iDiD

jSjS

QX

QX

,,

,,

0

0

i, j

∑ ∑= =

=−n nJ

j

I

i

iDjS XX1 1

,, 0

- 56 -

III.C.2.4. Particularities of the simulation

The expression of the surplus is slightly different when dealing with linear demand and

supply curves, and not stepwise curves as above.

iDX ,

jSX ,

iDP ,

jSP ,

nP

1, −jSP

1, −iDP

Price

Volume

Figure 33: Definition of the variables

The formulation of the consumers’ and producers’ surplus is the following:

∑∑=

−

=

−

⋅−⋅+⋅−

⋅−⋅−⋅

nn I

i

iDiDiDiDiD

J

j

jSjSjSjSjS XPPXPXPPXP1

,1,,,,

1

,1,,,, )(2

1)(

2

1

It is important to notice that this formula is not accurate. The problem comes from the

marginal offer, which is an offer partially accepted in most of the cases. Therefore, the price

for this offer is the marginal price, and not the price given in the offer. If we go back to the

previous example, we can see on the picture below that the calculation of the consumers’ and

producers’ surplus will not be accurate because of this last term Indeed, the formulation used

add a small term to the calculated area.

Marginale

Offre D X

Bid

Marginal D P

Offer

Marginal S P

n P

Price

Volume

Marginale

Offre S X

Figure 34: Particularities with linear curves

However, if we want to compute the accurate formula, the last term of the sum, the

one concerning the marginal accepted offer, will introduce a term in XPn ⋅ , which is a

quadratic term. In order to keep a linear optimisation problem, we will keep the previous

formula.

Using the Excel solver, we will formulate the surplus for one linear curve, and two

stepwise curves, in order to be as close as possible to the sequential model. However, since

- 57 -

the GAMS model will be used to simulate an open market coupling, we will only consider

stepwise curves in this model (when the scales are small, there is no significant differences).

III.C.2.5. Calculation of the market prices and surplus

Once we get the result of the optimisation, we obtain the energy transactions between

areas. The data are exported to an Excel File, and computations are then done using VBA.

The supply and demand curves of the markets are shifted in respect to the energy transactions

made, and we can then calculate the new market prices and the consumers’ and producers’

surplus for each market.

As a remark, in the calculation of the surplus with supply and demand curves of each

market, we use the following convention in case of price or volume indetermination:

nP

The equilibrium price is the

marginal price

1V 2V

2

21 VVVn

+=

Figure 35: Price and Volume indeterminations

This will explain slight differences between the objective function value (the global surplus)

and the global surplus calculated with the final supply and demand curves.

We will do the simulation on a small theoretical example, close to the example used to

describe the TLC in section III.B.2, and compare the result from the sequential model and the

optimisation problem solved with Excel. The example has been tested with GAMS as well,

and the results are almost the same (the differences are due to the hypothesis of the stepwise

curves).

- 58 -

III.C.3 Results of the simulation: Sequential model versus optimisation

As input to our simulation, we have the following supply and demand curves for each isolated

market:

Volume (MWh)

Pri

ce(€

/MW

h)

Supply curve

Demand curve

Volume (MWh)

Pri

ce(€

/MW

h)

Supply curve

Demand curve

Volume (MWh)

Pri

ce(€

/MW

h)

Supply curve

Demand curve

Calculation of the consumers’ and producers’ surplus (€)

Consumers’ Producers’

M1 3 090,9 2 137,2

M2 1 735 720

M3 945 2 960

Global Surplus : 11 588,125

M1: Market B

Price of the isolated market:

11,75 €/MWh

Volume of exchanged MWh :

347,5 MWh

M2: Market A


9 €/MWh


202,5 MWh

M3: Market C


23 €/MWh


235 MWh

- 59 -

� Scenario1: All ATCs are equal to 1000 MW

Table 5: Results of the simulation, scenario 1

Considering those results, we can deduce that the algorithm leads to the optimal

solution of the problem, since we obtain the same total surplus. Thanks to the large ATC,

there is no congestion.

Compared to the case of isolated markets, the surplus has increased by 13, 1%.

0

5

10

15

20

25

30

35

0 100 200 300 400 500

Volume (MWh)

Pri

x (

€/M

Wh

)

0

5

10

15

20

25

30

35

0 200 400 600 800 1000

Volume(MWh)

Pri

x (

€/M

Wh

)

Vente + Import

Achat + Export

Vente

Achat

0

5

10

15

20

25

30

35

0 200 400 600 800

Volume (MWh)

Pri

x (

€/M

Wh

)

M1:Market B

M2:Market A M3:Market C

0 MWh 120 MWh

130 MWh

15 €/MWh

15 €/MWh 15 €/MWh

Figure 36: Results of the simulation, scenario 1

Solver

Price of the coupled markets (€/MWh)

P1 15

P2 15

P3 15

Transmissions (MWh)

To M1 To M2 To M3

From M1 0 120,5

From M2 0 129,5

From M3 0 0

Surplus (€)


M1 2 054,9 3 372,5

M2 855 2 045

M3 3 515 1 265

Global Surplus : 13 107,5 €

Algorithm


P1 15

P2 15

P3 15

Transmissions (MWh)

To M1 To M2 To M3

From M1 0 120

From M2 0 130

From M3 0 0

Surplus (€)


M1 2 055 3 372,5

M2 855 2 045

M3 3 515 1 265


- 60 -

� Scenario 2: Transmissions limitation:

=

=

→

→

0

0

13

31

ATC

ATC

This is equivalent to the real case France/Belgium/Netherlands, with no transmission

limitations (Figure 20).


The results are the same than in the previous case, the transaction is done through the market

A.

0

5

10

15

20

25

30

35

0 200 400 600 800 1000

Volume(MWh)

Pri

x (

€/M

Wh

)

Vente + Import

Achat + Export

Vente

Achat

0

5

10

15

20

25

30

35

0 200 400 600 800

Volume (MWh)

Pri

x (

€/M

Wh

)

0

5

10

15

20

25

30

35

0 200 400 600 800

Volume (MWh)

Pri

x (

€/M

Wh

)

M1:Market B


250 MWh

120 MWh

15 €/MWh

15 €/MWh 15 €/MWh


Algorithm


P1 15

P2 15

P3 15

Transmissions (MWh)

To M1 To M2 To M3

From M1 120 0

From M2 0 250

From M3 0 0

Surplus (€)


M1 2 055 3 372,5

M2 855 2 045

M3 3 515 1 265


Solver


P1 15

P2 15

P3 15

Transmissions (MWh)

To M1 To M2 To M3

From M1 120 0

From M2 0 250

From M3 0 0

Surplus (€)


M1 2 054,9 3 372,5

M2 855 2 045

M3 3 515 1 265


- 61 -

� Scenario 3: Transmission limitations:

=

=

→

→

80

80

23

32

ATC

ATC and

=

=

→

→

0

0

13

31

ATC

ATC


This is equivalent to the real case France/Belgium/Netherlands, with a congestion

between Belgium and Netherlands (Figure 22). We obtain the same price in France and

Belgium, but the Dutch market is isolated and gets a higher price.

Compared to the case of isolated markets, the surplus has increased by 2,3% (the

increase of the surplus is smaller when a line is congested).

The results are illustrated in the picture below:

0

5

10

15

20

25

30

35

0 200 400 600 800

Volume(MWh)

Pri

x (

€/M

Wh

)

Vente + Import

Achat + Export

Vente

Achat

0

5

10

15

20

25

30

35

0 100 200 300 400 500

Volume (MWh)

Pri

x (

€/M

Wh

)

0

5

10

15

20

25

30

35

0 200 400 600 800

Volume (MWh)

Pri

x (

€/M

Wh

)

M1:Market B


80 MWh

15 MWh

Congestion

12 €/MWh

12 €/MWh

19 €/MWh


Algorithm


P1 12

P2 12

P3 19

Transmissions (MWh)

To M1 To M2 To M3

From M1 15 0

From M2 0 80

From M3 0 0

Surplus (€)


M1 3 005 2 225

M2 1 215 1 340

M3 2 030 2 040

Global Surplus : 11 855 €

Solver


P1 12

P2 12

P3 19

Transmissions (MWh)

To M1 To M2 To M3

From M1 15 0

From M2 0 80

From M3 0 0

Surplus (€)


M1 3 004,9 2 225

M2 1 215 1 340

M3 2 030 2 040

Global Surplus : 11 855 €

- 62 -


=

=

→

→

100

100

12

21

ATC

ATC and

=

=

→

→

0

0

13

31

ATC

ATC

Table 8: : Results of the simulation, scenario 4

This is equivalent to the real case France/Belgium/Netherlands, with a congestion

between France and Belgium (Figure 23). We obtain the same price in Belgium and

Netherlands, but the French market is isolated and gets a lower price.

Compared to the case of isolated markets, the surplus has increased by 11.8 %.

0

5

10

15

20

25

30

35

0 200 400 600 800 1000

Volume(MWh)

Pri

x (

€/M

Wh

)

Vente + Import

Achat + Export

Vente

Achat

0

5

10

15

20

25

30

35

0 200 400 600 800

Volume (MWh)

Pri

x (

€/M

Wh

)

0

5

10

15

20

25

30

35

0 200 400 600 800

Volume (MWh)

Pri

x (

€/M

Wh

)

M1:Market B


240 MWh

100 MWh

Congestion

16 €/MWh 16 €/MWh

14,56 €/MWh


Algorithm


P1 14,56

P2 16

P3 16

Transmissions (MWh)

To M1 To M2 To M3

From M1 100 0

From M2 0 240

From M3 0 0

Surplus (€)


M1 2 189,8 3 188,8

M2 750 2 290

M3 3 095 1 445


Solver


P1 14,56

P2 16

P3 16

Transmissions (MWh)

To M1 To M2 To M3

From M1 100 0

From M2 0 240

From M3 0 0

Surplus (€)


M1 2 189,8 3 188,8

M2 750 2 290

M3 3 095 1 445


- 63 -


=

=

→

→

50

50

12

21

ATC

ATC and

=

=

→

→

170

170

23

32

ATC

ATCand

=

=

→

→

0

0

13

31

ATC

ATC


Compared to the case of isolated markets, the surplus has increased by 6,6%.

This is equivalent to the real case France/Belgium/Netherlands, with a first congestion

between France and Belgium, which isolates the French market, and then a second congestion

between Belgium and Netherlands (Figure 24). We finally obtain three different prices.

0

5

10

15

20

25

30

35

0 200 400 600 800 1000

Volume(MWh)

Pri

x (

€/M

Wh)

Vente + Import

Achat + Export

Vente

Achat

0

5

10

15

20

25

30

35

0 200 400 600

Volume (MWh)

Pri

x (

€/M

Wh

)

0

5

10

15

20

25

30

35

0 200 400 600 800

Volume (MWh)

Pri

x (

€/M

Wh

)

M1:Market B


170 MWh

50 MWh

Congestion

Congestion

12,87 €/MWh

14 €/MWh17 €/MWh


Algorithm


P1 12,87

P2 14

P3 17

Transmissions (MWh)

To M1 To M2 To M3

From M1 50 0

From M2 0 170

From M3 0 0

Surplus (€)


M1 2 717,1 2 541,4

M2 960 1 810

M3 2 705 1 625


Solver


P1 12,87

P2 14

P3 17

Transmissions (MWh)

To M1 To M2 To M3

From M1 50 0

From M2 0 170

From M3 0 0

Surplus (€)


M1 2 717,1 2 541,4

M2 960 1 810

M3 2 705 1 625


- 64 -

III.C.4 Conclusions regarding the results

The solver is a way to validate the sequential model. Indeed, since the prices,

transactions and surplus calculated are the same, we can deduce that the sequential model is

optimal, and maximizes the global surplus.

Moreover, the example above shows the impact of a congestion on the global welfare.

However, the data used here are theoretical, and it would be more interesting to run the model

with realistic data.

The sequential model is based on the same principles that the TLC algorithm, besides a slight

difference due to the fact that the three countries are not necessarily aligned in the simulation.

But it is exactly the same mechanism for matching orders, and logically leads to the same

results14

.

The main difference between the sequential model and the optimisation is that the

complete supply and demand curves are not necessary in the sequential model, as it is the case

today in the TLC. This is mainly a strategic point, but it could stress the interest of a

sequential model compared to an optimisation formulation.

However, when dealing with more than three countries, an optimisation formulation is

necessary. Besides, it is a way to confirm that the market coupling mechanism actually

optimises the global economic surplus.

III.C.5 Perspectives

As a future work, it would be interesting to perform the optimisation using only the NECs.

Indeed, in a two markets situation, it is possible to compute the increase or decrease of the

economic surplus with the NECs, as shown in the picture below where the market A export

towards the market B.

14

When dealing with theoretical data, without block offers.

- 65 -

Figure 41: Calculation of the surplus using the NECs

In a bilateral coupling, it is possible to get the increase of the global surplus, using the

NEC of the exporting market and the NIC of the importing market.

Net Export (MWh)

Price

(€/MWh)

NEC A

NEC B

Net Export (MWh)

Price

(€/MWh)

NEC A

NIC B

AP0

BP0

finalP

B)(A Surplus +∆

Figure 42: Increase of the surplus resulting from the coupling

The aim of the optimisation would be to maximise the area representing the increase of

the global surplus. However, the difficulty would be in getting only two curves when dealing

with more than two markets. Therefore, it would be necessary to assume aggregations of

different markets to come down to two areas and a bilateral coupling. An iteration process

would be needed to test all the possible situations, and keep the most optimal.

- 66 -

III.D. Towards an Open Market Coupling

III.D.1 Elaboration of the scenarios

In this part, the aim is to focus on the potential extending of the market coupling

mechanism, especially to Germany, and run the GAMS simulation with realistic data. For this

purpose, we choose to build several scenarios for the second term of 2008.

The constructed supply and demand curves are based on historical data, and price

quotations. Regarding the prices, the scenarios will be based on futures’ prices for the second

term of 200815

; the following prices are used as a basis

France 53 €/MWh

Germany 55 €/MWh

Belgium 55,5 €/MWh

Netherlands 59 €/MWh

Table 10: Prices of the futures for the second semester 2008

Regarding the quantities traded in each market, we will base our argument upon

historical data from the day-ahead markets16

. As an indication, average data from 2006

concerning the different power exchanges are summarized in the table below:

Volume on the spot

market in 2006 (TWh)

Volume on the spot

market as a percentage of

the overall consumption

France 29 6 %

Germany 89 16 %

Belgium 0.5 (only since 22.11.2006) 6 %

Netherlands 19 16 %

Table 11: Volumes on the spot market in 2006

In the scenario, we will take the following volumes as an order of magnitude (it

represents the volume of energy traded during one hour on the day-ahead spot market):

France 3500 MWh

Germany 10 000 MWh

Belgium 1000 MWh

Netherlands 1 800 MWh

Table 12: Day-ahead market volumes

These data have been used as a start, but then they have been modified in order to

improve the scenarios.

The slope of the supply curve’ order of magnitude will be based on historical

aggregated curves, on the different kinds of production capacity of each country and

sometimes on resilience analysis.

15

The prices are based on Platts data. The prices for France, Belgium and the Netherlands take into account the

coupling (since it already existed when the quotation has been done) 16

The data are extracted from the power exchanges’websites: Belpex, ApX, EEX, Powernext.

- 67 -

We will assume that the demand curve is the symmetric of the supply curve (ie with

the opposite slope). Indeed, on the day-ahead market, only the marginal part of the production

and consumption is represented. This part is managed by traders, and we could say that the

demand curve is in fact a “non-production” curve: it represents the energy a trader prefers to

buy instead of produce.

The ATC between countries are based on the Etsovista data for the winter 2007. We assume

that the ATC is equal to one third on the Net Transfer Capacity.

France Germany Belgium Netherlands

France 0 900 1000 0

Germany 900 0 0 1200

Belgium 700 0 0 750

Netherlands 0 950 750 0

Table 13: ATC matrix (in MW)17

III.D.2 Result of the simulations18

The results of the base scenario are given below19

:

644.25 MW

673,75 MW 431 MW

55.262.4Netherlands

55.258.2Belgium

55.255.5Germany

55.249.9France

Coupled

Markets

Isolated

Markets

Prices (€/MWh)

Figure 43: Results from the base scenario using the ATC model

17

The countries on the vertical column export to the countries on the horizontal line. 18

In dot lines are represented the supply and demand curve before the coupling, in full lines after the coupling. 19

Since the data are available for one hour, a MW is equivalent to a MWh.

- 68 -

In the base scenario, the final prices are close to the German price. In France, the

isolated price is lower, but prices increase faster (the slope is larger) than in Germany.

The resulting energy transaction concerns the day-ahead implicit auction only, and must be

added to the transaction outside the day-ahead market.

The idea is

to simulate several situations, based on this base scenario in extreme situations.

• Scenario 1: A peak of wind is observed in Germany.

We assume an increase of 6 000 MW of production, due to the surplus of wind power.

However, all this quantity is not contracted on the day-ahead market. We assume that

wind forecast allow half of the quantity to be contracted outside the day-ahead market.

Therefore, we subtract 3 000 MW from the demand curve, and we add 3 000 MW to the

supply curve.

900MW

765.75 MW 1200 MW

415 MW

49.462.4Netherlands

49.458.2Belgium

46.737.5Germany

49.449.9France

Coupled

Markets

Isolated

Markets

Prices (€/MWh)

Figure 44: Results from the scenario 1 using the ATC model

Here we observe two congested lines, and the German market is isolated with the lowest

price. The three other markets get the same price.

- 69 -

• Scenario 2: A decrease of the temperature is observed, especially in France.

Indeed, France is very sensible to the coldness, because electric heating is very popular. In

the winter, the consumption increase by approximately 1500 MWh/° during the winter.

Here we consider an increase of 4 000 MW of demand, but only half of it is traded on the

day ahead market, assuming that the other part is contracted bilaterally. Therefore, we

subtract 2 000 MW from the demand curve, and we add 2 000 MW to the supply curve.

900MW

700 MW 811 MW

584 MW

58.762.4Netherlands

58.758.2Belgium

58.755.5Germany

6195.9France

Coupled

Markets

Isolated

Markets

Prices (€/MWh)


The lines towards France are both congested, which isolates the French market with a higher

price. The three other markets get equal prices.

- 70 -

• Scenario 3: A lack of wind is observed in Germany.

It leads to a decrease of production up to 4 000 MWh and increase the German price. Half

of this amount has been contracted outside the day-ahead market. Therefore, we subtract

2000 MW from the demand curve, and we add 2 000 MW to the supply curve.

900MW

782 MW 649 MW

750 MW

60.862.4Netherlands

5858.2Belgium

60.866.2Germany

5849.9France

Coupled

Markets

Isolated

Markets

Prices (€/MWh)


In this scenario we reach two groups of countries: Belgium and France on one hand, which

exports towards Germany and the Netherlands on the other hands, until the two concerned

lines get congested.

- 71 -

• Scenario 4: An increase of the price of gas is observed.

The French price is not changed, since the marginal production is more made of coal plant

in France. However, the German, Belgian, and Dutch prices are affected. In Germany, the

marginal production consist in coal or gas, so we assume an increase of the prices of 15

€/MWh (the supply curve is vertically shifted). In Belgium and the Netherlands, the part

of gas in the marginal production is more important, especially in the Netherlands: the

price is increased by 25 €/MWh on the Belgian market and by 30 €/MWh on the Dutch

market.

900MW

1000 MW 191.25 MW

562.25 MW

61.477.4Netherlands

61.469.1Belgium

61.463.4Germany

59.649.9France

Coupled

Markets

Isolated

Markets

Prices (€/MWh)


In this scenario, the French market is isolated with a lower price: it exports until both

outwards lines get congested. The three other markets get equal prices.

- 72 -

• Scenario 5: We assume an unavailability of 1 800 MW of production capacity on the

Dutch market.

Moreover, an unavailability of half the transmission capacity (ATC) on the line from

Belgium to the Netherlands is observed, because of network maintenance for example.

The aim of this scenario is to isolate the Dutch market. Contrary to the TLC, it is more

“difficult” to isolate the Netherlands, because the transaction can be done through

Germany.

640 MW

834.75 MW 1200 MW

375 MW

62.2114.6Netherlands

56.558.2Belgium

56.555.5Germany

56.549.9France

Coupled

Markets

Isolated

Markets

Prices (€/MWh)


The Dutch market gets isolated with a higher price, whereas the three other markets get the

same price.

- 73 -

• Scenario 6: We consider the same situation as in scenario 1, and we add a network

constraint: only half of the ATC is available on the line from Germany to the

Netherlands.

900 MW

1000 MW 600 MW

52.462.4Netherlands

52.458.2Belgium

44.437.5Germany

50.249.9France

Coupled

Markets

Isolated

Markets

Prices (€/MWh)


Due to the stronger constraint on the line from Germany tote Netherlands, the German market

gets isolated first. The line between France and Belgium becomes congested two. Only

Belgium and the Netherlands get the same price.

The aim of running the scenarios above was to get a better understanding of the

situation of an Open Market Coupling including Germany, and to reach different

configurations of prices and congestions.

It is interesting to point out that in this simulation, which only deals with commercial

capacities and transactions, one congestion does not lead to four different prices. Indeed, once

a line is congested, the transaction underway is done through the other possible “lines” (ATC

in fact). In the studied area, the four countries are on a circle. To get an isolated price, a

market must have both outwards and inwards line congested.

Moreover, building scenarios and working on the slope of the curves was interesting,

because the price sensitivity is specific to each countries and its means of production, and

influence the final result of the coupling. The data used are not accurate, but they give a

general idea of the kinds of situations which can occur.

- 74 -

Besides, in the studied cases, prices spreads due to congestions are quite numerous.

Another alternative to the method implemented with the ATC is the flow-based approach,

which takes into account the real power flows on the grid, and might allow an even better use

of the cross border transmission lines. We will try to implement this approach and compare

the results using the same scenarios.

- 75 -

III.E. Towards a flow-based market coupling

III.E.1 Formulation of the problem with the Power Transfer Distribution Factors

Another method to describe the cross-border transmission limit capacity is to establish a

flow-based model. It means that, instead of considering commercial transactions and

commercial capacities (ATC), we will consider the physical power flows on the line and the

physical cross-border transmission limitations.

When we consider the real meshed networks and its physical laws, an energy transfer

on an interconnection has an effect on the power flows on all the other lines. Indeed, a

commercial transaction between two countries leads to physical power flow on every line of

the meshed network, considering the Kirchoff’s law. In the following picture, the power flow

distribution of a 1000 MW transaction from France to Italy is represented.

Figure 50 : Power flow distribution of a 1000 MW trnasport from Northern France to Italy

The model of the power flows on the line is done by the means of the so-called Power

Transfer Distribution Factor (PTDF), which represent the percentage shared in transit on each

line, depending of the balance20

of the considered countries. Here we will work with zonal

PTDF factors (we consider a country as one node); they describe the influence a commercial

exchange between two countries has on the physical flows on a given interconnection [28].

In fact, the PTDF factors translate a commercial transaction between two countries to the

expected physical flow over the transmission network.

The overall formulation of the market coupling as an optimisation problem is the same

as before, except that we add a variable for the physical power flows, and the constraints are a

bit changed. This simulation is implemented with GAMS as well.

With a flow-based approach of Market Coupling, the commercial exchange between

two markets is no longer limited by the commercial capacity on the interconnection where the

transaction is done, but it is translated to physical flows through the entire transmission

network, and thus limited by physical capacity of the lines. Therefore, other countries besides

the considered markets are taken into account.

20

The balance of a country is equal to its production minus its consumption.

- 76 -

The European interconnected power system is divided into main regional areas. In this

study, we have considered the countries of the Central Southern Europe and Central Western

Europe (as represented on the picture above). The PTDF factors are the result of a multi-linear

regression between the flows on given interconnections and the net production of the

countries involved in the PTDF calculation (by net production, it is meant supply minus

demand). The data are observed data21

, averaged on the year 2006.

The lines are represented by a maximum allowable flow maxFlow and an estimated

flow 0T which is present prior to the additional transaction. Moreover, the transactions (still

represented by the variable mnExp → , results from the market coupling optimisation problem)

are considered as variation from an initial balance lB of the concerned country l.

The resulting flow on a cross border transmission line is represented by a variable mnFlow → .

The opposite flow nmFlow → is equal to mnFlow →− .

The new transmission constraints in our optimisation problem are the following:

where the set l describe the country, ie the countries taken into account in the PTDF

calculation, including the observed markets.

III.E.2 Data used in the model

We work with the eight countries of Central Southern Europe and Central Western

Europe, including the four markets of France, Germany, Belgium and the Netherlands. We

consider the four lines betweens those markets: Fr-De, De-Nl, Nl-Be, Be-Fr.

� How we calculate the initial balance

We have the average balance for each country (in MW), which include every type of

transaction and auctions:

Sl 45 MW

It -6099 MW

At 905 MW

CH 96 MW

Fr 7700 MW

De -238 MW

Be -616 MW

Nl -2048 MW

Table 14: Average balances in MW

21

www.etsovista.org

( )

≤

−+⋅→+=

→→

=

→→→→ ∑ ∑

MAXnmnm

L

l markets

mmarketmarketmlnmnm

FlowFlow

ExpExpBnmPTDFTFlow

,

1

made ons transacticommercial the todue Balance theofVariation

,0 )()(

44444 344444 21

- 77 -

We need to compute initial balance for each market, to which we will add the

additional balance due to energy transactions resulting of the simulation. We will consider

that the initial balance for each country is equal to two third of the average balance: one third

of the balance is represented by the market coupling. This is quite consistent with the

assumption made in the simulation using the ATC, where the ATC were assumed to be equal

to one third of the NTC. Indeed, we still consider that two third of the quantity available on

the market correspond to explicit auctions. We keep the average balance to the countries

which are not studied as market in the simulation:

Sl 45 MW

It -6099 MW

At 905 MW

CH 96 MW

Fr 5133,33 MW

De -158,67 MW

Be -410,67 MW

Nl -1365,33 MW

Table 15: Initial Balances in MW

� How we calculate the maximal flows

We are given the maximal flows observed on each line. However, the actual flows are

most of the time smaller. Since we do not have here a real model of the network to define

those maximal flows, we will take the strongest constraint between the observed flows and the

NTC.

� How we understand the given PTDF

The data used for the simulation are the following:

Fr →De De →Nl Nl →Be Be →Fr

T0 (MW) 560 437 437 437

PTDF (%)

Sl -0,7 22 22 22

It -8,6 -14,2 -14,2 -14,2

At -19,2 -1,3 -1,3 -1,3

CH -9,9 -9,6 -9,6 -9,6

Fr 15,8 -14,9 -14,9 -14,9

De -21,3 14,8 14,8 14,8

Be 2,2 -63,3 -63,3 36,7

Nl 6,8 -69,6 30,4 30,4

Table 16: Data used for PTDF and T0

- 78 -

In the studied network, France and Germany are linked to other countries than

Belgium and the Netherlands. Indeed, we do not consider in the calculation only the four

studied markets, but the eight countries of the CWE22

and CSE23

area. This explains why the

net flow coming out or in (using the studied lines) is not equal to zero for France and

Germany.

Indeed, if we take Germany:

- Concerning the transit prior to any additional transaction, we observe a net flow

outwards Germany equal to 560-437=123 MW: this flow is distributed towards the

others countries

- Concerning the PTDF, the sum of the factors on the line coming out from Germany is

not equal to 100% (PTDF (De,De →Nl)-PTDF(De, Fr →De)<100%), which means

that a part of the flow is distributed on the other lines connected to Germany. Here, the

sum of the factor on the line De →Nl (14.8%) minus the factor on the line Fr →De (-

21.3%) is equal to 36.1% : this means that 63.9 % of the flow is distributed on lines

towards the other countries (Sl, It, At, CH)

Concerning France and Germany, this let us understand why the net position (resulting from

the energy transaction calculated by the model) is not equal to the net power flow coming out

or in the market. Indeed, a part of the energy transaction is distributed towards the other

connected countries.

However, concerning Belgium and Netherlands, the net position due to commercial

transaction is equal to the net physical power flow coming in or out the country.

Indeed, if we take Belgium:

- Concerning the transit prior to any additional transaction, the net balance due to this

flow is equal to 437-437=0 MW

- Concerning the PTDF, the sum of the factors on the line coming out from Belgium is

equal to 100%: (PTDF (Country,Be →Fr)-PTDF(Country, Nl →Be)=100%).

Indeed, it is equal to 36.7-(-63.3) =100%: All the flow is distributed towards France

and the Netherlands, because there is no other line connected to Belgium in the studied

system.

22

Central West Europe 23

Central South Europe

- 79 -

III.E.3 Simulation on the scenarios

The aim here is to compare the result of the flow based model with the ATC model, by

running them on the scenarios. Since the data are not accurate, the aim here is just to point out

the main aspects of both methods, not to make a quantitative analysis.

Below are given the commercial transactions resulting from the base scenario.

213.25 MW

673,75 MW431 MW

Figure 51: Results from the base scenario using the PTDF model

Isolated Market (€/MWh) Coupled Market (€/MWh)

France 49.9 55.2

Germany 55.5 55.2

Belgium 58.2 55.2

Netherlands 62.4 55.2

Table 17 : Prices in €/MWh

Firstly, it is important to notice that, contrary to the ATC model, all the possible

commercial transactions are allowed. Indeed, in this simulation, the commercial transactions

are not limited by the ATC, but are used to calculate the physical power flows and then the

real power flow is limited by a maximum. Therefore, every way of transaction is allowed, like

between France and the Netherlands in this example.

We reach the same final price than in the ATC model, and the net position of each

market is the same. We get the same global economic surplus

- 80 -

Concerning the physical power flows, they are given below, in MW:

Fr →De De →Nl Nl →Be Be →Fr

1853,45608 2212,36842 416,035083 -668,381583

Table 18: Physical power flows, Base scenario

Flow Max Flow Min

Fr →De 2850 Fr →De -740

De →Nl 3850 De →Nl -158

Nl →Be 2400 Nl →Be -2400

Be →Fr 1793 Be →Fr -2997

Table 19: Constraints on the pysical power flows

As we can see here, the remaining margins between the power flows and the

constraints are quite large, so it will certainly be difficult to reach congestion, starting from

the base scenario. The flow-based method is supposed to result in a better use of the

transmission capacities, and therefore lead to fewer price spreads and a better economic

surplus.

The picture below summarizes the base scenarios using both commercial and flow-based

approach:

PTDF ModelATC Model

55.2

55.2

55.2

55.2

55.262.4Netherlands

55.258.2Belgium

55.255.5Germany

55.249.9France

Price of the Coupled Market

(€/MWh)

Price of the

Isolated

Market

(€/MWh)

Be NL

DeFr

Be NL

DeFr

Simulation using ATCs Simulation using PTDFs

673.25 MW

644.25 MW

431 MW 673.25 MW

213.25 MW

431 MW

7424115,457424115,45Global Surplus of

the coupled market

(€)

PTDF

Model

ATC

Model

Figure 52: Comparison of the results from the base scenario

We will compare the results from the optimisation using ATC and the flow based method,

based on the scenario.

- 81 -

� Scenario 1

PTDF ModelATC Model

49.4

49.4

46.7

49.4

48.262.4Netherlands

48.258.2Belgium

48.237.5Germany

48.249.9France


(€/MWh)

Price of the

Isolated

Market

(€/MWh)

Be NL

DeFr

Be NL

DeFr


765.75 MW

900 MW

1200 MW 1264.75 MW

2 574.75 MW

857 MW

415 MW


the coupled market

(€)

PTDF

Model

ATC

Model

Figure 53: Comparison of the results from the scenario 1

We observe no congestion with the flow-based model, and therefore a better global surplus of

the coupled markets. In this scenario, the flow –based approach allow a better use of the

transmission line capacities.

� Scenario 2

PTDF ModelATC Model

58.7

58.7

58.7

61

59.162.4Netherlands

59.158.2Belgium

59.155.5Germany

59.195.9France


(€/MWh)

Price of the

Isolated

Market

(€/MWh)

Be NL

DeFr

Be NL

DeFr


700 MW

900 MW

811 MW 198.255 MW

1847 MW

203 MW

584 MW


the coupled market

(€)

PTDF

Model

ATC

Model


- 82 -

Here as well the flow-based method leads to a single price and a better global surplus.

� Scenario 3

PTDF ModelATC Model

60.8

58

60.8

58

59.562.4Netherlands

59.558.2Belgium

59.566.2Germany

59.549.9France


(€/MWh)

Price of the

Isolated

Market

(€/MWh)

Be NL

DeFr

Be NL

DeFr


782 MW

900 MW

649 MW 292.25 MW

2009.25 MW

173 MW

750 MW


the coupled market

(€)

PTDF

Model

ATC

Model


We observe again that no congestion appears in the simulation using the PTDF.

� Scenario 4

PTDF ModelATC Model

61.4

61.4

61.4

59.6

6177.4Netherlands

6169.1Belgium

6163.4Germany

6149.9France


(€/MWh)

Price of the

Isolated

Market

(€/MWh)

Be NL

DeFr

Be NL

DeFr


1000 MW

900 MW

191.25 MW 476.75 MW

823.75 MW

771.5 MW

562.25 MW


the coupled market

(€)

PTDF

Model

ATC

Model


- 83 -

Contrary to the ATC model, we observe no congestion in this scenario either.

� Scenario 5

In this scenario, the ATC from Belgium to Netherlands was reducd by half. This could be

transposed in the flow-based method by reducing the maximal flow on the line from Belgium

to Netherlands.

Since the physical flows are global, there are equivalent to NTC in the commercial

approach. Besides, ATC were equal to one third of NTC. Therefore dividing the ATC by two

in the commercial approach is equivalent to divide the NTC by 6, and by this way to reduce

the physical flow by one sixth in the flow-based approach.

PTDF ModelATC Model

62.2

56.5

56.5

56.5

56.6114.6Netherlands

56.658.2Belgium

56.655.5Germany

56.649.9France


(€/MWh)

Price of the

Isolated

Market

(€/MWh)

Be NL

DeFr

Be NL

DeFr


834.75 MW

640 MW

1200 MW 437.75 MW

678 MW

1740.25 MW

375 MW


the coupled market

(€)

PTDF

Model

ATC

Model


In this scenario again, we observe no congestion and a better global surplus.

The physical power flows and their limitations are given below:

Fr_De De_Nl Nl_Be Be_Fr

1608,53883 3079,00542 -26,5779167 -874,994583

Flow Max Flow Min

Fr_De 2850 Fr_De -740

De_Nl 3850 De_Nl -158

Nl_Be 2400 Nl_Be -2000

Be_Fr 1793 Be_Fr -2997

Table 20: Physical power flows and their limitations

- 84 -

� Scenario 6

In this scenario, we reduce the maximal power flow from Germany to the Netherlands by one

sixth.

PTDF ModelATC Model

52.4

52.4

44.4

50.2

51.762.4Netherlands

51.358.2Belgium

46.737.5Germany

48.549.9France


(€/MWh)

Price of the

Isolated

Market

(€/MWh)

Be NL

DeFr

Be NL

DeFr


1000 MW

900 MW

600 MW 1071.75 MW

2093.75 MW

647 MW


the coupled market

(€)

PTDF

Model

ATC

Model


The physical power flows and their limitations are given below:

Fr_De De_Nl Nl_Be Be_Fr

1071,12651 3208,33333 1196 -286,419121

Flow Max Flow Min

Fr_De 2850 Fr_De -740

De_Nl 3208,33333 De_Nl -158

Nl_Be 2400 Nl_Be -2400

Be_Fr 1793 Be_Fr -2997

Table 21: Physical power flows and their limitations

This scenario is interesting, since we observe a congestion in both simulations.

However, we can clearly see here, in the flow-based approach, that once only one line is

congested, the four market zones get different prices. This is not the case with the simulation

using commercial capacities, because once an ATC is fully used, the commercial transactions

underway can continue using other ATCs.

In the flow-based approach, once a line is physically congested, no other additional

transaction can be done. Indeed, an additional congestion would lead to a distribution of the

flow on every line of the meshed network, which is not possible since one of them is

unavailable.

- 85 -

In this example, even with congestion, the global economic surplus is larger using the

flow-based method. We can not deduce general conclusions from one scenario, but the result

is interesting anyway.

III.F. The commercial approach versus the flow based approach

It is important to see that the data used in the simulation are not accurate, and come

from several hypotheses. The simulation gives only an illustration of the flow-based

approach. Afterwards, like the approach using the ATC, the model will lay down the problem

of the calculation of the needed data and their gathering.

In the studied cases, the flow-based approach allows a better use of the cross-border

transmission capacities, and therefore results in a better global economic surplus. It leads to

fewer situations of price spreads. Nevertheless, because of the calculation of the physical

power flows behind, it could appear as less transparent for traders.

Besides, the main aspect to see in this approach is that once a line gets congested, each

zone gets a different price, which induces more price volatility. Firstly, this can be seen as an

increase of the prices volatility and therefore an argument to reject the flow-based approach.

Secondly, it compromises the current method of distributing the income from a congestion to

the TSOs. Indeed, with the methods applied today, when a line gets congested (in the sense

of ATC), the income from the congestion is shared by the two TSOs concerned by the energy

transaction. With a flow-based approach, this is not possible anymore: a transaction between

two zones can create a congestion on a line between other zones, and all the prices are then

different. It will not be fair then to share the income between the two TSOs concerned by the

initial transaction.

Moreover, the Power Transfer Distribution Factors influence a lot the results, and their

calculation must be done fairly and accurately. An important coordination between TSOs is

needed to compute the data needed in this model (initial balances, T0, PTDF…).

- 86 -

Chapter IV. Conclusions

IV.A. Main aspects of the study

The first part of this master thesis aims at giving an overview of the balancing

mechanisms in Great-Britain and Germany, pointing out the likenesses and differences. As it

is a part of a larger project resulting in a benchmark of the different balancing mechanisms in

Europe, it is does not give a general overview of the situation in Europe, and what is to be

done in order to integrate these balancing markets. However, it can be a support to understand

the basics of balancing mechanism, and how they can be applied viewed from two different

countries.

The second part of the study is supposed to allow a better understanding of the principles

of the market coupling, and the different methods which can be carried out. The main interest

was to build a model of the mechanism, and to see the most important challenges of the

mechanisms.

Firstly, the sequential algorithm simulates the Trilateral Market Coupling24

as it is done

today. The main point is that it requires the Net Exportation Curves as input data, and not the

full supply and demand curves. This is strategic, but can be an important argument in support

of this model. However, when dealing with more than three countries, the model becomes too

complicated to implement. Indeed, a formulation as an optimisation problem is more suitable

for a simulation of an Open Market Coupling including Germany. The major drawback is that

the full supply and demand curves are then needed to calculate the prices and net position of

each market.

Finally, the optimisation formulation is done using two approaches: the “commercial”

approach and the flow-based approach. By “commercial” approach, we mean that the

transmission lines are characterised by their ATCs, and no real power flow appears in this

model (it is intrinsic to the calculation of the ATCs). This kind of approach is easier to

understand, because all the physic of the grid is not clearly visible. Indeed, a transaction can

be done using all the possible ways (which are the cross border lines), without considering the

actual physical state of this line. On the other hand, in the flow-based approach, the

consideration of the real physical power flow is inherent to the model. The physical power

flows are computed using the PTDFs, data given by the TSOs.

If the flow-based approach is a bit more complicated, it is nevertheless supposed to lead to

a better use of the cross border transmission lines. Indeed, the results from the scenarios show

that the flow based approach results in better economic surplus, and fewer price spreads.

Since a congestion leads to a different price in each zone, the flow-based approach can induce

more price volatility, which could be a drawback for power exchanges.

However, we cannot deduce any general conclusion from the simulations done. Indeed,

the PTDF used are zonal, and the model is rough, due to the data used and the hypotheses

made. Anyway, the study is interesting because it gives an overview of the two methods, and

the kind of situations which can occur when Germany will be integrated in the process.

24

Only the algorithm of the coordination module

- 87 -

IV.B. Perspectives

One of the main points arising from the market coupling mechanism is the question of the

centralisation of the needed information. Indeed, as said in III.B, Market Coupling can be

seen as a different mechanism from Market Splitting because it adopts a decentralised

approach: the coupling is done between independent markets, with their own design.

Nevertheless, in the TLC algorithm, it appears that a common organisation is needed, to

carry out the mechanism. Currently, the Dutch power exchange ApX is in charge of the

functioning of the coordination module, and therefore gather the information (NECs and

ATCs). It is therefore not accurate to say that the approach is decentralised, since a common

entity is needed. This existence of a common entity raises several strategic questions: Who

should gather the information and carry out the algorithm and which degree of information

should be shared?

That is why a model using only the NECs is tempting, because it allows less information

to be given. As a future work, it would be interesting to perform the optimisation using only

the NECs.

Besides, in the flow-based approach, the calculation of the PTDFs and the data needed

will be a main issue. The flow-based approach as it is done in this master thesis is quite rough,

but it can be seen as an introduction and a support to understand the basics of the method and

its differences compared to the method using the ATCs.

- 88 -

Appendix 1

Some Data from the German Balancing Mechanism

Each German TSO publishes the volume of activated minute reserve. These data are

interesting, because they show that in fact, the minute reserve is rarely used.

Let us observe one day25

, January the 9th

2007.

The table hereafter shows the periods of the day which have seen a use of some minute

reserve:

Period Utilised minute reserve

energy (MWh)

Affected TSO

Downwards Bids

00 :30-00 :45 -122.5 RWE

23 :30-23 :45 -51.250 Vattenfall

23 :45-00 :00 -51.250 Vattenfall

Upwards Offers

10 :15-10 :30 25 EnBW

10 :30-10 :45 50 EnBW

10 :45-11 :00 50 EnBW

Table 22: Activation of minute reserve

Indeed, the activation of a reserve minute order is quite rare, whereas the published

imbalance in each zone for each period of this day are not equal to zero:

Imbalances

-350

-300

-250

-200

-150

-100

-50

0

50

100

150

0 20 40 60 80 100 120

Settlement Period

Imb

ala

nce

Vo

lum

e (M

Wh

)

RWE

EnBW

EON

Vattenfall

Figure 59: Metered Imbalance

25

Here we take arbitrarily one day to give a concrete example, but similar situations occur each day

- 89 -

Appendix 2

ATC definition

A transmission line is characterised by its transmission capacity, which is the maximum

quantity of MW allowed on this line. The following definitions are used to describe a

transmission line:

Ther

mal

Cap

acit

y Security margin

TRM

TTCATC

AACNTC

Figure 60: Description of a line

• TTC: Total Transfer Capacity (Maximal capacity available, while ensuring the

network security)

• TRM: Transmission Regulation Margin (minimal reserve to ensure reliability)

• NTC: Net Transfer Capacity (capacity used by the actors)

• AAC: Already Allocated capacity (via explicit auctioning)

• ATC: Available Transmission Capacity (available for market coupling)

When a commercial exchange of energy happens between two countries, it has an impact on

all the lines of the meshed network. NTCs and ATCs are commercial capacities, the load flow

calculations are included in these values. Therefore, once they are calculated, ATCs are

simple to use. Indeed, when a transaction of energy is settled between a market A and a

market B, it “consumes” a part of the ATC between A and B, and there is no additional power

flow calculation to make (they are contained in the ATC value).

The NTC and ATC values are published by the TSO. The main point here is how they are

calculated, and if the given value allows an optimal use of the transmission lines.

- 90 -

Appendix 3

Sequential Algorithm for Market Coupling

The algorithm tree given below summarizes all the possible paths in the first case:

A B CA B C

B A C

Selection of the exportation offers by

price on the NECs of A and B

Transmissions on the lines A-C and B-C

Saturation of A-C Saturation of B-C



Transmissions on the lines A-B + B-C

if the offer is in A or only B-C if the

offer is in B

Case 1

BCAB PPPP −≤−

A and B export to C

Saturation of

A-B

Saturation

of B-C

A isolated

B exports

to C

PB=PC

Saturation

of B-C

C isolated

The less expensive

of A or B exports

towards the other

PA=PB

Saturation

of A-B



Transmission on the lines B-A + A-C

if the offer is in B or only C-A if the

offer is in A

Saturation of

B-A

Saturation

of A-C

B isolated

A exports

to C

PA=PC

Saturation

of A-C

C isolated

The less expensive

of A or B exports

towards the other

PA=PB

Saturation

of A-B

- 91 -

The algorithm tree given below summarizes all the possible paths in the second case:

A C B

A B CA B C

It is important to notice that in every case, if the three prices become equal, the algorithm

stops.

Selection of the importation bids by price on

the Net Importation Curves of B and C

Transmissions on the lines A-B and A-C

Saturation of A-B Saturation of A-C



Transmissions on the lines A-C + C-B if the

offer is in B or only A-C if the offer is in C

Case 2

ABBC PPPP −<−

B and C import from A

Saturation of

C-B Saturation

of A-C

B isolated

A exports

to C

PA = PC

Saturation

of A-C

A isolated

The less expensive

of B or C exports

towards the other

PB = PC

Saturation

of B-C



Transmission on the lines A-B + B-C if the

offer is in C or only A-C if the offer is in B

Saturation of

B-C

Saturation

of A-B

C isolated

A exports

to B

PA = PB

Saturation

of A-B

A isolated

The less expensive

of B or C exports

towards the other

PB = PC

Saturation

of B-C

- 92 -

Appendix 4

Incremental process: non-congested case

Step 0

The marginal price of markets A, B and C are respectively 10€/MWh, 20€/MWh and

60€/MWh. Market C is prone to import using cheap offers from markets A and B.

Commercial capacities on lines A�C , A�B and B�C are respectively Q°A�

C =1400MW,

Q°A�

B =510MW and Q°B�

C =1000MW.

Step 1

340MW of offers from market A are accepted to match bids from market C. PA=20€/MWh,

PB=20€/MWh and PC=60€/MWh. The remaining commercial capacity on line QA�

C is then

equal to 1060MW.

Step 2

170MW of offers from market B are accepted to match bids from market C. PA=20€/MWh,

PB=30€/MWh and PC=50€/MWh. The remaining commercial capacity on line QB�

C is then

equal to 830MW.

Step 3



C is then

equal to 890MW.

Step 4


PB=40€/MWh and PC=50€/MWh. The remaining commercial capacity on line QB�

C is then

equal to 660MW.

Step 5



C is then

equal to 720MW. The price of the three markets is the same, and no transmission constraint

has been reached. The markets are “coupled”. The algorithm stops.

- 93 -

Appendix 5

Incremental process: congested case

Step 0

The marginal price of markets A, B and C are respectively 10€/MWh, 20€/MWh and

60€/MWh. Market C is prone to import using cheap offers from markets A and B.

Commercial capacities on lines A�C , A�B and B�C are respectively :

Q°A�

C =400MW, Q°A�

B =110MW and Q°B�

C =1000MW.

Step 1


PB=20€/MWh and PC=60€/MWh.

Q1

A�

C =60MW, Q1

A�

B =110MW and Q1

B�

C =1000MW.

Step 2



Q2

A�

C =60MW, Q2

A�

B =110MW and Q2

B�

C =830MW.

Step 3


PB=30€/MWh and PC=50€/MWh. The remaining capacity between A and C is not large

enough to support the market needs. Thus, a part of the transaction between A and C is

transiting through zone B. 60MW of this transaction uses the available capacity on the line

A�C, whereas uses 110MW of capacity on the lines A�B and B�C.

Q3

A�

C =0MW, Q3

A�

B =0MW and Q3

B�

C =720MW.

Step 4



Q4

A�

C =0MW, Q4

A�

B =0MW and Q4

B�

C =550MW.

Step 5

170MW of offers from market A should be accepted to match bids from market C, but there is

no transmission capacity left between A and C, even through B. 45MW of offers from market

A should be accepted to match bids from market C. PA=30€/MWh, PB=40€/MWh and

PC=40€/MWh.

Q5

A�

C =0MW, Q5

A�

B =0MW and Q5

B�

C =505MW.

The prices of the three markets are different, and transmission limits have been reached on

lines A�C and A�B. The markets are not “coupled”. The algorithm stops.

- 94 -

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- 95 -

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Electricity Markets: Balancing Mechanisms and Congestion ...609988/FULLTEXT01.pdf · Master Thesis Report Mathilde Dupuy - 2 - ABSTRACT During the last few years, several European