Extrait
Contents
1Introduction
1.1 Motivation and Relevan
1.2 Research Objectiv
1.3 Main Contributio
1.4 The Structure of Thesi
1.5 List of Publication
2Literature Review 6
2.1 History of the Liberalization of Electricity Market in Euro
2.2 Relevant stakeholders of European Electricity Marke
2.2.1 Regulator
2.2.2 Producer
2.2.3 Transmission System Operator
2.2.4 Power Exchang
2.2.5 Auction Offices for Cross Border Capacit
2.3 Market Coupling Proce
2.3.1 Regional Electricity Market
2.3.2 Market Coupling Timelin
2.3.3 Congestion Management Allocation Method
2.3.4 Cross-border Trade Energy in
2.4 Market Integration: Benefits and Obstacl
2.4.1 The Benefits of Market Integrati
2.4.2 The Obstacles of Market Integrati
3European Target Model and Relevant Projects
3.1 Introducti
3.2 Capacity Allocation and Congestion Managemen
3.2.1 The ATC mode
3.2.2 The Flow-based mode
3.3 Projects of Market Coupling in Europ
3.3.1 Harmonization of Long Term Allocation Rules Proje
3.3.2 Price Coupling of Regions Proje
3.3.3 Cross-Border Intra-Day Market Projec
3.3.4 Cross Border Electricity Balancing Pilot Project
3.4 Conclusi
4The Coupling of Day-ahead Electricity Market
4.1 Introducti
4.2 Structure of Day-Ahead Electricity Market in Europ
4.2.1 Type of Order
4.2.2 Non-Convexities in the Day-Ahead Electricity Market Mode
4.2.3 Transmission Networ
4.3 Study Case: Price Coupling of Regions Project Impact on Italian Electricity Marke
4.3.1 Introductio
4.3.2 Italian Electricity Market and Coupling Proces
4.3.3 Data Analyze
4.3.4 Conclusion
4.4 Uniform Price for the European Day-Ahead Electricity Mark
4.4.1 Literature Revi
4.4.2 Motivations and contribution
4.4.3 European Day-Ahead Electricity Market Mathematic Mode
4.4.4 Test and Resul
4.4.5 Conclusio
4.5 Non-Uniform Price for the European Day-Ahead Electricity Marke
4.5.1 The Issues of Uniform Price Mod
4.5.2 Literature Revi
4.5.3 Approach and Contribution
4.5.4 Mathematic Mod
4.5.5 Case Study and Resul
4.5.6 Conclusio
4.thorough comparison among various approaches on the PUN Sub-Probl
4.6.1 Biograph
4.6.2 Mathematic Model based on complementarity theo
4.6.3 Test and Resul
4.6.4 Conclusio
4.7 Conclusi
5The Coupling of Intra-Day Electricity Market
5.1 Introducti
5.2 State-of-the-art of Intra-Day Market in Euro
5.2.1 Market Desig
5.2.2 Type of Order
5.2.3 Capacity Allocation Manageme
5.3 The Hybrid Intra-Day Market Mechani
5.3.1 Goal and Contributions of the Mod
5.4 Mathematic Mode
5.4.1 Optimization Proble
5.4.2 Data Processing Modul
5.5 Hybrid Intra-Day Market Mechanis
5.6 Test and Resul
5.6.1 Case Stud
5.6.2 Resul
5.7 Conclusi
6Conclusions and Future Work
6.1 Conclusio
6.2 Future Wo
Appendices
A The cost functions of orders
B The decomposition of power flow
C The minimum uplift approach
D The price-time priority rule
E The example of market sweep order
Nomenclature
Bibliography
List of Figures
2.1 EU Electricity Directiv
2.2 Regions involved in ERI project. From the top left: Baltic, Central-Est, Central-South, Central West, Northern, South-West, France-UK-Irelan
2.3 Capacity allocation methodologie
2.4 Market Coupling: (a) the uncongestion case and (b) the congestion cas
2.5 Energy trading in 2014 in Europ
3.1 The European Union target mode
3.2 Congestion management with its different step
3.3 Derivation of Available Transfer Capaci
3.4 The ATC method: (a) the zonal market model and (b) the domain of Available Transfer
Capacity (ATC) mode
3.5 Flow-based method: (a) the zonal market model and (b) the domain of Flow-Based (FB)
mode
3.6 The members of Price Coupling of Regions projec
3.7 The scheme of XBID algorith
3.8 The operation of Imbalance Nettin
4.1 The aggregated hourly order: (a) the stepwise curve and (b) the piecewise cur
4.2 The cumulative curve of the piecewise ord
4.3 The cumulative curve of the stepwise ord
4.4 The clearing procedure: (a) the steand (b) the ste
4.5 Load Gradient Conditi
4.6 The structure of profile block orde
4.7 The link block orde
4.8 The exclusive block ord
4.9 The flexible block orde
4.10 The Geographical areas: (a) market clearing price and (b) Prezzo Unico Nazionale (PUN) pri
4.11 The European simplify networ
4.12 The map of HDVC Interconnectors in Euro
4.13 The line sets in Nord Pool: (a) the line set NO1 and (b) the line set DK
4.14 An example of the hybrid mode
4.15 Market clearing price and bidding Zones at 12 o’clock on 2 nd February 2017 in Ital
4.16 Characteristic curve of the market clearing price between Italy and France before cou-
4.17 Characteristic curve of the market clearing price between Italy and Austria before cou- pling in case of the non-congestio
4.18 The flow-chart of the proposed mode
4.19 The flow chart of PUN-
4.20 The flow chart of PRMIC-
4.21 The flow chart of PRB-
4.22 Western European system topolog
4.23 The electricity price in Europe of the Config1
4.24 The electricity price and net position in Europe from perioto perioof the Config1
4.25 The electricity price and net position in Europe from perioto period 12 of the Config1
4.26 The electricity price and net position from period 17 to period 24 in Europe of the Config1
4.27 The sensitivity analysis of the initialization of Paradoxically Accepted MIC order (PAMIC)s
4.28 The sensitivity analysis of the parametean
4.29 The European simplify topolog
4.30 The market clearing price of CW
4.31 The market clearing price of CW
4.32 The example of non-convexity of block ord
4.33 The example of non-convexity of MIC ord
4.34 The proposed European DAM mode
4.35 The proposed PUN sub-problem in Non-Uniform mode
4.36 The Western European topolog
4.37 The VWAP of official and proposed mode
4.38 The Mixed Complementarity Problem mod
4.39 The topology of GME: (a) the graphic on [1] and (b) the full topology of G
5.1 The continuous trading mechanism: (a) the intra-day price evolution during trading pe- riod and (b) the market event
5.2 The discrete auction mechanism: (a) the organization of section in GME and (b) the organization of section in OMI
5.3 The iceberg orde
5.4 The market sweep orde
5.5 The option A: (a) GME and (b) OMI
5.6 The option B: (a) GME and (b) OMI
5.7 Continuous Trading Matching mode
5.8 Proposed iterative proce
5.9 European Intra-day market topolog
5.10 This chart represent the price generated for the generic area at time h. Pmax and Pmin are obtained from market released information
5.11 Maximum price of IDM in Epex Spot: (a) the realistic result and (b) the simulated result
5.12 The import and export energy of GME and OMIE in one day: (a) Non-Congestion and (b) Congestio
5.13 The deviation of trading volume of GME and OMIE in one day: (a) Non-Congestion and (b) Congestio
5.14 The deviation of average electricity price of GME and OMIE in one day: (a) Non- Congestion and (b) Congestio
B.1 The simple example of decomposition power flo
2.1 Transmission System Operators in Euro
2.2 Power Exchanges in Euro
4.1 An example of hourly stepwise orde
4.2 An example of hourly stepwise orde
4.3 Hourly submitted bid
4.4 Complex submitted bi
4.5 Technical data of one power plan
4.6 The characteristic of European Power Exchange (PX)
4.7 The High Voltage Dicrect Current (HDVC)s in Europ
4.8 The comparison of market clearing price between Italy and its neighbourhoods before and after couplin
4.9 The average capacity of the interconnector between Italy and its neighbourhoods for one year after couplin
4.10 The percentage of congestion and convergence of electricity market price before and after couplin
4.11 The report of the price maker after coupling in case of non-congestio
4.12 Price maker after coupling for uncongested cas
4.13 The structure of the orders in case stud
4.14 Configurations and computation tim
4.15 The summarize of the Config1
4.16 PRB-SP results for Confi
4.17 Total Energy trading for Confi
4.18 The report of the absolute value of the relative variation of simulated and realistic elec- tricity market price in percentage in CWE and Europe on 9 th, March
4.19 The days and hours activated Horizontal Search in PUN-
4.20 An example of the non-convexity of block order in the European day-ahead marke
4.21 An example of the non-convexity of MIC order in the European day-ahead marke
4.22 The comparison of official and proposed mode
4.23 The report of four configuration
4.24 The evaluation of new PUN_S
4.25 The report of six testing da
4.26 The time computation of six testing days in secon
5.1 Intra-day sessions schedule in GM
5.3 The execution restrictions in European I
5.4 Characteristics of orders in the European Intra-day Mark
5.5 The example of Set T
5.6 The information released by each PXs in Europ
5.7 The number of orders in the case stud
5.8 The deviation of the simulated and the real result in percentage in Epex Sp
5.9 The trading volume of the SC1 in MW
5.10 The global criteria for three scenario
5.11 The trading volume of GME and OMIE for three scenarios in GW
5.12 The volume-weighted average price of GME and OMIE for three scenario
D.1 The example of the price-time priority ru
E.1 The example of the market sweep orde
Acronyms
Abbildung in dieser Leseprobe nicht enthalten
CHAPTER 1
Introduction
1.1 Motivation and Relevance
THe liberalization of Electricity started from Chile in the post-World War II period with the 1982 Electricity Act, and then reached Europe in the 90s, first in the United Kingdom and subsequently, it speared panoramically all over Europe [2]. Basically, the electricity markets in Europe follow a zonal design, thus it neglects intra-zonal congestion. Consequently, market prices are equal for all market players in the respective zone and only reflect the marginal cost of generators and marginal utility [3]. Furthermore, the national electricity markets in Europe are not isolated but connected through transmission lines and economic arrangements. The congestion on interconnectors is managed ipreventive way by determining the available transfer capacity as well as by allocating it to market players according to implicit and explicit auctions.
It should be noted that the evolutionary of European electricity market is highlighted by the Internal Energy Market (IEM) on the wholesale market level with the main idea which is to creatharmonized and competitive electricity market in Europe in 2030. The IEM in Europe which ilong-term goal of the European Commission is known through the three European Energy Packages in 1996, 2003 and 2009 [4–6], respectively. The main goal of these packages is to creatEuropean electricity market with non- discriminatory freedom of competition anmaximum of cross-border trade which ultimately result in efficient gains and higher security of supply. In particular, the European Council reinforced the political support and effective integration process, fixespecific date, and accelerated the implementation in the third package [6]. However, transforming formerly regulated and nationalized electricity systems icomplex mission and requires the various measures and their practical implementation. Therefore, the Heads of State and Government stated that "The internal market should be completed by 2014 so as to allow gas and electricity to flow freely" [7] in order to providstrong momentum for this target.
Obviously, creatinEuropean IEM requires both "software" and "hardware" solutions, rules to trade across borders, and financial model to increase the physical capacity of interconnectors. Therefore, the set up of European Union target model is equivalent to the completion of the IEM to define market design for this purpose, but the raising question of whethemarket design which was chosen would either improve or risk hindering the market efficiency. This requires the coordination of the Agency for European PXs and the European Network of Transmission System operator (ENTSO-E) 1. However, there are many challenges which have made the delay of the completion of IEM in 2014 and put the IEM is at the critical crossroad. First and foremost, there isignificant problem regarding to congestion management between European electricity markets, for instance, the different operational process across members and decline to adapt it tcommon rule. On the other hand, there isignificant obstacle on the way how Renewable Energy Sources (RES) are supported and promoted in several countries (e.g, France, Germany and The United Kingdom). Therefore, it is necessary to evaluate the current and future impact of coupling market in Europe to support the creation of IEM.
From the economic point of view, on 13 th of May in 2014, the South-West Europe and North-West Europe Day Ahead Market (DAM) were successfully coupled. Aresult, the coupling of European DAM stretches from Portugal to Finland and now operates undecommon DAM price calculation using the implicit auctions known as Price Coupling of Regions (PCR) project. Since that date, the allocation congestion management on the interconnector between Spain and France has been implicitly allocated, replacing the explicit allocation. According to [8], after the implementation of the PCR, the use of cross-border capacity has increased significantly. In period May 13 th -July 31 th, the capacity of interconnector was fully used 94% of the time. Another aspect used to evaluate the efficiency of interconnector between Spain and France is the average capacity not used wheprice difference exists. In 2012 and 2013, around 515 and 454 MW were not used. In 2014, before Spain becammember of PCR project, this situation remained at the same level (around 453 MW) until 13 th of May. After this implementation of the new scheme, the capacity not used, when there waprice difference, was zero. Moreover, the new scheme also improve the price convergence between two markets, 8.4% of the time from 13 th of May to 31 th of December in 2014. This report shows that the coupling of DAM between the South-West Europe and North-West Europe is benefit and gives the motivation for Italy to become the official member since 24 th February in 2015 leading tquestion is what about the impact of PCR project on Italy?
From mathematic point of view, the implementation of the coupling DAM in Europe based on dif- ferent market rules is very complex since all European PXs do not agree to adapt their specific rules tcommon rule. Therefore, Pan-European Hybrid Electricity Market Integration Algorithm (EUPHEMIA) [9] is an algorithm developed by Europe PXs to couple all different market rules and handle either stan- dard and more sophisticated order types with all their requirements. The aim of this algorithm is to provide rapidlfeasible solution which does not conflict with the acceptance rules and increase the overall Social Welfare (SW). However, the optimization methodology provided in EUPHEMIA is based on MIQCP methodology and the heuristic search procedure are limiting the efficiency of the coupling DAM since the time computation of this methodology is very expensive. In fact, the mitigation of the non-convexities introduced in the mathematical model by the market rules requirelarge computa- tion time, mainly due to the large number of independent variables, discrete and continues, which these algorithms have to digest. Therefore, the model has to stop before convergence tfeasible, free of non- convexities, solution due to the official runtime limit of 10 minutes [10]. Therefore, the EUPHEMIA is so far introduced with many versions from EUPHEMIA 6.0 to EUPHEMIA 9.3 [9] aims to provide an efficient algorithm, but it could not solve the problem completely. This issue leads to the losses of SW and the unfairness for market players, thus it is necessary to understand clearly how the EUPHEMIA works since then proposing new techniques to thoroughly solve this problem.
The Intra Day Market (IDM) is gaining importance in the last years with the strong rise in energy production from RES due to the 20-20-20 directive as the ambitious goals of the directive 2009/29/CE [6] to force each European nation has at least 20% of total consumption energy is RES. In fact, these are by nature characterized by an intermittent and unpredictable power output in the various hours of the day. This means that their scheduled production, which is bid in the DAM, harelevant margin of error. Hence, they need the possibility to balance their position according to the more precise information available closer to actual production. This possibility could be furnished by the IDM allowing the owners of renewables power plants to trade up to less the one hour before energy delivering. Actually, the IDM segment in Europe showlow level of liquidity, which reduces this "self-balancing" possibility for users and increases consequently the social costs related to network balancing managed by Transmission System Operator (TSO)s.
Thereforesimilar project has been set up for the coupling of IDM in Europe, called XBID project [11]. The XBID project is willing to boost this level of liquidity in order to guarantee for REbetter environment to develop. This started already in 2012 and is supposed to achievfirst phase of market coupling in 2017, even if the final integration solutions seems to be still quite far. In particular, the main issue that must be faced to reach an integrated European IDM is the subdivision of the PXs in two distinct sets: those who have organized their IDM segment usinContinuous Trading (CT) mechanism and those who instead developesystem of Discrete Auction (DA)s. These two solutions present different advantages and disadvantages which can be extremely summarized saying that the first solution brings to higher exchanged volumes and ttrade closer to the actual delivering while the second maximizes the SW fogiven set of orders. Although the European Commission decided to develop an algorithm used to run the single European IDM based on the CT mechanism, OMIE and GME refused to change their market design from DA to CT. Hence, the single European IDM model is more difficult to develop than the single European DAM model since it requires the flexibility to be able to simulate the results of the European IDM under different possible design decisions about the integration of DA and CT mechanisms which have been not decided yet.
Therefore, the research will be presented in this book is mainly aiming to fill the above issues and put attention on the future of the European Electricity Market (EEM).
1.2 Research Objective
The main aim of this research is to propose the advanced mathematic models for the coupling of either DAM and IDM considering all market rules in Europe, enhancing the efficient performance of the models and minimizing the computation time. Moreover, the proposed model can be used in the real world application, thus all the proposed models must be able to work withuge number of bids, bidding areas, and interconnectors. The evaluation of the impact of the proposed models on the European DAM and IDM need to be done with the test data that have the same size and close to the realistic data. This is very important since it is impossible to obtain the realistic data of all European PXs. Therefore, this research seeks to answer three questions:
1. How is the EUPHEMIA working since it is not available to public for any researchers? How to improve the efficiency of this algorithm? Is there any other approach which can solve the market faster and more efficient in comparison to the conventional methodology adopted in EUPHEMIA?
2. How to coordinate two IDM designs which are DA and CT?
3. How can obtain the realistic data from the available sources to test and evaluate the proposed models?
Eventually, the research in this book puthigh attention about the impact of the IEM on the Italian electricity market by running the proposed models using the real data in the official website of GME [1].
1.3 Main Contribution
The main contributions from this research are as follows:
1. Evaluated of the impact of the PCR project on the Italian DAM from three point of views: (i) the convergence of electricity price, (ii) congestion management, and (iii) the price maker in case of no congestion using the statistic data from 2014 to 2016;
2. The available information regarding the EUPHEMIA description [9] is of general nature. There ilack othorough mathematical description in the official documentation. Therefore, what the aim of this research mainly did was to interpret the available information and market rules icompact and unified mathematical framework using the same approach as EUPHEMIA regarding to the solution process (the use of iterative sub-problems to set-up the constraints of the optimiza- Actually, this work is very good for the research community since all the papers published before did not compare to the official model;
3. Proposenew European DAM clearing model based on the make whole payment and the "min- imum uplift approach" is proposed. This model arrives frocompletely different idea in com- parison to the EUPHEMIA and the current payment of the European DAM since it adopted the non-uniform price for the payment. This model is potential to apply in the real-life since it fulfills all the requirement of the European DAM;
4. Developed successfullmodel to clear the PUN price in GME based on the complementarity theory. This model is used to confirm the efficiency of the new proposed model using the "mini- mum uplift approach" since many scientific papers propose to clear the Italian electricity market using the complementarity theory;
5. Proposed an advanced European IDM model formulated as Mix Integer Linear Problem (MILP) based on the official document [12]. The proposed model is very flexible to cope with any changes of the European IDM in future since the final decision has not yet made. Furthermore, the research also focuses on the impact of the possible hybrid mechanisms on the relevant PXs;
6. Provided the test data which has the same size and reflect the real European market to overcome the issue that all the PXs do not public their real bids, except the Italian PX. This work provides an ability to test the robustness of model and evaluate the impact of the proposed model on the European DAM and IDM.
Eventually, the detail of each point above is presented more detail in the relevant subjects.
1.4 The Structure of Book
The rest of this book is structured as follows:
- Chapter 2 presents the literature review of the European electricity market. The chapter starts with the history of the liberalization of the electricity market in Europe. Then, the information of the relevant stakeholders which involve to the integration of the European electricity market and the coupling process in Europe is presented. Eventually, the benefits and obstacles of the market integration is discussed;
- Chapter 3 not only provides an overview of the target model and the relevant projects but also discusses the capacity allocation and congestion management methodologies in Europe which are ATC and FB models;
- Chapters 4 and 5 constitute the main body of this work, in which present the mathematic models for the coupling of DAM and IDM in Europe, respectively; and discuss the impact of the coupling market on European countries. Especially, the topology of Europe and the network constraints presented in Chapteare used in both DAM and IDM:
– Chapter 4 presents the work about the coupling of DAM in Europe. First of all, the impact of PCR project on the Italian electricity market is evaluated using the real data from 2014 to 2016. Furthermore, this chapter contains two independent DAM models which are the Uniform Price Model (UPM) and the Non Uniform Price Model (NUPM) model. Here, the UPM represents the ideas of EUPHEMIA model, meanwhile, the NUPM is the new clearing model based on the make whole payment mechanism. Moreoversmall model is devel- oped using the complementarity theory to solve the Italian electricity market is successfully implemented to compare with the other two models to confirm the efficiency of the NUPM;
– Chapter 5 presents the work about the coupling of IDM in Europe contains the overview of the European IDMs, the mathematic model for each trading session and the evaluation of the hybrid IDM model on the relevant PXs;
- Finally, the book concludes in Chapter 6 by presenting the main conclusion of this research and suggesting directions for further researches.
1.5 List of Publications
1. L. H. Lam, V. Ilea and C. Bovo, "Impact of the price coupling of regions project on the day-ahead electricity market in Italy," 2017 IEEE Manchester PowerTech, Manchester, 2017, pp. 1-6. doi: 10.1109/PTC.2017.7981215
2. L. H. Lam, V. Ilea and C. Bovo, "European day-ahead electricity market coupling: discussion, modeling, and case study" submitted to Electric Power Systems Research (Accepted).
3. L. H. Lam, V. Ilea and C. Bovo, "New Clearing Model to Mitigate the Non-Convexity in European Day-ahead Electricity Market" submitted to International Journal of Electrical Power and Energy Systems (Under Review).
4. L. H. Lam, V. Ilea and C. Bovo, "Mixed Intra-day Electricity Market in Europe" will be submitted soon.
CHAPTER 2
Literature Review
2.1 History of the Liberalization of Electricity Market in Europe
THe start of electricity markets history took place in one of the most unexpected countries in the world: Chile. Here, the government of Santiago promulgates in 1982 the so-called "Electricity Act" which can be considered as the first liberalization law ever written [2]. This legislative act was the ending point oprocess started four years before and, despite all the obstacles found in the application of the measure, it turns off intsuccess [13].
The "Electricity Act" has been the first trial of unbundling of generation, distribution and transmission stages iworld where the certainties about electricity were questioned. Up to 1980s, in fact, electricity was thought apublic service which had to be guaranteed to the community; therefore, production was entrusted to firms directly owned and controlled by governments. Indeed also distribution and transmission systems were controlled by the same vertically integrated firm which was thus able to monitor directly all the stages of the supply chain.
Under this structure, every stage wadivision of the vertically integrated firm and scheduled its task in order to maximize the profit of the whole firm. Thanks also to the Chilean example, the picture changed in the second part of the decade when the disadvantages of this system became evident. In particular, the idea of maximizing the profit overtically integrated firm was less efficient compared to the case in which all the different stages of the supply chain are optimized. Moreover, the monopoly situation decreased the efficiency in energy production since without competition there was nostrong boost to reduce the cost function of the firm.
In addition to these economic motivations, the idea of the national owned firm was in contrast with the concept of free trade which is the base on which European Union (EU) was founded and which had been reinforced by the Maastricht treaty in 1992 [14]. After four years of negotiation, the first phase of the community [4] which was the effort to brings in 1996 contains two directives (the 90/547/EEC and 90/377/EEC) that tried to regulate the energy transit between different countries and defined com- mon transparency rules for the price. These directives did not actually modify the European electricity scenarios where national vertically integrated companies still managed all upstream and downstream operations, limiting the exchanges with other foreign firms [15].
This showed homore structured legislation process would have to start, based ogradual intro- duction of competition together with an unbundling of pre-existent monopoly firms.
In this climate of strong debate, the United Kingdom anticipated the Union decisions with the adop- tion of its "Electricity act" in 1989, exploiting the experience just matured with deregulation for transport and telecommunications industries. Briefly, the main points of this act are [16]:
- Division of Central electricity generating board into two generators (National Power and Power- Gen) anNational Grid Company, which would have to manage the network services;
- Privatization of Regional Electricity Boards and Regional Electricity Companies which had the competence of distribution and supply;
- Definition ounique tariff rule for transmission rights;
- No regulation for generation phase of production which was considered available for competition.
The United Kingdom example was very important in the legislative process of EU which could learn from the strengths of Great Britain choices, as well as the weaknesses. For example, the competition guessed for generation phase seemed (at leas in the firs year) to be quite an optimistic assumption.
The liberalization process could not happen overnight, it has beelong and slow process with many ups and downs and successive regulatory steps. In the last two decades, Europe’s energy policy has consistently been geared towards achieving three primary objectives: energy in the EU should be (i) affordable (ii) competitively priced, and (iii) environmentally sustainablewell integrated IEM ifundamental pre-requisite to achieve these objectives icost-effective way. Therefore, IEM has become the central pillar of European energy and climate change policy since 2011. The deadline for completing IEM was fixed for 2014 by the Heads of State or Government [17]. The essence of this market can be defined through the concept of the "four freedoms": freedom of (i) movement of goods, (ii) capitals, (iii) services and (iv) people. From this prospective, the liberalization process can be seen as just the first step in order to achievfree energy trading between all the different European countries. As in the case of the United Kingdom before liberalization, also the integration process was anticipated by some virtuous examples. It is the case of Nord Pool which already in 1996 integrated successfully the pre-existent Swedish and Norwegian power exchanges. In the following years many other countries joined this two forerunners and now Nord Pool has integrated in an unique markets the PXs of all the Scandinavian areas, Germany, Netherlands and Belgium [18]. Other example of countries which decided to integrate their markets without any direct imposition from the EU are Netherlands, Belgium and United Kingdom which defined in 199trilateral price coupling, the base of the present APX Group. However, the process is not finished yet and there are still serious problems which will be addressed. All the previous step taken by the Commission in energy policy led to the adoption of three directives which are summarized in Figure 2.1 [19] and presented as follow:
First energy Package (Directive96/92/CE) This first directive [4] had the goal oslight and partial opening of the electricity market in each member state. In fact, in this phase, the market was opened only foset of "eligible costumers", usually chosen between the biggest energy consumers. The directive set alsyearly increasing threshold for the share of energy volumes traded witcompetitive market, witmaximum of 33% in 2003. The two aspects that the directive had to treat to make this new-born market operational were: the unbundling of pre-existent vertically integrated firm anclear rules definition for transmission and distribution system access.
The pre-existent undertakings were thus forced to providseparate balance sheet for each division, that means that generation, supply and distribution activities had to be entities fiscally independent. This first unbundling step was called administrative unbundling.
Unlike what happens for the generation, competition for transmission services was not possible. The first energy package required thus the creation of one TSO for each member country. For the biggest countries, actually, there are more TSOs created, but working on different territories within that same country. This operator was in charge of manage the network assuring the security of supply, providing information the market needs and balancing the grid according to non-discriminatory and transparency criteria.
Abbildung in dieser Leseprobe nicht enthalten
Figure 2.1: EU Electricity Directives
The directive set also the basis on which the network should have been regulated. The cornerstone of this regulation was the Third Party Access (TPA). Due to the peculiarity of the electricity market, it was in fact extremely important to define the access to network service for all the users, according to transparency and not discriminatory rules. Strong differences in tariff regimes were found by the EU report and thus the union decided for the strongest regulation which took effect with the second energy package.
Finally, to monitor the correct working of the market and the behavior of the TSOnational authority had to be designed by each member country.
Second energy Package (Directive 2003/54/CE) The second energy package [5] was the logical con tinuation of the process started with the Directive 96/92/CE. It has the goal of completely open the electricity market to all users and fix the problems which arose with the implementation of national leg islation applying the dictates of the first energy package. In particular, all "non-Domestic" users were defined eligible from July, 2004 and the same for all domestic users from July, 2007. This means that the member states had time just up 2007 to create an operating market open to all the users.
As mentioned in the previous section, the TPA regulation was partially reviewed in the second energy package. In fact, at first countries were free to pick between three different regulating models but the results were not satisfactorymore strict regulation for TPA was thus established, in particular by the imposing the "regulating TPA" system. This model was based on the definition ocertain number of single defined and published tariffs, which would apply to all the users. In addition, the approval of the process which defines this tariff had to be communicated by TSO to national authorities which had to deliberate about it.
About unbundling process, the further step required by the 2003/54/CE [5] was the legal unbundling, that is that TSOs had to be completely independent of any supply firm operating in the energy sector.
Another hint that came from the experience of first energy package [4] was the sometimes difficult coexistence between regulators and authorities, with an ambiguity on the division of their roles. In order to solve this problem and to speed up the process of liberalization, the second energy package required fospecific authority tailored on the electricity market features. Previously, in the fact that many countries had chosen to use the pre-existent competition authorities for this intent.
Third energy Package (Directive 2009fi2/EC) Two years after the release of the second energy pack ages, the EU energy market did not flourish as expected [20]. Thus, EU started an inquiry findinlist of shortcomings to be solved witproper additional legislation. In particular, the problem arose with:
- Not sufficient level of unbundling between firm active on transmission and supply stages;
- Market concentration;
- Scarcity of liquidity;
- Not sufficient collaboration between markets of different member countries.
The last of the three packages [6] was thus edited by EU commission in 2009 and it had been planned and written to face these shortcomings. The first important obstacle to the competition seemed still to be the relation between TSOs and other firm operating in the energy sector. Despite the administrative and legal unbundling coming from the other two packages the TSO companies could be in fact still owned bfirm which had also the ownership of other companies operating in production or distribution phases.
To solve this situation three possibilities were offered by Directive 2009/72/EC [6]:
- Ownership unbundling between TSOs and firms having any interest in electricity sector;
- Independent System Operator (ISO): the TSO could be part overtically integrated firm buthird party entity would be in charge for the operations regarding the network management. This independent entity was chosen by the state itself under the approval of the Commission;
- Independent Transmission Operator (ITO): as for ISO the TSO can be part ogroup where with interest in supply or distribution but it must bregulated company with strong limitations in their long and short term decisions.
To solve the issues linked to the behavior of the market players the NRA powers were strengthened, including the possibility to take financial actions against misbehavior companies.
The problem of the minimal cooperation resulted instead inot so clear definition of the rules for cross-border capacities calculation and trade of transmission rights. These led to extremely low cross- border exchanges and thereforlow pressure from costumers to fix the problem. To solve this vicious cycle the EU decided not to act directly witregulatory act but to create the ACER. This agency had no decisional authority but it played an essential advisory function for the definition of common framework guidelines for cross-border energy exchanges.
This three packages defined the general structure anminimum level of harmonization between member countries market but leave to each statcertain degree of freedom. This choice was made to speed up the establishment ocompetitive market for electricity but it also ends up with 15 separate markets with different design choices, instead ounique market. Just after the complete transition to this new system, the process of markets integration could actually start, chasing the real objective of the EU: creatinsingle European market for electricity.
2.2 Relevant stakeholders of European Electricity Market
2.2.1 Regulators
The regulators set the legal framework in which other stakeholders operate. Furthermore, many market coupling initiatives have their origin in changing of regulatory frameworks. The most important ones are the following institutions:
- The Council of European Energy Regulator (CEER) [21]: established in 2000 for the coop- eration of the independent energy regulators of Europe iBelgian not-for-profit association. It seeks to facilitate the creation osingle, competitive, efficient and sustainable EU internal energy market;
- The Agency for the Cooperation of Energy Regulators (ACER) [22]: is an Agency of the EU followed by the Third Energy Package [6] in 2009. It was established in 2010 and has its seat in Ljubljana, Slovenia. The main purpose of the organization is to ensure that the single European market and the harmonization of regulatory frameworks are done in respect of the EU’s energy policy objectives. These goals armore competitive, integrated market, an efficient energy infrastructure anmonitored and transparent energy market guaranteeing fair and cost-reflective prices;
- The International Confederation of Energy Regulators (ICER) [23]: ivoluntary framework for cooperation between energy regulators from around the globe. The aim of this organization is to improve public and policy-maker awareness and understanding of energy regulation and its role in addressinwide spectrum of socio-economic, environmental and market issues. They are focusing on four main areas: (i) reality and security of supply, (ii) responding to climate change, (iii) competitiveness and affordability and (iv) the independence, powers, responsibility of regulators;
- National Regulators: beside those regulators which are responsible at the European level, there are national regulators for each country which are not further characterized.
2.2.2 Producers
The supply chain of electricity starts with its production. The methods of the electricity production heavily depend ocountry’s geographical shape as well as on the political framework and the political support of certain energy resources. Generally, generation sources can be distinguished as follow [24]:
- Fossil fuels: coal, oil, gas;
- Nuclear power;
- Hydro power: run-of-river, pumped storage plants, reservoir;
- Renewable energies: wind, photovoltaic, solar thermal;
- Others: geothermal or tidal power plants.
2.2.3 Transmission System Operators
The TSOs are operating the transmission system for electricity in the respective markets. As such, their role is essential for the management of cross-border congestion. In Europe, ENTSO-E [25] is the agency representing 43 TSOs of 36 different countries in Table 2.1 and is committed to maintain security of supply by ensuring the optimal functioning of European network. The non-discriminatory third party access requires that TSOs are operating independently from other electricity market players.
Table 2.1: T r ansmission System Operators in Europe
Abbildung in dieser Leseprobe nicht enthalten
2.2.4 Power Exchanges
A Power Exchange (PX) is the market place for electricity and plays an important role for the devel- opment towardEuropean internal energy market as they provide liquidity, reduce transaction costs and increase price transparency. Additionally, PXs provide key risk mitigation tools which market partici- pants can use to hedge their exposure. In fact, each nation has its own PX, but following the integration of electricity market, some of them designed to joint together to reduce barriers in power trading, e.g EPEX SPOT and APX grouThe Amsterdam Power Exchange (APX) contains Netherlands, United Kingdom and Belgiuin 2015. This mechanism brings fours benefits [26] for the members as follow:
- One harmonized trading, single rulebook, and admission process for the entire region;
- Centralized clearing to reduce trading costs and lowering entry barriers;
- A wider range of products and benefit from best-of-both standards and reliable customer;
- More effective governance and further facilitate the creation osingle European power.
In Europe, there were seven PXs. After 31 th March 2016, Epex Spot clears the market for Germany, Netherlands and Belgium. This activity established for the integration of APX and Epex Spot [27]. Therefore, at this moment, there are six main PXs presented in Table 2.2 contains all European countries.
In 2001, European PXs agreed to create the single body which is responsible for aligning with the European Commission, the EU Parliament and main stakeholders to the challenge coming from the integration of electricity market in Europe [33]. In 2002, the Europex [33]not-for-profit association of
Table 2.2: P ower Exchanges in Europe
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European Power Exchanges was established by seven PXs (27 members) in Assembly. This cooperation of all European PXs is one of the main factors in the development of the IEM. The activities of Europex include:
- Promoting the role of energy exchanges to increase competition by creating price transparency and implementing the European single electricity and gas market;
- Supporting the liberalization of the different European electricity and gas systems;
- Dealing with the issue of international trading, with special emphasis on providinmarket solu- tion to the congestion problems;
- Maintainindialog with the EU institutions and with other European electricity, gas and envi- ronmental markets related entities;
- Increasing co-operation between European energy exchanges and promoting free trade;
- Collecting information, preparing reports and providing advice in matters related to the aforemen- tioned objectives;
- Assessing the need for recommendations regarding market information dissemination and market rules especially related to market power abuse.
2.2.5 Auction Offices for Cross Border Capacity
In the past, the cross-border capacity was taken into account by many different specified auction offices. Some important offices are listed below [24]:
- European Market Coupling Company: It was an organization which promoted an efficient elec- tricity market between Central Western European, the Nordic and the Estonian region by using the market coupling was established in Hamburg, Germany in August 2008.
- Capacity Allocation Service Company (CASC.EU): It was the auction office for cross-border transmission capacity for Central Western Europe and for the borders of Italy, Northern Switzer- land and parts of Scandinavia. It providsingle auction platform for purchasing and selling transmission capacity.
- The Central Allocation Office (CAO): It was the auction office for cross-border transmission capacity Central East Europe region and since the beginning of 2013 for the borders of Croatia.
On 24 June 2015 the General Assemblies of CAO and CASC.EU, the two regional allocation offices for cross-border electricity transmission capacities, approved the merger agreement to create the Joint Allocation Office (JAO) [34] which contains twenty companies from seventeen countries. This imajor milestone for facilitation of the internal electricity market in the EU.
2.3 Market Coupling Process
2.3.1 Regional Electricity Markets
The same EU started the works for its ambitious coupling project when it launched the Electricity Regional Initiative [35] in 2006. It can be seen as the beginning of the single electricity market in Europe by creatinnumber of regional markets in Fig. 2.2 as interim steps from national markets towardpan-European market. This arrangement is expected to be strongly harmonized iphysical, institutional and political way.
Abbildung in dieser Leseprobe nicht enthalten
Figure 2.2: Regions involved in ERI project. From the top left: Baltic, Central-Est, Central-South, Central West, Northern, South-West, France-UK-Ireland
As displayed in Figure 2.2, this initiative splits the European territory and network into seven areas which would perform the role of an intermediary first step before the final continental integration. Seven regional electricity markets in Europe are:
1. Baltic: Estonia, Latvia, Lithuania;
2. Central-East: Austria, Czech Republic, Germany, Hungary, Poland, Slovakia, Slovenia;
3. Central-South: Austria, France, Germany, Greece, Italy, Slovenia;
4. Central-West: Belgium, France, Germany, Luxembourg, Netherlands;
5. Northern: Denmark, Finland, Germany, Norway, Poland, Sweden;
6. South-West: France, Portugal, Spain;
7. France, UK and Ireland (FUI): The Irish electricity market is seen as Single Electricity Market (SEM) as it includes the Republic of Ireland and Northern Ireland.
These seven regions brought together the relevant stakeholders such as regulators, companies, and the EU beside together to develop and implement solutions for an improvement in how regional mar- kets progress. The main purpose of these regional markets is to integrate formally fragmented national markets intbroader regional market context.
This first phase (from 1996 to 2009) was greatly useful since it allowed to firstly sharconsiderable amount of data between different TSOs and secondly defined for each zonproper path to make it ready for integration with other regions. The literature in this period is divided between those articles which try to predict the effect of imminent price coupling and those who analyse the evidence coming from coupled markets already in operation. For example Hobbs and Rijkers in [36] tried to understand what would happen in terms of competition and price with the integration between Dutch and Belgian markets. The results showed how the social surplus would significantly enhance the welfare by increas- ing the efficiency in the cross borders capacity. At the same time they put the attention on the danger onon-perfectly competitive market by showing hostrong market power exercised by the ex-national monopoly could affect the benefits of the coupling and even harm Dutch consumers througslight increase in electricity price. These results could somehow represent the general situation in this period when all around Europe more cooperation between PXs was requested, either to draw common and clear rules for cross border capacity computation either to take strong actions to limit market concentration. Schavemaker and Beune in [37] show how collaboration for PXs was essential to improve the cross bor- der capacity calculation. Without this joint efforts it was in fact impossible to implement more complex and advanced solution likflow_based model (see Section 3.2.2) for capacity computation. To the same results arrived also the Commission itself with its inquiry in 2005 and tried to remedy already with the same 2009/72/EC. With this directive indeed were founded ACER and ENTSO-E, the agency for cooperation of respectively the national regulators and the TSOs.
2.3.2 Market Coupling Timeline
The coupling electricity market icomplex process that requires time consuming to bring EU tsingle IEM. In Europe, the fist step of Market Coupling (MC) took place in Scandinavian countries in 1993. Meanwhile, until 1999, APX was the first PX which coupled their DAM in the mainland Europe. In 2006, the implicit MC of the Netherlands, Belgium and France which was an important step towards the integration of the North West European electricity markets is known as Trilateral Market Coupling (TLC). Following this step, in each regional electricity markets, additional coupling projects were implemented as below [24, 38]:
- Baltic: Estonia was coupled with Nordic markets through Estlink in 2014 ;
- Central-East: Markets of Hungary, Slovakia and the Czech Republic were coupled in 2013;
- Central-South: Italy and Slovenia are coupled in 2011;
- Central-West: Countries were coupled over Central Western Europe (CWE) oNovember
2010. In parallel, CWE coupled with the Nordic region over the ITVC initiative since November 2010;
- Northern: Countries were coupled with each other in 1996, over ITVC with the CWE region in 2010, over the NorNed cable with the Netherlands in 2008 and over the SwePol-cable between Sweden and Poland in 2000;
- South-West: Countries were coupled since 1 st July, 2007;
- FUI: The IFA interconnector coupled the UK with France, the East West interconnector connects UK with Ireland in 2012, while the BritNed cable linked the UK over Netherland with the CWE region in 2011.
The most important step of the coupling market took place on 4 th of February 2014, when North- Western Europe (NWE) successfully coupled their DAM. This is the first step of the foundation for multi-regional coupling. The fully integrated electricity market is expected in 2020. This will bring a better flow of electricity across borders, guaranteeing the security of supply and making cheap electricity prices across Europe for end users [38].
2.3.3 Congestion Management Allocation Methods
Congestion management has become an issue in the process of liberalizing the EEM. However, the method to take into account the available transmission capacity is not straightforward because the power flow does not go directly from the generator to consumer but it spreads out over all parallel paths in the network, according to the Kirchhoff’s laws. Hence, the fundamental of physical and commercial flow is completely different. The electricity flow resulting frotrade opower exchange is ruled by physical laws like Kirchhoff’s law and Ohm’s law. It means that electric power takes several parallel "ways" from its sink to its destination and is named physical power flow. Contrary, commercial power flow not only shows us exactly the direction from seller and buyer but also prevent the transactions lead to power flow totally different from what could have been intuitively expecting [39]. Imeshed grid, the commercial exchange will lead to the transfers that follodifferent path than the direct geographic path between the sink and the source. Hence, the physical congestion is different with commercial congestion as well. The physical congestion is the network situation occurring in the real time when the system security is at risk such as violate the thermal limit of the elements of the grid and voltage stability or the angle stability of the power system. The commercial congestion occurs when the available capacity made by TSO focertain time is not sufficient to cover all the market trade requests and trades [40]. As the consequence, the commercial congestion between two bidding zone can not be fully allocated sincpart of capacity can be used by parallel flow resulting from the trade between or within other market zones. This issue refers to the cross-border capacity allocation.
There are two market methods for allocating interconnection capacity in Europe which are displayed in Fig.2.3. These methods are "market-based" congestion management methods, in which the Net Trans- fer Capacity (NTC) is allocated in cross-border power auctions inon-discriminatory" [41].
Abbildung in dieser Leseprobe nicht enthalten
Figure 2.3: Capacity allocation methodologies
The first method based osmall degree of coordination among TSOs is the explicit auction mech- anism. Here, the cross-border transaction is divided into two parts: (1) cross-border electricity contract (submitted bids), (2) the capacity on the interconnector (Financial Transmission Right). The intercon- nector capacity is sold to the highest bidder and the payment can be based on the pay-as-bid or marginal bid. Ipay-as-bid auction, the capacity is allocated to each player according to their bid price, starting from the highest bid. Meanwhile, imarginal bid auction, the price to pay for the interconnector ca- pacity is the same for all bidders and equal to the level of the marginal bid [24]. Before 24 th of February 2015, the congestion management on the Italian interconnections with France, Austria, Switzerland, and Greece was solved through explicit auction. The interconnection capacity access rules for the intercon- nections between Italy and its neighborhoods were defined by TERNA (Italian TSO) with RTE (France TSO), APG (Austria TSO), Swissgrid (Switzerland TSO), ELES (Slovenia TSO) and HTSO (Greece TSO) [42]. Here, TERNA would check the eligibility of the applicant within three working days from receipt of the application. Then, it would seVirtual Production/Consumption Unit (UPV/UCV) in the Italian market zone, and the margin of the above UPV/UCV. The margin of UPV/UCV would be set equal to the capacity of Physical Transmission Right (PTR). Finally, TERNA shall provide GME witlist of UPV/UCV and the relatives margins.
The second market-based method is known as the implicit auction mechanism and can be imple- mented by two methods ("Market Splitting" and "Market Coupling"). The main difference between two methods is that "Market Splitting" describemethod used imarket operated bsingle power ex- change, while "Market Coupling" is the implementation of implicit auctions imarket operated by co-operation of multiple power exchanges. In "Market Coupling", there are two coupling methodologies mainly differ in the way that they calculate the price, called "Volume Coupling" and "Price Coupling". The price is done centrally, and the coupling is called price coupling, otherwise it is called volume cou- pling. Unlike the explicit auctioning, there is no separate capacity market, it thus is less complex for the market participants. In order to avoid congestionso-called market operator surchargecertain fee on the bids that use the interconnector. An example is given in Fig. 2.4, in which Markeis exporting energy to Markewith two cases can happen (i) uncongested case 2.4a and (ii) congested case 2.4b. When there is noncongestion between two markets, the electricity price of two markets (P ∗ and P ∗) are A B the same. In Fig. 2.4b, the electricity price of Markeis lower than the electricity price of Market B because the available capacity betweeanis not sufficient. The difference of prices between two markets is paid by costumer in Markecalled congestion fee.
Abbildung in dieser Leseprobe nicht enthalten
Figure 2.4: Market Coupling:
(a) the uncongestion case and (b) the congestion case
In the implicit auction, the available capacity is allocated simultaneously with the physical energy in the domestic markets. The market coupling idecentralized mechanism jointly managed by operators who sharcommon matching algorithm. Since January 1 st, 2011 the electricity DAM of Italy (GME) and Slovenia (BSP) allocate the cross-border transmission capacity by implicit auction mechanism, this is scheduled in five steps:
1) The market participants send their bids to two power exchange (GME and BSP);
2) The two Transmission System Operators (Terna and Eles) share the available transmission capacity for each hour of the next day;
3) The two markets communicate their information about the anonymous offers involving the use of the available transmission capacity;
4) The bids and quantities are taken into account by each power exchange;
5) If the capacity constraints are respected only one common price is formed, otherwise, the two markets are split into two areas with different prices, the importing area having the highest.
2.3.4 Cross-border Trade Energy in 2014
This section presents the consumption and production of energy for each country in Europe in 2014. Moreover, the cross-border energy is shown as well. This period is selected to present because, at that moment, the level of coupling market in Europe was still low. The statistic data is collected from [43]. The result is shown for entire Europe in Figure 2.5, respectively. The investigated result can providgeneral overview about energy exchanging in Europe.
From Figure 2.5, it can be seen by the observation that the biggest net exporte1 is France with 77 TWh and followed by Germany with 74,5 TWh in 2014. In the Eastern Europe, the main exporter is Czech Republic with 28 TWh. Meanwhile, the biggest importe2 is Italy with 37.8 TWh. It should be noted that Switzerland is not only the third exporter with 23.5 TWh but also has very large importing energy about 33.6 TWh. It is supported that Switzerland is playing an important role as the "transit nation" in the heart of the EEM. There are some highlights for each region presented below:
1. Baltic: The most important exchanges are from Estonia to Latvia with 3,8 TWh and from Lithua- nia to Latvia with 244 GWh. Here, the Baltic countries are linked with Finland by the DC in- terconnector (Estlink) which carries 3,5 TWh from Finland to Estonia. In general, the market of Baltic countries is still small in comparison to other markets in EEM.
2. Central-East: The biggest market is Germany with 562 TWh for production and 518 TWh for consumption in 2014. Here, Germany, Czech Republic and Slovenia are the net exporters, while the rest of countries are the net importers.
3. Central-South: Germany is also the biggest market followed by France which has 540 TWh for producer and 465 TWh for consumption in 2014. The biggest net importer, not only in this region but also in Europe, is Italy. In fact, Switzerland is not in this region but it is playing an important role as an essential transfer country.
4. Central-West: Beside the two biggest markets which are France and Germany, Netherlands is the third biggest market with 96 TWh for production and 111 TWh for consumption. All the Benelux countries are net importers.
5. Northern: Germany is the biggest market followed by Sweden with 151 TWh for production and 134.8 TWh for consumption. Finland is the largest net importer in this region occupying the second position in Europe after Italy. The most important exchange energy are from Sweden to Finland with 18 TWh, from Norway to Sweden with 11 TWh.
6. South-West: France is the largest market with 540 TWh for production and 465 TWh for con- sumption. Spain is ranked second and followed by Portugal. France and Spain are the net ex- porters, while Portugal is beinnet importer.
7. FUI: The largest market is France, UK ranked second with 41.6 TWh for production and 31.4 TWh for consumption. In this region, the only one exporting country is France. The most important exchange energy are from France and Netherlands to UK.
Abbildung in dieser Leseprobe nicht enthalten
Figure 2.5: Energy trading in 2014 in Europe
2.4 Market Integration: Benefits and Obstacles
2.4.1 The Benefits of Market Integration
The market integration between neighboring PXs has been obviously conceived in order to obtaimajor efficiency in terms of social surplus. This gain comes in the first place frobetter use of generation capacity, reducing the costs for obtaining the maximum volume needed to guarantee the security of supply [44]. To simplify this concepsimilitude with what happens for industrial facilities can be used. For instance, supposed to have two different factories, each of them using an electricity generator to feed its energy needs. The two generators must be dimensioned on the peak consumption of each of the two factories which are not necessary to come at the same time. This means that to substitute the two previous generators witsingle unit, the maximum capacity of this new one would be lower than the sum of the two initial units.
Similarly, if the peak demand of two neighboring countries is not at the same hour the capacity needed to answer to demand will be lower. Hence the related result will bdecrease of the clearing price since the plant to be switched off are obviously the ones on the right of the supply curve and thereupon those with higher marginal cost. It is interesting to point out how the explosion of renewables energies strongly influences the shape of the supply curve and thus increase this beneficial effect of market integration. Italy can be an example, in which the abrupt increase of solar energy has greatly distorted of the supply curve that now shows completely diverse shape depending on the hour of the day. In concrete terms, this means that during day time the electricity price is generally low while when the sun starts to set over the price strongly increases. This effect could be dumped by integration since, hypothetically speaking, the country from northern Europe, where the share of wind energy is very high, could sell low price electricity to Italian consumers during night-time. Of course, the more countries decide to coupled their market the more benefits they can obtain from these peaks divergence.
Another positive effect of market integration is the decrease of market concentration, with thereforlower possibility for biggest companies to exercise market power and thus getting closer tperfectly competitive market. The ACER in its annual report published the results oseries of simulation that showed how market shares of biggest firms in CWE (in 2012) [45] had decreased with respect to the values shown before the coupling. This led also to an increment in gains of trade of 250 Me with respect to the isolated PXs case.
Finally, the most trivial of the benefits is the maximization of transmission capacity efficiency. In fact, when two markets are separated the cross-border capacity is traded separately from the electricity trading, often withouclear and homogeneous regulation. This inevitably reduces the inefficiency by decreasing the maximum volume exchangeable between the two areas. The flows in the interconnectors are in fact not based on price signals coming from the isolated markets but assigned through bilateral agreements between producers and costumers in the two areas. Indeed the main point to understand the best design for the integrated market is to find the best way to compute cross zonal capacities.
2.4.2 The Obstacles of Market Integration
The process of EEM integration has been all but simple and it has to faclist of issues which origin is diversified. The first problem that has to be solved is the different rules each PXs had been free to choose to carry out the dictates of the three energy package. These differences between various markets had forced the integration process to give up the simplest solutions like the market splitting method. In any case, the coordinated efforts between TSOs and PXs of the member countries can bsolution to overcome this issue.
A more relevant problem seems to be the different regulation for users that PXs try to keep after the market coupling. Two strong evidence can be brought to support this point: the danger of anti- competitive behavior of the ex-vertically integrated firms and the incentives for RES [46]. In [36], ifirm can exercise market power the benefits of market coupling are declined and for the market where that firm was not presented before integrating the situation can get even worse. It is important therefore that homogeneous actions against anti-competitive behavior are defined for all the member states in order not to creatdangerous regulatory disparity between them.
The incentives question is extremely wide and equally debated. Each of the member states had to define an incentives plan in order to meet the carbon dioxide reduction targets. They were thus free to deliberate following the way they considered most convenient, as long as they reach the famous 20-20-20 objective before 20203 [47]. This means that in the market coupling some users can benefit from much greater incentives with respect to the others and this obviously createmarket distortion.
A strong collaboration between TSOs and national authorities is needed to solve this problem, espe- cially for the IDM and the Balancing Market (BM) that are markets segments where RES are supposed to solve their unbalancing problem. The best solution would be to draw an integrated European plan for incentives. This waproper agency cold havbetter view of the big picture and act accordingly. It could not just adopt an uniform regulation but also take initiatives to promote different RES according to the territory features. Hypothetically speaking, for example, it can think of the enormous gains from trade that could be obtained by concentrating effort for wind energy in North Europe and Solar Energy in the South Europe, with adequate investments in the transmission capacity.
CHAPTER 3
European Target Model and Relevant Projects
3.1 Introduction
AS discussed, in the market coupling, players do not need to receive the allocation of cross-border but just submit their bids on the PXs. Then, the PXs minimize the price difference between two or more areas by using the available cross-border transmission capacity. It thus maximizes the SW, avoids any splitting of the markets, and send the most relevant price signal for investment in cross-border transmission capacities.
Unlike the financial market, the design of electricity market is very complex include many levels such as forward market, spot market and balancing market:
- The forward market which forwards with different maturities are traded aims to hedge the short- term price risks and uncertainties. In Europe, the highest growth in 2015 was recored in the French forward market [48];
- The spot market can be divided into DAM and IDM. The DAM which is the most prominent among spot market is hosting contracts for the delivery of electricity of the next day. Meanwhile, the IDM which imarket for energy sale/buy during the delivery day is used to adjust the schedule dispatch from the DAM before the real-time market.
- The balancing market includes all decision and operations from "gate-closure" to the real-time operation. The TSOs are responsible for managing this service to ensure the security and stability of the system.
In the coupled markets, the available transfer capacity has to be traded according to the representative electricity contracts. To reach clarity on this issue, the European Commission in cooperation with rele- vant stakeholders has developetarget model for market integration which is known as the EU target model for Market Integration focus on four main features [49]: (i) Capacity Calculation, (ii) Capacity Allocation and Congestion Management, (iii) Balancing and (iv) Governance. The aim of this model is to proposmarket design for forward market, spot market and balancing market towarsingle electricity market in Europe. The Target Model was developed by the European Commission, Regula- tory associations such as ACER, National Regulators, TSOs and other relevant stakeholders. In order to achieve this target, there are several relevant projects which are responsible for the coupling of each market design has been published and summarized in Fig. 3.1.
Abbildung in dieser Leseprobe nicht enthalten
Figure 3.1: The European Union target model
3.2 Capacity Allocation and Congestion Management
The Capacity Allocation and Congestion Management (CACM) developed by ENTSO-E represents an important step in the Target Model for the design of the EEM. It has been developed through an open and transparent process involving stakeholders at every stage and therefore reflectbroad range of views. The CACM Guideline is developed based on four main factors [50]:
1. The day-ahead market: all players can submit bids or offer to buy or sale energy for the following day. The allocation management based on the implicit auction.
2. The intra-day market: allow market players manage the risks and respond to adjust their schedule delivery of the day-ahead market by trading closer to real time.
3. The capacity calculation: making the most efficient use of the interconnectos through implement
ing the "flow-based" model.
4. Market players can buy or offer energy in the DAM, IDM and forward market without having to require the transmission capacity to conclude their trade, respecting the transparent and promote the competition.
Generally speaking, in Europe, PXs incorporate to calculating cross-zonal capacity in the electricity markets through two permissible approaches [51]: (i) ATC and (ii) FB models. The difference between ATC and FB are shown in Fig. 3.2 [52]. The origin and computation for the optimal power flow of interconnections in these models are completely different, in spite of coming from the same concept (security of supply considering N-1 criterion constraints). These models create the prominent distinction between commercial flow and physical flow. To sum up, the important in congestion management is the difference between commercial and physical flows: electricity will not flow according to the Kirchhoff's laws but follow commercial path.
3.2.1 The ATC model
Currently, most of market model in Europe is based on the ATC approach. The ATC model considers that there is an interconnector between two zones when these zones sharborder crossed by at least one physical link. In fact, in order to calculate the ATC of interconnectors, TSOs estimate the parallel flows that occur in the market result based on the heuristic rules and D-2 estimations of the market
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Figure 3.2: Congestion management with its different steps
outcome [39]. This iweak approximation of the steady state of AC power flow equations. The ATC of an interconnector represents the remaining power allowed to transit through it given the foreseen equilibrium point of the system aresult of long-term nominations and taken into accounsecurity margin for the actual operation of the system. Mathematically, the ATC model ilinear network flow with the limitation is the maximum and minimum available capacity of the interconnector. The ATC is derived from the NTC, which is defined by the Total Transfer Capacity (TTC) in Fig. 3.3 [53].
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Figure 3.3: Derivation of Available Transfer Capacity
An example is given in Fig. 3.4 includes three zones in Fig. 3.4a. The ATC domain of this system is rectangular (see Fig. 3.4b), characterized by the ATC value. From Fig. 3.4b, the ATC of an interconnec- tor is independent with the others. Therefore, the mathematic formulas of the ATC model of this system as follows:
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3.2.2 The Flow-based model
The Flow-based model was developed in both CWE and Central Eastern Europe (CEE). Although they developed the model on their both own way, the idea is similar. Nevertheless the development standstill in CEE, it has been activated in Europe at the 21 th May, 2015 [54]. According to the relevant
Abbildung in dieser Leseprobe nicht enthalten
Figure 3.4: The ATC method:
(a) the zonal market model and (b) the domain of ATC model
report performed in CWE, the FB model has higher usage interconnector capacity as compared to the ATC model [55], because the security boundaries of the transmission system are more accurate than the ATC model.
From the mathematical point of view, the FB constraint iset of linear constraints on the net ex ports of the network element that is available for further PXs. Each constraint reflects the impact of the relative position of the zones ocritical element of the system (a transmission linetransformer, etc.), and is obtained througdetailed analysis of the system using an accurate representation of the physics of the network. To make the link between the position ozone and the flows inside itnet export is mapped to nodes of the network through some pre-established generation shift keys (GSKs) [56]. The most important parameters for TSOs that have been discussed on Flow-based Market Coupling imple mentation in CWE region are the selection of critical branches (CB), the flow reliability margin(FRM), generation shift key (GSK), and remedial action [52]. In general, the GSKs includes only power plants that are flexible in changing the output power such as coal-fired plants, gas-fired plants, oil-fired plants, pumped storage units, and conventional hydro units [39]. But in order to run the market the PXs only need two parameters which are Power Transfer Distribution Factor (PTDF) and Remaining Available Margin (RAM). In the DAM, flow requirements of the already nominated exchanges must be evaluated by PTDF which must be calculated for each critical branch (cb) in the base case and in the combination with each of its critical outages (co). Additionally, the commercial flow througcritical line is limited by the RAM. An example of FB model given by [39] and shown in Fig. 3.5 contains nine buses in three zones. Here, only one bus per zone is considered, but all critical branches are take into account. According to the observation, the domain of the FB is larger than the ATC (see Fig. 3.4b and Fig. 3.5b) because the physical characteristic of the grid is better presented in the FB. Therefore, the mathematic formulas of the ATC model of this system as follows:
- The net position:
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- The Flow-Based model:
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Nevertheless, the application of FB model has contained an issue in the clearing of commercial congestion, namely non-intuitive exchanges [55], in which the power flow goes from high price zone to low price zone. Despite the fact that it leads to the maximum SW, this result may be unacceptable for market designers and participants, because they perceive as the unfairness for aggressive behavior [57].
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Figure 3.5: Flow-based method:
(a) the zonal market model and (b) the domain of FB model
Thus, the participant who perceives the electricity market as any other commodity market has an overlook on physical properties of the system that induce non-intuitive exchanges.
Obviously, this activation of the new methodology for congestion allocation in CWE has brought the inspired to many researchers in recent years. There are several publications which focus on the FB model. In [52, 54], the overview of the methodology including model and important parameters was introduced. The impact of wind power on commercial and physical flows within the CWE region was published in [58], aiming to providbetter understanding of this methodologydeep analysis of this methodology which contains conventional model, innovated model about flow-based methodology and deals with 'non-intuitive' problem was presented by Vlachos, A. G. and P. N. Biskas in [57].
Despite these advantages, the complexity and the scarce experience of the FB model make the ATC still the most common way to compute cross-border capacity. Actually, the FB model is only used in CWE and only to compute day-ahead capacities, while for the intraday segment the ATC model is used everywhere. The same Commission and ACER in the CACM suggesFB model be preferred but still allow the member regulators to chose differently [40].
3.3 Projects of Market Coupling in Europe
Generally, the European Target Model includes both the explicit allocation of transmission capacities in the form of annual and monthly transmission rights for the forward market as well as the implicit allocation in the spot market and balancing market.
3.3.1 Harmonization of Long Term Allocation Rules Project
ENTSO-E is responsible for the securing capacity of several years ahead to the day ahead, the intra day and the balancing market. The harmonization of cross-border markets in all time frames will lead tmore efficient European market and benefits to customers. Therefore, the forward market is playing an important role in securing capacity and hedging positions ahead of the day-ahead time frame. On 1 s t Oc tober 2013, the Network Code on Forward Capacity Allocation (NC FCA) was delivered by ENTSO-E and sent to the ACER. Two months later, the ACER published an opinion which presentnumber of issues on which adjustments were required [59]. There arnumber of projects which is designed as the beginning by TSOs will contribute to finish the IEM sooner. One of them is the Harmonization of long term Allocation Rules (HAR) expected to be delivered before 1 s tJ anuary, 2016 [60].
Long-term transmission right is the rights to transfer energy oveduration of one week to one year. In fact, the most common rights are monthly and armual transmission rights. The future transmission rights auction is proposed to be done with the explicit auction, in which uses two principles, so called the Financial Transmission Right (FTR) and the Physical Transmission Rights (PTR) [61]. The FTR which is the pure financial right or the "real" transmission rights and havUse-It-Or-Sell-It (UIOSI) has the consequence of having to payout the resale value of the transmission rights which have not been used by registerinschedule. Meanwhile, the FTR which is only entitled to the nomination of cross-border schedules is always followed by the payout of the resale value and does not contain the right to registeschedule.
In both methodologies, the resale value is derived from the day-ahead allocation capacity. In the case of the explicit auction, the payout equals the auction price of the respective hour, meanwhile, in the case of the implicit auction, the disbursements according to the difference of hourly prices between two bidding zones as long as it is greater than zero [62].
To sum up, the owner of the rights will pay the auction price for the respective period of one year or one month, receive the payout from TSOs for the difference of hourly price at the day-ahead market between two bidding zones as long as it is positive.
3.3.2 Price Coupling of Regions Project
As discussed, the European Union’s proposed Internal Energy Market, first of all, European countries are going to be to fully couple their DAM, because the wholesale market is holding the largest amount of energy trading in each country.
In the fact that EPEX Spot halong-standing experience in DAM coupling projects, the market harmonization was achieved on 9 th November 2010, with the launch of market coupling in CWBelgium, Netherlands, France, and Germany). There wagood progress in implementing the target model ovoluntary basis in North-Western Europe and as bilateral projects osemi-voluntary base in the Iberian Countries (Spain and Portugal), in Italy and Slovenia as well as in the Czech Republic and Slovakia [63]. The most importance step is 4 th February 2014, when Price Coupling in North-Western Europe was activated. It can be seen as the initiative of PCR project, in which the calculation of price and power flow of European DAM based on the implicit auction, and then it speared to CWE, United Kingdom and Scandinavian countries. Since the launch of NWE, two extensions of the PCR have taken place: in May 2014, Spain and Portugal joined and on 21 th February 2015, Italy joined the project being coupled with France, Austria, and Slovenia.
The members of PCR are presented in Fig. 3.6, in which contains seven PXs such as APX, Belpex, EPEX Spot, GME, Nord Pool Spot, OMIE, and OTE [9]. The majors benefit of the Market Coupling ap- proach resides in improving the market liquidity combined with the beneficial side effect of less volatile electricity prices. Market players are no longer need to acquire transmission capacity rights to carry out cross-border exchanges since these cross-border exchanges are given as the result of the market coupling mechanism, it thus is more beneficial. They only have to submisingle order in their market (via their relevant PXs) which will be matched with other competitive orders in the same market or other markets (provided the electricity network constraints are respected).
In order to operate European Coupling DAM, on the top of European PXs, the market coupling systems collects all supply and demand bids from these PXs and network constraint from TSOs and take into account maximizing welfare, optimal power flow between adjacent market areas and electricity price for each bidding zone of these PXs as well. Finally, the PXs run their own auction incorporat- ing the cross-border flows and incorporating the cross-border flows and the price signals. For example, the SESAM system [64] coupled the biding areas of Nordic region that consist of Denmark, Estonia, Finland, Lithuania, Norway, and Sweden, it was in used since 2007; the most important examples is COSMOS algorithm [65] was implemented in Central West of Europe (France, Germany, Luxembourg and Netherlands) in 2011 and had been the topic of researchers in the recent past. The mathematical pro- gram of COSMOS [65] contains two sets of conditions: network and market constraints. The purpose of network constraints are to enforce the physical feasibility of product delivery, therefore it containsimplified network model with transmission line, transmission capacities, and corresponding allocation mechanism. In PCR, it is focusing on the development of single price coupling algorithm, which will be used to take into account energy allocation and electricity price across Europe, maximizing social welfare. To this aim, it is based on three main principles: (1) one single algorithm, (2) decentralized
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Figure 3.6: The members of Price Coupling of Regions project
operation, and (3) decentralized governance [9]. In order to solve the problem associated with the cou- pling of the day-ahead power markets in PCR, an algorithm which can be viewed ahybrid of different Power exchange companies is called EUPHEMIA [9]. The EUPHEMIA can be viewed as the modified and extended version of COSMOS with transplanted concepts from other exiting European PX designs. Obviously, the hybrid of the algorithm could be risky if one looks at the coherence of its specified market rules, but also put stress on the implementation. However, this initiative is severely burdened by exist- ing local differences with many specified rules which were implemented already and the uncoordinated national decisions.
3.3.3 Cross-Border Intra-Day Market Project
The Cross-Border Intraday Market Project (the abbreviations is X-BID market project) is represen- tative for the European IDM [62], based on the continuous trading mechanism and implicit auction [11]. As discussed, the single European market would imply an important benefit in terms of social welfare allowinmore efficient use of generation resources across Europe. Moreover, it will increase the competition level and above all liquidity. This is particular useful fosegment like IDM which still shows low levels of exchanged volume preventing users to completely exploit the possibility of close- to-delivery tradingmore liquid IDM would also allow the users to balance their position by itself, reducing this way the amount of reserve needed and thus the social costs carried to balance the network. In order to operate the single IDM in Europeproposal developed by all TSOs and PXs is presented in [12]. In order to ensure that the proposal continues to promote effective competition, provide for non- discriminatory access to cross-zonal capacity, operational security, promote fair and non-discriminatory treatment; PXs shall consult market players at least every two years. This does not only benefit from the national IDM liquidity, but also from the liquidity in other areas. Particularly, Switzerland ipart of this project while it does not participate in the European Coupling DAM.
In the European single IDM, market participants submit the orders for continuous matching in one country can be matched by orders submitted in any other countries as long as the transmission capacity is available. It can be done based on the key-point ocommon IT system able to match bids coming from different countries according to the available transfer capacity of the network. Fig. 3.7 shows the general structure of the algorithm, which is based on three main element: Share Order Book (SOB), the capacity allocation management module and the shipping module. This structure has of course afundamental preconditionstrong cooperation among the different PXs and among national TSOs. The first of all, the members of the single IDM must share their local order book in an unique the SOB which contains all the bids submitted in the various PXs trading platforms. The TSOs must collaborate to create the capacity management module which will contains all the parameters needed to define the European network, defining for each cross border connector the available transfer capacity in both direction. Bids in the SOB are matched icontinuous way and the results are sent to the shipping module which is in charge of providing information from trades concluded to all relevant parties at the configured moments.
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Figure 3.7: The scheme of XBID algorithm
The operation of single IDM is based on the continuous trading market design, thus the single IDM algorithm is called the Continuous Trading Matching Algorithm (CTMA). The CTMA developed for each Trading Session (TS) contains three major steps: (i) maximize economic surplus, (ii) Update SOB, and (iii) Re-calculate available capacity. In order to ensure the fair and orderly price formation for all products, the price-time-priority is also adopted and the requirement of CTMA is presented detailed in [66]. The price-time-priority means that if the submitted price of orders is the same, the priority is given for the earliest submission order to select first. This trading system is supposed to work every day, 24/24 hours per day and support all the orders types that are available today for Continuous Trading market in the member PXs.
3.3.4 Cross Border Electricity Balancing Pilot Projects
The electricity balancing market is very important because it ensures the security of supply and pres- ence on the cost of costumers. In fact, the BM represents only 2-3% of the total volume of the wholesale market, but in the recent reports of European Commission, the efficiency of the sharing balancing re- sources between countries can gain the security of supply and reducing balancing cost. Therefore, this istrong motivation to develocross-border balancing market. Moreovercross-border balancing market can mitigate the effect of the RES, it thus allow the efficient integration of RES into the grid.
It is not the same with these other markets since it contains many different kinds of balancing services such as Imbalance Netting, Automatic Frequency Restoration Reserves, Manual Frequency Restoration Reserves and Replacement Reserves. In 2012, ENTSO-E publishesurvey to show the complex of this market and emphasize the challenge for harmonization. Further more, ENTSO-E has proposed several pilot projects [67] to evaluate the feasible of the European Target Project, test the associated implement impact and report on the experience gained. In fact, there are nine projects which are presented in [67] and summarized in [68]. The first pilot project which can be seen as the first step toward the single balancing market is Imbalance Netting pilot project. This project which involved four German TSOs aims to avoid the counter activation of automatic Frequency Restoration Reserves (aFRR) since 2010.
Since April 2014, the Imbalance Netting which focuses on the International Grid Control Coopera- tion (IGCC) pilot project contains six TSOs such as the four German TSOs and Energinet, TenneT NL, Swissgrid, C˘ EPS, Elia and APG [69]. RTE becampart of this project since May 2014. The objective of this project is to decrease the use of balancing energy cost and increase the system security. This cooperation is seen as the reference to put the other TSOs into practice.
Basically, in Europe, the cooperation of TSOs is based on an aFRR-Optimization System for the activation of aFRR in their respective areas. The principle of Imbalance Netting is published in [70], in which it avoids the simultaneous activation of aFRR in the opposite direction as Fig. 3.8, this thus optimizes the use of aFRR.
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Figure 3.8: The operation of Imbalance Netting
An example given in [70] to show the potential benefit which gains from the Netting Imbalance project. Here, it shows clearly that without this pilot project, the IGCC members need to activate more energy of aFRR with higher price to balance the system.
At the same time, the TSOs of Austria, Belgium, Germany and Netherlands have studied on the inte- gration of Frequency Restoration Reserves market [71] which focus on the consistency of the complete market model and identifies the major issues of the harmonization of the European balancing market.
3.4 Conclusion
The evolution of IEM requires the large change and deep impact in the current electricity market. In order to achieve the single electricity market in 2030, the European Commission introduces the European Target Model which presents the requirements of each market such as day ahead market, intra-day market and balancing market. In fact, there are several projects which are responsible for implementing the single market for each market as presented above. The most challenges are the coherence of different market rules in each PXs, the transparent and fair market solution. Consequently, it puts stress on the implementation of the mathematic model in which require the minimal time computation and the fairness for players, thus the issues will be investigated and solved in the next sections. Obviously, with the synchronous of the coordination of all stakeholders, TSOs and PXs, the single Europeau market cau achieve in the near future.
CHAPTER 4
The Coupling of Day-ahead Electricity Market
4.1 Introduction
IN Europe, the spot market is operated by the PXs, while the TSOs provides network boundary condi- tions, in which the system feasibility and security is guaranteed. Some PXs have split their market into several bidding zones based on national borders or network bottlenecks. For instance, the EPEX Spot has three bidding areas (France, Germany/Austria, and Switzerland) [30], while the GME (Italy) has more than 20 bidding areas [1].
The idea osingle energy market in Europe has been proposed in the IEM [17] project for the last two decades, to achieve three primary objectives: (i) affordable energy, (ii) competitive prices and (iii) environmental sustainability. In the first step of IEM, the PCR has entirely coupled the DAMs of GME, EPEXSpot (only France, Germany and Austria in PCR), APX (UK and Netherlands), Belpex (Belgium), Nord Pool Spot (Scandinavian countries), OMIE (Spain and Portugal), and OTE (Czech Republic). The main PCR benefits [72] are (i) improving the market liquidity; (ii) guaranteeing the overall welfare, and (iii) implicit allocation management.
The PCR focuses on the development osingle price coupling algorithm based on the SESAM [64] and COSMOS [65], to calculate energy distribution, electricity price across Europe. The algorithm is named the EUPHEMIA [9], and its goals are to cover all specified conditions of every particular PX simultaneously and give solution withireasonable time frame. Obviously, the combination of PXs could be risky if one looks at the coherence of its market rules. In details, one of the major problems is the non-convexity of electricity price due to "fill-or-kill" condition of block orders, Minimum Income Condition (MIC) in Spain or Portugal, and PUN (National Uniform Price) price in Italy [73]. Moreover, the collaboration of the allocation methodologies (ATC and FB models in Section 3.2), the false rejected block orders, and the decreasing of the fairness for market players because of the short computing time also put stress on the implementation of EUPHEMIA.
Eventually, European PXs are using the Market Clearing Price (MCP) (another name is uniform price), in which all energy traded at the same location at the same period receives at the same price. This mechanism ensures that there is no missing money, in which the total payment of demand and supply is balanced.
4.2 Structure of Day-Ahead Electricity Market in Europe
4.2.1 Type of Orders
In Europe, there are two ways to submit offers and bidsunit (GME and OMIE) or portfolio (Nord Pool Spot, Epex Spot, APX Group, Belpex and OTE). In portfolio bidding, each participant (producer, demand) has the ability to submit one hourly portfolio offer/bid curve, internalizing all technical and cost elements of its production facilities or demand forward contracts or trading contracts. And then, the DAM is responsible for clearing based upon all submitted portfolio offer/bid curves. Moreover, in hourly single or portfolio offer/bids, most of PXs allow participants to submit complex bids that are totally different between each PX, in which introduce inter-temporal constraints and some of the unit technical constraints and multi-period cost structures. Papers [10, 68] show the main characteristics of the European DAM, while [9] presents the structure and acceptance rule of all type of orders, including aggregated hourly, complex, block, and PUN orders. According to [10], the daily number of block orders doubled from 2011 to 2015, from 1500 to 3100 blocks, respectively. The hourly PUN steps have increased 81% since 2011. The complex order seems to be stable with 78 producers.
1. Aggregated Hourly Orders
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Figure 4.1: The aggregated hourly order: (a) the stepwise curve and (b) the piecewise curve
Demand or Supply orders from all market participants belonging to the biding area a will be aggregated intsingle curve as aggregated curve defined for each period t. The aggregated supply and demand curves can be of the following three types:
(a) Linear piecewise curves (Fig. 4.1b): Participants will senbid, which includes volume and two different consecutive points of the price, except for the first bid defined at the max- imum/minimum prices of the bidding area. Nord pool spot and Epex spot use this kind of order.
For supplier:
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For demand:
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[...]
1 the ENTSO-E was established through the Third Legislative Energy Package [7] for the IEM
1 The net exporting energy of each country is the total exported energy with the neighboring countries.
2 The net importing energy of each country is the total imported energy with the neighboring countries.
3 20% reduction of C O 2 emissions, 20% of energy production from RES, increase of 20% of energy efficiency
- Citation du texte
- Le Hong Lam (Auteur), 2017, The Integration of the European Electricity Market, Munich, GRIN Verlag, https://www.grin.com/document/495127
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