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Power markets have been gradually integrated to achieve the target of a single European market. A major step was the introduction of the flow-based market coupling (FBMC) in Central Western and Eastern Europe (Core region). FBMC reflects the physical constraints of the underlying transmission grid in detail. However, the European Commission and regulators imposed minimum margins to increase cross-border trade and to foster price convergence between the different bidding zones, neglecting physical constraints and increasing redispatch volumes. Integrating redispatch poten-tials into FBMC allows for moving closer to physical reality while maintaining a high level of cross-border trade. In this study, we develop a multi-stage model covering capacity calculation, market coupling, and redispatch stages. This study is the first to evaluate different options for integrating FBMC and redispatch potentials based on a large-scale numerical analysis of Central Europe. The results reveal that minimum margins effectively increase cross-border trade. However, this comes at a high cost due to additional redispatch needs, which reduce overall welfare. Integrating redis-patch potentials in the market-clearing stage leads to a more efficient increase in cross-border ca-pacities and elevates welfare. In the case of combining both approaches, the analysis indicates improved welfare of roughly 80 M€ per year.

The European electricity market is immersed in an integration process that requires a fundamental transformation. In this process, Flow-Based Market Coupling, which was employed for the first time in the Central Western Europe electricity market in 2015 as a means to manage cross-border capacity allocation, is a crucial cornerstone. The novelty of this paper lies in the analysis of the price convergence or congestion across the Central Western Europe region since the Flow-Based Market Coupling was implemented. We propose using random forests to build learning models that are trained and tested with features from connected markets of this region during 2016 and 2017. These machine learning models are used for mining knowledge about our target variable, price equalization. To search for robust predictive patterns that decision-makers can use to understand congestion situations, we have tested different combinations of learning schemes, several estimators and different model parameters. The results of all implemented models are robust and reveal that promoting renewable energy can contradict the integration of the electricity market if the grid network and, in particular, the transmission lines are not adapted to the new paradigm.

Nowadays, the payment scheme of European Day-Ahead Market is based on the market clearing price by running the Pan-European Hybrid Electricity Market Integration Algorithm. However, this conventional payment scheme is challenging because of the non-convexity and the short computation time requirement. Thus, the aim of this work is to propose a new clearing model in order to mitigate this challenge. The model is based on make-whole payment mechanism and it includes two major steps: (i) maximizing social welfare and (ii) achieving a Walrasian equilibrium by the “minimum-uplift approach”. The proposed model is validated and investigated by two case studies: one is an artificially created Day-Ahead Market session containing all type of bids encountered in Europe and containing a very large number of bids to stress the algorithm and the other is a reduced, but realistic, model of European market where real data from February to December of 2017 were considered. The tests show a consistent improvement of the numerical performances of the proposed model with respect to the conventional one while the economic performance is not altered, but is slightly improved. Moreover, because the tests are based on real data during a long period of time, the results show that proposed model is very promising for the real application.

The European Union has set out to reduce the carbon intensity of its electricity generation substantially, as defined in the European Roadmap 2050. This paper analyses the impact of foresight towards decarbonization targets on the investment decisions in the European electricity sector using a specific model developed by the authors called dynELMOD. Incorporating the climate targets makes the investment into any additional fossil capacity uneconomic from 2025 onwards, resulting in a coal and natural gas phase-out in the 2040s. Limited foresight thus results in stranded investments of fossil capacities in the 2020s. Using a CO2 budgetary approach, on the other hand, leads to an even sharper emission reduction in the early periods before 2030, reducing overall costs. We also find that renewables carry the major burden of decarbonization; nuclear power (3rd or 4th generation) is unable to compete with other fuels and will, therefore, be phased out over time.

The definition of the bidding zones is an essential aspect to develop an electricity market on large power systems, by trading off between situations with uniform price and nodal prices. In this paper, the results of the application of a set of clustering algorithms (k-means, k-medoids, hierarchical clustering, and price differential clustering) to the formation of the bidding zones are presented. The classical versions of the methods used require post-processing to identify connected bidding zones. The customised versions of the methods incorporate topology constraints in the clustering procedures. The input data are given by locational marginal prices (LMPs), power transfer distribution factors (PTDFs), and network topology information. The clustering algorithms have been applied to the study of a reduced model of the European transmission system, for different numbers of clusters. The results have been assessed by using two synthetic indicators that represent clustering validity and the possible occurrence of market power in the bidding zones formed. Finally, a conjecture has been expressed: methods that use LMPs tend to be more effective according with classical clustering validity-based indicators, while methods that use PTDFs tend to be more effective according with market power-based indicators.

The process of building the European electricity market was initiated in the 1980s. Recently, however, significant acceleration of this process can be observed, resulting in many legal regulations determining the current and future market design. The paper discusses legal regulations shaping the energy market in Europe, both the existing ones and those still being drafted, as well as their impact on the domestic electricity market.

"Market Coupling'' is currently seen as the most advanced market design in the restructuring of the European electricity market. Market coupling, by construction, introduces what is generally referred to as an incomplete market: it leaves several constraints out of the market and hence avoids pricing them. This may or may not have important consequences in practice depending on the case on hand. Quasi-VariationalInequality problems and the associated Generalized Nash Equilibrium can be used for representing incomplete markets. Recent papers propose methods for finding a set of solutions of Quasi-Variational Inequality problems. We apply one of these methods to a subproblem of market coupling namely the coordination of counter-trading. This problem is an illustration of a more general question encountered for instance in hierarchical planning in production management. We first discuss the economic interpretation of the Quasi-Variational Inequality problem. We then apply the algorithmic approach to a set of stylized case studies in order to illustrate the impact of different organizations of counter-trading. The paper emphazises the structuring of the problem. A companion paper considers the full problem of market coupling and counter-trading and presents a more extensive numerical analysis.

This paper examines the evolution of the Irish Single Electricity Market in order to comply with the European Target Model for electricity. In particular, this work focuses on the challenges raised by the high concentration in the generation sector of the Irish electricity market. We examine the theoretical and empirical conditions under which forward markets promote competition in the spot and retail markets. We also investigate the impact of market concentration on the new capacity payment mechanism. In order to ensure a competitive outcome for consumers, the regulatory authorities should promote competition in the forward market; moreover, the regulator should extend regulation to the price and quantity that the dominant firm bids for holding new reliability options.

This paper compares the impact of the Nodal Pricing and European Market Coupling organizations on different economic agents of the power system under two main wind policies. Under the "priority dispatch" policy, Transmission System Operators (TSOs) must accommodate all wind energy produced, which thus has the priority over energy produced by conventional plants; in the "no priority dispatch" policy, TSOs can decide not to inject all potential wind power in the grid in order to limit congestion problems. The effects of these two wind policies are measured by developing simple stochastic programming models that consider cases with different wind penetration levels, existing capacities and endogenous investments, as well as assumptions on the EU-ETS. Our computational experiments show that, when there is "priority dispatch", Nodal Pricing and Market Coupling evolve in a similar way as long as wind penetration is not too high. In contrast, a significant increase of wind penetration causes the collapse of the Market Coupling organization while Nodal Pricing continues to perform well. On the other hand, "no priority dispatch" removes most of the problems resulting from Market Coupling, which still exhibits a slightly lower efficiency than Nodal Pricing. These outcomes do not depend on the contextual assumptions (fixed capacities vs. investment; EU-ETS vs. non EU-ETS) that characterize the several cases analyzed. This suggested that our policy conclusions are robust. Furthermore, our models overestimate the flexibility of conventional plants, which means that these conclusions would likely be reinforced with a more detailed model.

12 pages; The aim of the article is to understand how the drivers for investment decisions in the capacities of electricity production have evolved over time, from 1945 to the present day, in the specific context of Europe facing wars and conflicts, scientific and technological progress, strong political and academic developments. We study the electric investment decisions by comparing the history of the European electricity markets with the successively dominant economic theories in this field. Therefore, we highlight differences between rational behaviors, such as described by the theories, and actual behaviors of investors and governments. Thus the liberalization of electricity markets in the European Union, more than twenty-five years ago, parts of a rationalization prescribed by new economic theories. It is clear that liberalization is being discussed. First, it remains very heterogeneous, which complicates the goal of creating a large single market for electricity in the Union. Second, we see a recent re-centralization of energy policy in the European Union (EU), which takes the form of a new regulation mainly relating to climate and renewables. However, this re-regulation is different from centralized control experienced by all European electricity markets until the mid-1980s.

The main focus of this thesis is to find out what factors have the biggest influence on the price of electricity for household consumers in the European Union in the context of creating the internal electricity market in the EU. By means of the cluster analysis six EU Member States have been selected according to the following criteria: electricity consumption, electricity production, and the price of electricity. As a result of that Belgium, the Czech Republic, Estonia, Hungary, Malta and Sweden have been selected. Consequently, the regression analysis has been carried out to find out what factors influence the electricity prices in every country individually. The independent variables are mainly various sources of electricity production. It was found out those renewable resources most influent the electricity price for households in Belgium, Estonia, Hungary, and Sweden. Nevertheless, in the context of Europe 2020 strategy and the formation of the European energy market, one of the European Commission's objectives is to increase the share of renewable sources in the production of electricity in the EU Member States. Therefore, it will bring about higher prices of electricity, which goes against the Commission's effort to decrease the price of electricity for households through the liberalisation of electricity and the creation of the internal electricity market.

Cross-border trade remains a contentious issue in the restructuring of the European electricity market. Difficulties stem from the lack of a common market design, the separation between energy and transmission markets and the insufficient coordination between Transmission System Operators (TSOs). This paper analyzes the cross-border trade problem through a set of models that represent different degrees of coordination both between the energy and transmission markets and among national TSOs. We first present the optimal organisation, not implemented in Europe, where energy and transmission are integrated according to the nodal price paradigm and Power Exchanges (PXs) and TSOs are integrated. This is our reference case. We then move to a more realistic representation of the European electricity market based on the so-called market-coupling design where energy and transmission are operated separately by PXs and TSOs. When considering different degrees of coordination of the national TSOs’ activities, we unexpectedly find that some arrangements are more efficient than the lack of coordination might suggest. Specifically we find that even without a formal coordination of the TSOs’ counter-trading operations, non discriminatory access to common counter-trading resources for all TSOs may lead to a partial implicit coordination of these TSOs. In other words, an internal market of counter-trading resources partially substitutes the lack of integration of the TSOs. While a full access to counter-trading resources is a weaker requirement than the horizontal integration of the TSO, it is still quite demanding. We show that quantitative limitations to the access of these resources decrease the efficiency of counter-trading. The paper supposes price taking agents and hence leaves aside the incentive to game the system induced by zonal systems.

An efficient and non-discriminatory capacity allocation and congestion management is a core task of transmission system operators in any restructured electricity sector. For historic reasons, the allocation of transmission capacity in the European electricity sector of today usually takes place at political borders between countries. While being a pragmatic approach, such an allocation does not reflect very well the structure of the highly meshed European electricity network and its bottlenecks. Driven by the rising cross-border electricity trading and the large-scale integration of volatile renewable energy sources such as wind power, this incoherence between institutions and technology is increasingly limiting the performance and sustainability of the European electricity system as well as endangering the achievement of an integrated European electricity market by 2015, as foreseen by the European target model. A similar challenge has been faced by the European air transport sector in its quest to develop a Single European Sky out of national airspaces. In order to improve its capacity allocation performance, the European air transport sector developed – among other measures – the concept of Functional Airspace Blocks that manage air traffic flows according to functional instead of political borders. Together with Eurocontrol’s Central Flow Management Unit, this approach is expected to significantly reduce delays and emissions by making better use of airspace capacity. In analogy to the air transport sector, the idea of Functional Airspace Blocks is applied to capacity allocation in the European electricity sector by developing a network- and performance- based algorithm to configure functional congestion management zones. The algorithm is based on the identification of critical network elements and a network sensitivity analysis, in order to cluster nodes with the most similar impact on critical network elements into a preferred number of zones, thereby optimizing the utilization of the transmission capacity and minimizing the expected redispatch cost. Hence the algorithm proposed by this thesis fulfils two of the key requirements posed by the ACER framework guideline on congestion management and capacity allocation (CACM) published in 2011. The algorithm is tested on several real snapshots of the European electricity system (peak and off-peak; before and after the 2011 shut-down of eight German nuclear power plants; and on a 2020 network model, including all planned generation and network extensions). The results of the zonal configuration are visualized graphically, reflecting the real structure of the European electricity network. The results of the thesis show that a majority of critical network elements are located not at political borders, but rather inside national transmission systems. In consequence, a functional configuration of congestion management zones usually does not follow political boundaries and it may change substantially within hours, depending on the generation and flow patterns. Regarding the number of congestion management zones, the thesis shows that 5 to 10 functional zones could achieve about the same congestion management performance (in terms of transmission capacity utilization and expected redispatch costs) as today’s 27 political zones. 20 functional zones may improve the congestion management performance by 8 to 12% and 40 functional zones by 11 to 23% compared with today’s political configuration, saving between 400 and 800 million Euro in expected redispatch cost per year. To further improve the congestion management performance and better reflect the increasingly dynamic generation and flow pattern due to variable renewable energy sources, the thesis recommends considering the implementation of a nodal electricity market design at the European scale. Apart from the optimization of congestion management, the sensitivity-based clustering algorithm developed in this thesis could also be a valuable tool for visualizing the network structure and critical network elements as a transparent basis for network investment decisions. Finally, the thesis also analyses the use of transmission rights in the European electricity market. It concludes that the current European approach based on yearly and monthly physical transmission rights may be insufficient to cope with the expected, massive amount of short-term volatility caused by wind and solar power, since they fragment the European electricity market, withdraw much-needed capacity from the day-ahead and intraday-day time-frame relevant for renewable energies, and prevent an optimized capacity allocation at the European level. Beyond the implementation of the day-ahead market coupling, the thesis recommends moving even further by allocating and optimizing all of the physical transmission capacity in efficient intraday and real-time (balancing) markets at the European scale. For managing the forward price risk, it is recommended to issue financial transmission rights (i.e., congestion revenue rights) in monthly and yearly timeframes. Some of the key requirements for the introduction of financial transmission rights are investigated in this study. This development may question the organizational separation of power exchanges and network operators (TSOs) in the long run, and it will require an entity responsible for capacity management at the European level.

“Market Coupling” is currently seen as the most advanced market design in the restructuring of the European electricity market. Market Coupling, by construction, introduces what is generally referred to as an incomplete market: it leaves several constraints out of the market and hence avoids pricing them. This may or may not have important consequences in practice depending on the case on hand. Quasi-Variational Inequality problems and the associated Generalized Nash Equilibrium can be used for representing incomplete markets. Recent papers propose methods for finding a set of solutions of Quasi-Variational Inequality problems. We apply one of these methods to a subproblem of market coupling namely the coordination of counter-trading. This problem is an illustration of a more general question encountered, for instance, in hierarchical planning in production management. We first discuss the economic interpretation of the Quasi-Variational Inequality problem. We then apply the algorithmic approach to a set of stylized case studies in order to illustrate the impact of different organizations of counter-trading. The paper emphasizes the structuring of the problem. A companion paper considers the full problem of Market Coupling and counter-trading and presents a more extensive numerical analysis.

Like in the US, the EU “internal electricity market” remains unfinished and its construction can stall, fracturing into “national blocks” separated by permanent “border effects”. This is exactly what this paper seeks to avoid in the expected life of the current European Commission (2005-2009). It identifies the critical factors: national and EU market designs, industry structure and competition policy, deeper regional cooperation between TSOs and Regulators. It suggests 8 priority actions and 12 secondary improvements to sustain the dynamics of the construction of an EU set of open r egional markets with limited “border effects”, and explains the rationale for these recommendations.

Članak se bavi ulogom obnovljivih izvora energije u opskrbi električnom energijom. Izvorni razlog za njihovo uvođenje i razvoj bio je stvaranje protuteže porastu stvaranja stakleničkih plinova koji nastaju pri proizvodnji električne energije iz fosilnih goriva. Europska unija predstavlja najbolji primjer delegirane politike i propisa koje zakonodavci i vlade prikladno tumače. Zakoni na području energije i okoliša usvojeni u Republici Hrvatskoj približili su se europskom zakonodavstvu, s ciljem integriranja Republike Hrvatske u untarnje europsko tržište električne energije i Europsku uniju., This article deals with the role of renewable sources in the electricity supply industry. The original reason for their introduction and development was to help offset the rise in the production of greenhouse gases due to electricity genaration from fossil fuels. The EU represents the best example of federally delegated policy and regulation interpreted differently by national regulators and goverments. The laws in the area of energy and the environment enacted by the Republic of Croatia have been approximated to the European legislation in order for the Republic of Croatia to be integrated in the internal market and EU.

The horizontal integration of the energy market and the organization of transmission services remain two open issues in the restructured European electricity sector. The coupling of the French, Belgian and Dutch electricity markets (the trilateral market) in November 2006 was a real success that the inclusion of Germany to the trilateral market should soon prolong. But the extension of market coupling whether in Central Western Europe or in other European regions encounters several difficulties and the future remains far from clear. The highly meshed grid of continental Europe complicates things and it is now sometimes recognized that the penetration of wind will further exacerbate these difficulties. The nodal system could go a long way towards solving these problems, but its implementation is not yet foreseen in the EU. This paper analyzes versions of market coupling that differ by the organization of counter- trading. While underplayed in current discussions, counter-trading will become a key element of market coupling as its geographic coverage expands and wind penetration develops. We consider a stylized six node example found in the literature and simulate market coupling for different assumptions of zonal decomposition and coordination of TSOs. We show that these assumptions matter: market coupling can be quite vulnerable to the particular situation on hand; counter-trading can work well or completely fail depending on the case and it is not clear beforehand what will prevail. Our analysis relies on standard economic notions such as social welfare, Nash and Generalized Nash equilibrium. But the use of these notions is probably novel. We also simplify matters by assuming away strategic behaviour. The nodal organization is the reference first best scenario: different zonal decompositions and degrees of coordinations are then studied with respect to this first best solution.