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Economic Effects of the Liberalization of the European Electricity Market – Simulation Results of a Game Theoretic Modelling Concept

Claudia KEMFERT, a Diana BARBUa and Vitaly KALASHNIKOVa January 2003 a

Research Group S.P.E.E.D., Scientific Pool of Environmental Economic Disciplines University of Oldenburg, Faculty of Computing Science, Business Administration, Economics and Law, D- 26111 Oldenburg (E-mail: [email protected], [email protected], [email protected]), Tel.:+49 (0)441 798 4106/4099/4349 Fax:+49 (0)441 798 4101

Abstract Electricity market liberalization aims to boost competition at the level of each member state as well as within the European Union (EU). Therefore, observing the strategic behavior of the market players (e.g. related to net access, cooperation or refusal to collaborate, etc.) becomes crucial. There are different mathematical models for describing the behaviour of a competitive market. For the scope of this paper, the EU electricity market is modelled using a game theoretic model. The authors compare the strategic behaviour of the market players reflected by their market influences based on the Nash equilibrium theory among an environment of perfect competition. In the case of perfect competition, each agent acts as a price taker, equalizing prices and marginal costs in order to optimise profit. The paper further considers the (generalized and extended) Cournot model, at the Nash equilibrium, where electricity firms aim to maximize their profit and enlarge their market shares taking into consideration various relationships between the real market elasticities and assumptions about the behaviour of other players. The paper provides a comprehensive overview of issues triggered by the liberalization process of European electricity markets and argues that the extended Cournot model can be considered when analysing a transition process from an oligopolistic market towards the ideal case of a perfect competitive market.

Kemfert, Barbu, Kalashnikov: Economic Impacts of the Liberalisation of the European Electricity Market

1. Introduction Electricity systems are currently being restructured in many parts of the world. This process does not follow a single paradigm, but some features are common to most situations. While electricity generation is already open to competition in many countries, transmission and distribution still have the status of natural monopolies and therefore remain regulated and/or bottlenecked for third-party access to the networks. As a consequence, it is expected that the organization of the national electricity markets will differ across Europe, depending on how the member states understand how to address the issues of market power, regulation vs. deregulation, and competition. Differences already exist in today’s European electricity markets. While some countries like the UK, Scandinavian countries and Germany seem to be the front runners in opening up their electricity markets for competition, other nations like France, Italy or Belgium display a rather slow progress in this respect. Concerning the internal organization of the market, members states spread over a wide range, with Germany on one side as a self-regulated market, and France and Belgium on the other side as heavily regulated markets where the incumbent “players” are actually de facto monopolies. On the road to perfect competition in the electricity market, the strategic behaviour of the market participants (i.e. cooperation, refusal of collaboration, refusal of net access, etc.) will determine the development of the market structure of energy suppliers and the composition of technologies employed. Energy suppliers will optimise their production gains and their strategic behaviour by maximizing market shares, increasing electricity prices, and lowering demand or consumption surplus. New energy products such as energy services, and new market actors such as electricity brokers, will be established. Maximizing market shares could particularly lead to higher electricity prices, increasing production and decreasing consumption surpluses, while perfect competition warrants lower prices and market gains and an apparent increase in electricity demand. In liberalising electricity markets, some consumers are granted the freedom of choice (freedom to switch) and suppliers the freedom of offering their services to the grid operator (freedom of trade). All these transformations are bringing the European electricity market closer to a perfectly competitive market. However, more competition could also lead to an oligopolistic market situation where electricity suppliers react strategically, influencing prices through market shares and power by cooperation (collusion) among firms and/or mergers. The economic impact of electricity market liberalisation concerns all players in a national and regional economy. Experiences in the UK and Scandinavia show that liberalisation is likely to induce employment reactions and changes in energy prices (Newberry 2002a). The planned opening of the European electricity market provides the opportunity for the firms to react strategically as global market players by joining and merging market shares and gains. Various authors have examined different kinds of noncooperative games within various and spatially distinct markets. Murphy et al. (1986) uses a mathematical programming approach to determine oligopolistic market equilibriums. Salant and Shaffer (1999) illustrate the theoretical impacts on production and social welfare using two-stage Cournot-Nash solutions by including investments due to learning by doing and R&D determining marginal costs of identical agents differently. For Europe, Wei and Smeers (1999) modelled an oligopolistic electricity market within a Nash equilibrium using 2


a sophisticated game theoretic modelling tool. Standard electricity capacity expansion models (e.g., Bloom et al. (1984)) refer only to a single economic paradigm, namely monopolies or centralization. In contrast, models involving market power can reveal quite different economic assumptions. Roughly speaking, the optimisation paradigm, which characterizes the standard capacity expansion models, is replaced by the Nash equilibrium paradigm. This can lead to different types of equilibrium depending on the assumed behaviour of the agents. In this paper, we analyse the impacts of the liberalisation of the European electricity market by a game theoretic modelling tool. We use a game theoretic Nash-Cournot modelling framework (Kemfert and Tol 2000) and enlarge it to include some of the main European electricity suppliers. The main aim of the paper is to analyse and compare a perfect competition scenario of the European electricity market against an oligopolistic market case where utilities can influence market prices and increase market shares. As the computation experiment results demonstrate, the price, the electricity export and import within the EU, and market share values correspond to the perfect competition and Cournot-Nash models. The paper is organized as follows: Section 2 sets the framework for the discussion and highlights some of the main challenges associated with the process of liberalisation of the electricity market within the European Union. The role of competition at different levels along the electricity value chain, and deregulation together with market consolidation and electricity trading are briefly explained. Section 3 provides a detailed description of the model used while Section 4 discusses the model results. Section 5 concludes and provides additional annexes.

2. Impact of Liberalization on European Energy Markets Doing business in today’s energy markets is becoming increasingly complex. On the global level, energy systems are moving from vertically integrated business units to open, diverse market places. Great Britain and the US led the way to fundamental restructuring of the electricity markets, and Western Europe and South America are following suit. As the process advances, questions arise such as: What new requirements are going to emerge? How can the incumbent companies maintain their competitive edge, and just as important, how can new companies gain it? How do market participants adapt and what does all this mean for the energy consumer? These are just few of the multitude of very legitimate questions, and some answers can be found only if the liberalisation process is fully understood in its complexity. The introduction of market forces in the energy sector can only be successful if the “freedom of choice” rule prevails. In practice, this would mean that suppliers are free to offer their services (both domestically and cross-border) and the customer is free to switch suppliers. In other words, no barriers exist to either trade or switch. This, however, is more easily said than done. An effective process of liberalising energy markets would require (among others) transparency, changes in regulatory behaviours, and increased competition.

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Indicators of Electricity Market Liberalisation

Competitive Market Areas

Competition in generation

Wholesale markets

Non-Competitive Market Areas

Network access conditions

Retail sales

Interconnection of national network

Regulatory influence

Source: EU-DGTREN1

The Role of Competition Competition in generation was one large step towards liberalised energy markets. It assumes that there are numerous investors ready to invest. In large markets, this might very well be the case although even here fighting against incumbent companies remains a daunting task. In smaller markets however, true competition in generation must await the development of commercial and competitive technologies, e.g. fuel cells. Therefore, one major outcome to be expected from increased competition is likely to be the boost in developing new technologies that are able to provide clean, reliable energy. Competition in wholesale and retail markets is likely to support the standardisation of the wholesale market and increase the international exposure of the supply market. Competition will come at a cost but will bring about benefits as well. Competition will almost invariably result in greater uncertainty, higher price volatility and greater concern for energy security.2 Greater concern will also be shown for lower prices to the energy consumer, at least on the average and over a period of time.3 Looking back at what happened in the European energy markets since 1996, experience so far seems to follow, at least to some extent, traditional economic thinking. The progressive liberalisation of energy markets has already resulted in structural changes and widespread price decreases, and has had a major impact on companies’ profitability, particularly in Germany. As Annex I shows, when countries started the liberalisation process and allowed increased competition in their energy markets, electricity prices went up (beginning of 1990s). Following the transition period towards an open, more competitive market, the electricity price for the consumer eventually decreased. In some cases, reductions have been quite significant in e.g. Germany and the UK. In other countries like Italy and Portugal who are 1

EU-DGTREN, Electricity Liberalisation Indicators in Europe, www.europa.eu.int Great Britain was doing quite well from the security of supply point of view as a free energy market. Its reserve in 2002 was 35%. However, in 2002, low prices determined by high competition caused plant withdrawal and the reserve margin dropped to 25%. For more see D. Newberry (2002b). 3 The situation might soon be exactly the opposite since the transition to a free market also comes at a cost. Some costs will be directly absorbed by the consumers in relation to the previous inequality among various consumer categories. Other participants in the value chain will also incur costs. However, this will depend on the design of the national market if these costs will be passed on to the consumers or shared with the utilities’ shareholders and the government. 2

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much slower in restructuring their energy markets, consumers have yet to enjoy the benefits of competition. The Role of Deregulation4 Competition was not embraced easily by the incumbent utilities nor by governments. Politicians feared (and still fear) the consequences of increased competition on the public service obligation5 while the incumbents saw their competitive advantage (especially resulting from ownership of transmission and distribution networks and their client base) becoming blurred. To balance out various vested interests, there is a need for regulatory oversight. But if the introduction of competition does not mean the complete removal of the need for regulatory supervision, it may however mean less and better regulation. California learned the hard way. What happened in California showed that poor market design coupled with inappropriate regulatory and political intervention can rapidly produce disastrous results.6 Deregulation should happen gradually and involve only a few essential steps:7 • • • • •

establish the regulator’s independence from the industry; adopt a regional perspective; think across energy sources, not only about electricity; define business segments that are independently viable, without subsidies from the government; change the regulatory structure only in those segments that can sustain clear, transparent and meaningful competition.

At least two of these stages will involve an additional condition: privatisation of the utilities. To keep the regulator independent and to be able to define business units that operate fully on market principles, change of ownership is becoming of crucial importance. There is no clear evidence that state owned companies cannot function efficiently,8 or that private entities are always profitable and well managed. However, the benefits of privatisation are beyond doubt. By changing ownership, a business becomes fully taxable. A fully taxable business as opposed to a non-taxable one does wonders for a public budget. But what really makes the difference is that business decisions in a private business are not passed directly to the taxpayer who has nothing to say in the process, but instead involves the shareholders who have a more direct stake. Therefore, privatisation is a precondition for a successful deregulation.

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For the purpose of this paper, deregulation is defined as the removal of governmental control over the industry to allow a free and efficient market. 5 One of the most notorious stances on this matter is the position of France. See note 4 above. 6 See note 2 above. 7 See Hall (2002). 8 France arguably seems to again provide a unique example. However, the relative success of EdF has many explanations, one of which being that France seems to like competition outside its borders, having acquired various utilities, especially in the UK.

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Fig. 1: Industry Change after Deregulation Full Regulation

Transition

Competitive Acceleration

High profit High cost Limited competition Little innovation

Partial deregulation New entrants Selected competition Electricity Medium cost markets today reductions Reduced profit Cost restructuring

Market-Driven Competition

Innovation Minimum profit Market segmentation

Source: World Power 2002

A snapshot of the European electricity markets today shows that: -

-

-

The EU electricity market remains segmented due to geographical and technical constraints: A main market area consisting of France, Germany and Benelux countries remains distinctive from the isolated market such as UK/Ireland, Scandinavia, Italy and Spain. Domestic markets are far from uniform: The structure of costs and sources differ significantly across European countries; some national markets are very fragmented (e.g. Austria) or concentrated (e.g. France); production and distribution activities are carried out by either separated or integrated private and public utilities. With respect to third party access, most European countries chose the regulated third party access. However, Germany opted for negotiated third party access (less transparent) and Portugal and Italy opted for a single buyer model. All member states except Germany, Austria, the Netherlands and Luxemburg designated a regulatory authority specifically for the electricity sector.

As a result, the liberalisation of energy markets in Europe has seen the emergence of a multigeared market where different countries opened or are about to open their energy markets at different speeds (see Table1).

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Table 1: Liberalisation of Electricity Markets in Europe Market Share of Main Companies 68%

Users Who Changed Electricity Providers 5-10%

97% 75% 54% 98%

5-10% n/a 30% 5-10%

63%

10-20%

100%

None

yet

Bewag, E.On, EnBW, RWE, Veag AEH (public company) ESB Elettrogen, Enel

97% 79%

yet

Cegetel Essent, Nea EDP

90% 64% 85%

Endesa, Hidroelectrica del Cantabrico, Iberdrola, Union Fenosa Sydkraft, Vattenfall British Energy, Innogy, Powergen, Scottish and Southern Energy, Scottish Power

79%

30% Less than 5% N/a 10-20% Less than 5% Less than 5%

Country

Degree of Liberalisation

Date of Full Liberalisation

Main Companies

Austria

100%

2003

Belgium Denmark Finland France

35% 90% 100% 30%

Germany

100%

2007 2003 1997 Discussions not yet finalised9 1999

EVN, Verbund, Wiener Stadtwerke Electrabel SK Power Company Fortrum, Ivo Group EDF

Greece

30%

Ireland Italy

97% 35%

Luxemburg Netherlands Portugal

50% 33% 30%

Spain

45%

Not discussed 2007 Not discussed 2007 2003 Not discussed 2003

Sweden UK

100% 100%

1998 1998

yet

77% 44%

n/a 80%

Source: Financial Times10

At the Barcelona Summit, member states agreed on a new timetable11 to open up electricity markets. By the end of 2004, all non-household consumers should have the freedom to choose suppliers.12 The liberalisation process makes it certain that companies will face increasing levels of competition. This is the main driver likely to reshape their market strategy. In this new environment, incumbent companies fear that competition will put them at risk while the new entrants relish the prospects of carving out their own patch of the newly deregulated market. Many fundamental changes are still to come. For the purpose of this paper, two of the expected outcomes are briefly discussed: an increasing pressure for market consolidation and new developments in electricity trading.

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During the EU Barcelona Summit in March 2002, the schedule for the full liberalisation of energy markets within the EU Member States was delayed because France rejected any possible date. France accepted opening the door to competition in the industrial and commercial sectors but not in the residential sector, which accounts for 35% of the market. In addition, France has also called for special legislation to protect public service obligations. For more, see Global Energy Regulation, March issue 2002 on www.nera.com and Sheldon and Dodwell (2002). 10 www.news.ft.com, searched on May 3rd, 2002. 11 This meaning is different from the initial one from Electricity Directive. 12 See Prodi, R. (2002).

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Market Consolidation While the liberalisation of energy markets might indeed lead to the breakup of old monopolies, it certainly whetted the appetite for consolidation and the rise of multinational companies. The past decade saw an increasing number of mergers among various utilities, and some even questioned if merging has not simply become the “herd instinct at work”. But taking a closer look, the underlying reasoning seems to have been more fundamental than first thought. With competitive markets emerging, firms began to initially merge to gain economies of scale and lower costs. Then companies sought to re-aggregate functions such as generation and distribution to enable them to market a complex service at competitive prices (see Box 2 below). More interestingly, many mergers were also triggered by financial reasons due to the utilities’ need for a rate of return equivalent to the level expected by the capital markets.13 Box 2 In 2000 and 2001, a few expansion strategies and transactions were observed in European energy markets: The Swedish group Vattenfall took over the German company HEW. Electrabel purchased Epon, the main Dutch generator. EDF purchased London Electricity in the UK, acquired control of EnBW (number three in Germany) and then purchased more shares in the Italian company Montedison. E.On took a majority stake in the Swedish company Sydkraft and launched a takeover bid for Powergen in the UK (number two in the UK). Enel bought production assets in the Spanish Endesa, and Endesa in turn purchased a minority stake in the French medium-sized producer SNET.

Europe was by far the front runner in terms of mergers. In the second quarter of 2002, the number of mergers in the energy sector was 54 as opposed to 35 in North America, 29 in Asia-Pacific and only 7 in South & Central America.14 The fact that so many mergers have been allowed is a clear sign of the difficulties in reconciling old energy policy concerns with the experience of market liberalisation. On the other hand, exercising market power might prove (however implausible it may sound) Source: Andersen Legal15

difficult in Europe. Defining the size of the market is challenging and critical in assessing the potential for market power. This challenge stems on the one hand from the fact that in electricity, the size of the market changes hourly. On the other hand, the more a country is interconnected and active in the international arena, the less likely it will be for a domestic utility to exercise market power even if its share in the domestic market is relatively significant. Since the European market is moving towards a consolidated market (internal energy market), domestic players may lose their domestic market power.

Electricity Trading The correlation between market liberalisation and trading is obvious. As markets become more competitive, risk increases and market participants focus on trading activities. During the liberalisation process, opportunities continue to rise in various ways:16 - the benefits of different levels of competitiveness, i.e. utilities seek to merge with other utilities outside their national boundaries if competition is more aggressive in the domestic market;17 13

See Flowers (2002). See Price Waterhouse Coopers (2002). 15 See Trevisani V. (2002). 16 See EGL Research (2002). 14

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-

by taking advantage of the difference between the price level today and the future “perfectly” competitive market;18 by arbitrating between different markets.

In Europe, the greatest volume traded has been recorded in Scandinavian countries, the UK and Germany. Not coincidentally, these countries already have fully liberalised markets. With respect to trading, there are still issues to be resolved. Due to recent reforms, crossborder transactions are another major bottleneck in the development of the internal EU electricity market. The old pricing and capacity allocation mechanisms for international transmission lines are inadequate for the new framework and have so far led to poor volumes of cross-border trade. In addition, capacity constraints and the more contentious issue of tax harmonisation further hamper electricity trading.19

3. The Applied Modelling Tool The authors used a game theoretic modelling tool that was originally applied for the German electricity market, described in Kemfert and Tol (2000) and Kemfert et al. (2002). In order to investigate the economic impacts of the strategic behaviour of German utilities, a game theoretic modelling framework was established that included the strategic behaviour of firms and market agents. The model can be characterized as a computational game theoretic modelling tool for investigating the strategic behaviour of firms within a liberalised electricity market. This paper’s main aim is to analyse the economic impact of the European electricity market liberalisation using a game theoretic modelling tool (EMELIE: European Market Liberalisation Investigation). For this purpose, the authors enlarged the previous model developed for the German electricity market to include 10 other EU member states: Belgium, Denmark, France, Finland, Germany, Italy, the Netherlands, Spain, Sweden and the UK. In the first stage, the main generators are defined as firms owning the largest electricity plants in the country (more than 500 MW p.a., for members like Finland more than 350 MW p.a., for wind energy plants 10 MW p.a.).20 Profits are calculated based on marginal production costs and prices are dependent on demand, with the latter relationship being represented by an inverse demand function which is twice continuously differentiable. We use the main producers as representatives for each country. Furthermore, because of the recent developments at the EU level regarding the increased use of renewables, in addition to hydro technologies we consider wind energy as well. Wind power generators are seen as the only renewable technologies to date that are competitive and comparable with other traditional energy sources such as gas-fired plants. Therefore, the model takes into consideration the following fuel types: nuclear, hard coal, brown coal, gas, oil, water and wind. 17

For instance, in the US, more than 53% of the mergers were with companies outside the US. See also note 10 above. 18 Mergers may occur in a very subtle form. It is becoming a practice that long-term power purchase contracts replace foreign direct investments, therefore blurring the line between energy contracts, FDI and mergers. 19 Wilcox and Binns (2002). 20 Data: IEA Statistics 2001, issued in 2002.

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A Cournot-Nash game is characterized by mutual strategic reactions of individual market agents. This results in a Nash equilibrium where the strategies adopted by all market agents are optimal responses to the behaviour of other market participants. In EMELIE, 52 energy suppliers or market agents are distinguished, corresponding to their home countries (international cross ownerships have not been modelled yet). Each individual energy supplier reacts as a market player which observes a quantity strategy within a non-cooperative oligopolistic game and maximizes his/her individual profit assuming that all other players also apply the gain maximization strategy. The electricity produced by one competitive player affects the sales and trade volumes of other producers. However, in a classical Cournot model, each producer assumes only they themselves vary output, not other producers. On the contrary, in this paper the authors assume that electricity producers consider oligopolistic interrelations, looking for a conjectural Nash equilibrium. The producer’s conjectures are taken into consideration in the elasticity parameter, as is explained further in this paper. In a perfectly competitive market, agents behave as price takers, equalizing market prices to marginal production costs.21

4. Scenario Results In the Cournot-Nash equilibrium scenario, the game theoretic model obtains market shares which influence monopoly markups through price elasticities. We assume that utilities pay a fixed amount for electricity transport as regulated in Germany.22 The following assumptions are made: Price elasticity of demand Uniform tariff per 100 km Tariff per km (above 100 km) Cost of net utilisation Capacity constraint on interregional electricity transport

0.4 0.55 cents/ KWh 0.01 cent/ KWh/ km 1 cent/ KWh 100 TWh / year

We distinguish between two basic scenarios: Perfect Competition (PC) and a Cournot-Nash equilibrium (CN). The next table presents price, demand, export and import relations between European countries:

21 22

The appendix shows the detailed mathematical model description. These assumptions need to be modified in a more sophisticated model approach.

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Table 1 European Model Results: Perfect Competition (PC) vs Cournot-Nash Equilibrium (CN) Country

Belgium Germany France Netherlands England Sweden Denmark Finland Italy Spain

Prices in EURO/KWh PC 0.141 0.135 0.137 0.144 0.144 0.154 0.142 0.161 0.163 0.160

CN 0.295 0.300 0.297 0.300 0.305 0.315 0.306 0.321 0.323 0.306

Demand in TWh/year PC 88.840 676.560 500.100 109.6503 56.490 115.340 37.320 63.600 226.800 162.990

CN 66.950 430.630 329.130 87.780 288.000 102.910 28.640 60.060 205.930 144.690

Export in TWh/year PC 28.120 140.255 224.440 0.0 0.0 0.0 44.550 0.00 0.00 0.00

CN 59.250 360.419 180.763 6.192 10.950 27.670 38.020 10.780 4.580 26.080

Import in TWh/year PC 0.00 51.360 0.00 28.120 127.590 43.780 36.320 31.192 102.990 16.590

CN 7.466 60.600 22.236 68.170 168.161 59.020 22.111 39.916 150.570 24.370

Perfect competition leads to lower prices and triggers increases in demand but also reduces trade23 in comparison to the Cournot-Nash scenario. The main reason for this development can be explained as follows. Strategic behaviour (represented in the Cournot-Nash scenario) causes increased market shares and increased prices. Higher electricity prices on the other hand cause reduced demand but increased trade because firms intend to increase revenues through increased trade. The only exemption in this exercise is France whose exports follow the pattern of a full competition case because of low production costs (high share of nuclear technology). In France, strategic behaviour leads to increased electricity prices and decreased electricity demand causing decreased trading as well. The same pattern also applies to Denmark because of low production costs. In all other regions, higher electricity prices increased trade because of increased revenues for the firms. It is also important to note that in our model all firms tend to exhaust their production capacities. Table 2 shows the market shares of the Perfect Competition (PC) and Cournot-Nash case (CN) scenarios. In nearly all represented countries, strategic behaviour leads to higher market shares. This is because firms in each country intend to increase gains and revenues by influencing electricity prices. Perfect competition causes lower electricity prices, fewer gains and less trade. Strategic behaviour increases regional electricity prices, decreases demand, but increases trade effects and market shares.

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In a perfectly competitive market there are no opportunities for arbitrage, therefore no scope for trading.

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Table 2: European Model Results- Market Shares for Perfect Competition (PC) vs. CournotNash Equilibrium (CN)

Scenario/ Firms in: Belgium Germany France Netherlands England

PC CN 0.020 0.327 0.316 0.047 0.118

0.036 0.333 0.358 0.077 0.139

PC CN 0.022 0.465 0.294 0.017 0.061

0.026 0.532 0.300 0.018 0.080

PC CN 0.034 0.281 0.332 0.025 0,118

0.041 0.367 0.388 0.031 0.150

PC CN 0.034 0.347 0.281 0.076 0.130

PC 0.039 0.464 0.335 0.097 0.143

0.034 0.294 0.272 0.051 0.170

CN 0.033 0.336 0.343 0.073 0.244

It is important to stress that the model results represent the first attempts to assess the economic impact of the liberalisation process of the European electricity market. Further research is necessary to represent the different stages of the liberalization process in each country, to reflect the different domestic transportation and net access opportunities, and to simulate different trade options. Furthermore, different demand categories and interregional trade to non-European countries need to be explored. Finally, the environmental impact of the liberalization process needs to be studied.

5. Conclusions Liberalisation could lead to better investment decisions, especially in generation and higher labour productivity likely to appear in distribution due to changes in regulatory oversight, competition, further privatisation and market consolidation. Some regulatory oversight will help increase confidence in the sector (especially in the wake of the Enron failure) by ensuring a level playing field between incumbent utilities, new entrants, and consumer protection (but to a lesser extent than in previous monopolistic structures). Financial regulation also will become more and more relevant to the electricity sector as trading develops, especially in derivatives trading. In this paper, we have studied the potential impacts of the European electricity market using the game theoretic modelling concept EMELIE. The main conclusion that can be drawn from this analysis is that liberalisation of the European electricity market does lead to decreased electricity prices. However, this price decrease causes lower electricity demand and fewer trade effects, and market shares are lower than in the Cournot-Nash case. On the other hand, oligopolistic market behaviour leads to increased gains and revenues for regional utilities, and increased electricity prices increase European electricity trade.

Acknowledgement We greatly appreciate the funding from the Ministry of Science and Culture in Germany as well as funding from the EU (contract number NNE5-2001-00519) for the EMELIE project to build the European electricity market model and to finalise this paper. The views expressed in this paper are solely those of the authors.

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Green, R.J. 1994. Britain’s Unregulated Electricity Pool. From Regulation to Competition: New Frontiers in Electricity Markets. M.A. Einhorn, ed. Kluwer Academic Publishers, 73-96. Green, R.J. 1997. Symposium on Transmission Pricing, A Special Issue of Utilities Policy. R.J. Green, ed. forthcoming. Green, R.J., D.M. Newbery. 1992. Competition in the British Electricity Spot Market. J. Polit. Econom. 100 (5), 929-953. Hall, D. (2002) Financial Aspects of Competition and Deregulation in Electricity, www.aims.ca Harker, P.T. 1986. Alternative Models of Spatial Competition. Oper. Res. 34 (3), 410-425. Harker, P.T. 1991. Generalized Nash Games and Quasi-Variational Inequalities. Euro. J. Oper. Res. 54, 81-94. Harker, P.T., J.-S. Pang. 1990. Finite-dimensional variational inequalities and nonlinear complementarity problems: A survey of theory, algorithms and applications. Math. Programming 48, 161-220. Hashimoto, H. 1995. A spatial Nash equilibrium model. Spatial Price Equilibrium: Advances in Theory, Computations and Application. P. Harker, ed. Springer-Verlag, Berlin, 20-40. Hobbs, B. 1986a. Network models of spatial oligopoly with an application to deregulation of electricity generation. Oper. Res. 34 (3), 395-409. Hobbs, B. 1986b. Mill pricing versus spatial price discrimination under Bertrand and Cournot spatial competition. J. Indust. Econom. 35 (2), 173-191. Hobbs, B., K.A. Kelly. 1992. Using game theory to analyze electric transmission pricing policies in the United States. Euro. J. Oper. Res. 56, 154-171. Hogan, W.W. 1992. Cournot networks for electric power transmission. J. Regulatory Econom. 4, 211-242. Kalashnikov, V.V. 1995. Complementarity Problems and Generalized Oligopoly Models, (in Russian, Habilitation Thesis), Central Economics and Mathematics Institute, Moscow, 243 pp. Kalashnikov, V.V., N.I. Kalashnikova. 1988. Global convergence of inexact Newton method solving complementarity problems ( in Russian). Optimizatsia 42 (59), 66-85. Kalashnikov, V.V., N.I. Kalashnikova. 1988. Step accuracy control for Newton method solving nonlinear complementarity problems ( in Russian). Optimizatsia 43 (60), 2740. Kalashnikov, V.V., N.I. Kalashnikova. 1996. Solving two-level variational inequality, J. Global Optim. 8 (3), 289-294. Kemfert, C. 1999. Das Mixed Complementarity Problem (MCP) – Problemstellung und Anwendungen. IER AP—99—3, Stutgart. Kemfert, C., Kalashnikova, N.I. Simulation of Electricity Systems by Oligopolistic Models. Proceedings of the International Applied Business and Research Conference (ABERC’2002), March 14-19, 2002, Puerto Vallarta, Mexico. Kemfert, C., R. Tol. 2000. The liberalization of the German electricity market. Modeling an oligopolistic structure by a computational game theoretic modeling tool. Kemfert, C., Lise, W., Tol, R. (2002) Strategic Action in the Liberalised German Electricity market, submitted to ENERGY POLICY Kinderlehrer, J.G., G. Stampacchia. 1980. An Introduction to Variational Inequalities and Their Application. Academic Press, New York. Klemperer, P.D., M. Meyer. 1989. Supply function equilibria in oligopoly under uncertainty. Econometrica 57 (6), 1243-1277. Murphy, F., H. Sherali, A. Soyster. 1986. A mathematical programming approach for determining oligopolistic market equilibria. Math. Programming 24, 92-106. 14


Newberry (2002a): Problems of liberalising the energy utilities, European Economic Review, Vol 4. Newberry (2002b): Regulatory challenges to European Electricity Liberalisation Oren, S.S. 1997. Economic inefficiency of passive transmission rights in congested electricity systems with competitive generation. Energy J. 18 (1), 63-83. PriceWaterhouseCoopers (2002), Power Deals Report, Analysis Q2 2002, www.pwcglobal.com/energy Prodi ,R. (2002), (President of the European commission) Where we go from Barcelona to the European Parliament, Brussels, Speech on 20 March 2002, www.europa.eu.int Rutherford, T. 1993. MILES: a mixed inequality and nonlinear equation solver. Salant, S.W., G. Shaffer. 1999. Unequal treatment of identical agents in Cournot equilibrium. The American Economic Review 89 (3), 585-604. Schmalensee, R.B., W. Golub. 1984. Estimating effective concentration in deregulated wholesale electricity markets. RAND J. Econom. 15 , 12-26. Sheldon,J. and A. Dodwell (2002) Energy Liberalisation in the pipeline in Energy Briefing, www.ashursts.com Smeers, Y., J.-Y. Wei. 1997. Capacity Set-up and Welfare Performance under Various Assumptions on the Short-run Competition. CORE, Université Catholique de Louvain, Belgium. Trevisani V.(2002), The deregulation of the electricity market in France, legal guide, pg.2, (on file with the authors) Van der Fehr, N.-H., M., D. Harbord. 1993. Spot market competition in the UK electricity industry. Econom. J. 103, 531-546. Wei, J.-Y., Y. Smeers. 1999. Spatial oligopolistic electricity models with Cournot generators and regulated transmission prices. Oper. Res. 47 (1), 102-112. Wilcox,J. and M.Binns (2002) :Importance of European liberalisation to trading, pg.24 in World Power Report 2002

15

Kemfert, Barbu, Kalashnikov: Economic Impacts of the Liberalisation of the European Electricity market

Annex 1. Industry Electricity Price in selected OECD countries in US dollars/kWh

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

Austria Belgium

0,039 0,054 0,065 0,066 0,056 0,065 0,067 0,070 0,071 0,072 0,081 0,081 0,081 0,078 0,059 .. .. 0,043 0,052 0,056 0,054 0,052 0,070 0,067 0,071 0,067 0,067 0,077 0,073 0,062 0,061 0,056 0,048 ..

Denmark Finland France Germany Greece Ireland Italy Luxembourg Netherlands Norway Portugal Spain Sweden United Kingdom

0,046 0,040 0,034 0,047 0,044 0,057 0,062 0,042 0,040 0,020 0,060 0,046 0,028

0,045 0,046 0,042 0,066 0,053 0,073 0,070 0,053 0,044 0,026 0,078 0,062 0,028

0,041 0,053 0,047 0,082 0,060 0,064 0,077 0,065 0,049 0,028 0,090 0,077 0,035

0,050 0,055 0,048 0,084 0,059 0,065 0,077 0,065 0,044 0,032 0,091 0,085 0,039

0,057 0,053 0,046 0,079 0,053 0,058 0,075 0,060 0,042 0,030 0,083 0,081 0,042

0,062 0,063 0,056 0,091 0,065 0,068 0,098 .. 0,052 0,035 0,098 0,097 0,043

0,065 0,060 0,054 0,088 0,065 0,066 0,105 .. 0,053 0,035 0,110 0,103 0,050

0,067 0,055 0,057 0,093 0,070 0,070 0,113 .. 0,051 .. 0,133 0,105 0,053

0,070 0,046 0,055 0,089 0,059 0,060 0,091 .. 0,064 .. 0,118 0,085 0,055

0,063 0,050 0,053 0,089 0,055 0,061 0,091 .. 0,065 .. 0,112 0,078 0,035

0,069 0,060 0,060 0,100 0,062 0,065 0,093 .. 0,075 .. 0,118 0,081 0,036

0,073 0,062 0,057 0,086 0,059 0,066 0,101 .. 0,072 .. 0,108 0,080 0,039

0,064 0,052 0,049 0,072 0,054 0,063 0,094 .. 0,063 .. 0,094 0,064 0,045

0,068 0,050 0,047 0,067 0,050 0,059 0,095 .. 0,062 .. 0,090 0,059 0,034

0,066 0,046 0,044 0,057 0,050 0,057 0,086 .. 0,061 .. 0,078 0,056 ..

0,058 0,039 0,036 0,041 0,042 0,049 0,089 .. 0,057 .. 0,067 .. ..

0,060 0,038 .. .. .. .. .. .. 0,059 0,034 0,066 .. ..

0,046 0,053 0,058 0,066 0,061 0,071 0,072 0,076 0,068 0,067 0,068 0,065 0,065 0,065 0,064 0,055 0,048

Source: IEA Statistics, Electricity information 2002

16


Annex II: Mathematical Description of the European EMELIE model EMELIE can be characterized as a game theoretic model for the electricity market assuming perfect information, constant price elasticity within all regions, linear cost functions and a regional electricity production linked by trade flows. Each producer renders his/her supply only in one region. With F R I and

- set of firms - set of countries - set of technologies - location mapping such that l ( f ) = r if and

l:F →R

only if firm t(l(f),r) c(i) de0(r) pe0(r) σ ( f ,r ) r conjectured by firm f capaco(r,r*) xlim(i,f) pe(r) mc(f) t(l(f),r) l(f) to country r ms(f,r) s(f,r) x(i,f) netx(r,r*)

f is located mainly at country r - net access for electricity l(f) to countries including taxes - variable production costs for technology i - reference demand for electricity in country r - reference price for electricity in country r - regional price elasticity of electricity demand in region -

international net capacity maximal capacity of technology i in firm f demand price for electricity in country r marginal costs of electricity production by firm f - shadow price of electricity transportation from region

- market share of firm f in country r - supply of firm f to country r - production by firm f with technology i - net export of electricity from land r to land r*

The Nash equilibrium is determined by the optimality conditions for profit maximization, equalizing marginal production plus transportation costs and prices corrected for monopoly markup and price elasticity of demand. The MCP expression applies the optimality conditions of non-linear programs as KKT conditions and obtains the optimal value of the decision variable due to their upper and lower bounds (see Ferris and Sinaoiromsaran, 1998). Following the Kemfert and Tol (2000) framework, we can write the equilibrium conditions as follows.  υ ( f ,r )  mc( f ) + τ (l ( f ), r ) + t (l ( f ), r ) = pe(r )1 − × nash  ,  σ ( f ,r )  (1) with

∀r ∈ R ,∀f ∈ F


τ (l ( f ), r ) = t (l ( f ), r ) = 0 if l ( f ) = r and nash=0 for perfect competition, nash=1 for Nash-Cournot equilibrium. Electricity is transported and traded from region l(f) to country r if l ( f ) ≠ r . Marginal production costs may increase together with the shadow prices of the capacity constraints. Net access include taxes. In the Nash equilibrium, prices are presented by the inverse demand function which includes price elasticity of demand and the market share of firms. The individual demand share is determined by:

υ ( f ,r ) =

∑ s(g ,r ) g∈F

∀r ∈ R ,∀f ∈ F . s( f , r ) An upper bound of marginal costs is given by

mc( f ) ≤ c(i )

(2)

∀i ∈ I ,∀f ∈ F .

(3)

Note that this inequality constraint is formulated this way because the lower bound of mc is zero. The total supply is equal to the total production (that is, the market is cleared completely):

∑ x(i , f ) = ∑ s( f ,r ) i∈I

∀f ∈ F .

(4)

r∈R

Aggregate supply of firms in region r equals the corrected total demand in that country, i.e. −σ ( r )

 pe(r )   s ( f , r ) = de0 (r ) ⋅  ∀r ∈ R (5) pe r ( )  0  f ∈F where σ (r ) >0 is a parameter based upon the elasticity conjectured by firms-producers at country r. The specific form of this relationship may be various, for example,

∑

σ (r ) = max{σ ( f , r ), f ∈ F }

σ (r ) =

or

1 F

∑σ ( f ,r ) ,

(6)

f ∈F

as in fact, this relationship defines the inverse demand function for country r. Net exports of country r to country r* with r ≠ r * is established by

(

) ∑ s( f , r ) − ∑ s( f

netx r , r * =

*

f ∈M

where M = { f ∈ F l ( f ) = r}

f ∈M *

*

,r

)

∀r , r * ∈ R and r ≠ r * ,

{

( )

M * = f * ∈ F l f * = r*

and

(7)

*

}.

Exports and imports are limited by net capacity:

(

)

(

netx r , r * ≤ capaco r , r *

)

∀r , r * ∈ R and r ≠ r * .

18

(8)


The maximum net production of each individual technology i bounds production or supply of electricity by firm f : x (i , f ) ≤ x lim (i , f ) ∀i ∈ I and ∀f ∈ F . (9) Nonnegative constraints are valid for the variables below:

s( f , r ), x(i , f ), pe(r ), mc( f ),τ (l ( f ), r ),υ ( f , r ) ≥ 0.

(10)—(15)

These models relationships are programmed in the language GAMS as a MCP solved by the algorithm MILES. An optimal solution is found by maximizing regional profits under all the constraints.

19