Modelling strategic bidding behaviour in power markets

MODELLING STRATEGIC BIDDING BEHAVIOUR IN POWER MARKETS 1 Dr, Konstantin Petrov Dr Gian Carlo Scarsi Wim van der Veen KEMA Consulting GmbH

Abstract This paper briefly explains the background and benefits of the use of strategic bidding models and illustrates how these models can be applied to quantify “gaming behaviour”. Such type of modelling is important for regulatory authorities and system/ market operators to: (1) assess whether market participants are becoming dominant and can abuse their market power; (2) to undertake measures related to the improvement of market rules or the strengthening of market monitoring. Finally, strategic bidding models are important to enable market participants to: (1) forecast market price developments; (2) estimate revenue streams for asset valuation purposes; (3) understand the rationale and drivers of bidding strategies; and (4) evaluate and optimise their power supply portfolios. Keywords: Strategic bidding; market power; supply function equilibrium.

1.

INTRODUCTION

There is now substantial evidence of the abuse of market power in the wholesale electricity sector. The UK experience from the early 1990s showed a considerable dissatisfaction with the results of the UK’s ESI restructuring, as the (then) duopolists, National Power and PowerGen, were perceived as exercising substantial market power in the Pool of England and Wales. This was also apparent when the (original) vesting contracts that had been drawn up during the restructuring phase expired, only to be renegotiated by the RECs on much less advantageous terms. More recently one of the reasons for the dramatic price increase in California was the strategic withholding of capacity. Franc Wolak estimated that the exercise of market power in California raised the cost of electricity supply by almost US$9 billion between May 2000 and April 2001. Back to Europe, the huge price spikes on the Amsterdam Power Exchange (APX) in the Netherlands (reaching 1200 Euro/MWh) have caused heated debate on the correct functioning of the market and the “gaming” behaviour of market players. A number of industry participants classified such behaviour as undesirable and called upon the Regulator (DTe), APX, and TenneT to improve market transparency and monitoring.

1

The authors are with KEMA Consulting GmbH, Dechenstrasse 10, D-53115 Bonn, Germany. They can be reached on +49 228 969 630, Fax +49 228 969 6320, or via email on [email protected]

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Research Symposium European Electricity Markets The Hague - September 2003

Compared with the Netherlands, prices on the European Energy Exchange (EEX) in Germany have generally been much more stable. However, in December 2001 the market was taken by complete surprise when prices for base load at the then-LPX reached more than 200 €/MWh. Although such levels have not been reached again, there were several occasions in 2002 when prices for individual hours increased to several hundred Euros per MWh. Following the first price spikes in December 2001, several players claimed that this development was caused by dominant players “gaming” the market, and, in particular, by reduced imports from France. Conversely, the power exchange stated that the price spikes were a result of cold weather and a tight balance between supply and demand. Finally, while the German antimonopoly office, the Federal Cartel Office (Bundeskartellamt) announced its willingness to analyse the situation more carefully in case of official complaints, no investigation has actually started to our knowledge. Finally, price spikes and market power may play a major role in the development of an integrated Dutch/Belgian wholesale market. This is discussed, with an application, at the end of this paper.

2.

BEHAVIOUR OF A FIRM WITH MARKET POWER

In contrast to price taking firms, a firm that exercises market power sets its production level and/or its prices independent of its competitors ([12], [13]). It may influence the market price by withholding output at the margin or raising the price at which it is willing to sell this marginal output (see Fig.1). By taking such actions the firm risks selling less, but it raises the price it will get for all the output that it does sell, including – most notably –‘infra-marginal’ output. Therefore, the central idea behind the strategic behaviour of firms is that in a market where all output is sold at the same price, a firm that can influence price in the market will do so in order to raise the price for all the production it sells. When is it profitable for a firm to behave like this, restricting its output or raising its offer price in order to affect the market price? It is profitable so long as the gain in profit by selling all the output after the market price increases is still greater than the profit reduction it faces by selling fewer units, if any. Two factors are crucial in determining the extent to which such a behaviour is likely to be profitable for the firm: the sensitivity of demand to price changes and the sensitivity of supply from other producers to price changes ([4], [11]). If demand must adjust to having one less unit to consume, then the price must rise to reduce demand accordingly. If demand is very sensitive to price, i.e. if demand has a high price elasticity then it will not take a huge price rise to reduce demand by one unit. Practically, the degree of demand elasticity depends on the availability of alternative sources (e.g. distributed generation), the nature of the technological process (some processes could, for instance, allow for discontinuous electricity consumption), and on consumer assessment of the ‘value of lost load’ (i.e. the benefit foregone because of non-consumption of electricity).

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Price mark-up

Price offers

P* Variable costs

Mark-Up Strategies

Demand Quantity

Q* Supply

Total capacity Capacity withdrawal

P*

Variable costs Demand

Capacity Withdrawal Strategies

Q*

Figure 1: Diagrammatic presentation of strategic bidding. Similarly, if supply from other firms is very sensitive to price changes, then any one firm in isolation will be unlikely to find it profitable to reduce its output or raise its offer price on marginal units in order to raise the market price. If the firm attempted to do this, then even a small increase in the market price would bring about additional supply from other producers to replace the unit of supply that the firm has decided not to offer or to offer at a higher price. The small increase in price would then not be sufficient to make up for the firm’s overall reduction in sales. Practically, the degree of supply elasticity in the short term depends on the degree of intensiveness of competition (determined by the number of players and generation technologies) and available generation capacity that could be readily introduced. The ability to exercise market power is someway correlated with a producer’s market share. A firm with a very small market share is more likely to see demand as relatively price elastic and the supply of other firms as relatively price elastic over the range of output that it might contemplate removing from the market or offering at a higher price. On the other hand, a firm with a larger share of the market will be more likely to reduce its output or raise the offer price on part of its output in a way that is difficult for consumers to counteract. Likewise, other companies may find it much more difficult to replace the output reduction of a large firm without running into production constraints that would drive up their own costs ([4]). Fig. 2 shows the quantification of price-mark ups as a function of a number of companies. A larger number of companies increase the degree of competition and correspondingly reduce price mark-ups.2 A number of studies have been performed in the past with respect to the optimal number of players on the wholesale electricity market. E. g. Green and Newbery [6] found out that five noncolluding generators would have been sufficient in Britain assuming that they sold into a unified market.

2

Britain’s experience shows considerable dissatisfaction with the results of the UK restructuring process. The opposite solution could be observed in Poland (more than 30 companies) and Argentina (currently, around 40 companies), where a large number of companies were created with, however, questionable outcomes with respect to the critical mass of some companies.

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Price Mark-Ups as a Function of Number of Equal Players 25.00%

20.00%

15.00%

10.00%

5.00%

0.00%

Demand [MW]

2 players

3 players

4 players

5 players

10 players

Figure 2: Price-Mark-ups as a function of the number of equal players (symmetric portfolio distribution). Simulation performed with the strategic simulation tool SYMBAD (see Section 4).

3.

MODELLING STRATEGIC BEHAVIOUR

Traditionally, market power has been analysed with the help of some static indicators, like the Herfindahl-Hirschman Index (HHI) or the Price Cost Margin Index (PCMI).3 While the PCMI attempts to describe the overall economic impact of market power, it suffers from the fact that it can only be analysed ex post, i.e. when firms have actually exercised (abused) their market power. In addition, neither measure allows the identification of those firms that may actually be in a position to manipulate the market. In contrast to these traditional, more descriptive measures, game theory has evolved as one of the most promising approaches to the understanding of competition dynamics in deregulated electricity markets.

3.1

The Game-Theoretical Approach

Game theory has long been a discipline within the broader field of industrial organization, and is now finding applications in the study of strategic behaviour in deregulated generation markets. In particular, the notion of Nash Equilibrium that specifies strategies by which competing firms aim at maximising their profits on a non-cooperative basis, can be applied to understand the likely behaviour of rational firms in deregulated yet oligopolistic markets. The Nash Equilibrium conditions specify that each player is satisfied with its choice of strategy. In particular, this means that, even knowing the exact strategies of all other players, every player is unable to find a more profitable strategy than her equilibrium strategy. In other words, the Nash equilibrium is simply a set of strategies, one for each player, such that no player can do better by changing its strategy, given that the other players stick to their equilibrium strategies. In wholesale electricity markets, a game theory framework with a dynamic Nash Equilibrium outcome is best represented by the “Supply Function Equilibrium” (SFE) concept.

3

While the HHI is a measure of market concentration, which is obtained by summing up the square of each firm’s market share (in %), the PCMI expresses the percentage amount by which market prices are above the perfectly competitive level.

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3.2

Supply Function Equilibrium

The concept of Supply Function Equilibrium (SFE) has recently emerged as a promising model of interaction in deregulated power markets and as one which lies between the two extremes of Bertrand and Cournot competition. SFE recognizes the fact that, differently from Bertrand-type competition, generators price their output prior to actually producing it. Further, the SFE model offers the possibility of developing an insight into the bidding behaviour of companies, particularly in markets where they are constrained to bid repeatedly and consistently over an extended period of time. The general SFE approach was introduced by Klemperer and Meyer [7] and applied by [6], [8] and to [1] the electricity industry reform in England and Wales, and by [10] to the Pennsylvania Electric System. One recent example of this application is the use of the SFE framework by the Market Monitoring Committee of the California Power Exchange [3]. Therefore, the case for the SFE approach is its realism regarding the bidding behaviour of companies in electricity markets.

4.

SYMBAD (SIMULATION OF BIDDING ACTIONS AND DECISIONS)

SYMBAD4 incorporates the game theoretical background of the Nash equilibrium and is based on the Supply Function Equilibrium (SFE) approach [7]. The modelling approach used expands on the Baldick/Kahn approach [1] by introducing (1) piecewise affine MC functions, thus giving more precise approximation of the actual marginal costs in case the linear one is not appropriate; and (2) several demand segments where different demand slopes and different values of capacity non-availability may be given. The model also considers capacity constraints, which affect the units’ MC curves. The model’s methodology postulates linearity of both MC curves and supply functions. Linearity is assumed in the construction of portfolios’ marginal cost and supply functions since they need to be affine (or piecewise affine) in order to be modelled according to the linear SFE concept which the model follows. Hence the actual data for generating units’ capacity parameters (including constraints) and their variable costs are approximated in the form of linear (or piecewise linear) marginal cost curves. The great advantage of the SFE with linear marginal costs over the more general form is its ability to handle asymmetric companies when there are more than two “strategic” companies. The construction of MC and supply curves is described below. Using the input data for each unit we construct the unit-specific MC curve. We aggregate these unit-specific MC curves for the units within a portfolio and define the portfolios’ MC curves. They incorporate all the values provided for variable costs and the various capacity constraints. Further, the constructed MC curves are mathematically identified via regression analysis and linear approximation. In the following step, the individual MC curves are summed up to derive the aggregate MC curve. This curve represents a supply curve for a “perfectly competitive” market. In fact, this is the supply curve in case of perfectly competitive bidding, i.e. bidding at marginal cost. After constructing the aggregate marginal cost curve, representing the supply curve in case of “perfectly competitive” bidding, we construct the portfolios’ supply curves in case of dynamic Nash Equilibrium (as defined by the linear SFE) and aggregate them to form a “total” market supply curve (aggregate supply function).

4

SYMBAD was developed by KEMA Consulting and can be used in combination with unit commitment models, such as the well-known program PROSYM. Based on these results, SYMBAD simulates the bidding behaviour of specified generators, optimises the expected mark-ups of bid prices in the market, and predicts market prices under different bidding strategies.

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Defining the Demand Segments

Production Cost Bidding

Production Cost Curve (estimation of the system marginal cost) Gaming

Estimation of the mark ups for the different demand segments

Figure 3: Overview of strategic bidding modelling used in SYMBAD. The demand function is defined as a linear curve: slope and characteristic demand values are given as inputs. Demand segments are defined in order to recognise the differences in the power market’s characteristics between different periods of the year (different demand elasticities and different capacity availability). The demand curve is essential for determining the market price both in the marginal cost case and in the supply function case. The equilibrium quantity and price in the market with strategic behaviour and in the perfectly competitive market are defined as the intersection between the demand curve and the marginal cost curve (or the supply function curve in the case of “strategic” markets) (see Fig. 4). The model derives a separate set of mark-ups for each demand segment and for each value of demand within the separate demand segments. The price mark-up is defined as MUp = MPSFE – MPMC, where MPSFE is the equilibrium price on the market with strategic behaviour and MPMC is the equilibrium price on the perfectly competitive market. Supply

Price

mark-up D

S MC

Price Mark-up Demand

Figure 4: Price and supply mark-ups.

5.

RESULTS FOR THE DUTCH POWER MARKET

In the year 2001, cross-border capacity has been auctioned in the Netherlands, and an adjustment market has developed. The price spikes on the Amsterdam Power Exchange (APX) of up to 1200 Euro/MWh have caused debate on the correct functioning of the market. Some argue that these price spikes are caused by coincidental reduction in supply because of maintenance and unavailability of power plants in the Netherlands and Belgium. Others suspect that dominant players deliberately withdraw generation capacity and offer higher prices on the APX dayahead market. Research Symposium European Electricity Markets The Hague - September 2003

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In order to analyse the developments as indicated in the introduction, KEMA Consulting has performed a first assessment of the Dutch power market with the help of the simulation tool SYMBAD. In a first step, KEMA´s existing database of Dutch power plants and the optimisation tool PROSYM were used to determine marginal cost curves for all major power plants. These were then entered into SYMBAD and assigned to corresponding owners. Similarly, import capacity was distributed on these same portfolio owners and a number of “independent players”. For simplicity, marginal cost of import was assumed to be at the lower end of the Dutch plants, i.e. they would always be competitive. Finally, we differentiated between peak and off-peak hours and used actual load data to estimate demand values and assign different slopes to both demand segments. Subsequent simulations in SYMBAD clearly showed different prices for day and night hours. For “optimal” circumstances with full availability of generation and import capacity, peak hour prices remained moderate at levels of up to 40 €/MWh, and off-peak hours around 20 €/MWh. However, when reducing import capacity, peak hour prices already increased considerably. When these reductions further coincided with outages (or withdrawals) of larger power plants within the Netherlands, prices during peak demand suddenly skyrocketed – sometimes reaching levels of several hundred Euros per MWh. The next diagram thus shows the possible impact of a considerable reduction in import capacity and availability of power plants within the Netherlands as compared with “optimal” circumstances.

Im pact of plant outages and im port reductions 350

Plant outages, reduced import 300

Prices [€]

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150

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100% plant availability, full import 0 1h

5h

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Curves show market price; demand for typical summer weekday

Figure 5: Impact of import reduction and plant outage on market prices. Not only does Fig. 5 show the obviously massive increase in prices during peak hours. In addition, it also displays some substantial variation during the most “important” hours. All other conditions being equal, relatively minor fluctuations in demand therefore seem to cause substantially larger price deviations. In fact, the simulations also led to situations where prices did only peak in individual hours, albeit starting from an already relatively high level. Such phenomena have also occurred in the APX. This observation may be explained by another instructive example, which is shown in Figure 6. Here, price mark-ups are shown as a function of demand. One can clearly see that the mark-ups do only slowly increase with increasing demand; in fact, they may even decrease afterwards.5 At a certain point, however, mark-ups suddenly start rising, indicating substantial market power

5

The drop in price-mark-ups could be explained by the fact that in some demand segments, the degree of competition may rise (a larger number of players start competing) and prices increase more slowly than marginal cost.

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Research Symposium European Electricity Markets The Hague - September 2003

of some players.6 The main point here is that even small, supposedly negligible changes in demand may thus lead to extreme price fluctuations.

Figure 6(a): Price mark-ups as a function of demand. 80 70

Price [€/MWh]

60 50 40 30 20 10 0

0:00 h

6:00 h

12:00 h

18:00 h

Figure 6(b): Price developments over time [prices reflect the mark-ups shown in figure 6(a)]. Recent research on liberalised electricity markets suggests that forward and bilateral markets lessen the significance of the conventional pool mechanism but, on the other hand, may influence the bidding strategies and behaviour of the generating units in the pool. The contractual position of generators thus needs to be modelled in order to better simulate the generators’ behaviour. Therefore, KEMA Consulting has recently upgraded SYMBAD to include the modelling of forward contracts.

6.

RESULTS FOR THE GERMAN POWER MARKET

Any simulation of the German power market is complicated by a number of facts. To start with, the four major players combined hold at least 80% of total generation capacity, the remainder being distributed across more than 900 regional and local utilities - as well as industrial autoproducers and IPPs. Similarly, one has to consider approx. 300 generation units even when neglecting all generation units below 100 MW. Finally, there exists substantial transmission interconnection capacity with most neighbouring countries. Any simulation of the German market would therefore have to consider market prices in Denmark, the Netherlands, France, Switzerland, Austria, the Czech Republic, and Poland too. For practical reasons, we have therefore only considered major plants above a certain size,7 and reduced system load by the estimated production of all other generators. Similarly, we have used “generic” cost figures for different types of power plants only, and estimated market prices

6

7

Usually, this phenomenon can be observed in the peak demand periods, where most of the participants had already bid their capacity and the residual players (i.e. those players that still have available capacity) could exercise significant market power. This effect could lead to substantial mark-ups. Depending on the scenarios, 100 MW or 150 MW.

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of imported electricity from different countries. Import and export capacities were finally set to the Net Transfer Capacities (NTC) as published by the relevant TSOs. Some results from these simulations are summarized in Figure 7. 40

Reduced import No import Full availability Limited outages & reduced import Major outages Equilibrium price

30

20

10 38 GW

43 GW

49 GW

54 GW

59 GW

64 GW

70 GW

75 GW

Demand

Figure 7: Impact of import reductions and plant outages on the German market. More specifically, this figure shows the relative equilibrium prices for a number of scenarios. Clearly, prices grow with increasing demand. However, prices hardly change when import capacities are reduced. When import reductions are however combined with some outages of nuclear power stations, prices may start to increase, as indicated by the blue line. Moreover, this effect may be even larger when more plants are removed from service within the country, but imports are allowed to resume. As a consequence, it seems that available import capacities are much less important for Germany than for, say the Netherlands. In the Dutch case, previous simulations have clearly shown available import capacities to be a decisive factor for potential market power. To some extent, this difference can certainly be explained by the limited relative size (< 10%) of imports to total installed capacity in Germany. Conversely, outages of (major) power plants may obviously result in situations where individual players enjoy some market power.8

Supply Mark-Up (%)

40%

20%

0% 40 GW

45 GW

50 GW

55 GW

60 GW

65 GW

70 GW

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SystemLoad (GW) Status quo

After Establishment of "Fourth Force"

Figure 8: Impact of establishing the „Fourth Force” on the German Power Market. Apart from different impacts of import and local generation capacities, we have also briefly analyzed the influence of the recent merger of three major companies to form Vattenfall Europe, the so-called “Fourth Force”. This merger was triggered by two previous mergers in 2000, when RWE and E.ON emerged as the two major utilities in Germany, becoming considerably larger than their competitors.9 Part of the undertakings imposed on RWE and E.ON by the Federal Cartel Office and the European Commission related to the sale of their shareholdings in three other major utilities, namely BEWAG, HEW, and VEAG. The underlying ration8 9

Naturally, these effects strongly depend on the power plants (i.e. their owners) that are actually taken out of service. The „third“ player is EnBW, which is majority-owned by EdF of France.

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Research Symposium European Electricity Markets The Hague - September 2003

ale was to create a fourth major player on the German market that should help limit the market power of RWE and E.ON. This leads to an interesting question, i.e. whether the establishment of just another major player can actually help achieve this goal. On the other hand, could this simply strengthen the oligopolistic nature of the market and thus market power? We have therefore run another round of simulations and compared the results before and after the establishment of this “fourth force”. As illustrated by Figure 8, the initial results are somewhat inconclusive. The supply mark-up, indicating the use of market power, both increases and declines for different ranges of demand. Consequently, the establishment of another dominant player appears to have both strengthened and weakened market power. Overall, however, the negative impacts seem to outweigh the benefits as the increases are much more marked than any reductions. From this perspective, it seems rather questionable whether the establishment of the “fourth force” will be able to deliver any substantial benefits to German power consumers.

7. GAMING POTENTIAL FROM THE POSSIBLE INTEGRATION OF THE DUTCH AND BELGIAN POWER MARKETS The liberalisation of the Dutch electricity market is almost completed. In 2004, all customers will be free to choose their supplier. Wholesale prices have decreased and the volume traded over the APX spot market has increased over the past few years. Imports, especially from Germany, are still playing an important role. Due to the fact that cross-border capacity is auctioned separately, there still exist some market imperfections [14], [16]. A possible solution to the problem would be market integration. In the meantime, Belgium is thinking about the introduction of a spot market exchange. The Boston Consulting Group has investigated a possible integration of the Dutch and Belgian markets [2]. One of the conclusions of the Report was that: ”…the formation of a single Benelux market could create potential market power problems”. Integration creates a larger market that would normally lead to increased competition and lower prices. However, it is necessary to better analyse the possibility that strategic behaviour or gaming could force up prices. Quantifications are necessary to get a better insight into the risk of market power abuse. Based on the recent upgrade of SYMBAD, we have simulated the influence of the integration of the Dutch and Belgian electricity markets on wholesale market prices in both countries.10 At first, the impact of forward obligations is shown for the Belgian market. At the moment, Electrabel owns the majority of the generating units and thus dominates the Belgian market. Electrabel will have to divest part of this capacity by selling the output to third parties, resulting in so-called Virtual Power Plants. This will have a similar effect as forward obligations. The results of our simulations with SYMBAD are shown in Figure 9.11

10

11

For the simulations, we assume that a so-called „copper plate“ is created from the Dutch and Belgian systems. Possible congestion at the border must be managed by the TSOs. This form of integration is quite different from the concept of “market coupling” that is currently being prepared by APX. For adequate quantification, very detailed information is required. Most information has been based on the Market Analysis Database of KEMA. For other items such as possible import, load, and forward obligations, some assumptions have been made.

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Price [EUR/MWh]

60 50 40 30 20 10 0 4

6

8

10

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14

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Forwards

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Figure 9: Belgium - Impact of forward obligations on market prices 70

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L o ad [G W ] S upply c urve

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Figure 10: Impact of the integration between Belgium and the Netherlands on market prices. The base (red) line shows the equilibrium prices in the market with the present dominant position of Electrabel. Prices rise sharply when the load is approaching the peak in the system. If part (40%) of the generation of Electrabel is divested, prices will drop considerably (yellow line). The gaming potential at high loads has vanished. The system, however, remains very sensitive to strategic bidding when, say, more than average generating capacity is not available. The blue line illustrates this effect where 1,000 MW extra generating capacity has been shut down. More competition will make markets less sensitive to gaming. Simulations have been made with SYMBAD to quantify the effects of a combined Belgian and Dutch market. The results are shown in Figure 10. The blue line shows the combined supply curve of the Belgian and Dutch power plants. The brown line represents the combined equilibrium points of the two separate markets. The line is, actually, only the sum of the results of the two markets without any integration. Market prices are 10-50% higher than those based on marginal cost (perfectly competitive supply curve). The red line shows market prices when both markets are fully integrated. There is one TSO for both systems and the transmission system is considered as a copper plate contrary to market coupling. At low loads, the integration leads to lower prices, but at higher loads the integration may lead to extremely high prices. An obvious reason for this is the increased market power of Electrabel, whose generating portfolios from both markets are joined as the two countries integrate.

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In order to estimate the influence of Electrabel in the Benelux market, simulations have been performed whereby the Dutch and Belgian components of the Electrabel group are kept as two separate portfolios with two different owners. Market prices from this configuration (yellow line in Figure 10) are much lower than in the case of just one Electrabel-wide portfolio. Prices are also lower than expected in the separate market. Understandably, the results presented in this section have to be viewed with some caution since several assumptions were made for the Dutch, Belgian and the integrated market. However, even this first exercise clearly shows that the effect of the establishment of one Benelux market would highly depend on the treatment of the present generation portfolios, and on the amount of forward obligations in existence. In particular, our simulations confirmed the vulnerability of the integrated Benelux market to the market power of Electrabel.

8.

CONCLUSIONS

Apart from overt collusion, prices in liberalized electricity markets may also be influenced by individual actors exercising market power by means of strategic bidding. Game theory has evolved as a promising approach for the analysis and simulation of strategic bidding, with the Supply Function Equilibrium being of particular importance for the power sector. Based on a strategic bidding model, our simulations of the German and Dutch power markets have revealed some scope for exercising market power. The results indicate that market and ownership structures may result in considerable market power for individual players, enabling them to unilaterally push up prices given that certain conditions are met. Apparently, our results are largely related to the allocation and outages of power plants in Germany and the Netherlands. While the availability of import capacity has a significant impact on the market performance in the Netherlands, it is less important for the German power market. In particular, the Dutch market is vulnerable to reductions in import capacity, especially at times when a certain amount of domestic generation capacity is not available. The establishment of a fourth major player in the German market will actually help limit the extent to which the two dominant German utilities can engage in strategic bidding and exercise market power. Of course, these results have to be viewed with some caution since they are based on a simplified representation of the German power market and on a number of important assumptions. Nevertheless, in both cases, our results indicate that there is indeed scope for market power, and that some price spikes on the European Energy Exchange and the Amsterdam Power Exchange may not be the result of any overt collusion or breach of market rules, but of strategic bidding on the part of market players. Such behaviour is becoming a recurring phenomenon in deregulated power markets. Finally, our simulation results on the possible integration between the Dutch and Belgian wholesale markets indicate that the prices in an integrated Benelux market may be lower than in the present separate markets when Electrabel is split up, but also that they might potentially become much higher if the generating portfolio of Electrabel were kept intact. Such tools as SYMBAD can be used to further investigate the issue of market power, and to determine the conditions (if any) that would keep possible strategic bidding at an acceptable level from a policy-making standpoint. Moreover, our results confirm that the analysis and modelling of strategic behaviour may be important for regulatory, anti-monopoly authorities and system/market operators in order to: (1) assess whether market participants may abuse any dominant position; and (2) to undertake measures aimed at improving market rules and/or strengthening market surveillance. Similarly, strategic bidding models can be important for market participants in order to: (1) forecast market prices; (2) estimate revenue streams for asset valuation purposes; (3) understand the rationale and drivers of bidding strategies; and (4) evaluate and optimise their own contract portfolios.

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Baldick, Ross; Grant, Ryan; and Kahn, Edward, [2000] “Linear Supply Function Equilibrium: Generalizations, Application, and Limitations”, University of California Energy Institute. Borenstein, Severin [August 1999]: “Understanding Competitive Pricing and Market Power in Wholesale Electricity Markets”, University of California Energy Institute, PWP-067. Bohn, R., A. Klevorick and C. Stalon, “Second Report on Market Issues in the California Power Exchange Energy Markets”, prepared for the Federal Energy Regulatory Commission by the Market Monitoring Committee of the California Power Exchange, March 1999. Borenstein, Severin; Bushnell, James, [1999] “Market Power in Electricity Markets: Beyond Concentration Measures”, Energy Journal, 1999, Vol. 20, Issue 4, p. 65. Bushnell, James; Day, Cristopher; Duckworth, Max; Green, Richard; Halseth, Arve; Read, E. Grant; Rogers, J. Scott; Rudkevich, Aleksandr; Scott, Tristram; Smeers, Yves; Huntington, Hillard, [1999] “An International Comparison of Models for Measuring Market Power in Electricity”, Energy Modeling Forum, Stanford University, March 24, 1999. Green, Richard J.; Newbery, David M. [1992]: “Competition in the British Electricity Spot Market”, Journal of Political Economy, Vol. 100, n° 5, p. 929-953. Klemperer, Paul D.; Meyer, Margaret A. [1989]: “Supply function equilibria in oligopoly under uncertainty”, Econometrica, 57(6), 1243-1277. Newbery, D.M., [1995]: “Power Markets and Market Power”, The Energy Journal, Vol. 16, no. 3, pp. 41-66. Palermo, Jeff [March 2001], “What went wrong in California?” (in Dutch: De Californische puinhoop: Wat ging er mis?), Energietechniek. Rudkevich, Aleksandr; Duckworth, Max; Rosen, Richard, Ph.D. [1998] “Modeling Electricity Pricing in a Deregulated Generation Industry: The Potential for Oligopoly Pricing in a Poolco”, The Electricity Journal, January. Von der Fehr, N.-H. & Harbord, D., [1998]: "Competition in Electricity Spot Markets. Economic Theory and International Experience," Memorandum, Oslo - Department of Economics. Wied - Nebbeling S. [1995]: Markt- und Preistheorie, zweite verbesserte Auflage, Heidelberg. Wolak, Frank A. [1998]: “Market Design and Price Behaviour in Restructured Electricity Markets: An International Comparison”, Department of Economics, Stanford University. Giesbertz, P., Hewicker, C. and A. Paalman [2003], “The role and impact of interconnectors in the Dutch power market”, CIGRE Symposium Shanghai, China, April 2003. The Boston Consulting Group [2003], “The development of a spot market exchange infrastructure for Belgium”. P. Giesbertz, “Behaviour of Market Players in the Dutch Power Market, How to Quantify Gaming Potentials?“. Presentation at Powergen 2002, Milan. Hewicker, Chr., and Petrov, K [2003], “Potential for Market Power in the German Electricity Market”, IAEE Conference 2003 at Prague.

AER/CPB/ECN

Research Symposium European Electricity Markets The Hague - September 2003

CURRICULA VITAE Paper Presenter: Company: Country:

Dr. Gian Carlo Scarsi Position: KEMA Consulting Germany

Senior Consultant

Dr Gian Carlo Scarsi joined KEMA Consulting recently, after having worked for LECG and, previously, for London Economics. Gian Carlo is an economist by background and training, and specialises in comparative efficiency analysis. He holds the title of Doctor of Philosophy (DPhil) in Economics from the Department of Economics at Oxford University (United Kingdom), and has also obtained a separate Research Doctorate in Economics and Public Policy (Dottorato di Ricerca) in Milan. He has written a number of academic and journal publications on comparative efficiency analysis in electricity distribution and, more generally, on the reform of public-utility network industries in the UK and the EU.

Paper Author: Position: Company: Country:

Dr. Konstantin Petrov Senior Consultant KEMA Consulting Germany

Dr. Konstantin Petrov has studied Electrical Engineering and International Business. In 1997, he completed his PhD at the Institute for Energy Economics of Cologne University. Dr. Petrov joined KEMA Consulting in 1998. He has been involved in a number of projects related to technical and economic aspects of restructuring and regulation in Europe, Asia, Africa, and Central America (particularly in Germany, Belgium, Luxembourg, the Netherlands, Belarus, Bulgaria, Slovenia, South Korea, Thailand, Tunisia, and several locations in Central America). His major expertise is concentrated in the area of pricing and price regulation, market design, and market analysis and modelling. Dr. Petrov is a member of the International Association of Energy Economists (IAEE).

Paper Author: Position: Company: Country:

Mr. Wim van der Veen Senior Consultant KEMA Consulting Germany

Wim van der Veen has 22 years’ experience in the energy industry. His primary areas of expertise include market analysis, energy market simulations, price forecasting, corporate strategy, feasibility studies, master energy planning, and integrated resource planning. Prior to his career with KEMA Consulting, Mr. van der Veen spent 19 years with KEMA as a Principal Coordinator in the Energy Planning Group. Recently, he has been involved in a number of market studies in the gas and electricity markets, both in the Netherlands and abroad. His project experience spans numerous countries including Korea, the United Arab Emirates, the Russian Federation, Belarus, the Ukraine, Poland, Austria, Tunisia, Ethiopia, Sudan, Suriname, Indonesia, Yemen, and the Netherlands..

Research Symposium European Electricity Markets The Hague - September 2003

AER/CPB/ECN