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Market power in the Nordic electricity market
Utilities Policy 7 (1998) 259–268
Market power in the Nordic electricity market Arve Halseth
*
ECON Centre for Economic Analysis, PO Box 6823, St Olavs plass, N-0130, Norway
Abstract This paper investigates the potential for market power in the Nordic electricity power market. Numerical simulations have been conducted using ECON’s model for the electricity market. A special case of a supply curve equilibrium model is used to describe strategies of the large producers. The conclusion is that the largest producer, Vattenfall, has incentives to withdraw some nuclear capacity from the market in order to raise spot market prices. However, Vattenfall’s incentives are to some extent limited by the excess capacity of the smaller producers. The model also indicates that it may be profitable for Vattenfall to operate its nuclear plants at full capacity if market prices increase due to exogenous factors, e.g. consumption growth. The simulations do not indicate that hydro production will be withheld, because of the low marginal operating costs in these plants. 1999 Elsevier Science Ltd. All rights reserved. Keywords: Electric utilities; Production pricing; Market structure; Size distribution of firms
1. Introduction This paper presents a quantitative analysis of the extent to which the large Nordic power producers have incentives to exercise market power. The analysis concentrates on how the producers will schedule existing plants, i.e. on whether they consider it profitable to reduce production in order to force the spot price up. We will not consider the extent to which strategic interests will influence the investment in new capacity. Simulations that have been conducted using ECON’s model of the Nordic power market are used as a point of departure for the analysis. In this model, the producers strategy has been modelled according to a special case of a supply curve equilibrium model (see Klemperer and Meyer, 1989). An equilibrium is calculated on the basis of an interactive non-cooperative game among the producers, where the supply curve of each individual producer is a function of its marginal production costs, capacity, the price elasticity of demand, and the extent to which the other producers will adjust their output to changes in market prices. Whether the individual producers will find it profitable to exercise market power depends on a large number of factors. We will therefore start the analysis by consider-
* E-mail: [email protected]
ing a “base case” where external factors such as the framework for the market, the level of consumption, and production and transmission costs correspond to autumn 1995 values. Next, we will consider whether the incentives to exercise market power are influenced by the degree of integration between the Nordic countries, or the demand level (i.e. the underlying price level in the market). Before the model analysis is carried out, a brief presentation of the Nordic electricity market and the model concept is given.
2. The Nordic electricity market There is a clear trend toward a liberalised Nordic electricity market. The Norwegian Energy Act was passed in 1991, and competition in Norway’s national market is intensive. Sweden and Finland have also restructured their electricity sectors along the same line as Norway’s. In Denmark, discussions are ongoing, with some form of restructuring as the likely result. The key elements in the reforms are access to the grid for third parties, regulated grid tariffs (to prevent monopoly profit), and a “postage stamp system” or “point tariff system” is implemented (which means that consumers are paying the same grid tariff, not influenced by which supplier they choose). The electricity systems in the Nordic region are
0957-1787/99/$ - see front matter 1999 Elsevier Science Ltd. All rights reserved. PII: S 0 9 5 7 - 1 7 8 7 ( 9 9 ) 0 0 0 0 3 - X
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A. Halseth / Utilities Policy 7 (1998) 259–268
Table 1 Production capacity, GW (1995)
Hydro Nuclear Conventional thermal Renewables
Norway
Sweden
27.3a
16.2a 10.0 8.3
0.3
Denmark
Finland
9.6 0.6
2.8a 2.3 9.6
Source: Nordel. a Hydro production is limited by the inflow of water, 113 TWh in Norway, 64 TWh in Sweden and 12 TWh in Finland.
closely connected with several interconnectors. There has been extensive trade between these countries over the last 30 years, mainly to take advantage of the differences in production costs between the predominantly hydro systems in Norway and Sweden, and the predominantly thermal based systems elsewhere (see Table 1). Over the last 5 years, a more integrated Nordic market has evolved. Currently, the interconnectors are, with some exemptions, operated under the same competitive principals as the national grid in Norway. The mix of production capacity is shown in Table 1, illustrating a well differentiated supply side in the region as a whole. Most of the demand can be met by hydro and nuclear sources, making coal the marginal technology in normal situations. However, in periods with low precipitation, oil-condensing plants may be the marginal source. Conversely, nuclear power may be marginal in situations with high hydro inflow. The electricity demand in the region is around 350 TWh/year and peak demand was 54 GW in 1995 (see Table 2). Power intensive industries like aluminium, pulp and paper, ferroalloys, chemicals, etc., consume around 1/3 of the total electricity. Residential consumption is also high, especially in Norway where electricity is used for heating.
3. Model concept ECON’s model calculates prices, power production, consumption and trade in the Nordic market (Norway, Sweden, Denmark and Finland). Equilibrium is calculated for each month throughout a year. Each month is further split into three typical load periods, nights/weekends, medium load and peak hours. In total Table 2 Peak demand GW (1995) Norway Sweden Denmark Finland Source: Nordel.
17.7 20.6 5.8 9.9
12 ⫻ 3 ⫽ 36 periods are calculated simultaneously in the model. 3.1. Consumption The demand (d) in country i, sector c at time t ⫽ 1…36 is modelled by the following Cobb Douglas function: dc,i,t ⫽ ␣c,i,tPt c,i
(1)
where P is the market price and  the price elasticity of demand. Subscript t represents the periods. The subscript i represents the countries Norway, Sweden, Denmark (Jylland and Sjælland) and Finland. Subscript c includes different sectors like residential, small industry, services, power intensive industry and large electric boilers. Each sector is not represented in every country (only Norway and Sweden have a significant consumption in electric boilers and Denmark does not have a power intensive industry). Hence, 17 different consumer groups are modelled. The price elasticity () is dependent on both country and sector and is on average approximately ⫺ 0.5. The transmission costs and excise taxes account for around 30–50% of the total electricity price paid by end consumers. This gives a demand price elasticity around ⫺ 0.25 to ⫺ 0.35 at the producer’s price level. We have chosen to use estimated annual price elasticities reported by Statistics Norway, which normally is significantly higher than short-term elasticities (e.g. on a weekly or hourly basis). Since price elasticity influences the incentives to exercise market power heavily, different assumptions may give rise to contrary conclusions when market power is debated. Even if demand is rather inelastic in the short term, we will argue that producers must discount long-term effects through the contract markets if they’re considering exercising market power. The contract market is not modelled explicitly. Instead we assume that contract prices will fully reflect the expected spot market prices, and in equilibrium all consumers will in reality face the spot price. Hence, it is probably adequate to use an annual price elasticity in the model. This assumption is quite different than that
A. Halseth / Utilities Policy 7 (1998) 259–268
used by Green (1996b) and consequently contracts will not necessarily mitigate market power, as argued in this paper. The constant term ␣ is calibrated so that the model results correspond to the actual observed combination of annual price and consumption in each sector and country. The constant term is calibrated according to the level of demand in autumn 1995. All of the simulations presented below cover this time frame. Variations due to seasonal demand and different load categories are also represented by the constant term ␣. Indexing the Norwegian average demand to 100, Table 3 shows the variation in the constant terms by country over the year. 3.2. Transmission The transmission grid is represented in the model by a flow matrix (Tt,i,j where subscript i is the exporting country, subscript j is the importing country, D is aggregated consumption and X is the aggregated production). Dt,i ⫹
冘
Tt,i,j ⫽ Xt,i ⫹
j
冘
Tt,j,i
Even though this concentration is relatively modest compared with other markets, some smaller participants allege that the large utilities are abusing their dominant positions. In the model, the supply side in each country is formally represented by different types or classes (l) of power stations. Each class is assigned a marginal operating cost [c⬘(x)] where x is the level of production. Hydro and nuclear stations are modelled as one class each, while the thermal stations are differentiated in up to six categories, characterised by type of fuel (oil, coal and natural gas) and the energy conversion rate. Further, the production is restricted by the installed capacity (xc) within each class and by the requirement for annual maintenance (m). m represents the time for which a plant is taken out for maintenance (typically between 10 and 20% or 876 and 1752 hours annually). Formally we may write a producer’s (K) maximising problem as: max
冘
(ptxt,k,l ⫺ c(xt,k,l))
(4)
t,l
(2)
xt,k,l ⱕ xck,l
(5)
(3)
冘
(6)
j
Tt,i,j ⱕ T ci,j
261
t
Import and export between the different countries is restricted by the capacity in the grid, T ci,j . Losses are represented as a fixed percentage of the volume and transmission is charged with a tariff (t). The central grid itself (lines and nodes) is not modelled which means that loop flow effects are not considered explicitly in the model. The constraints on transmission are based on information from the Nordic ISOs and reflect their experience on the import/export capacity given the normal Nordic load pattern. 3.3. Production The supply side is represented by different producers who have different technologies and capacity at their disposal (Table 4). There is some concentration on the supply side in the market. The Swedish producer Vattenfall has a market share of around 20% of the annual Nordic electricity production. In addition, a number of other producers have market shares of between 5 and 10%.
1 x ⱕ mxck,l t t,k,l
The inter-temporal aspects in Eq. (6) imply that the model is solved for all 36 periods simultaneously. Hence, the producers are assumed to have rational expectations. The marginal operating costs in the hydro [c⬘(x)] and nuclear plants are relatively low, 0–1 ¢/kWh. Most of the Danish and Finnish thermal capacities are coal based, implying a marginal cost of between 1.5 and 2 ¢/kWh. The rest of the capacity, mainly oil condensing plants, has relatively high operating costs (3–5 ¢/kWh), implying relatively high prices in periods with high demand and/or low inflow. Because of the hydro dominance in the Nordic electricity market, the hydro scheduling is a central part of the model. The market share of hydro production is around 50% of the annual production, and the reservoir capacity is around 2/3 of the annual average inflow. The inflow peaks in summer while consumption is highest in the winter because electricity is used for room heating.
Table 3 Seasonal variations in demand in the Nordic region, index
Peak load winter Night/weekends summer
Norway
Sweden
147.5 62.5
177.3 73.0
Note: Average Norwegian demand equals 100.
Denmark 56.1 18.5
Finland 84.4 36.7
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Table 4 The main producers’ capacities, TWh/year Hydro
Statkraft, Norway Vattenfall, Sweden Sydkraftb, Sweden IVOb, Finland Elsam and Elkraft, Denmark Independent producers
Nucleara
33.7 35.6 7.0 6.9
40.5 17.5 8.5
104.8
21.5
Thermala
8.9 6.0 18.0 58.2 103.5
Market share (%) 7.1 18.0 6.4 7.1 12.3 48.8
a
7.000 hours of operation is assumed. The market shares of both IVO and Sydkraft have increased since 1996 through mergers with smaller producers. In addition, cross-ownership and alliances are established between producers.
b
The hydro power supply from day to day depends heavily on the expected future market conditions, i.e. water is stored (released) if spot prices are expected to increase (decrease). The inter-temporal hydro optimisation is formally modelled by restricting annual hydro production to be less than annual inflow (w). Further, inflow may be stored (ma) between periods, but the storage must be within the reservoir capacity (mac). Formally we may add the following constraints to the maximising problem (3):
冘
xt,k,hyd ⱕ
冘
wt,k
(7)
mat ⫹ 1,k ⱕ mat,k ⫹ wt,k ⫺ xt,k,hyd
(8)
mat,k ⱕ mack
(9)
t
t
3.4. Market power The point of departure when modelling the market power is a simple supply function equilibrium model (Klemperer and Meyer, 1989). It can be shown that such models generally do not have a unique equilibrium, unless one assumes an unrealistically large (for the Nordic market) range of demand. Hence, in the simulations we have restricted the producer’s strategy to the submission of linear supply functions to the market, characterised by a constant mark up relative to the shortterm marginal production costs. Although we are using linear supply functions, our approach is somewhat different to that of Green (1996a). In that paper, the mark up is proportional to the level of production and the production costs are represented by a continuous quadratic function with no capacity constraints. For simplicity, we have assumed that the producers do not face uncertainty with respect to consumption when the bids are submitted. Following Green and Newbery (1992), they do, however, face a range of demand levels for different
time periods to which a single supply curve must be applied. In the following discussion of our restricted supply curve model, we have simplified the notation a great deal relative to the full specification of the numerical model. The supply function can mathematically be represented as follows, assuming that one producer only possesses one technology and hence faces only one capacity constraint. Pt ⫽ t,k ⫹ c⬘(xt,k)
(10)
For a particular level of production (xt,k), the producer (k) will have a specific marginal cost (c⬘), which in turn will depend on that firm’s marginal technology (hydro, nuclear or thermal) and capacity constraints. For thermal plants, the marginal production costs are determined by the price of fuel and the energy conversion rate. In Eq. (10), the capacity constraints will imply a discontinuity in the cost function, i.e. c⬘(xct,k) ⫽ ⬁. In hydro stations, inflow and reservoir may be constrained as well. To realise a production level xt,k, Eq. (10) implies that the price must at least be high enough to cover the production cost and a mark up (). We have restricted the numerical model further by assuming that each producer’s supply function is characterised by a single (i.e. not differentiated with respect to technology). The margin may, however, vary between the different time periods and load situations. It is assumed that each producer submits its supply function to the market simultaneously. In a perfectly competitive market, the supply functions will be characterised by the marginal costs only, i.e. equals 0. If is increased, the supply curve is shifted upwards, and given a downward sloping demand curve, output will decrease as price increases. One more analytical point of departure may help us to interpret Eq. (10) more closely. We find the optimal production for producer k by differentiating the profit function (11).
A. Halseth / Utilities Policy 7 (1998) 259–268
t,k ⫽ ptxt,k ⫺ c(xt,k)
(11)
The first order condition1 is: dpt x ⫹ pt ⫺ c⬘(xt,k) ⫽ 0 dxt,k t,k
(12)
By differentiating the inverse demand function (p ⫽ D(Xt), where Xt ⫽
冘
xt,k and D⬘ ⬍ 0) we find
k
冉 冘 冊
dpt ⫽ D⬘(Xt) 1 ⫹ dxt,k
o
dxt,o , for o⫽k dxt,k
3.5. Solving the model3
(14)
冉
dpt 1 dpt ⫽ D⬘(Xt) 1 ⫹ dxt,1 c⬙(xt,2) dxt,1
冊
(15)
Rearranging Eq. (15) (i.e. finding ␦p/␦x1) and inserting in Eq. (12):
冘 c,i,t
⫺
−
1
1 ⫹ c,i
c,i c,i  ␣c,i,t Dc,i,j 1 ⫹ c,i
冘
⫺
冘 (
k
⫹ ct,k,l)xt,k,l
with perfect competition, i.e. price will equal marginal production costs. 쐌 If producer 2 never has excess capacity2, i.e. c⬙2 is infinite for all x1, the expression within the parentheses will be reduced to D⬘, which corresponds to the classical Cournot model. 쐌 Between the two extremes, 1’s production will determine whether 2 has excess capacity or not (and viceversa). In this case, several equilibria may occur, i.e. either one producer will exercise market power (and the other will produce at full capacity) or an equilibrium may be determined in mixed strategies.
(13)
For simplicity, assume only two producers. We can find an expression for how producer 1 will respond if producer 2 changes his output by differentiating Eq. (10) and substituting it in Eq. (13): dpt dxt,2 ⫽ c⬙(xt,2) dxt,1 dxt,1
(16)
For a given set of producer strategies () the model is solved by optimisation. The objective is the “area” underneath the demand curve, i.e. integrating the inverse demand function (1) minus production and transmission costs, given the constraints (5)–(9) above.
冘 c,i,t
⫺
(a)
(b)
(c)
쐌 If producer 2 always has excess capacity, i.e. c⬙2 ⫽ 0 for all x1, the fraction inside the parentheses equals zero, and hence the optimal is 0. The supply curve equilibrium will in this case correspond to the equilibrium
(d)
dpt d2pt x ⫹ ⫺ c⬙(xt,k) ⱕ 0 dx2t,k t,k dxt,k Profit max is reached unless the demand function is very concave.
(
k
⫹ ct,k,l)xt,k,l
(17)
t,k,l
ti,j Tt,i,j
The margins () are endogenous in the model. An equilibrium may be found as follows.
Eqs. (16) and (10) imply that 1 (defined as the difference between p and c⬘1) is a function of the price sensitivity of demand (D⬘) and the cost function of producer 2 (c⬙2). If we assume that power production is characterised by constant marginal costs (i.e. c⬘(x) ⫽ c) if production is not constrained by its capacity, we can distinguish between three situations.
Order condition:
冘
t,i,j
t,k,l
ti,j Tt,i,j
1 ␣−c,iD1 ⫺ c,i ⫺ 1 ⫺ c,i c,i,t c,i,j
冘
t,i,j
1
263
First iteration: each producer is given a margin () equal to 0 or any other arbitrarily chosen start point. Each producer’s supply function is aggregated up to a supply function for the whole market, and the market-clearing price is found. Second iteration: for one producer at a time evaluate if reduced output will increase profit compared with the market equilibrium in the first iteration. If so, increase4 , if not decrease . After this procedure is repeated for all large producers, a new supply curve is aggregated up, and a new market price is calculated. Repeat (c) until doesn’t change when another iteration is done.
The calculated margins () will through Eq. (10) represent the optimal or profit maximising supply curve for 2 Note that if producer 2 is at full capacity in optimum and 1 is withholding capacity, 2 is not uniquely determined only in the range [0, p ⫺ c⬘2), where p ⫽ 1 ⫹ c⬘1. 3 The model has been programmed in GAMS, see Brooke et al. (1992). 4 The increase was unfortunately not based on a rapid and robust algorithm, the size was rather a fixed ratio which was set “pragmatically” to reach convergence.
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Fig. 1. Production by company, TWh/year. VAT, Vattenfall (SWE); SYD, Sydkraft (SWE); IVO, Imatran Voima (FIN); STA, Statkraft (NOR); ELS, Elsam (DEN); ELK, Elkraft (mainly Sjællandske Kraftværker) (DEN).
each producer, i.e. a supply curve equilibrium. Given the other producers’ supply functions, no producer can increase its profit by changing its strategy (i.e. the margin). Hence we have reached a Nash equilibrium. We have not extensively investigated whether our algorithm finds a unique equilibrium or just one of many possible equilibria. This can be done theoretically, or as we have done, by choosing different starting points, and see if they converge with the same set of supply curves. The latter seems to give stable results, indicating that the results presented above represent a global equilibrium.
4. Model simulations 4.1. “Base case” Fig. 1 shows the production of the largest producers under the assumption of perfect competition, i.e. where the price equals the short-term marginal production costs, and under the assumptions of oligopolistic competition. From the figure we see that the largest Swedish generator Vattenfall, and to some extent the Finnish generator IVO, both have incentives to force the spot price up by reducing their market supply. Under oligopolistic conditions, the calculated price lies slightly under 2.5 ¢/kWh (cf. The Norwegian Central Grid), which is 15% above the perfect competitive price equilibrium. Vattenfall’s relatively low output reflects the company’s large market share, some 20% of the Nordic market and around 50% of the total Swedish production. Whether or not it will be profitable to exercise market power depends on a two-part calculation. Firstly, if some of the capacity is removed from the market, the econ-
omic contribution margin5 of this production will lapse. For such a decision to be profitable, this lapse must be compensated by the increase in contribution margin for the remaining production which follows from the increased prices. The greater the market share, the greater will be the volume which achieves a larger contribution margin, making it more profitable to exercise market power to begin with. It is interesting to note that Statkraft has scant incentives to reduce output, because its generating capacity is 100% based on hydropower. In hydro-based plants, as noted in Section 3, the contribution margin of marginal production equals almost 100% of the power price. This means that the price must increase more sharply for the company to defend a decision not to exploit all of its production capacity. The calculations thus clearly indicate that the Nordic hydropower generators—including Vattenfall, which has a nearly 50/50 hydro/nuclear capacity portfolio—will find it more profitable to utilise their hydropower generating capacity to the full. Fig. 1 also shows that supply from independent noncollusive generators within the Nordic market and the Danish generators Elsam and Elkraft increase somewhat due to the higher prices. However, the calculations also indicate that there is little capacity available at prices below 2.5 ¢/kWh among all the small generators, which otherwise would have made it unprofitable for Vattenfall and IVO to exercise any significant degree of market power. It is interesting that the Danish generators contribute to reducing the largest power producers’ incentives to exercise market power. The home markets of these companies are (so far) sheltered and prices to end5 Contribution margin ⫽ market price minus variable production costs.
A. Halseth / Utilities Policy 7 (1998) 259–268
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users have remained fairly independent of prices in the overall Nordic market. This in turn means that a higher Nordic spot price will have little influence on the yield of the Danish firms, so Elsam and Elkraft may increase their yield per produced kWh through a reduction of capacity utilisation only to a limited extent6. The fact that Finland’s IVO has incentives to exercise market power reflects two interesting aspects. Firstly, the marginal production of the company involves coal condensation. Operating costs in these plants were relatively high due to CO2 charges (around 2.31 ¢/kWh in 1995)7 Such taxation results in low contribution margins on the capacity being withdrawn from the market, which again increases the incentives to exercise market power. In addition, bottlenecks between Sweden and Finland create protection for IVO in the sense of limiting the extent to which the company’s dominant position in the Finnish market might be substituted by import. 4.2. The importance of bottlenecks and border tariffs8 In recent years, there has been a process within and between the Nordic countries for closer integration of national electricity markets. Central to the debate here has been whether such integration will influence incentives to exercise market power. Fig. 2 shows the effects on market prices of removing cross-border protective regulations (illustrated by border tariffs in the model) at all the Nordic interconnectors. In 1995 such tariffs were implemented on all interconnectors, except those between Denmark and Norway. In January 1996 the tariffs on the Swedish/Norwegian border were banished, and it is expected that the tariffs on the Swedish/Finnish interconnectors will be removed in the course of 1998/99. The column for “Base case (O)” shows the prices in the situation which is described in Section 4.1, i.e. that prices in Norway and Sweden are different as a consequence of border tariffs. When these are removed (“No interconn. tariffs (O)”), prices will converge. However, we also see that a reduction in border tariffs will tend to increase Norwegian prices (and Danish production costs) more than it tends to reduce Swedish prices. The reason is that, if common Nordic prices are introduced, Vattenfall will reduce its production further, so as to keep prices up. Since there is no shelter for the Swedish market under “free trade” conditions, Vattenfall will be “forced” to keep prices up in the entire Nordic market. As for IVO, free trade paradoxically leads to even higher prices and increased production. This is perhaps 6 In line with the plans of opening up for competition in the Danish market, however, the Danish producers’ incentives to exercise market power will be stronger. 7 The CO2 tax was removed in 1997. 8 Tariffs charged for the use of interconnectors.
Fig. 2. Power prices by country. O, oligopolistic competition; PC, perfect competition. The “price” in Denmark corresponds to the plants’ marginal production costs.
a counter-intuitive result, since generally free trade would be expected to increase competition and reduce prices, in the Finnish market. However, reduced trade barriers make base-load Finnish exports to Sweden more profitable, but bottlenecks make it impossible to increase imports during peak-load periods. So Finnish net export (and production) increases, and that leads to higher overall prices and higher domestic production. 4.3. Sensitivity to demand levels The basis for the analysis this far has been an underlying consumer price corresponding to the autumn 1995 level. Let us see whether the incentives to exercise market power change under the assumption of a tightening of the market with higher prices. Fig. 3 shows how output is distributed between companies, where “1995” equals the demand level which has been applied until now, and “ ⫹ 20%” refers to a partial increase (20%) in the underlying consumption. In the calculations, the price level increases from around 2.5 ¢/kWh to slightly less than 3.4 ¢/kWh in the Norwegian part of the market. The price under perfect competition equals 3.2 ¢/kWh. We see that Vattenfall’s incentives to exercise market power are clearly reduced. While 18 TWh/year of its
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A. Halseth / Utilities Policy 7 (1998) 259–268
Fig. 3.
Output held out of the market by demand alternative.
generating capacity (i.e. the difference in production between oligopolistic and perfect competition) is being held out of the market with an underlying demand corresponding to that of 1995, only 3 TWh are held out under a 20% increase in demand. The reason for such a large difference is that prices increase considerably in a tighter market. Increased prices mean an increased contribution margin in Vattenfall’s nuclear power plants, which in turn means that the “cost” of keeping this part of the capacity out of the market increases. The difference in production between perfect and oligopolistic competition is that the company keeps some thermal plants with marginal costs at some 3.1 ¢/kWh out of the market. Sydkraft is in the same situation. 4.4. Trade with the European continent In recent years, Norwegian power generators have seen increased trade with the Continent as an interesting business opportunity. Three long-term contracts have been signed, and a corresponding number of interconnectors to Germany and the Netherlands are being planned. Swedish and Danish companies have also entered into similar agreements with Continental counterparts. One element keenly debated in these agreements is the partners’ exclusive right to use the cables. Some fear that the generators will execute their rights in order to increase prices by “draining” the Nordic power market. Calculations indicate that the new cable connections will be used for net import under perfect competition. The trade pattern reflects the system and cost differences between hydro-based systems and thermal-power-based systems. Since hydro-plants are competitive for peak load production (due to the relatively low costs related to load management and marginal generating capacity), the cables are used for export from the Nordic countries to the European Continent in top load periods. During
medium and low load periods, capacity in the thermal power plants will normally not be exploited to the full, and production costs will only reflect fuel costs. This means it will be profitable to use the cables for import from the Continent during such periods. Calculations also indicate that the market power connected to the exclusivity of the cable connections is a limited problem. Statkraft seems to have incentives not to exploit its import possibilities to the full during medium and low load periods. Vattenfall, on the other hand, seems to find it profitable to export as much as possible through its connections, independent of load type. However, the fact that Statkraft has extra import possibilities contributes to limiting Vattenfall’s incentives to keep nuclear capacity out of the market. This is due partly to a reduction in Vattenfall’s market share following the net import from the Continent and partly to available import capacity by Statkraft under low and medium load. Taken together, the new connections to the Continent therefore reduce the problem of market power in the Nordic market. 4.5. Cooperation The model concept may help to shed light on the question of whether the generators will profit from collaborating on keeping capacity out of the market. In the calculations, this has been illustrated by testing the degree to which varying constellations are better off by collaborating than they are when playing non-cooperative strategies represented by the Nash–Cournot equilibrium, assuming a pro rata reduction in supply to the market. This analysis shows that large producers will find it increasingly profitable to collaborate as more and more companies join in. This is natural because the market share increases and because competition between the generators by definition is reduced in terms of number of competitors and market concentration.
A. Halseth / Utilities Policy 7 (1998) 259–268
The next important finding is that Vattenfall participates in all profitable constellations. This reflects the fact that the costs associated with keeping volumes off the market are now distributed to some of the other generators, which gives Vattenfall a relatively larger market share at a given market price. Finally, we find that none of the constellations where Vattenfall does not participate are profitable. This model result shows that if Vattenfall decides not to cooperate in keeping prices high, the company will increase its output if prices are forced up as a result of the cooperation of other generators. 4.6. Conclusion The most important result of the calculations is that the problem of market power mainly turns on Vattenfall. However, the company may only manipulate the market prices through reduced production in the nuclear plants. For many reasons, a low exploitation of capacity in the nuclear plants is unrealistic, something that reminds us of the limitations connected to such model analyses. Firstly, there are several owners of the Forsmark plant. Admittedly, Vattenfall has around 50% of the shares, but the company may of course not decide the day-to-day running of the plant alone. Secondly, the current debate concerning a removal of all nuclear power in Sweden probably requires considerable caution, assuming that they want to keep the plants in the long run9. A low exploitation of capacity may lead antinuclear activists to question the need for the plants, or their safety, if a capacity reduction is explained by increased maintenance periods. Third, there has been no evidence so far that Vattenfall has a low utilisation in their plants. Further, there is no evidence that Vattenfall abuses the exclusive rights on the interconnectors, which the model simulations suggest would be profitable.
5. Different market models give different results There is a growing literature using model simulations like ours to anlayse market power. In this section we’ll examine in more detail the importance of the model applied to the differences in results between market power studies, i.e. this paper report much less incentives to use market power to raise prices than similar. In our model framework the Cournot model is characterised by assuming that the market actors behave as if they expect the supply functions to all other producers to be vertical. The margin between marginal costs and 9 The Swedish government proposed to go further with the moratorium by suggesting that one reactor be closed down by June 1998. Sydkraft, which owns the reactor, is disputing the legal grounds of these proceedings, and at the end of 1998 the case remained unsolved.
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market prices is then completely a function of market share and demand price elasticity. The Cournot model will hence predict more potential market power than the model used in our calculations. Bushnell and Borenstein (1997) use a Cournot model to study market power in a deregulated Californian market. They report a significant potential for market power especially in peak periods, i.e. in periods where the competitive fringe utilises its full capacity and the large producers’ market share is relatively high. The Cournot model is also applied in several other papers examining market power in stylised three node electrical networks with loop flow effects, see Oren (1997) and Hogan (1997). Green and Newbery (1992) use a supply function equilibrium model in a study of market power in the UK market. The calculated prices are around 50% higher than the competitive prices. This paper follows a more general Klemperer and Meyer concept, taking explicit account of several possible equilibria within the model framework. Expressed by Eq. (10), Green and Newbery assume a positive slope on the supply functions, due to continuous convex cost functions10 and a non-negative derivative of the margin () with respect to output (X). Both assumptions will in general imply steeper supply functions and therefore stronger incentives to exercise market power. However, since the “classical” Cournot model on average represents an upper limit on the margin, the Green and Newbery model will predict less incentive to abuse a dominant market position than the Borenstein and Bushnell paper. This short comparison may shed some light on why our paper ends up with calculations showing much less potential for market power than the studies mentioned above. It is partly due to differences in the model framework, and of course partly due to a completely different structure between the Nordic, UK and Californian markets. We will not argue that one model gives more reliable results than others. Generally the oligopoly theory is inconclusive, and there are major differences in regulatory framework, traditions and structure between electricity markets. However, this paper suggests one should try out different market power models before drawing strong conclusions based on model simulations.
Acknowledgements The author would like to thank James B. Bushnell, fellow colleagues at ECON, Hill Huntington, Frank Wolak, and one anonymous referee for useful comments. Support from the Norwegian Research Council and The Federation of Norwegian Electricity Utilities is greatly acknowledged.
10
This point is also noted in Von der Fehr and Harbord (1993).
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References Brooke, A., Kendrick, D., Meeraus, A., 1992. GAMS: A User’s Guide, Release 2.25. The International Bank for Reconstruction and Development/The World Bank, 1992. Bushnell, J., Borenstein, S., 1997. An empirical analysis of the Potential for Market Power in California’s Electricity Industry. Paper presented at Power Conference, Berkeley 14 April 1997. Green, R., Newbery, D., 1992. Competition in the British Electricity Spot Market. Journal of Political Economy 5, 929–953. Green, R., 1996a. Increasing Competition in British Electricity. Journal of Industrial Economics 2, 205-216.
Green, R., 1996b. The Electricity Contract Market. University of Cambridge, Department of Applied Economics Working Paper, Amalgamated Series: 9616. Hogan, W., 1997. A Market Power Model with Strategic Interaction in Electricity Networks. The Energy Journal 18 (4), 107–141. Klemperer, P., Meyer, M., 1989. Supply Function Equilibria in Oligopoly Under Uncertainty. Econometrica November 57 (6), 1243– 1277. Oren, S., 1997. Economic Inefficiency of Passive Transmission Rights in Congested Electrical System with Competitive Generation. The Energy Journal 18 (1), 63–83. von der Fehr, N.H., Harbord, D., 1993. Spot Market Competition in the UK Electricity Industry. Economic-Journal 103 (418), 513–546.
Market power in the Nordic electricity market Arve Halseth
*
ECON Centre for Economic Analysis, PO Box 6823, St Olavs plass, N-0130, Norway
Abstract This paper investigates the potential for market power in the Nordic electricity power market. Numerical simulations have been conducted using ECON’s model for the electricity market. A special case of a supply curve equilibrium model is used to describe strategies of the large producers. The conclusion is that the largest producer, Vattenfall, has incentives to withdraw some nuclear capacity from the market in order to raise spot market prices. However, Vattenfall’s incentives are to some extent limited by the excess capacity of the smaller producers. The model also indicates that it may be profitable for Vattenfall to operate its nuclear plants at full capacity if market prices increase due to exogenous factors, e.g. consumption growth. The simulations do not indicate that hydro production will be withheld, because of the low marginal operating costs in these plants. 1999 Elsevier Science Ltd. All rights reserved. Keywords: Electric utilities; Production pricing; Market structure; Size distribution of firms
1. Introduction This paper presents a quantitative analysis of the extent to which the large Nordic power producers have incentives to exercise market power. The analysis concentrates on how the producers will schedule existing plants, i.e. on whether they consider it profitable to reduce production in order to force the spot price up. We will not consider the extent to which strategic interests will influence the investment in new capacity. Simulations that have been conducted using ECON’s model of the Nordic power market are used as a point of departure for the analysis. In this model, the producers strategy has been modelled according to a special case of a supply curve equilibrium model (see Klemperer and Meyer, 1989). An equilibrium is calculated on the basis of an interactive non-cooperative game among the producers, where the supply curve of each individual producer is a function of its marginal production costs, capacity, the price elasticity of demand, and the extent to which the other producers will adjust their output to changes in market prices. Whether the individual producers will find it profitable to exercise market power depends on a large number of factors. We will therefore start the analysis by consider-
* E-mail: [email protected]
ing a “base case” where external factors such as the framework for the market, the level of consumption, and production and transmission costs correspond to autumn 1995 values. Next, we will consider whether the incentives to exercise market power are influenced by the degree of integration between the Nordic countries, or the demand level (i.e. the underlying price level in the market). Before the model analysis is carried out, a brief presentation of the Nordic electricity market and the model concept is given.
2. The Nordic electricity market There is a clear trend toward a liberalised Nordic electricity market. The Norwegian Energy Act was passed in 1991, and competition in Norway’s national market is intensive. Sweden and Finland have also restructured their electricity sectors along the same line as Norway’s. In Denmark, discussions are ongoing, with some form of restructuring as the likely result. The key elements in the reforms are access to the grid for third parties, regulated grid tariffs (to prevent monopoly profit), and a “postage stamp system” or “point tariff system” is implemented (which means that consumers are paying the same grid tariff, not influenced by which supplier they choose). The electricity systems in the Nordic region are
0957-1787/99/$ - see front matter 1999 Elsevier Science Ltd. All rights reserved. PII: S 0 9 5 7 - 1 7 8 7 ( 9 9 ) 0 0 0 0 3 - X
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Table 1 Production capacity, GW (1995)
Hydro Nuclear Conventional thermal Renewables
Norway
Sweden
27.3a
16.2a 10.0 8.3
0.3
Denmark
Finland
9.6 0.6
2.8a 2.3 9.6
Source: Nordel. a Hydro production is limited by the inflow of water, 113 TWh in Norway, 64 TWh in Sweden and 12 TWh in Finland.
closely connected with several interconnectors. There has been extensive trade between these countries over the last 30 years, mainly to take advantage of the differences in production costs between the predominantly hydro systems in Norway and Sweden, and the predominantly thermal based systems elsewhere (see Table 1). Over the last 5 years, a more integrated Nordic market has evolved. Currently, the interconnectors are, with some exemptions, operated under the same competitive principals as the national grid in Norway. The mix of production capacity is shown in Table 1, illustrating a well differentiated supply side in the region as a whole. Most of the demand can be met by hydro and nuclear sources, making coal the marginal technology in normal situations. However, in periods with low precipitation, oil-condensing plants may be the marginal source. Conversely, nuclear power may be marginal in situations with high hydro inflow. The electricity demand in the region is around 350 TWh/year and peak demand was 54 GW in 1995 (see Table 2). Power intensive industries like aluminium, pulp and paper, ferroalloys, chemicals, etc., consume around 1/3 of the total electricity. Residential consumption is also high, especially in Norway where electricity is used for heating.
3. Model concept ECON’s model calculates prices, power production, consumption and trade in the Nordic market (Norway, Sweden, Denmark and Finland). Equilibrium is calculated for each month throughout a year. Each month is further split into three typical load periods, nights/weekends, medium load and peak hours. In total Table 2 Peak demand GW (1995) Norway Sweden Denmark Finland Source: Nordel.
17.7 20.6 5.8 9.9
12 ⫻ 3 ⫽ 36 periods are calculated simultaneously in the model. 3.1. Consumption The demand (d) in country i, sector c at time t ⫽ 1…36 is modelled by the following Cobb Douglas function: dc,i,t ⫽ ␣c,i,tPt c,i
(1)
where P is the market price and  the price elasticity of demand. Subscript t represents the periods. The subscript i represents the countries Norway, Sweden, Denmark (Jylland and Sjælland) and Finland. Subscript c includes different sectors like residential, small industry, services, power intensive industry and large electric boilers. Each sector is not represented in every country (only Norway and Sweden have a significant consumption in electric boilers and Denmark does not have a power intensive industry). Hence, 17 different consumer groups are modelled. The price elasticity () is dependent on both country and sector and is on average approximately ⫺ 0.5. The transmission costs and excise taxes account for around 30–50% of the total electricity price paid by end consumers. This gives a demand price elasticity around ⫺ 0.25 to ⫺ 0.35 at the producer’s price level. We have chosen to use estimated annual price elasticities reported by Statistics Norway, which normally is significantly higher than short-term elasticities (e.g. on a weekly or hourly basis). Since price elasticity influences the incentives to exercise market power heavily, different assumptions may give rise to contrary conclusions when market power is debated. Even if demand is rather inelastic in the short term, we will argue that producers must discount long-term effects through the contract markets if they’re considering exercising market power. The contract market is not modelled explicitly. Instead we assume that contract prices will fully reflect the expected spot market prices, and in equilibrium all consumers will in reality face the spot price. Hence, it is probably adequate to use an annual price elasticity in the model. This assumption is quite different than that
A. Halseth / Utilities Policy 7 (1998) 259–268
used by Green (1996b) and consequently contracts will not necessarily mitigate market power, as argued in this paper. The constant term ␣ is calibrated so that the model results correspond to the actual observed combination of annual price and consumption in each sector and country. The constant term is calibrated according to the level of demand in autumn 1995. All of the simulations presented below cover this time frame. Variations due to seasonal demand and different load categories are also represented by the constant term ␣. Indexing the Norwegian average demand to 100, Table 3 shows the variation in the constant terms by country over the year. 3.2. Transmission The transmission grid is represented in the model by a flow matrix (Tt,i,j where subscript i is the exporting country, subscript j is the importing country, D is aggregated consumption and X is the aggregated production). Dt,i ⫹
冘
Tt,i,j ⫽ Xt,i ⫹
j
冘
Tt,j,i
Even though this concentration is relatively modest compared with other markets, some smaller participants allege that the large utilities are abusing their dominant positions. In the model, the supply side in each country is formally represented by different types or classes (l) of power stations. Each class is assigned a marginal operating cost [c⬘(x)] where x is the level of production. Hydro and nuclear stations are modelled as one class each, while the thermal stations are differentiated in up to six categories, characterised by type of fuel (oil, coal and natural gas) and the energy conversion rate. Further, the production is restricted by the installed capacity (xc) within each class and by the requirement for annual maintenance (m). m represents the time for which a plant is taken out for maintenance (typically between 10 and 20% or 876 and 1752 hours annually). Formally we may write a producer’s (K) maximising problem as: max
冘
(ptxt,k,l ⫺ c(xt,k,l))
(4)
t,l
(2)
xt,k,l ⱕ xck,l
(5)
(3)
冘
(6)
j
Tt,i,j ⱕ T ci,j
261
t
Import and export between the different countries is restricted by the capacity in the grid, T ci,j . Losses are represented as a fixed percentage of the volume and transmission is charged with a tariff (t). The central grid itself (lines and nodes) is not modelled which means that loop flow effects are not considered explicitly in the model. The constraints on transmission are based on information from the Nordic ISOs and reflect their experience on the import/export capacity given the normal Nordic load pattern. 3.3. Production The supply side is represented by different producers who have different technologies and capacity at their disposal (Table 4). There is some concentration on the supply side in the market. The Swedish producer Vattenfall has a market share of around 20% of the annual Nordic electricity production. In addition, a number of other producers have market shares of between 5 and 10%.
1 x ⱕ mxck,l t t,k,l
The inter-temporal aspects in Eq. (6) imply that the model is solved for all 36 periods simultaneously. Hence, the producers are assumed to have rational expectations. The marginal operating costs in the hydro [c⬘(x)] and nuclear plants are relatively low, 0–1 ¢/kWh. Most of the Danish and Finnish thermal capacities are coal based, implying a marginal cost of between 1.5 and 2 ¢/kWh. The rest of the capacity, mainly oil condensing plants, has relatively high operating costs (3–5 ¢/kWh), implying relatively high prices in periods with high demand and/or low inflow. Because of the hydro dominance in the Nordic electricity market, the hydro scheduling is a central part of the model. The market share of hydro production is around 50% of the annual production, and the reservoir capacity is around 2/3 of the annual average inflow. The inflow peaks in summer while consumption is highest in the winter because electricity is used for room heating.
Table 3 Seasonal variations in demand in the Nordic region, index
Peak load winter Night/weekends summer
Norway
Sweden
147.5 62.5
177.3 73.0
Note: Average Norwegian demand equals 100.
Denmark 56.1 18.5
Finland 84.4 36.7
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Table 4 The main producers’ capacities, TWh/year Hydro
Statkraft, Norway Vattenfall, Sweden Sydkraftb, Sweden IVOb, Finland Elsam and Elkraft, Denmark Independent producers
Nucleara
33.7 35.6 7.0 6.9
40.5 17.5 8.5
104.8
21.5
Thermala
8.9 6.0 18.0 58.2 103.5
Market share (%) 7.1 18.0 6.4 7.1 12.3 48.8
a
7.000 hours of operation is assumed. The market shares of both IVO and Sydkraft have increased since 1996 through mergers with smaller producers. In addition, cross-ownership and alliances are established between producers.
b
The hydro power supply from day to day depends heavily on the expected future market conditions, i.e. water is stored (released) if spot prices are expected to increase (decrease). The inter-temporal hydro optimisation is formally modelled by restricting annual hydro production to be less than annual inflow (w). Further, inflow may be stored (ma) between periods, but the storage must be within the reservoir capacity (mac). Formally we may add the following constraints to the maximising problem (3):
冘
xt,k,hyd ⱕ
冘
wt,k
(7)
mat ⫹ 1,k ⱕ mat,k ⫹ wt,k ⫺ xt,k,hyd
(8)
mat,k ⱕ mack
(9)
t
t
3.4. Market power The point of departure when modelling the market power is a simple supply function equilibrium model (Klemperer and Meyer, 1989). It can be shown that such models generally do not have a unique equilibrium, unless one assumes an unrealistically large (for the Nordic market) range of demand. Hence, in the simulations we have restricted the producer’s strategy to the submission of linear supply functions to the market, characterised by a constant mark up relative to the shortterm marginal production costs. Although we are using linear supply functions, our approach is somewhat different to that of Green (1996a). In that paper, the mark up is proportional to the level of production and the production costs are represented by a continuous quadratic function with no capacity constraints. For simplicity, we have assumed that the producers do not face uncertainty with respect to consumption when the bids are submitted. Following Green and Newbery (1992), they do, however, face a range of demand levels for different
time periods to which a single supply curve must be applied. In the following discussion of our restricted supply curve model, we have simplified the notation a great deal relative to the full specification of the numerical model. The supply function can mathematically be represented as follows, assuming that one producer only possesses one technology and hence faces only one capacity constraint. Pt ⫽ t,k ⫹ c⬘(xt,k)
(10)
For a particular level of production (xt,k), the producer (k) will have a specific marginal cost (c⬘), which in turn will depend on that firm’s marginal technology (hydro, nuclear or thermal) and capacity constraints. For thermal plants, the marginal production costs are determined by the price of fuel and the energy conversion rate. In Eq. (10), the capacity constraints will imply a discontinuity in the cost function, i.e. c⬘(xct,k) ⫽ ⬁. In hydro stations, inflow and reservoir may be constrained as well. To realise a production level xt,k, Eq. (10) implies that the price must at least be high enough to cover the production cost and a mark up (). We have restricted the numerical model further by assuming that each producer’s supply function is characterised by a single (i.e. not differentiated with respect to technology). The margin may, however, vary between the different time periods and load situations. It is assumed that each producer submits its supply function to the market simultaneously. In a perfectly competitive market, the supply functions will be characterised by the marginal costs only, i.e. equals 0. If is increased, the supply curve is shifted upwards, and given a downward sloping demand curve, output will decrease as price increases. One more analytical point of departure may help us to interpret Eq. (10) more closely. We find the optimal production for producer k by differentiating the profit function (11).
A. Halseth / Utilities Policy 7 (1998) 259–268
t,k ⫽ ptxt,k ⫺ c(xt,k)
(11)
The first order condition1 is: dpt x ⫹ pt ⫺ c⬘(xt,k) ⫽ 0 dxt,k t,k
(12)
By differentiating the inverse demand function (p ⫽ D(Xt), where Xt ⫽
冘
xt,k and D⬘ ⬍ 0) we find
k
冉 冘 冊
dpt ⫽ D⬘(Xt) 1 ⫹ dxt,k
o
dxt,o , for o⫽k dxt,k
3.5. Solving the model3
(14)
冉
dpt 1 dpt ⫽ D⬘(Xt) 1 ⫹ dxt,1 c⬙(xt,2) dxt,1
冊
(15)
Rearranging Eq. (15) (i.e. finding ␦p/␦x1) and inserting in Eq. (12):
冘 c,i,t
⫺
−
1
1 ⫹ c,i
c,i c,i  ␣c,i,t Dc,i,j 1 ⫹ c,i
冘
⫺
冘 (
k
⫹ ct,k,l)xt,k,l
with perfect competition, i.e. price will equal marginal production costs. 쐌 If producer 2 never has excess capacity2, i.e. c⬙2 is infinite for all x1, the expression within the parentheses will be reduced to D⬘, which corresponds to the classical Cournot model. 쐌 Between the two extremes, 1’s production will determine whether 2 has excess capacity or not (and viceversa). In this case, several equilibria may occur, i.e. either one producer will exercise market power (and the other will produce at full capacity) or an equilibrium may be determined in mixed strategies.
(13)
For simplicity, assume only two producers. We can find an expression for how producer 1 will respond if producer 2 changes his output by differentiating Eq. (10) and substituting it in Eq. (13): dpt dxt,2 ⫽ c⬙(xt,2) dxt,1 dxt,1
(16)
For a given set of producer strategies () the model is solved by optimisation. The objective is the “area” underneath the demand curve, i.e. integrating the inverse demand function (1) minus production and transmission costs, given the constraints (5)–(9) above.
冘 c,i,t
⫺
(a)
(b)
(c)
쐌 If producer 2 always has excess capacity, i.e. c⬙2 ⫽ 0 for all x1, the fraction inside the parentheses equals zero, and hence the optimal is 0. The supply curve equilibrium will in this case correspond to the equilibrium
(d)
dpt d2pt x ⫹ ⫺ c⬙(xt,k) ⱕ 0 dx2t,k t,k dxt,k Profit max is reached unless the demand function is very concave.
(
k
⫹ ct,k,l)xt,k,l
(17)
t,k,l
ti,j Tt,i,j
The margins () are endogenous in the model. An equilibrium may be found as follows.
Eqs. (16) and (10) imply that 1 (defined as the difference between p and c⬘1) is a function of the price sensitivity of demand (D⬘) and the cost function of producer 2 (c⬙2). If we assume that power production is characterised by constant marginal costs (i.e. c⬘(x) ⫽ c) if production is not constrained by its capacity, we can distinguish between three situations.
Order condition:
冘
t,i,j
t,k,l
ti,j Tt,i,j
1 ␣−c,iD1 ⫺ c,i ⫺ 1 ⫺ c,i c,i,t c,i,j
冘
t,i,j
1
263
First iteration: each producer is given a margin () equal to 0 or any other arbitrarily chosen start point. Each producer’s supply function is aggregated up to a supply function for the whole market, and the market-clearing price is found. Second iteration: for one producer at a time evaluate if reduced output will increase profit compared with the market equilibrium in the first iteration. If so, increase4 , if not decrease . After this procedure is repeated for all large producers, a new supply curve is aggregated up, and a new market price is calculated. Repeat (c) until doesn’t change when another iteration is done.
The calculated margins () will through Eq. (10) represent the optimal or profit maximising supply curve for 2 Note that if producer 2 is at full capacity in optimum and 1 is withholding capacity, 2 is not uniquely determined only in the range [0, p ⫺ c⬘2), where p ⫽ 1 ⫹ c⬘1. 3 The model has been programmed in GAMS, see Brooke et al. (1992). 4 The increase was unfortunately not based on a rapid and robust algorithm, the size was rather a fixed ratio which was set “pragmatically” to reach convergence.
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Fig. 1. Production by company, TWh/year. VAT, Vattenfall (SWE); SYD, Sydkraft (SWE); IVO, Imatran Voima (FIN); STA, Statkraft (NOR); ELS, Elsam (DEN); ELK, Elkraft (mainly Sjællandske Kraftværker) (DEN).
each producer, i.e. a supply curve equilibrium. Given the other producers’ supply functions, no producer can increase its profit by changing its strategy (i.e. the margin). Hence we have reached a Nash equilibrium. We have not extensively investigated whether our algorithm finds a unique equilibrium or just one of many possible equilibria. This can be done theoretically, or as we have done, by choosing different starting points, and see if they converge with the same set of supply curves. The latter seems to give stable results, indicating that the results presented above represent a global equilibrium.
4. Model simulations 4.1. “Base case” Fig. 1 shows the production of the largest producers under the assumption of perfect competition, i.e. where the price equals the short-term marginal production costs, and under the assumptions of oligopolistic competition. From the figure we see that the largest Swedish generator Vattenfall, and to some extent the Finnish generator IVO, both have incentives to force the spot price up by reducing their market supply. Under oligopolistic conditions, the calculated price lies slightly under 2.5 ¢/kWh (cf. The Norwegian Central Grid), which is 15% above the perfect competitive price equilibrium. Vattenfall’s relatively low output reflects the company’s large market share, some 20% of the Nordic market and around 50% of the total Swedish production. Whether or not it will be profitable to exercise market power depends on a two-part calculation. Firstly, if some of the capacity is removed from the market, the econ-
omic contribution margin5 of this production will lapse. For such a decision to be profitable, this lapse must be compensated by the increase in contribution margin for the remaining production which follows from the increased prices. The greater the market share, the greater will be the volume which achieves a larger contribution margin, making it more profitable to exercise market power to begin with. It is interesting to note that Statkraft has scant incentives to reduce output, because its generating capacity is 100% based on hydropower. In hydro-based plants, as noted in Section 3, the contribution margin of marginal production equals almost 100% of the power price. This means that the price must increase more sharply for the company to defend a decision not to exploit all of its production capacity. The calculations thus clearly indicate that the Nordic hydropower generators—including Vattenfall, which has a nearly 50/50 hydro/nuclear capacity portfolio—will find it more profitable to utilise their hydropower generating capacity to the full. Fig. 1 also shows that supply from independent noncollusive generators within the Nordic market and the Danish generators Elsam and Elkraft increase somewhat due to the higher prices. However, the calculations also indicate that there is little capacity available at prices below 2.5 ¢/kWh among all the small generators, which otherwise would have made it unprofitable for Vattenfall and IVO to exercise any significant degree of market power. It is interesting that the Danish generators contribute to reducing the largest power producers’ incentives to exercise market power. The home markets of these companies are (so far) sheltered and prices to end5 Contribution margin ⫽ market price minus variable production costs.
A. Halseth / Utilities Policy 7 (1998) 259–268
265
users have remained fairly independent of prices in the overall Nordic market. This in turn means that a higher Nordic spot price will have little influence on the yield of the Danish firms, so Elsam and Elkraft may increase their yield per produced kWh through a reduction of capacity utilisation only to a limited extent6. The fact that Finland’s IVO has incentives to exercise market power reflects two interesting aspects. Firstly, the marginal production of the company involves coal condensation. Operating costs in these plants were relatively high due to CO2 charges (around 2.31 ¢/kWh in 1995)7 Such taxation results in low contribution margins on the capacity being withdrawn from the market, which again increases the incentives to exercise market power. In addition, bottlenecks between Sweden and Finland create protection for IVO in the sense of limiting the extent to which the company’s dominant position in the Finnish market might be substituted by import. 4.2. The importance of bottlenecks and border tariffs8 In recent years, there has been a process within and between the Nordic countries for closer integration of national electricity markets. Central to the debate here has been whether such integration will influence incentives to exercise market power. Fig. 2 shows the effects on market prices of removing cross-border protective regulations (illustrated by border tariffs in the model) at all the Nordic interconnectors. In 1995 such tariffs were implemented on all interconnectors, except those between Denmark and Norway. In January 1996 the tariffs on the Swedish/Norwegian border were banished, and it is expected that the tariffs on the Swedish/Finnish interconnectors will be removed in the course of 1998/99. The column for “Base case (O)” shows the prices in the situation which is described in Section 4.1, i.e. that prices in Norway and Sweden are different as a consequence of border tariffs. When these are removed (“No interconn. tariffs (O)”), prices will converge. However, we also see that a reduction in border tariffs will tend to increase Norwegian prices (and Danish production costs) more than it tends to reduce Swedish prices. The reason is that, if common Nordic prices are introduced, Vattenfall will reduce its production further, so as to keep prices up. Since there is no shelter for the Swedish market under “free trade” conditions, Vattenfall will be “forced” to keep prices up in the entire Nordic market. As for IVO, free trade paradoxically leads to even higher prices and increased production. This is perhaps 6 In line with the plans of opening up for competition in the Danish market, however, the Danish producers’ incentives to exercise market power will be stronger. 7 The CO2 tax was removed in 1997. 8 Tariffs charged for the use of interconnectors.
Fig. 2. Power prices by country. O, oligopolistic competition; PC, perfect competition. The “price” in Denmark corresponds to the plants’ marginal production costs.
a counter-intuitive result, since generally free trade would be expected to increase competition and reduce prices, in the Finnish market. However, reduced trade barriers make base-load Finnish exports to Sweden more profitable, but bottlenecks make it impossible to increase imports during peak-load periods. So Finnish net export (and production) increases, and that leads to higher overall prices and higher domestic production. 4.3. Sensitivity to demand levels The basis for the analysis this far has been an underlying consumer price corresponding to the autumn 1995 level. Let us see whether the incentives to exercise market power change under the assumption of a tightening of the market with higher prices. Fig. 3 shows how output is distributed between companies, where “1995” equals the demand level which has been applied until now, and “ ⫹ 20%” refers to a partial increase (20%) in the underlying consumption. In the calculations, the price level increases from around 2.5 ¢/kWh to slightly less than 3.4 ¢/kWh in the Norwegian part of the market. The price under perfect competition equals 3.2 ¢/kWh. We see that Vattenfall’s incentives to exercise market power are clearly reduced. While 18 TWh/year of its
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Fig. 3.
Output held out of the market by demand alternative.
generating capacity (i.e. the difference in production between oligopolistic and perfect competition) is being held out of the market with an underlying demand corresponding to that of 1995, only 3 TWh are held out under a 20% increase in demand. The reason for such a large difference is that prices increase considerably in a tighter market. Increased prices mean an increased contribution margin in Vattenfall’s nuclear power plants, which in turn means that the “cost” of keeping this part of the capacity out of the market increases. The difference in production between perfect and oligopolistic competition is that the company keeps some thermal plants with marginal costs at some 3.1 ¢/kWh out of the market. Sydkraft is in the same situation. 4.4. Trade with the European continent In recent years, Norwegian power generators have seen increased trade with the Continent as an interesting business opportunity. Three long-term contracts have been signed, and a corresponding number of interconnectors to Germany and the Netherlands are being planned. Swedish and Danish companies have also entered into similar agreements with Continental counterparts. One element keenly debated in these agreements is the partners’ exclusive right to use the cables. Some fear that the generators will execute their rights in order to increase prices by “draining” the Nordic power market. Calculations indicate that the new cable connections will be used for net import under perfect competition. The trade pattern reflects the system and cost differences between hydro-based systems and thermal-power-based systems. Since hydro-plants are competitive for peak load production (due to the relatively low costs related to load management and marginal generating capacity), the cables are used for export from the Nordic countries to the European Continent in top load periods. During
medium and low load periods, capacity in the thermal power plants will normally not be exploited to the full, and production costs will only reflect fuel costs. This means it will be profitable to use the cables for import from the Continent during such periods. Calculations also indicate that the market power connected to the exclusivity of the cable connections is a limited problem. Statkraft seems to have incentives not to exploit its import possibilities to the full during medium and low load periods. Vattenfall, on the other hand, seems to find it profitable to export as much as possible through its connections, independent of load type. However, the fact that Statkraft has extra import possibilities contributes to limiting Vattenfall’s incentives to keep nuclear capacity out of the market. This is due partly to a reduction in Vattenfall’s market share following the net import from the Continent and partly to available import capacity by Statkraft under low and medium load. Taken together, the new connections to the Continent therefore reduce the problem of market power in the Nordic market. 4.5. Cooperation The model concept may help to shed light on the question of whether the generators will profit from collaborating on keeping capacity out of the market. In the calculations, this has been illustrated by testing the degree to which varying constellations are better off by collaborating than they are when playing non-cooperative strategies represented by the Nash–Cournot equilibrium, assuming a pro rata reduction in supply to the market. This analysis shows that large producers will find it increasingly profitable to collaborate as more and more companies join in. This is natural because the market share increases and because competition between the generators by definition is reduced in terms of number of competitors and market concentration.
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The next important finding is that Vattenfall participates in all profitable constellations. This reflects the fact that the costs associated with keeping volumes off the market are now distributed to some of the other generators, which gives Vattenfall a relatively larger market share at a given market price. Finally, we find that none of the constellations where Vattenfall does not participate are profitable. This model result shows that if Vattenfall decides not to cooperate in keeping prices high, the company will increase its output if prices are forced up as a result of the cooperation of other generators. 4.6. Conclusion The most important result of the calculations is that the problem of market power mainly turns on Vattenfall. However, the company may only manipulate the market prices through reduced production in the nuclear plants. For many reasons, a low exploitation of capacity in the nuclear plants is unrealistic, something that reminds us of the limitations connected to such model analyses. Firstly, there are several owners of the Forsmark plant. Admittedly, Vattenfall has around 50% of the shares, but the company may of course not decide the day-to-day running of the plant alone. Secondly, the current debate concerning a removal of all nuclear power in Sweden probably requires considerable caution, assuming that they want to keep the plants in the long run9. A low exploitation of capacity may lead antinuclear activists to question the need for the plants, or their safety, if a capacity reduction is explained by increased maintenance periods. Third, there has been no evidence so far that Vattenfall has a low utilisation in their plants. Further, there is no evidence that Vattenfall abuses the exclusive rights on the interconnectors, which the model simulations suggest would be profitable.
5. Different market models give different results There is a growing literature using model simulations like ours to anlayse market power. In this section we’ll examine in more detail the importance of the model applied to the differences in results between market power studies, i.e. this paper report much less incentives to use market power to raise prices than similar. In our model framework the Cournot model is characterised by assuming that the market actors behave as if they expect the supply functions to all other producers to be vertical. The margin between marginal costs and 9 The Swedish government proposed to go further with the moratorium by suggesting that one reactor be closed down by June 1998. Sydkraft, which owns the reactor, is disputing the legal grounds of these proceedings, and at the end of 1998 the case remained unsolved.
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market prices is then completely a function of market share and demand price elasticity. The Cournot model will hence predict more potential market power than the model used in our calculations. Bushnell and Borenstein (1997) use a Cournot model to study market power in a deregulated Californian market. They report a significant potential for market power especially in peak periods, i.e. in periods where the competitive fringe utilises its full capacity and the large producers’ market share is relatively high. The Cournot model is also applied in several other papers examining market power in stylised three node electrical networks with loop flow effects, see Oren (1997) and Hogan (1997). Green and Newbery (1992) use a supply function equilibrium model in a study of market power in the UK market. The calculated prices are around 50% higher than the competitive prices. This paper follows a more general Klemperer and Meyer concept, taking explicit account of several possible equilibria within the model framework. Expressed by Eq. (10), Green and Newbery assume a positive slope on the supply functions, due to continuous convex cost functions10 and a non-negative derivative of the margin () with respect to output (X). Both assumptions will in general imply steeper supply functions and therefore stronger incentives to exercise market power. However, since the “classical” Cournot model on average represents an upper limit on the margin, the Green and Newbery model will predict less incentive to abuse a dominant market position than the Borenstein and Bushnell paper. This short comparison may shed some light on why our paper ends up with calculations showing much less potential for market power than the studies mentioned above. It is partly due to differences in the model framework, and of course partly due to a completely different structure between the Nordic, UK and Californian markets. We will not argue that one model gives more reliable results than others. Generally the oligopoly theory is inconclusive, and there are major differences in regulatory framework, traditions and structure between electricity markets. However, this paper suggests one should try out different market power models before drawing strong conclusions based on model simulations.
Acknowledgements The author would like to thank James B. Bushnell, fellow colleagues at ECON, Hill Huntington, Frank Wolak, and one anonymous referee for useful comments. Support from the Norwegian Research Council and The Federation of Norwegian Electricity Utilities is greatly acknowledged.
10
This point is also noted in Von der Fehr and Harbord (1993).
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