The optimal fuel mix and redistribution of social surplus in the Korean power market

Energy Policy 38 (2010) 7929–7938

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Energy Policy journal homepage: www.elsevier.com/locate/enpol

The optimal fuel mix and redistribution of social surplus in the Korean power market Hyunsook Kim a,n, Sung-Soo Kim b a b

Department of Economics, Soongsil University, 511 Sangdo Dong, Dongjak Gu, Seoul 156-743, Republic of Korea Graduate School of Knowledge based Technology and Energy, Korea Polytechnic University, 2121, Jeongwang-Dong, Siheung-Si, Gyeonggi-Do 429-743, Republic of Korea

a r t i c l e in fo

abstract

Article history: Received 4 May 2010 Accepted 25 August 2010 Available online 29 September 2010

This paper investigates the difference between the optimal fuel mix incorporating a pre-installed generation capacity constraint and the actual fuel mix in the Korean power market. Since the restructuring of the market, the fuel mix has been determined partly by investors and partly by the Basic Plan for Long-Term Electricity Supply and Demand (BPE). Both the system marginal price (SMP), and the capacity payment (CP), which has been based on the fixed cost of a specific gas turbine generator, were intended to provide an investment incentive in the market; however, they did not bring about an optimal fuel mix in Korea. Under the circumstances of a shortage of base load generators, these generators may garner excessive profits due to a high SMP level. However, the adjustment scheme of profit between KEPCO and Gencos left scant profit for generators. This paper suggests that a contract is needed to create the appropriate profit and tax levels for these base load generators. The redistribution of profit improves equality between consumers and generators, and the proper margin creates incentives for base load technology investment in Korea. & 2010 Elsevier Ltd. All rights reserved.

Keywords: Optimal fuel mix Equal treatment Korean power market

1. Introduction The electric utilities have been vertically integrated with generation, transmission, distribution, and even sales due to economies of scope, and they have generally operated in the form of a public or a private monopoly. To properly deliver power from generators to consumers, the demand and supply of electricity should be balanced at every instant. That challenging task requires a central entity to control all electricity sectors. The risk to operate an electric utility has been shared across the electricity sectors, which have different risks. The tariffs have been regulated and the investment decision has been controlled by the government. When a social planner decides to build power plants in accordance with nationwide load level, she will want to maximize the social surplus or to minimize the generation cost given the power grid. Based on the actual or expected load duration curve and the costs of generation technologies, she finds the optimal fuel mix to achieve this goal. Joskow (2007, 2008) shows that the optimal portfolio of generation technologies that also includes demand response is derived under the least cost mix procedure. He finds that the cost of the demand response is based on the value of lost load (VOLL),

n

Corresponding author. Tel./fax: + 82 2 828 7256. E-mail address: [email protected] (H. Kim).

0301-4215/$ - see front matter & 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.enpol.2010.08.047

and that the running hours of the demand response depend on the level of the VOLL. Under the ideal condition without friction, the social planner’s portfolio of generation technology achieves the optimal fuel mix for society. However, these results are not reflected in empirical reality. Regulated monopolies have suffered from a lack of competitive forces, and the regulated tariffs have taken cost-saving incentives away from electric utilities. Though there are various gradations of the deregulation of power markets, one purpose of deregulation was to enhance competition and efficiency. Since the worldwide deregulation of electricity industry, the generators have been in charge of generation investment, and the fuel mix is obtained through a market mechanism; however, room remains in several markets for government intervention in investment. The Korean power market has used two schemes to obtain resource adequacy after 2001 deregulation.1 First, the Basic Plan for Long-Term Electricity Supply and Demand (BPE), co-operated by the government and the Korea Power Exchange (KPX), ensures that a sufficient reserve margin exists every other year. Second, the capacity payment (CP) scheme motivates generators to invest voluntarily. The CP is a compensation scheme for the fixed costs of

1 Korea started the deregulation of electricity industry in 2001. The main direction was to divide the generation and distribution sectors into 5–6 number of firms and to privatize them in the future. However, that plan stopped in 2004.

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all generators. Originally different CP levels existed for base load generators and peak units, which also had two marginal market clearing prices. Because the dichotomized market system was abolished and the uniform system marginal price (SMP) was launched in 2007, the uniform CP has been applied to all generators based on the fixed cost of one LNG unit, Ulsan #2. Since the Korean government and the KPX established the BPE, they have collected investment information from KEPCO subsidiary generating companies (Gencos) and independent power producers (IPPs). They have also acquired information about transmission network construction, maintenance and operation plans, and demand management from KEPCO. The CP based on the annualized fixed cost of a marginal unit is an incentive scheme for Gencos and IPPs to build new generation capacities with the SMP in the energy market. In an ideal situation, the generation plan in the BPE should be identical to the investors’ decisions based on the CP and the SMP, and it should reflect the optimal fuel mix. However, several constraints create differences between the optimal fuel mix and the BPE plan. We will determine the extent to which the optimal fuel mix deviates from the BPE blueprint in Korea. This paper aims to determine the optimal fuel mix in Korea and shows the difference between the optimal and actual fuel mix. We also determine the price differences to show the profit margin for each generator under the current, non-optimal fuel mix. Based on the base load generators’ excessive profits, we suggest a fair distribution of margin between consumers and generators. Section 2 examines the social planner’s optimization problem. In particular, we incorporate a pre-installed generation capacity constraint to obtain the optimal fuel mix in Korea. Section 3 derives the competitive equilibrium prices for the optimal and current fuel mix. We compare them with the BPE fuel mix case as well. In Section 4, we analyze excessive profits by fuel types and provide a way to redistribute these profits to improve fairness between consumers and producers. Section 5 analyzes the effect of a change in the demand level, fuel prices and fixed costs of each fuel type, and of the incorporation of a transmission network constraint on the optimal fuel mix and profit margin. Section 6 concludes this paper.

2. Optimal fuel mix and the social planner’s problem 2.1. The social planner’s problem in a simple model2 The social planner may solve the following simple constrained optimization model without considering the transmission network3 and other detailed operational constraints. XX X minKi ,Git Fi ðKi Þ þ Cit ðGit Þ ð1Þ iAI tAT

iAI

s.t. X Git ¼ Dt

8t A T

ð2Þ

iAI

X Ki ZK

Git r aKi

8iA I, t A T

ð4Þ

where I is the set of all generators and T is the set of all hours in a year. Ki is generator i’s generation capacity, and Git is generator i’s generating quantity at time t. Fi ðKi Þ is generator i’s fixed cost when its capacity is Ki , and Cit ðGit Þ is generator i’s variable cost when it generates the amount of power Git at time t. The objective function of Eq. (1) is to co-minimize the fixed and variable costs of system-wide generation. Eq. (2) is the equality constraint of system-wide supply and demand at every hour. To calculate the first constraint, we use average values of demand quantities from 2003 to 2008 and construct the load duration curve over 8760 h. Eq. (3) indicates that total generation capacity should exceed a minimum requirement capacity (K) to maintain system reliability. The level of K depends on the reserve margin. For the calculation, we use 1.154 times the maximum value of the demand quantity of 2008. Eq. (4) shows that the actual generating quantity of generator i at time t, Git is bounded by the maintenance schedule and forced outage of generator i at time t, i.e., a ¼ ð1maintenance ratioÞ  ð1forced outage rateÞ with its nameplate capacity. The range of a is between 0 and 1 and we use 0.925 based on Korean historical data. The Lagrangian function for this optimization is X XX X X X L¼ Fi ðKi Þ þ Cit ðGit Þ þ lt ðDt  Git Þ þ mðK Ki Þ iAI

þ

XX

iAI tAT

nit ðGit aKi Þ

tAT

iAI

iAI

ð5Þ

iAI tAT

The first order conditions for Eq. (5) with respect to Git and Ki are lt ¼ Cuit ðGi,t Þ þ nit and m ¼ Fui ðKi ÞaSt A T nit . The shadow value of the generating quantity at time t is the marginal cost of generator i at time t and margin, nit . nit is a positive value when a generator produces the full capacity and has zero value when its generating quantity is less than its capacity. For generation capacity, the shadow value is the marginal capital cost of generator i 5 minus a times the sum of the energy market margin, nit , for time t. We assume that there are three types of fuel: nuclear energy, coal unit and LNG unit. The nuclear plant has the highest fixed cost, Fu1 , and the lowest variable cost, c1 ¼ Cu1 , and the LNG plant has the lowest fixed cost, Fu3 , and the highest variable cost, c3 ¼ Cu3 . The coal plant has the intermediate values, Fu2 and c2 ¼ Cu2 . Fig. 1 shows the marginal fuel types for three time periods based on a typical load duration curve in Korea. From the first order condition of Eq. (5), we can derive lt1 ¼ c3 , lt2 ¼ c2 , and lt3 ¼ c1 . For the optimization solution, we need to input existing plants’ average fixed and variable costs for the three fuel types. To calculate these averages, we refer to the cost information in the KPX. Using the fixed and variable cost information presented in Table 1,6 we discovered that the optimal fuel mix ratio should be 63.5%:20.5%:16.0% for nuclear energy, coal, and LNG, respectively. Table 2 shows the optimal generation capacities and generating quantities for the three fuel types in 1 year. If we consider demand response in the manner of Joskow (2007, 2008), then we need to make demand response the fourth

ð3Þ

iAI

2 We call this a simple model because we consider only basic constraints for optimization. 3 The Korean wholesale power market has adopted uniform market clearing prices without considering the transmission network. Recently, the market segmented into two regions, the Peninsula and Jeju Island. We incorporate the transmission capacity constraint to obtain a more realistic view of the optimal fuel mix in Section 5.2.

4 We set 15% as the appropriate reserve margin rate. The Korean market sets 12–20% as the appropriate margin range. 5 We converted fixed cost into per kWh term. 6 There are a few steps to obtain the fixed cost of each fuel type. First, the annualized construction cost is calculated based on the construction cost, discount rates, and life cycle. Second, we convert annualized construction cost to the construction cost per kWh by dividing it to 8760 h times availability factors. Third, we add O&M cost. The availability factors presented in Table 1 are based on the available generation capacities of each fuel type. The variable cost of each type is based on the heat rates and the fuel costs during 2007–2009.

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LNG

Coal

t1

Nuclear Energy

t2

t3

Fig. 1. Marginal fuel types by generating hours.

Table 1 Basic information for the cost calculation of each fuel type. Source: Korea Power Exchange.

Construction cost (1000 won/kW) Discount rates (%) Life cycle (year) Maintenance days Forced outage rates (%) Availability factors O&M cost (1000 won/year) Fuel prices (won/Gcal) Heat rates (kcal/kWh) Cost recovery factor Construction cost (won/kWh) O&M cost (won/kWh) Fixed cost (won/kWh) Variable cost (won/kWh)

Nuclear energy (1000 MW)

Coal (500 MW)

LNG (500 MW)

2122 7.5 30 32 5.0 0.867 101.76 1295 2315 0.085 23.66 13.40 37.07 3.00

1145 7.5 30 27 4.7 0.883 40.32 14,555 2061 0.085 12.54 5.22 17.76 30.00

741 7.5 30 32 6.3 0.855 37.92 61,125 1636 0.085 8.38 5.06 13.44 100.00

Note: 1000 Korean won is approximately 0.85 US dollar in August 2010. Table 2 Optimal fuel mix and generation quantities in a simple model. Variables

Nuclear energy

Coal

LNG

Capacity (MW) Share (%) Generation (TWh)

45,791 63.5 364.9

14,763 20.5 51

11,539 16.0 0.9

generation technology. The VOLL level is a variable operating cost of demand response, and determines the operating hours for demand response. The fixed cost of an LNG unit remains the same with VOLL times operating hours of demand response under the simple optimization model (Joskow, 2007, 2008). Thus, we can interpret the fixed cost of an LNG unit as the total amount of scarcity rent.

obtained. However, there are previously installed generation facilities, and new investment can be limited by the installed capacity. For a more realistic perspective, we include the additional preinstalled generation constraints for the new optimization problem. For existing facilities, we apply capacity constraints based on the actual generation capacities for the three fuel types, Ki r K i , where i represents each of the three fuel types. The capacities for previously installed generators (K i ) are 28,142 MW for the LNG unit,7 22,898 MW for the coal unit, and 17,716 MW for the nuclear unit. We also consider their fixed capital costs to be zero because their fixed costs are foregone sunk costs and may not be considered in their generating decision for each time t.8 The Lagrangian function incorporating pre-installed generation capacity is changed into Eq. (6): L2 ¼ Lþ

2.2. Installed generation capacity constraints Suppose that there are no pre-installed generation facilities and that we allocate the entire power supply for each fuel at the initial stage. The solution of a simple model above may be

X

pi  ðKi K i Þ

ð6Þ

i A Iold

7 This includes all other fuels such as oil and hydro, excluding nuclear and coal fuels, to simplify our optimization. 8 We will alleviate this assumption in Section 5.5.

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Table 3 Optimal fuel mix and generating quantities with installed generation capacity constraint. Variables

Nuclear energy Coal

Output (installed) Capacity (MW) 17,716 Share (%) 20.7 Generation(TWh) 143.6 Output (new) Capacity (MW) 16,830 Share (%) 19.7 Generation (TWh) 136.4

LNG

22,898 28,142 26.8 32.9 133 3.93 0 0 0 0 0 0

where pi is the shadow value of installed generation capacity constraint of an old unit i and Iold ¼ {old nuclear unit, old coal unit, old LNG unit}. Table 3 displays the optimization result. Compared to the result using Eq. (5), the nuclear plant’s share decreased from 63.5% to 40.4% but new investment in the nuclear unit is still required.9 In contrast, the shares of coal and LNG increased. The share of each fuel type may be sensitive to fuel price changes, but the treatment of installed plants’ fixed capital costs, whether the depreciation cost is zero or positive, does not impact the optimal fuel mix. Section 5 will detail the sensitivity of the optimization results due to several input conditions.

3. Competitive equilibrium and the Korean power market design 3.1. Competitive equilibrium Joskow (2008) shows that the optimal fuel mix and generating quantities for each fuel unit can be achieved by the marginal cost pricing, and the allocation of scarcity rent in the energy market. Cho (2003)10 and Cho and Kim (2007) show that there is a profile of zonal marginal cost prices that sustain socially optimal outcomes as competitive equilibrium outcomes by the second welfare theorem. If we address a uniform pricing scheme in the Korean power market, the second welfare theorem holds easily as it did in Joskow (2007, 2008). Furthermore, if we divide the zonal pricing scheme into three regions, the Metropolitan area, the Southern area and Jeju island11 without considering any loop flow in Korea, the second welfare theorem holds according to Cho (2003). The marginal cost pricing with scarcity rent is a competitive equilibrium to achieve the least cost generation. However, the scarcity rent is difficult to implement because the level of VOLL is very high and difficult to compute (Joskow and Tirole, 2007). Without compensating for a scarcity rent, every generator takes a loss, which creates a missing money problem (Joskow, 2007). Therefore, power markets usually have capacity compensation schemes to solve a missing money problem. In north-eastern US markets such as PJM (Pennsylvania–New Jersey–Maryland), NE (New England), and NY (New York), the efficient allocation is implemented by a price-bidding energy market with price caps that lie below the VOLL, and by a capacity market that compensates the fixed cost of the marginal unit. Margins always exist in an energy market with price bidding (Cramton, 2004). Capacity market prices are then readjusted by 9 When we consider that nuclear plants are very lumpy in investments, the scale adjustment for the nuclear unit’s capacity is needed. However, it does not change the optimal fuel mix a lot. 10 Cho (2003) showed that the second welfare theorem holds only for generating quantities under given a fuel mix. However, the result can be extended to the fuel mix by considering capital cost with variable cost. 11 The Metropolitan area includes Seoul Gyeonggi-Do. The Southern area is the remaining peninsula excluding Seoul and Gyeonggi-Do.

the amount of the energy market margin to achieve the cost minimization. The Korean power market has implemented two pricing schemes to clear the wholesale market. One is the SMP, which compensates each unit’s generating quantities. The other is the CP, which compensates the generator’s capacity investment. The SMP consists of the marginal fuel cost and an additional adjusted term reflecting start up and idling costs. Basically, the SMP is the highest marginal cost among generating quantity bidding units in a certain hour, and is determined by the KPX based on the Cost Evaluation Committee’s cost calculation. The SMP can only cover the variable cost and cannot compensate the fixed cost of an LNG unit. The CP is the term for the fixed cost compensation of an LNG unit, which is a scarcity rent. Therefore, by the second welfare theorem, the social planner’s optimization results can be sustained as a competitive equilibrium in Korea. Without considering the transmission network, the price for the generating quantity, i.e., the shadow value lt is Cuit ðGit Þ þ nit . Therefore, the price of the generating quantity at time t is the marginal cost of the marginal production unit. nit is the positive margin for an infra-marginal unit and is zero for a marginal unit. The price of generation capacity, m, is Fui ðKi ÞaSt A T nit . The marginal unit is the LNG plant in our simple three-fueltype model at t1 (see Fig. 1). Then lt1 ¼ c3 , n1t1 ¼ c3 c1 4 0, n2t2 ¼ c3 c2 40, n3t3 ¼ c3 c3 ¼ 0, and m ¼ Fu3 ðK3 Þ. lt is the SMP at time t and m is the CP. The level of SMP and CP in a competitive equilibrium is 28.5 won/kWh on average and 13.44 won/kWh, respectively, based on the optimization results. Now, when we consider the pre-installed generators’ capacity constraints, the first order condition of Eq. (6) with respect to the pre-installed generation’s capacity constraint is mpi ¼ Fui ðKi Þ a S nit . The pre-installed generators’ CP should be the annual tAT

fixed cost of a new LNG plant minus the reduction in capital cost of a pre-installed generator with the same fuel type. For example, if the fixed cost of an old LNG plant is zero, then the CP for that plant should also be zero. Table 4 displays the average market price and the different generators’ revenues, costs, and profit levels under the pre-installed generators’ capacity constraint. Only a new nuclear plant needs to be built with a pre-installed capacity constraint and the SMP level is 43.1 won/kWh on average, higher than that in a simple model. If we set up the CP as the level of the fixed cost of an old LNG unit, the level of CP is zero. In this case, we do not have to construct a new LNG plant, and a new nuclear plant can cover its total cost by the SMP alone. Both old coal and nuclear plants have positive profits. The Korean market design is an ideal exercise among the several competitive equilibriums. Therefore, we can compare Korean market performances with the results that are derived from an above competitive equilibrium solution.

3.2. Current fuel mix and the SMP level The generation capacity presented in Table 2 is an ideal fuel mix; the actual fuel mix in Korea is quite different from the optimal one in a simple model. The generation capacity presented in Table 3 reflects a realistic version of the optimal fuel mix considering pre-installed generation capacities. We need to compare the current fuel mix with the optimal one while considering pre-installed generation capacities to predict the additional investment direction for the future. Because the pre-installed capacity is taken as given, the optimal fuel mix under the given installed capacity is an addition of a new nuclear unit to the current fuel mix.

H. Kim, S.-S. Kim / Energy Policy 38 (2010) 7929–7938

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Table 4 SMP, cost, and profit level with pre-installed capacity constraint.

SMP Variable cost (billion won) Fixed cost (billion won) Total cost (billion won) Total revenue (billion won) Profit a

a

won/kWh Share (%)

(billion won) (won/kWh)

Nuclear energy

Coal

LNG

New nuclear energy

Total

3 0 431 0 431 6184 5753 37.1

30 81 3991 0 3991 6417 2426 12.1

100 19 393 0 393 393 0 0

3 0 409 5465 5874 5874 0 0

43.1 – 5224 5465 10,689 18,868 8179 10.9

Profit (won/kWh) is derived from the total profit divided by each unit’s capacity  8760 h.

Table 5 Profit level in the current fuel mix. Nuclear energy

Coal

LNG

won/kWh 3 30 100 SMP Share (%) 0 4.1 95.8 Variable cost (billion won) 431 5551 8825 Fixed cost (billion won) 0 0 0 Total cost (billion won) 431 5551 8825 Total revenue (billion won) 13,937 17,998 8825 Profit (billion won) 13,506 12,447 0 (won/kWh) 87.0 62.1 0

Total

97.1 – 14,807 0 14,807 40,760 25,953 43.1

Next, we need to figure out price differences. We investigate the SMP and CP levels, as well as profit margin for each fuel type under the current fuel mix. Because there is a lack of nuclear capacity in the actual fuel mix, the SMP level is quite high. We assume that only three generation technologies exist. Based on the same assumption about fixed and variable costs for each generator presented in Table 1, the frequency at which the nuclear, coal, and LNG unit will be the marginal unit is 0%, 4.1%, and 95.8%, respectively, and the average SMP is 97.1 won/kWh. The CP is zero because the fixed cost of the old LNG unit is assumed to be zero. The extra profit for an old nuclear plant is approximately 87 won/kWh and the coal plant earns 62.1 won/ kWh as profit.12 For an LNG unit, the generator obtains 100 won/ kWh when it generates power but does not gain from the SMP (see Table 5).13 Under the uniform or regional SMP with the current fuel mix, there is an extraordinary net profit for infra-marginal units. Even if the fixed costs for the old units are assumed to be the same as for the new ones, the profit of old nuclear energy is 50 won/kWh and the profit of old coal is 44.3 won/kWh.

3.3. Fuel mix and market prices in the BPE The BPE shows the official road map for the fuel mix until year 2020 in Korea. According to the BPE, the share of the nuclear unit in 2020 is 31.7%, which is lower than the 40.4% share it would have in the optimal fuel mix. The share of the coal unit is 28.8% and the share of LNG and other generators excluding nuclear and 12 The profit per kWh is calculated as Total Margin/(capacity*8760). The CP level from the optimization result is zero. 13 The actual fuel mix includes hydroelectric units, a storage pump, oil, and three basic fuels. Thus, actual SMP is slightly different from the results in our model. The actual time frequency for a nuclear, coal, or LNG unit to be the marginal unit in 2009 was 0%, 16.4%, and 83.5%, respectively. The average SMP of 2009 was 105.04 won/kWh. The CP based on Ulsan GT #2’s capital cost was 7.49 won/kWh in 2009.

coal units is 39.5%.14 The share of the coal unit is similar to our optimization result, but the share of LNG and others is about 6.6% higher.15 To observe the change of long-run SMP levels and each generator’s profit level, we need to simulate the SMP level using current fuel prices under the BPE in 2020 and compare it with the SMP level in the optimal fuel mix. Table 6 shows the results under the BPE. The average SMP level under the BPE will be 65 won/kWh. The gap between the SMP level under the BPE and under the optimal fuel mix is approximately 22 won/kWh. The old nuclear and coal units have positive profits, but their levels are lower than in the current fuel mix. For new nuclear and coal units, the differences from the margin with old units are the fixed capital costs. For the new nuclear and coal units, the profits are 20.3 and 14.6 won/kWh, respectively. 3.4. Efficiency evaluation In terms of long-run efficiency, i.e., the optimal fuel mix, the Korean market is problematic. The optimal fuel mix gives an efficient allocation and a low level of SMP. The SMP level based on the current fuel mix, 97.1 won/kWh, is more than twice as high as the SMP level in the optimal fuel mix with installed generation capacity constraints. Therefore, we can conclude that the Korean power market has not achieved long-run efficiency by the SMP and CP scheme. To achieve long-run investment efficiency, we need to know the main reasons that nuclear and coal generators do not have sufficient capacities. The main hindrance to having a sufficient base load capacity may be regulatory uncertainties. Ten years after deregulation began, the Korean power market is largely intact, and it is difficult to predict the future market design and ownership structure. After KEPCO suffered a huge loss due to high fuel prices and consequently high SMP level, KEPCO introduced an adjustment scheme to share its loss with Gencos.16 Under the circumstances, even though a private IPP was willing to build a coal plant, the IPP did not ensure future returns and was reluctant to enter into the business. Therefore, we need to establish clear market rules and regulatory policies to induce long-run investment. Another reason for insufficient base-load technologies can be the exercise of market power. However, the adjustment scheme weakens the incentive for generators to increase market prices by not investing in base load generators. The incentive to gain higher profit is not feasible in the Korean market. 14 This share is calculated based on all fuel types including oil and hydro units in the BPE. It is different from the share of the BPE under the tree-fuel-type model. 15 The capacities of the nuclear energy and coal units are 27,316 MW, 24,880 MW under the BPE in 2020. 16 KEPCO classifies the ex-post adjustment coefficients by fuel types and by companies to collect extra profit from its subsidiary Gencos.

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Table 6 SMP, cost, and profit level in the BPE.

SMP Total generation (TWh) Variable cost (billion won) Fixed cost (billion won) Total cost (billion won) Total revenue (billion won) Profit

won/kWh Share (%)

(billion won) (won/kWh)

Nuclear energy

Coal

LNG

New nuclear energy

New coal

3 0 143.6 431 0 431 9331 8900 57.3

30 39 168.2 5047 0 5047 11,541 6494 32.4

100 50 18.3 1828 0 1828 1828 0 0

3 0 77.8 233 3117 3351 5056 1706 20.3

30.0 11 9.0 270 311 581 837 256 14.6

The Korean cost based pool (CBP) market may take advantage of short-run efficiency. The energy market is cleared on the marginal cost of a marginal unit. Because the marginal cost of each unit, which is submitted to the Cost Evaluation Committee,17 is rigorously tested, there is no room for a marginal unit to obtain a high mark-up or to exercise market power in principle. However, there are several flaws in the SMP formula and the energy market clearing system that need to be remedied.18 One such flaw is the lack of a cost-minimizing incentive for marginal LNG units. There is no incentive for marginal units to economize their O&M cost in the short term. If we allow price bidding within a bound based on fuel prices and variable O&M costs, this may provide an incentive for marginal LNG units to minimize their variable costs. Although there are minor problems for short-run operating efficiency, the investment inefficiency will be a more serious problem to deal with.

4. Redistribution of the social surplus There are different ways to resolve resource allocation.19 Both contracts and markets may be effective. Contracts sometimes take place of markets when the risk allocation cannot be obtained through the markets. Risk allocation is needed to build base load generators in Korea. Its failure to do so has created a non-optimal fuel mix and the resultant unfair distribution of surplus. The contract is a good organizational choice to solve those problems in Korea. As long as the Korean power market maintains the SMP and CP rules and the current fuel mix is unchanged, the infra-marginal nuclear and coal plants can achieve substantial margins. However, under the current ownership structure, the margins for inframarginal units are minimal. To stimulate base load technology investment, a high SMP is worth considering. Although the Korean energy market price has maintained a high level, the Korean power industry has suffered from the shortage of base load generation investment after the 2001 deregulation. IPPs were unsure of whether market-based returns were guaranteed in the long run. Our goal is to provide an incentive for generators to build more infra-marginal units through a contract and to rearrange excessive profit gains to improve fairness if excessive profits exist during a transition period toward the optimal fuel mix. 17 The Cost Evaluation Committee evaluates each power unit’s technical performance, quarterly and calculates the coefficients of a quadratic cost function for each unit. The generators only bid their generating quantities and the SMP is determined by the KPX. 18 The new design of the energy market clearing system is not the main topic of this paper and we do not deal with it in detail. 19 Michaels (2006) mentioned three basic ways to organize economic activity. These are markets, contracts and vertical integration.

4.1. Equity between consumers and generators Instead of using the adjustment coefficients between KEPCO and Gencos as an implicit contract, we suggest three criteria for judging the appropriateness of a profit level for Gencos and IPPs.20 The explicit contract can be settled by the following standards. First, we consider the BPE as a strictly binding regulatory constraint for generators. When the generators begin operating, they estimate their medium-term or long-term expected returns based on the market prices under the BPE. This implies that the margin that will be left to generators under the BPE should be obtained and only the difference of current margin per kWh and the margin per kWh under the BPE can be collected as a tax. The extra margin may be collected via transitional vesting contract management. Another reason why we left a greater margin for a nuclear unit relative to a coal unit in the BPE is to stimulate an increase in a nuclear energy investment. Second, we may consider the average rate of return in the worldwide electricity industry as the benchmark return for generators. Compared to other industries, the electricity industry has a relatively high risk due to the large fixed capital cost and fairly long construction period. Consequently, the industry may require a relatively higher rate of return. When we measure profit margins and ROE for large electricity companies worldwide such as RWE, AEP, EDF, Con Edison, E.on AG, and British Energy, they vary across electric firms.21 In terms of mark-up in the PJM market, the average rate of mark-up from 2003 to 2006 is about 8%,22 and the PJM market is regarded as a fairly well-operated market without high mark-up. Because the Korean energy market, for which clearing price is a marginal cost of the marginal unit, does not allow the mark-up in principle, we cannot compare an adequate rate of return in terms of the mark-up. Further, it is difficult to calculate ROE in our three-fuel-type model. Therefore, we compare the profit margin of each fuel unit with other electric firms’ profit margins. The remaining profits for new nuclear and coal units are 20.3 and 14.6 won/kWh based on the BPE constraint (see Table 6). The current SMP level is 97.1 won/kWh. The profit margin for new nuclear and coal units is 20.9% and 15.0%, respectively, and they are higher than the profit margins of other large electric companies. This finding implies that the margin allowed in the BPE

20 There is no absolute criterion of prices and quantity amounts of vesting contracts. For example, the Singaporean government uses the Cournot model to decide the prices and quantities of vesting contracts. 21 The 2009 profit margin for RWE, AEP(2008), EDF, Con Edison, E. on AG, TEPCO, and British Energy was 8%, 10%, 6%, 9%, 3%,  1.4%, 12%, respectively. The ROE was 28.5%, 13.2% (2008), 13.5%, 11.3%, 22.6%,  3.3%, 8.8%, respectively. A large electric company usually operates generation, distribution, sales and even sometimes transmission in a form of vertical integration. It is difficult to specify the return to generation, alone. 22 See Frayer et al. (2007).

H. Kim, S.-S. Kim / Energy Policy 38 (2010) 7929–7938

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100 90 80 70

297 29.7

60 50

29.7

40 30

57.3

20

32.4

10 0 old LNG unit

0 old nuclear unit

old coal unit

margin

transfer to consumers

Fig. 2. Margin and transfer amount for generators (won/kWh).

constraint is larger than worldwide electric firms’ average profit margin. Third, if an agreement or a contract exists for an adequate rate of return between the regulatory authority and generators, such a contract is binding. The adequate regulated rate of return for KEPCO was 6.9% on average from 2000 to 2008, whereas the actual rate of return for KEPCO was 4.18% during the same period. The profit margin in the BPE is higher than the adequate regulated rate of return for Korean regulated public firm, KEPCO. Based on these three criteria, we conclude that the profit margin left for generators under the BPE constraint is larger than the profit margins in other two criteria. If generators obtain the profit margins guaranteed in the BPE, then this will be an acceptable return for generators to deal with different types of risk and uncertainties. The additional profit above the profit margin in the BPE should be collected and redistributed to consumers.23 Fig. 2 shows the amount of old generators’ margin and the number of the transfers to consumers. For the marginal LNG unit, there is no margin and no transfer.

5. Simulation The optimal fuel mix and margin depend on each generator’s capital cost, fuel prices and other physical constraints. In this section, we determine the optimal fuel mix and profit level change due to the change of demand level, the transmission capacity constraint and different cost variables. 5.1. Demand fluctuation It is realistic to consider a random demand level based on the weather and other variables instead of considering a deterministic demand function as in Eq. (2). However, it is beyond the scope of this paper to use a dynamic model incorporating the change of demand. Instead, we change the model in a simple way. Let the demand level have three states, J¼{high, low, reference} with probability pj such that Sj A J pj ¼ 1. Now, the social planner’s problem is changed into Eq. (7) subject to Eqs. (8)–(10): X XXX minK ,Gj Fi ðKi Þ þ pj Cit ðGjit Þ ð7Þ i

4.2. The CP level

it

iAI

iAI jAJ tAT

X j Git ¼ Djt ,8j A J,t A T

ð8Þ

iAI

Under the current fuel mix, every generator receives zero or positive profit with only the SMP as long as we treat the fixed costs of old LNG units as zero. For the BPE and the optimal fuel mix with installed generation capacity constraint, only new nuclear units need to be added, and all generators can still obtain zero or positive profit without the CP. Therefore, if we give a proper signal for the investment and fair distribution of profit, then the CP level should be zero. If we count the fixed cost of the old LNG unit as positive, the compensation for that LNG unit needs to cover its fixed cost and its variable cost, and the CP level should be the annualized fixed cost of the old LNG unit based on its depreciation cost. 23 KEPCO, a sole buyer in the wholesale electricity market, suffered a loss in year 2008. The profit margin was  14.3% and the ROE was  7.2% in that year. The transfer of a part of the profits from generators to KEPCO can be interpreted as a transfer to consumers.

X Ki Z K

ð9Þ

iAI

Gjit r aKi

8i A I, j A J, t A T

ð10Þ

We consider two simple cases. First, pj ¼ 0:25 for j ¼high or low, ¼ 1:05  Djt ¼ reference , and Djt ¼ low ¼ 0:95  Djt ¼ reference for a mild change of demand. Second, pj ¼ 0:30 for j ¼high or low, Djt ¼ high ¼ 1:1  Djt ¼ reference , and Djt ¼ low ¼ 0:9  Djt ¼ reference for more extreme change.24 The optimization result changes little for two cases. For the first case, the capacity of nuclear energy is 45,690 MW and the

Djt ¼ high

24 The gap between the actual and forecasted demand level, which is performed by the KPX, is about 5–10% in Korea. Two scenarios of demand fluctuation reflect this gap.

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capacity of the coal unit is 15,450 MW. The nuclear share decreases by only 0.2%, but the coal share increases 4.7%. The LNG unit’s share decreases about 3.6%. For the second case, the capacity of nuclear energy decreases by 358 MW. However, the share of nuclear energy is 63%, which differs from the benchmark case by only 0.5%. The new nuclear unit’s capacity considering installed generation capacity increases from 16,830 to 17,078 and 17,732 MW, respectively, in each case. When we allow the change of demand level to proceed in a rather deterministic format, the nuclear unit’s share is quite robust to the change of the demand level, but the capacities of coal unit and LNG unit undergo some change. 5.2. Transmission capacity constraint The total generation capacity in the Metropolitan area is lower than its demand level and it should import power from the Southern area, which has nuclear plants and most of the coal units. The transmission capacity from the Southern to the Metropolitan region is limited by 9500–11,500 MW depending on the hours, and congestion between the Southern and the Metropolitan area occurs quite often. The Lagrangian function incorporating pre-installed generation and transmission capacities is changed into Eq. (11): X X L3 ¼ L2 þ jt ðDM Git TtSM Þ ð11Þ t  t

i A I_M

where jt is the shadow value for transmission capacity constraint at time t, DM t is the demand in Metropolitan area at time t, Si A I_M Git is the sum of generating quantities of the generators located in the Metropolitan area at time t, and TtSM is the transmission capacity from the Southern to the Metropolitan area at time t. Table 7 shows the optimization result. Compared to the result in Table 3, the nuclear plant’s share decreased from 40.4% to 34.9%. In contrast, the LNG unit’s share increased. A new nuclear plant can only be built in the Southern area, and that size is limited by the transmission capacity constraint. At the same time, a new LNG unit is needed in the Metropolitan area, and the new capacity is about 450.8 MW. The transmission capacity constraint decreases the share of the nuclear unit. The new nuclear unit’s capacity is 9922 MW and it can be the lower bound of new investment in a nuclear unit. 5.3. CO2 emission price and nuclear social cost There are three possible scenarios. One is the addition of CO2 emission prices into a coal unit’s variable cost. Two, the fixed cost of the nuclear unit may be higher than the cost our calculations suggest. It is difficult to compute the social cost level of a nuclear plant, including the search cost for an available building site and the ex-post treatment cost of radioactive waste. However, there is a consensus that the social fixed cost for a nuclear plant may be Table 7 Optimal fuel mix and generating qunatities with installed generation and transmission capacity constraints. Variables

Nuclear energy Coal

Output (installed) Capacity (MW) 17,716 Share (%) 22.4 Generation (TWh) 143.6 Output (new) Capacity (MW) 9922a Share (%) 12.5 Generation (TWh) 80.4 a b

LNG

22,898 28,142 28.9 35.6 156.3 36.5 0 450.8 0 0.6 0 0.1

The capacity of a new nuclear unit in the Southern area. The capacity of a new LNG unit in the Metropolitan area.

b

higher than the cost we calculated. Three, we need to consider these two factors, together. The fuel price of coal can be changed if we introduce a CO2 emission trade market in the near future of Korea. In the BPE, the CO2 emission price is assumed to be 13,000 won/ton. If we convert this to per kWh, it is about 11 won. Coal’s variable cost then becomes 41 won/kWh instead of 30 won/kWh. In this case, the optimal solution is to build more nuclear units compared to the benchmark case. The reserve margin is increased and the share of nuclear energy increases slightly. Second, we change the fixed cost of the nuclear unit by incorporating the social cost of the nuclear unit. Suppose that the additional fixed cost is 10 won/kWh, which is a 27% increase in the fixed cost. The coal unit is more efficient, and coal generation, rather than nuclear, becomes a cost-saving technology. The optimal fuel mix for this case is 21.1%:45.4%:33.5% of nuclear, coal, and LNG units, respectively, and only new coal capacity is added, by 14,440 MW. The average SMP is 49.2 won/kWh and is higher than our benchmark level, 43.1 won/kWh. Suppose that the additional fixed cost for a nuclear unit is 5 won/kWh. Then our optimal solution changes little from the benchmark scenario. As long as a nuclear unit has a relative cost advantage over a coal unit, the optimal fuel mix changes little, and only the reserve margin is changed. The social cost level of a nuclear unit depends on, for example, a country’s social attitude toward a nuclear energy, the availability of appropriate building sites, and a government’s willingness to construct a nuclear unit, and it is difficult to estimate the monetary value of the social cost. We illustrated two cases for this value that show fundamentally different results for the optimal fuel mix. Third, if we combine these two factors, there is still little change in the optimal fuel mix. The SMP level increases, however. If we assume the additional nuclear fixed cost is 5 won and the CO2 emission price 11 won, then the SMP increases by 5.4 won. If we assume the additional nuclear fixed cost is 10 with the 11 won additional coal price, the SMP increases by approximately 10.8 won. As long as there is no cost inversion between a nuclear energy and a coal unit, the optimal fuel mix remains stable. Only the SMP level and reserve margins are changed. Table 8 shows the change of optimal fuel mix, SMP level and reserve margin in each scenario. Table 9 shows the profit per kWh for each fuel type in different scenarios. When we perform the same simulation for the BPE plan, the fuel mix stays the same for all scenarios. When the CO2 emission price is added, the SMP is 71 won/kWh due to the increase in the coal fuel cost from 30 to 41 won/kWh. However, each fuel’s optimal capacity and generation level stay the same. The additional nuclear fixed cost does not influence on each fuel type’s capacity, dispatch or the SMP level. In conclusion, only CO2 emission price impacts the SMP level, but none of the scenarios affects the fuel mix. The profit in each scenario depends on the cost difference. For example, for an increase in the CO2 emission price, the old coal unit’s margin decreases 5.1 won (32.4–27.3) and the old nuclear unit’s margin increases by 5 won (57.4–62.4). Table 10 summarizes each generator’s profit for each scenario in the BPE. For the current fuel mix, the simulation produces the same results as in the BPE. None of the dispatches is changed, but the SMP level and the margin change for each fuel type. The gap in profits between the BPE and the current fuel mix is also changed. The tax range of an old nuclear unit should be about 15.1– 24.6 won/kWh and the tax range for an old coal unit should be about 25–29.7 won/kWh. The profits for nuclear and coal units in Table 10 are maintained, and extra margin above these levels would be collected via a contract.

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Table 8 Optimal fuel mix change due to CO2 emission price and nuclear fixed cost. Scenario

Optimal fuel mix (%)

CO2 emission price (11 won/kWh for variable cost) Nuclear social cost 5 won/kWh for fixed cost 10 won/kWh for fixed cost Nuclear 5 won + CO2 11 won Nuclear 10 won + CO2 11 won

Nuclear energy

Coal

LNG

42.8 39.2 21.1 41.2 40.0

25.6 27.3 45.4 26.4 26.9

31.5 33.5 33.5 32.4 33.1

SMP level (won/kWh)

Reserve margin (%)

43.1 48.5 49.2 48.5 53.9

29.9 22.2 22.2 26.2 23.7

Table 9 Profit for each fuel in different scenarios in the optimal fuel mix. Scenario

CO2 emission price (11 won/kWh for variable cost) Nuclear social cost

Each fuel profit (won/kWh)

5 won/kWh for fixed cost 10 won/kWh for fixed cost

Nuclear 5 won +CO2 11 won Nuclear 10 won + CO2 11 won

Nuclear energy

Coal

LNG

New nuclear energy

New coal

37.1 42.1 42.7 42.1 47.1

2.4 17.1 17.8 6.9 11.9

0 0 0 0 0

0 0 – 0 0

– – 0 – –

Table 10 Profit for each fuel type in the BPE. Scenario

CO2 emission price (11 won/kWh for variable cost) Nuclear social cost

Each fuel profit (won/kWh)

5 won/kWh for fixed cost 10 won/kWh for fixed cost

Nuclear 5 won + CO2 11 won Nuclear 10 won + CO2 11 won

5.4. The LNG fuel price Suppose that the range of the LNG fuel price is 80–140 won/kWh based on the forecast of the future LNG fuel prices. The optimal share of nuclear energy will be between 39.4% and 41.6% due to the slight change in a new nuclear capacity. The fuel mix in the BPE does not change, and the result is the same for the current fuel mix, as well. Only the SMP level is changed in these two mixes. Because the profit gap between the BPE and the current fuel mix is maintained, the fuel price change of LNG does not influence equity treatment. 5.5. Fixed cost treatment of installed generation capacity Even if we treat the fixed cost of installed units differently, the optimal capacity for a new unit and the optimal generating quantities of all units do not change. Only the CP and the margin change. The level of CP depends on how we treat old units’ fixed costs. Suppose that the old units’ capital costs are the same with new ones. The CP level for optimization with the installed capacity constraint is the LNG unit’s fixed cost, 13.44 won/kWh, and the remaining profits from SMP and CP for old nuclear and coal units are 13.4 and 7.8 won/kWh, respectively, instead of 37.1 and 12.1 won/kWh presented in Table 4. The CP level for the BPE is also 13.44 won/kWh and the remaining profits for old nuclear and coal units are 33.7 and 28.1 won/kWh, respectively, instead of the 57.4 and 32.4 won/kWh shown in Table 6. The short-run optimization result under the

Nuclear energy

Coal

LNG

New nuclear energy

New coal

62.4 57.4 57.4 62.4 62.4

27.3 32.4 32.4 27.3 27.3

0 0 0 0 0

25.4 15.3 10.3 20.4 15.4

9.5 14.6 14.6 9.5 9.5

current fuel mix gives the same CP level, and the profits for old nuclear and coal units are 50 and 44.3 won/kWh, respectively. The tax is about 16.3 won/kWh for old nuclear units (50–33.7) and 16.2 won/kWh for old coal units (44.3–28.1). The profits for new nuclear energy and coal units are increased by 13.44 won/kWh. 5.6. The sensitivity analysis As long as the total cost of a nuclear unit is relatively cheaper than that of a coal unit, there is a little change in the nuclear share from 39.2% to 42.8% due to infra-marginal or marginal units’ cost variation in the optimal fuel mix. A fixed cost treatment of installed capacities does not change the optimal fuel mix, either. The optimal fuel mix is quite robust to the change in fixed or variable cost as long as the order of the base, shoulder and peak load generator is not reversed. A change in demand also has only a small effect on the fuel mix. Only the transmission capacity constraint can substantially shrink the availability of new nuclear energy. Because the fuel mix cannot be changed over a short period, the small size of change in the optimal fuel mix due to the change in input cost variables and demand levels shows that our result is reliable. For the SMP, tax and remaining profit, there is some variation according to the change in the fixed and variable costs of generators. The range of the remaining profit for each fuel generator is summarized in Fig. 3. The profit range for a new nuclear unit is 11–33.7 won/kWh, and that for a new coal unit is

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H. Kim, S.-S. Kim / Energy Policy 38 (2010) 7929–7938

40.0

35.0

33.7

30.0

28.1 25.4

25.0 20.3

20.4

20.0

15.0

15.3

14.6

14.6 11.0

9.5

10.0

9.5 5.4

5.0

0.0 benchmark

CO2 emission

nucelar 5 won+CO2 LNG price (80 won) emission new nuclear new coal

nuclear 5 won

full fixed cost

Fig. 3. Remaining profit for generators in different scenarios (won/kWh).

5.4–28.1 won/kWh. This profit range applies to old nuclear and coal generators only if old units’ fixed costs are the same as the cost of new units. If old units’ fixed costs are zero, the remaining profit for each old unit is increased by the amount of each unit’s fixed cost. The profit for an LNG unit is always zero. The SMP, CP, and collected tax levels can be calculated based on changes in the input prices over time, and the tax level can be easily adjusted to fulfill equity treatment between distributors (or final consumers) and generators. Our result in Fig. 3 is based on the assumption that the order of efficient generators is not reversed. If that order is changed in the extreme case, we need to compensate each fuel unit’s loss when some generators suffer a loss.

generators based on a government regulation constraint, the BPE, to achieve a fair treatment. This contract provides a way to achieve investment efficiency and a fair redistribution of social surplus. The adequate normal rate of return for each fuel generator does not have any clear reference thus far, and we used the BPE as a regulatory constraint that binds private investment decisions for a medium-term period until 2020 in Korea. However, it is worthwhile to find an appropriate rate of return for each fuel unit and consider it as a qualified criterion for the equality argument as long as the Korean power market is heavily regulated. However, the formal investigation into a good criterion for equality judgment remains a future project.

6. Concluding remarks

References

It is instructive to know the difference between the current fuel mix and the optimal fuel mix. Even though we do not incorporate all possible physical constraints to calculate the optimal fuel mix, the optimal fuel mix under the installed capacity constraints is a good estimate. Whereas the SMP and CP could be sustained as an efficient competitive equilibrium price without the transmission network or with a radial network in Korea, the actual market outcome has not achieved long-run investment efficiency. The results of inefficient investment are high SMP, excessive profits for infra-marginal units, and unequal treatment between distributors and generators. This paper shows the optimal fuel mix and the excessive return for generators in the current fuel mix. While we provide an incentive to build nuclear and coal units in Korea, we also suggest that a contract is needed to guarantee the profit level for

Cho, In-Koo, 2003. Competitive equilibrium in a radial network. Rand Journal of Economics 34 (3), 438–460. Cho, In-Koo, Kim, Hyunsook, 2007. Market power and network constraint in a deregulated electricity market. Energy Journal 28 (2), 1–34. Cramton, Peter, 2004, Competitive bidding behavior in uniform-price auction markets. In: Proceedings of the Hawaii International Conference on System Sciences, pp. 1–12. Frayer, Julia, et al., 2007. A Comparative Analysis of Actual Locational Marginal Prices in the PJM Market and Estimated Short-run Marginal Costs: 2003–2006. London Economics International LLC. Joskow, Paul L., 2007. Competitive electricity markets and investment in new generating capacity,. In: Helm, D. (Ed.), The New Energy Paradigm. Oxford University Press. Joskow, Paul L., 2008. Capacity payments in imperfect electricity markets: need and design. Utilities Policy 16 (3), 159–170. Joskow, P.L., Tirole, J., 2007. Reliability and competitive electricity markets. Rand Journal of Economics 38 (1), 60–84. Michaels, Robert J., 2006, Vertical Integration and the Restructuring of the US Electricity Industry, Policy Analysis, No. 572, CATO Institute.