1

Venezuelan Restructured Electricity Market - Analysis of a Dominant Firms Market Power

Carlos A. Dortolina, Member, IEEE Dept. of Electric Power Studies,

Inelectra, Caracas, Venezuela

Abstract: Venezuela is currently restructuring its electric power industry in order to create competition for the generation of electricity, while the transmission and distribution of electricity remain regulated monopolies. The restructuring plan was designed to offer large customers (5 MW, initially) a choice regarding the source of their electricity, stimulate required investments, improve system reliability and reduce the price of electricity. This paper deals with the ability of a dominant firm to exercise market power in Venezuelan electricity market. Results will show that, given current and currently forecast market and system conditions, one hydro electric generating company would have the ability to set prices above marginal costs. Among the options to create effective competition, and mitigate dominant firms market power are measures to encourage the entry of new firms, and the imposition of price caps and/or cost plus for hydro plants based on the cost of opportunity of the water. Keywords.- Energy Marketplace. Dominant Firm. Market Power.

I. INTRODUCTION

When effective competition doesnt exist, a firm or group of firms could have market power and can profitably set price above marginal cost. The existence of excessive market power would significantly erode the economic benefits of electric restructuring. In Venezuela, one firm (we will call it HYDRO-GENCO, or HGC) owns more than 60% of the generation capacity through several hydro generating plants. It seems intuitively obvious that market power would be a greater concern where one firm controls most of the existing generation. The results of the analysis will show that, given current and currently forecast market and system conditions, these hydro electric generating plants would have the ability to set prices above marginal costs. It is a short-run analysis, in that it attempts to measure the amount of market power that would exist immediately after restructuring is implemented in year 2002. The study investigates several cases under which HGCs market power might be mitigated. The entry of 450-500 MW of natural gas turbine generation into the restructured central or eastern Venezuelan market would reduce HGCs market power.

Two methodologies previously developed were combined to estimate the market behaviour. The first one was developed to simulate the behaviour of a hypothetical Energy Marketplace in Venezuela, considering the possible reactions of its participants [1], while the second one was developed to investigate the dominants firm market power in a restructured electricity market [2].

II. VENEZUELAN ELECTRICITY MARKET

Venezuelan electric power sector is comprised of several public (five in total) and privately (eight in total) owned utilities. As of 1999, the national installed capacity was 21,186 MW including 13,215 MW from hydro units (see Table 1). Maximum demand reached 12,060 MW for the same year, meaning that hydro units could have supplied 100% of the demand, before considering transmission and other technical constraints.

Table 1 Venezuelan Electric Sector.

1999 Basic Data [3]

Generation \Installed Capacity MW % Hydro Units 13,215 62.4Steam Units 5,011 23.7Gas Units 2,887 13.6Diesel Units 73 0.3TOTAL 21,186 100.0

Additionally, the Electric Service Law was officially signed in 1999. This law establishes competition for both generating and commercial agents. Customers with demands larger than 5 MW can choose between power pool and bilateral contracts to satisfy electric energy needs. Both transmission and distribution agents were established as natural monopolies. This law requires a minimum period of two years to fully start operations. Transmission voltage levels are 765, 400, and 230 kV. Sub-transmission voltage levels are 138 and 115 kV. Fig. 1 shows the Venezuelan electric map including transmission and sub-transmission lines. Recent gathered information determined that the required investment in the Venezuelan electric power sector is close to US$ five billions in the next five years, as follows:

2

Generation: US$ 2,300 Millions, Transmission: US$ 1,700 Millions, and Distribution: US$ 1,000 Millions.

Fig. 1

Venezuelan Electric Map. The most important factors that affect a generation firms ability to exercise market power in a particular region are the amount of owned generation, transmission constraints, demand location and demand density. The only source of HGCs generation is Caronis River hydroelectric dams, located in the southeastern part of the country (see Guri and Macagua II in Fig. 1). These assets provide Venezuelas electric customers with electric energy rates below national average. Because of its low cost generation and high reserve margins, it is a net exporter of its low cost power to the rest of the National Grid.

III. THEORETICAL FRAMEWORK The analysis focuses on horizontal market power, in contrast to vertical market power. Horizontal market power accrues to firms that control a large market share. When considering the generation of electricity business, defining the potential for horizontal market power is not an easy task. Generating units are different, so they have unique operating constraints. Transmission nets characteristics for any region also affect the markets. The relative location of demand, generation, and transmission paths create bottlenecks on the grid that can prevent firms from entering certain markets. Venezuela has one large firm (HGC) that currently provides electric service to most of its customers. In fact, this firm generated in 1999 more than 68% of the total energy consumed in the country. It looks intuitively obvious that market power would be a great concern where one firm controls most of the existing generation.

This paper shows a measure of the ability of a dominant firm to exercise market power in the Venezuelan restructured generation market. It is a short-run analysis, and so it looks to measure the amount of market power that would exist after restructuring begins (expected date: end of 2002), given the existing firms, their generation, and the existing transmission capacity. The behaviour of HGC will be the result of a number of decisions it makes in developing the business strategy. Therefore, the intent of this analysis is not to predict how it might behave in the restructured market. Instead, the goal is to provide information about how to measure generation market power, and a means to compare options for mitigating market power. HGC owns 96% of the generation capacity in eastern Venezuela, while most of the electricity demand (32,189 GWh in 1999, 55% of the total energy consumption in the country) is concentrated between western and central Venezuela. The analysis focuses on a period of four years after the electric framework begins, i.e., 2003-2006, and the market power that HGC could exercise in eastern Venezuela during that period of time. The analysis initially uses a simulation model to compute the market outcome that would occur if perfect competition existed. Then, the model assumes that when there is insufficient uncommitted alternative generation at a given level of demand to mitigate HGCs market power, then HGC can apply a profit-maximizing mark-up over its marginal cost (assumed to be the cost of opportunity of water). The percentage of the year over which the mark-up can be applied and the average amount of this mark-up serve as measures of market power. Several cases were considered to determine a feasible one under which HGCs market power might be mitigated. However, no dynamic interactions that might take place between regions were considered.

IV. THE HERFINDAHL-HIRSCHMANN INDEX A common measure of market power is the Herfindahl-Hirschmann Index (HHI) [2]. The HHI is the sum of the squared market shares for each firm competing in a given market.

( )=

=

n

iisharemarketHHI

1

2_ (1)

where I= firms 1,,n It should be noticed that markets with a high HHI are more likely to experience problems with market power, since the HHI is not a direct measure of a firms ability to exercise market power. In this sense, HHIVENEZUELA5,770, while HHIEAST_VEN9,165, where for a monopoly HHI=10,000, and for oligopoly

Barbacoa Casanay

Indio

Colombia

Cuatricentenario

230 kV

Cabudare

Isiro

S.Agatn

Tablazo P.Centro

Cuatricentenario

Tablazo

Macagua II

Tigre

La Canoa

400 kV

P.Pez

B.Vista

SENECA

115 kV

Jose

Guayana B

El FurrialMorochas

Uribante

S.Teresa

Palital

S.Gernimo

Malena

Guri

OMZ

Arenosa

Yaracuy

Horqueta

765 kV

Corozo

3

HHI=100. Therefore, it could be intuitively said that HGC could have the ability to exercise market power. The HHI is a helpful tool for measuring market power in generation markets, but it also has deficiencies. The dimensions of an electricity market change considerably as a function of transmission constraints. Thus, the HHI is a static measure of a dynamic situation. While the HHI measures only one of aspect of market power, the price elasticity of customer demand (||) also affects the ability of firms to charge prices in excess of marginal cost (MC).

pricedemandedquantity

_%__%

= (2)

The price elasticity of demand in generation markets is inelastic, i.e., || < 1. This means that when a generation firm increases its price by 1%, consumers reduce demand, but the reduction is less than 1%. Therefore, the firm can increase its total revenue by increasing price. In a market with n identical firms, it can be shown that the percent mark-up of price over marginal cost is as shown:

HHInP

MCP =

=

001.1 (3)

Equation (3) highlights the fact that price responsive demand plays an important role in an analysis of market power [4]. In an ideal Venezuelan market with a demand elasticity close to |0.15| and 13 more or less equally sized firms, (3) indicates that market price would be approximately twice marginal cost. As demand elasticity increases to |1.0|, firms realise little additional profit if they increase price.

V. SOLUTION APPROACH Dominant firms act as a price makers when they exercise market power. They control such a large share of a markets generation that they are able to set the market price above marginal cost. In addition to controlling a large share of the market, two other conditions help the dominant firm exercise market power, price elasticity of demand that is inelastic and inelastic supply of the alternative firms. When demand is inelastic, consumers cannot readily reduce their quantity demanded in response to a price increase. This is a particular problem in electricity markets. Only very large customers can operate their own generation economically. There is another condition required for the dominant firm to exercise market power and it is that the supply of smaller alternative firms is inelastic; there is a capacity constraint on alternative generation. An additional problem in generation markets is the time required to construct new generation, which is twelve to twenty months by some estimates [5].

Economic theory provides an explanation of how a dominant firm exercises market power to maximize profits. The dominant firm calculates the equilibrium that would occur under perfect competition (Fig. 2). The overall market supply can be broken down into the dominant firms own supply curve, and the supply of all of its competitors. This model assumes that competitive firms are price takers; they will accept whatever price the dominant firm sets. The dominant firm subtracts the supply curve of the competitive firms from market demand to determine residual demand. Residual demand is the amount of demand left over when alternative supply is exhausted at a particular price and quantity. From the residual demand curve, the dominant firm calculates its marginal revenue curve. Marginal revenue is the amount of revenue the firm earns if it chooses to produce an additional unit of output. The intersection of the dominant firms marginal revenue curve and supply curve determines the profit-maximizing quantity that the dominant firm will supply to the market (qDominant firm). Tracing up from this quantity, the residual demand curve, at qDominant firm, determines the optimal market price for the dominant firm (PM). At this price, the overall market demand curve determines how much electricity consumers will purchase (QMarket). The difference between the market quantity demanded (QMarket) and the quantity that the dominant firm will supply ((qDominant firm) will be made up by the competitive alternative (qalternative).

Price

PM

MC

MarginalRevenue

ResidualDemand

Equilibriumwith Market

Power

DominantFirm Supply

MarketSupply

CompetitiveEquilibrium

Quantity

QMarket

qalternativeqdominant firm

MarketDemand

Fig. 2. Dominant firm mark-up.

Therefore, the dominant firm uses its market power to restrict the quantity it supplies to the marketplace and increase price above marginal cost. The profit maximizing strategy for the dominant firm can be calculated mathematically. If the dominant firm is maximizing profits, it calculates the difference between price and marginal cost at a given level of demand as shown.

Market

FirmDomFirmantDo

Qq

PMCP

Markupice __min 1_Pr =

=

(4)

4

The first factor of (4) is the inverse elasticity of demand, suggesting that, if the dominant firm is able to price discriminate, different customer classes might face different price markups. The second factor is the dominant firms market share. The larger the market share of the dominant firm, the greater the mark-up of price over marginal cost. The market power the dominant firm can exercise can be measured by both the percent of a year that a dominant firm can apply a price mark-up and the average price mark-up that the dominant firm is able to impose. The average markups is calculated as follows:

( ) =i

ii MarkupicetMarkupAverage _Pr_ (5)

where ti is the percent of a year that a particular mark-up can be applied. Prices are competitive when there is no price mark-up.

VI. IMPLEMENTATION DETAILS The approach that will be used to analyse the potential for HGCs market power in a restructured Venezuela generation market is as follows: First of all, the market outcome in eastern, western and central Venezuela has to estimated with a utility production cost model (UPCM), considering perfect competition. Then, UPCMs output is input to determine when HGC can exercise market power, calculate price markups, and analyse power flows among the regions. From this procedure the base case scenario is obtained. Finally, alternative cases under which HGCs market power might be mitigated are analysed. The general procedure is divided in three phases, and it is further explained as follows: A. First Phase UPCM is used to estimate a competitive equilibrium in the eastern, western and central Venezuelan markets, using only the local generation. UPCM was developed by Inelectra and tested in a Venezuelan electric power utility [5]. In order to calculate the competitive market equilibrium, UPCM requires both detailed data on each generation resource, and an hourly load curve for each region. This data is obtained from national public statistics [6]. The hourly load from each area is added together to get the overall hourly load curve. Fig. 3 reflects the energy consumed in 1999 by each region. Forecasts for these values were also available [7]. Bilateral contracts are modelled by assigning a share of a particular generation resource to a company [1]. UPCM estimates the least cost generation set for each area on an hourly basis. It dispatches generation to service demand in order of increasing cost [1].

Central30%

East45%

West25%

Fig. 3. Venezuelan energy consumed in 1999 by region.

B. Second Phase UPCM provides the economic dispatch order, the time that each individual plant is the marginal producer, and an estimate of market prices that would exist under competition. This data is useful to determine when HGC can exercise market power, calculate price markups, and analyse power flows among the regions. The economic dispatch order tells how to array plants against the load duration curve (Fig. 4). The time marginal for each plant tells what portion of a year each plant is marginal along the load duration curve. During the time each plant is marginal, HGCs market share is calculated.

Fig. 4.

Eastern Venezuela economic dispatch order . and time marginal.

The effect of imports from western and central (where several thermal units operate) Venezuela is not included since it is assumed that there is not enough installed capacity in those regions. If they were available, the quantity of alternative generation that were not committed to serve local load in those regions (qf_E.Ve, qf_C.Ve) would have been identified at the same point along the load duration curves for the regions. If HGC would attempt to exercise market power, uncommitted alternative generation in western and central Venezuela that would be available would enter the eastern Venezuela market up to the level permitted by transmission constraints. When all uncommitted alternative generation is identified, HGCs

4,296

Hours

MW

Hydro 2 (HydroGenCo)

5,486

Hydro 3 (HydroGenCo)

Hydro 1 (HydroGenCo)

Hydro 4 (HydroGenCo)Thermal 2 (Alternative)

Time Period whenThermal 1 is Marginal

Thermal 1 (Alternative)

Thermal 3 (Alternative)

5

market share if it attempted to exercise market power is calculated as shown:

market

VeEfVeCfVeWfHydroGenCo

Qqqqq

ShareMarketHGCAdj ._._.__.

= (6)

In (6), qHGC is the quantity HGC would supply if the market were competitive. The terms, qf_E.Ve, qf_W.Ve and qf_C.Ve, are the quantities of uncommitted alternative generation in each region. HGCs adjusted market share can then be used in (4) to calculate HGCs mark-up over marginal cost. These calculations are performed over the entire load duration curve. The base case tries to capture all of the current and currently forecasted factors that affect the electricity market. These factors include current and planned generation, forecasted load growth, bilateral contracts, transmission constraints, and interactions with other regions. Main assumptions related to this case are shown. 1) Elasticity of demand is linear. Market outcomes are

calculated for the following elasticities: 0.9, 0.7, 0.4 and 0.1. These values were selected because the same values were used in [8].

2) 53% of HGCs capacity is committed through bilateral contracts to central and western Venezuela.

3) Assumed required spinning reserve: 8%. 4) Relative competition occurs in central and western

Venezuela. 5) Alternative generation serves its local load first;

uncommitted alternative generation would compete (if available) for HGCs market share.

6) The shape of the hourly load curves for eastern, central and western Venezuela are the same.

C. Third Phase Now, alternative cases are modelled to calculate the effect of various conditions on HGCs market power. As these policies cause the parameters of the model to change, the entire procedure is repeated under the new conditions so that the duration and amount of price markups can again be estimated. The following cases were considered: a) Case 1. Both generation and transmission constraints are assumed not to affect the flow of power within the country. In this sense, it is assumed that a new 450 MW COMBINED CYCLE IPP is located in central Venezuela. The intent here is simply to provide an estimate of how HGCs market power in eastern Venezuela might be affected when generation and transmission constraints are relaxed. b) Case 2. Assume that 500 MW of open cycle natural gas turbines generation enters the eastern Venezuela market, through new generation construction in eastern Venezuela, minimising wheeling charges. While entry is not normally modelled in a short-run economic analysis, the intent of this alternative case is to explore the effect of entry by alternative

firms on HGCs market. These plants are assumed to operate with the cost characteristics of a typical gas turbine facility. This methodology is only a first attempt to calculate HGCs market share when the firm exercises market power. In general, though, HGCs market share is so large that, for most price elasticities of demand, the methodology described does, in fact, maximize profits. The calculated markups are so large that the market price is set at a level higher than any generation resource in the country.

VII. TEST RESULTS Overall, the results of this model show that HGC can exercise a large degree of market power in a restructured Venezuelan electricity market. In the base case, HGC can apply a mark-up over marginal cost between 75% and 83% of the year, each year from 2003 through 2006 (see Table 2).

Table 2. Summary of Results.

The average markups customers would face are a function of the price elasticity of demand. Average markups for 2003 vary from 9% to 878% as the price elasticity of demand is decreased from |0.9| to |0.1|. It would be unlikely that HGC would actually apply the full mark-up in any case. As mentioned earlier, price gouging of this magnitude would probably invite re-regulation, encourage customers to seek other suppliers and reduce or shift load, and encourage other firms to construct new generation in central or eastern Venezuela. Nevertheless, it is more likely that HGC would attempt to select a lower level of profits that satisfies its shareholders, to avoid both the angry on customers and the increase on social discomfort.

Base Case 2003 2004 2005 2006HGC Competitive Market Share 98% 98% 98% 97%HGC Market Share with Price Markup 80% 76% 80% 72%% of year HGC can apply a Price Markup 83% 79% 83% 75%Markup @ |e| = 0.9 9% 9% 9% 8%Markup @ |e| = 0.7 40% 40% 40% 39%Markup @ |e| = 0.4 144% 144% 145% 143%Markup @ |e| = 0.1 878% 877% 879% 871%

Case 1 2003 2004 2005 2006HGC Competitive Market Share 95% 93% 92% 91%HGC Market Share with Price Markup 35% 38% 42% 26%% of year HGC can apply a Price Markup 38% 42% 46% 29%Markup @ |e| = 0.9 6% 4% 2% 1%Markup @ |e| = 0.7 36% 34% 31% 30%Markup @ |e| = 0.4 139% 134% 130% 128%Markup @ |e| = 0.1 855% 836% 820% 813%

Case 2 2003 2004 2005 2006HGC Competitive Market Share 98% 98% 98% 97%HGC Market Share with Price Markup 63% 51% 63% 72%% of year HGC can apply a Price Markup 67% 54% 67% 75%Markup @ |e| = 0.9 9% 9% 9% 8%Markup @ |e| = 0.7 40% 40% 40% 39%Markup @ |e| = 0.4 144% 145% 145% 143%Markup @ |e| = 0.1 878% 878% 879% 871%

6

Results suggest that competition will not force prices to marginal cost for a significant portion of the year. These studies must consider the possibility that prices will be above marginal cost and include some type of sensitivity analysis for price. Another result suggested by this model is that if a utility is able to segregate the market by customer class, price markups could vary substantially among customer classes. Specifically, customers with a |0.1| price elasticity of demand face a price mark-up much higher than customers with a |0.9| price elasticity of demand. Market structures should be carefully designed so that treat each customer class fairly. A common pool that all firms and customers bid into for short-term energy sales would be one option. The pool would set the price for all customers, regardless of class. For long-term needs, large industrial customers have an advantage over residential customers in negotiating deals because of the size of their loads. In terms of mitigation strategies, relaxing generation and transmission constraints within the country (Case 1) can only affect the portion of the year over which HGC can exercise a mark-up, when new additional generation (450 MW IPP) is considered in central Venezuela. The reason why this occurs is that there is simply not enough uncommitted alternative generation in central and western Venezuela to this date. The entry of 500 MW of new alternative generation in eastern Venezuela (Case 2) appears to have a limited effect upon HGCs ability to exercise market power. Over the period 2003-2006, the time of year over which HGC could apply a price mark-up falls from a 75%-83% range to a 54%-67%.

VIII. CONCLUDING REMARKS This study represents an initial effort at quantifying the effects of the market power of a dominant firm in the Venezuelan restructured electricity market. What size market share must a dominant firm own to cause concern? There is no easy answer. In generation markets, defining the relevant market as a basis to estimate market share is not an easy task. One could begin by analysing the transmission network relevant to a particular area, and its constraints. In the case of Venezuela, the analysis was simplified by the fact that it was divided in only three regions, eastern, central and western Venezuela, comprising all of Venezuelas restructured electricity market. The only two paths between western and central Venezuela are Arenosa-Horqueta and Arenosa-San Gernimo lines and these are frequently constrained. The only four paths between central and eastern Venezuela are Santa Teresa-Jose, San Gernimo-Jose, San Gernimo-Tigre and San Gernimo-Malena lines (see Fig. 1). The role of the National Operations Center could, therefore, be assumed to be very limited. Future studies might either divide

the country in a different way, or consider HGCs market power in all Venezuela as one region alone. The most important conclusion that can be drawn from this analysis is that there is no guarantee that electric restructuring would force prices to marginal cost in a country with a dominant firm. This outcome alone, is important previous to any calculation of the benefits of electric restructuring or stranded costs. Estimates of electric restructuring benefits or stranded costs should incorporate a sensitivity analysis that portrays a range of markups over marginal cost. Additional cases will be appropriate for analysis in order to develop specific market structures. For instance, what are the pricing effects of social benefits charges and stranded cost recovery?.

IX. REFERENCES [1] A. Ferreira, C. Dortolina, and Y. Da Silva. Energy Marketplace:

The Colombian Deregulation Model Applied to Venezuela, Proceedings of the I IEEE Conference of the Andean Region. Margarita, Venezuela. September 1999 (in Spanish). Pages 155-160.

[2] A. Sweetser, An Empirical Analysis of a Dominant Firms Market Power in a Restructured Electricity Market, A Case Study of Colorado, Working paper. Denver, Colorado. Colorado School of Mines, April 1998.

[3] CAVEINEL (Electric Power Industry Venezuelan Chamber), Consolidated National Statistics, Caracas, Venezuela, 1999.

[4] S. Borenstein, J. Bushnell, E. Kahn and S. Stoft. Market Power in California Electricity Markets. Working paper. Berkeley, Calif.: University of California Energy Institute. 1996.

[5] G. Gonzlez, J. Puchi, C. Dortolina and J. Martnez, "A Business Scheme for the Electric Power Generation Expansion Plan of a Utility: IPP B.O.O.T. Scenario", 2000 CIER Conference, Buenos Aires, Argentina, November 2000 (in Spanish).

[6] Venezuelan Electric System Operations Bureau (OPSIS), Annual Report, Caracas, Venezuela, 1998 (in Spanish).

[7] OPSIS, Venezuelan Power System Energy Forecasts: Period 1994-2013. Final Report, Caracas, Venezuela, May 1994 (in Spanish).

[8] S. Borenstein and J. Bushnell. An Empirical Analysis of the Potential for Market Power in Californias Electricity Industry. Working paper. Berkeley, Calif.: University of California Energy Institute. 1997.

X. BIOGRAPHY

Carlos A. Dortolina (S89-M91) was born in Venezuela on December 5, 1966. He received an Electrical Engineering Degree from Simon Bolivar University (SBU), Caracas, Venezuela, in 1990, the MSEPE from Rensselaer Polytechnic Institute, Troy, NY, in 1995, and the MBA in Economics from Andres Bello Catholic University, Caracas, Venezuela, in 1999. In 1990 he joined Inelectra (a Venezuelan engineering and construction firm), and since then he has hold several positions, always in the Dept. of Electric Power Studies. He was an

Associate Professor at SBU in the Department of Energy Conversion and Delivery in 1996. He has co-authored several papers in the IEEE, as well as in other national and international technical events. His main interests are in the areas of energy system planning, operation and economics., with emphasis in dynamic modelling, system simulation and risk management. He is currently the manager of several projects related to natural gas, electric power and railroad services at Inelectra.