An Engineering Approach to Monitoring Market Power in Restructured Markets for Electricity

The high average prices and high volatility of prices in many restructured markets for electricity have raised concerns about the abuse of market power by generators. At the same time, information about the true costs of generation, that was readily available under regulation, is no longer disclosed by generators. Hence, it is becoming impractical to use a comparison of actual prices with competitive prices as the basis for identifying the use of market power. In this paper, an engineering procedure is proposed for a given pattern of dispatch to measure the potential for market power for all generators in a network. This procedure is equivalent to a set of factor demand equations in a standard neoclassical model of production. An optimal dispatch, for given sets of offers to sell and constraints on capacity, can be replicated exactly by resolving the dispatch using the optimal nodal prices as offers with no constraints on capacity. Market power exists when the degree of substitutability for power generated at a particular site is low. Withholding capacity and/or raising offers to sell at such a site would be one of the possible ways to exploit market power. Sensitivity of the results for any given pattern of dispatch can give some indication of how effectively prices have been raised by a generator. Under competitive conditions, submitting higher offers to sell at a site will result in a substantial reduction of the capacity dispatched, and the own-price elasticity of demand for generation at the site is very large (negative). As market power increases, the own-price elasticity gets smaller and approaches zero. These effects can be aggregated easily to deal with a specified group of generators, which could represent generators in a load pocket or ownership by a parent company. Use of these procedures is illustrated by evaluating the results of two experiments designed to test market power. These experiments were conducted with undergraduates and utility executives using POWERWEB, which simulates a full AC network with 30 buses, six of which are generators. The objective of the experiments was to determine whether two of the generators could discover that they were in a load pocket and raise their profits by exploiting market power.