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To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.ejor.2005.03.037 Byline: Raquel Garci'a-Bertrand (a), Antonio J. Conejo (a), Steven Gabriel (b) Keywords: Quadratic programming; Market equilibrium; Pool-based electric energy market; Linear complementary problem; Minimum profit conditions Abstract: This paper provides a tool to determine the near-equilibrium of an electric energy market. This market works under locational marginal pricing, i.e., generating units and demand loads are paid and pay, respectively, the locational marginal prices corresponding to the nodes they are connected to. The near-equilibrium is defined as the energy transaction levels for which generating companies maximize their respective profits and consumption companies maximize their respective utilities. An independent system operator clears the market maximizing the social welfare. Conditions that ensure minimum profit for generating units can be included. However, these conditions may render a generating unit uncompetitive and expel it from the market. Demands are taken to be non-constant and values are determined as part of the solution. The near-equilibrium is obtained through the solution of a mixed-integer quadratic problem equivalent to a mixed linear complementarity problem that includes the minimum profit conditions. It is important to note that the near-equilibrium concept presented in this paper does not solve a market equilibrium when indivisibilities such as start up costs or the like are present. Lastly, we validate the proposed model on a case study using data from the IEEE Reliability Test System. Author Affiliation: (a) Department of Electrical Engineering, Universidad de Castilla -- La Mancha, Ciudad Real, 13071 Spain (b) Department of Civil and Environmental Engineering, University of Maryland, College Park, MD 20742, USA Article History: Received 14 October 2003; Accepted 21 March 2005

A dynamic tool for calculating near-equilibrium in electricity markets under minimum profit conditions and marginal pricing is presented.