Energy bidding in a day-ahead electricity market using fuzzy optimization

Abstract

Optimal bidding is considered to be one of the most challenging task for energy producers to bid in a day ahead electricity market. The randomness and uncertain nature associated with the generation of stochastic resources further increase the complexity of the problem. In this paper, an optimal bidding strategy is developed for a Generation Company (GENCO) to participate in a day ahead electricity market, taking into account conventional and stochastic generation resources. GENCO tries to maximize the profit and minimize the risk associated with the uncertainty of stochastic generation and market price. An optimal bidding strategy is developed to participate in a day-ahead market to achieve GENCO owner maximized profit and reduced risk for the system operator. The problem is formulated as a fuzzy Mixed Integer Linear Programming (MILP).