Optimal Bidding Strategy in an Open Electricity Market using Genetic Algorithm

Abstract

In this paper optimal bidding strategy problem modeled as a stochastic optimization problem and solved using Genetic Algorithm (GA). In an open electricity market environment, maximizing profit by suppliers is possible through strategic bidding. Because of the gaming by participants (power suppliers and large consumers) in an open electricity market, this is more an oligopoly than a competitive market. Each participant can increase their own profit through strategic bidding but this has a negative effect on maximizing social welfare. It is assumed that each supplier/large consumer bids a linear supply/demand function, and the system is dispatched to maximize social welfare. Each supplier/large consumer chooses the coefficients in the linear supply/demand function to maximize benefits, subject to expectations about how rival participants will bid. A numerical example with six suppliers and two large consumers is used to illustrate the essential features of the proposed method and the results are compared with a Monte Carlo approach. Test results indicate that the proposed algorithm gives more profit, converge much faster and more reliable than Monte Carlo approach.