Congestion Influence on Optimal Bidding in a Competitive Electricity Market using Particle Swarm Optimization

Electricity market plays an important role in improving the economics of electrical power system. Transmission network is vital entity in an open access restructured electricity market. Whenever transmission network congestion occurs in an electricity market, it divides the market in different zones and the trading price of electricity will no longer remains the same for the whole system. Bidding strategies in an electricity market, where by changing the bid, market player changes the revenue of every participant of the market. In this paper, the bidding strategy problem with congestion management is modeled as an optimization problem and solved using Particle Swarm Optimization (PSO). Search procedure of PSO is based on the concept of combined effect of cognitive and social learning of the members in a group. The effectiveness of the proposed method is tested with a numerical example and the results are compared with Genetic Algorithm (GA) approach. The results shows that PSO takes less computational time and maximizing the social welfare compared to GA approach.