Suppliers Bidding Strategy in Single Auction Power Pools using Varying Population based Bacterial Foraging Algorithm

This paper proposes a novel optimization algorithm Varying Population based Bacterial Foraging Algorithm (VPBFA), to solve optimal bidding strategy in a pool based electricity market. In a power market, Generating Companies (suppliers) participate in the bidding process in order to maximize their profits. Each supplier bid strategically for choosing the bidding coefficients to counter the competitors bidding strategy. Most of the Evolutionary Algorithms (EAs) are based on fixed population evolution, which does not attain the full potential of effective search and demands a large amount of computation. In this paper, a varying population algorithm is developed from the study of bacterial foraging behavior. This algorithm, for the first time, explores the underlying mechanisms of bacterial chemotaxis, quorum sensing and proliferation etc., which have been successfully combined into the varyingpopulation frame. The VPBFA algorithm has been applied to the optimal bidding strategy problem and it has been evaluated by simulation studies, which were undertaken on 75-bus Indian practical system, in comparison with fixed population based algorithms like Bacterial Foraging Algorithm (BFA), Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and conventional optimization method called Golden Section Search (GSS) method. The results affirmed the robustness and competence of proposed methodology over BFA, PSO and GA. KeywordsElectricity market, Bidding strategies, Market Clearing Price (MCP), Bacterial Foraging, Varying Population.