A Solution of Bid-based dynamic economic load dispatch using a hybrid Mutualism based Pathfinder algorithm

This paper introduces a hybrid mutualism based pathfinder algorithm (mPFA) for solving the bid-based dynamic economic load dispatch (BBDED) problem by taking into consideration of various bidding strategies in a deregulated environment. In a deregulated environment BBDED problem is evolved to achieve different goals, such as resource scheduling, maximize social profits, and simultaneously to intend power system security. The IEEE-30 bus test system is considered, which contains 6-power generators and 2-consumers who are supposed to bid in two separate trading periods under various bidding strategies in a day-ahead electricity market. The market co-ordinator known as independent system operator (ISO) matches different bids received from supply and demand side participants and tries to maximize the social profit. In this work, a novel hybrid meta-heuristic algorithm, namely mPFA is proposed, which combines the Pathfinder algorithm (PFA) and the mutualism phase of the Symbiotic Organisms Search (SOS) algorithm. The proposed mPFA scheme avoids the slow and premature convergence of original PFA by exploration with PFA and exploitation with the mutualism phase of SOS. The proposed hybrid scheme was compared to different meta-heuristic algorithms, including Pathfinder algorithm (PFA), Differential Evolution (DE) algorithm, particle swarm optimizer (PSO), and Salp Swarm Algorithm (SSA). The simulation results show that mPFA has the capability and adequacy to solve BBDED.