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Environmental/Economic Transaction Planning Using Multiobjective Particle Swarm Optimization and Non-Stationary Multi-Stage Assignment Penalty Function

This paper presents a new approach for environmental/economic transaction planning model of the electricity market. The environmental/economic transaction planning problem is formulated as a multi-objective optimal power flow (MOPF) problem. A novel algorithm using multiobjective particle swarm optimization (MOPSO) and non-stationary multi-stage assignment penalty function is proposed to solve this problem. PSO is modified by using dynamic neighborhood strategy, new particle memory updating, and one-dimension optimization to deal with multiple objectives. Incorporating of non-stationary multistage assignment penalty function in solving OPF problem can improve the convergence. The proposed method is demonstrated on the IEEE 30-bus system. The results show that the proposed approach can efficiently gain multiple pareto optimal transaction planning that match with the sustainable development strategy