Multiobjective electricity power dispatch using multiobjective particle swarm optimization

  • Authors:

  • Hongwen Yan;Rui Ma

  • Affiliations:

  • Changsha University of Science and Technology, Changsha, China;Changsha University of Science and Technology, Changsha, China

  • Venue:
  • ACOS'06 Proceedings of the 5th WSEAS international conference on Applied computer science
  • Year:
  • 2006

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Abstract

This paper presents a new approach for Environmental/Economic transaction planning problem in 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 multi-stage 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.