Research on energy-saving and emission-reduction dispatch method based on multi-objective particle swarm optimization

PEI Xu，HUANG Min-xiang，XV Guo-feng

（College of Electrical Engineering，Zhejiang University，Hangzhou 310027，China）

Abstract：In order to solve the problems of economic emission load dispatch，a model of multi-objective energy-saving and emissionreduction load dispatch was established，along with an improved multi-objective particle swarm optimization algorithm. The conception of semi-feasible region was introduced to treat constrained conditions，the complicated process of finding appropriate penalty parameters was avoided. Elite filing technology were used to enhance the speed of convergence and the quality of solutions. Adaptive mesh method was adopted to renew and maintain the external elite set in order to gain the Pareto front distributed uniformly. The rules of personal best selection and global best selection were proposed based on the conception of semi-feasible region. This method was applied to multiobjective load dispatch of a real power plant of six power units，and well-distribution Pareto-optimal solutions were obtained. Fuel cost and pollution emission were reduced effectively. The analysis result confirms the feasibility and validity of this approach.
Key words：energy-saving and emission-reduction load dispatch；multi-objective article swarm optimization algorithm；semi-feasible region；elite filing technology；adaptive mesh；Gauss mutation