基于改进粒子群优化算法的负荷分配方法研究

针对多目标粒子群优化算法求解负荷优化分配问题时所出现的最优解分布不均,局部最优等问题,引入了精英交叉算子并基于拥挤度对非劣解集进行排序,给出了精确计及网损时的机组出力等式不等式约束处理方法。最后在有无网损两种情况下针对3机组系统进行负荷优化分配。仿真结果表明改进后的粒子群优化算法寻优能力得到提升,同样利用模糊隶属度函数筛选Pareto解集得到的结果明显优于常规粒子群优化算法,有效降低了发电成本及污染物排放,且求解结果严格满足约束条件。

Research on Load Distribution Method Based on Improved Particle Swarm Optimization Algorithm

For multi-objective particle swarm optimization algorithm to solve the problem of uneven distribution of optimal solutions and local optimal problems when solving load optimization allocation problems, an elite crossover operator is introduced and non-inferior solution sets are ranked based on the congestion degree. Constraint treatment method for unit output equation inequality when network loss is taken into account. Finally, load optimization is performed for the three-unit system with or without network loss. Simulation results show that the improved particle swarm optimization algorithm has improved the optimization ability. The results obtained by screening the Pareto solution set using the fuzzy membership function are also significantly better Based on the conventional particle swarm optimization algorithm, the power generation cost and pollutant emissions are effectively reduced, and the solution results strictly meet the constraints.