邹子君,杨俊华,杨金明.基于多种群遗传算法的波浪发电最大功率跟踪控制[J].电测与仪表,2017,54(23):. Zou Zi Jun,Yang Junhua,Yang Jinming.Maximum power point tracking algorithm based on multiple population genetic algorithm for wave power systems[J].Electrical Measurement & Instrumentation,2017,54(23):.
基于多种群遗传算法的波浪发电最大功率跟踪控制
Maximum power point tracking algorithm based on multiple population genetic algorithm for wave power systems
All individual of the population tends to the same state quickly and stop evolution in genetic algorithm (GA), therefore GA has difficulty in discovering the optimum solution in the maximum power point tracking (MPPT) of the wave energy generation system. A novel multiple population genetic algorithm (MPGA) was proposed to solve the problem of the traditional GA. MPGA introduced multiple populations to search simultaneously at the beginning. Different populations were given different crossover probability and mutation probability so that the novel algorithm can balance global search and local search. At the same time, immigration operator was added to maintain the connection between population and artificial selection operator was used to establish quintessence population. The criteria for the convergence of the algorithm was based on the quintessence population. The simulation results show that this algorithm can improve the capture rate of wave energy of the wave energy generation system.
