电机与控制应用2017，Vol.44Issue(10)：13-18,6.
基于模拟退火粒子群算法的波浪发电系统最大功率跟踪控制
Maximum Power Point Tracking Algorithm Based on Simulated Annealing Particle Swarm Optimization for Wave Power Systems
摘要
Abstract
The particle swarm optimization (PSO) algorithm has low probability in searching global optimization and premature convergence in the maximum power point tracking (MPPT) control of the wave energy generation system.A novel simulated annealing particle swarm optimization (SA-PSO) algorithm was proposed to solve the problem of the traditional PSO.When the speed and position of each particle were updated with SA-PSO,the replacement value of the global maximum from all particles was confirmed by comparing the fitness of each particle of the current temperature and the random number value.As a result,the new algorithm could escape local maximum at the premature convergence and quickly discover global optimum solution.The simulation results showed that this novel algorithm could make the wave energy generation system effectively avoid the local optimization and fast achieve global MPPT control.The capture rate of wave energy was improved.关键词
波浪发电/最大功率点跟踪/模拟退火粒子群算法Key words
wave energy generation/maximum power point tracking (MPPT)/simulated annealing particle swarm optimization (SA-PSO)分类
信息技术与安全科学引用本文复制引用
邹子君,杨俊华,杨金明..基于模拟退火粒子群算法的波浪发电系统最大功率跟踪控制[J].电机与控制应用,2017,44(10):13-18,6.基金项目
国家自然科学基金资助项目(513770265) （513770265）
广东省科技计划项目(2016B090912006) （2016B090912006）
广东省自然科学基金项目(2015A030313487) （2015A030313487）
广东省教育部产学研合作专项资金(2013B090500089) （2013B090500089）
