摘要
在局部阴影条件下,光伏阵列的功率–电压特性曲线呈现多峰状,传统最大功率点跟踪方法出现搜索精度低和收敛速度慢的问题.针对此问题提出一种基于模糊控制的粒子群优化算法,采用模糊控制器对粒子群优化算法的惯性权重ω进行优化,实时调整参数,使光伏阵列在光照强度变化时有较好的动态特性和稳态性能.分别采用常规PSO算法和模糊PSO算法在相同条件下对系统进行仿真,结果表明所提出的算法在局部阴影条件下能快速跟踪外部环境变化,且准确地工作在最大功率点.
Under partially shaded conditions,multiple local maximum can be exhibited on the power–voltage characteristic curve. To solve the problem of the low rate of searching precision and convergence using conventional maximum power point tracking methods,a control algorithm based on Particle Swarm Optimization algorithm using fuzzy control was pro-posed. Fuzzy controller was used to optimize the inertia weightω of PSO algorithm to ensure that the system has better dy-namic response speed and steady-state accuracy when solar radiation changes. Simulation was performed with the PSO method and Fuzzy PSO method under the same condition,and the results indicate that the proposed global MPPT algorithm can quickly and accurately track the global maximum under partially shaded conditions.
出处
《天津科技大学学报》
CAS
北大核心
2015年第1期73-77,共5页
Journal of Tianjin University of Science & Technology
基金
天津市自然科学基金重点资助项目(13JCZDJC29100)
关键词
最大功率点跟踪
局部阴影
粒子群优化算法
模糊控制
maximum power point tracking（MPPT）
partially shaded conditions
particle swarm optimiza-tion（PSO）algorithm
fuzzy control
