基于LOGPSO算法的光伏系统MPPT研究  

Research on MPPT of PV system based on LOGPSO algorithm

作　　者：王书金 米根锁[1] Wang Shujin;Mi Gensuo(College of Automatic ＆ Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, Chin)

机构地区：[1]兰州交通大学自动化与电气工程学院,甘肃兰州730070

出　　处：《可再生能源》2017年第11期1620-1625,共6页Renewable Energy Resources

基　　金：国家自然科学基金项目(51667013)

摘　　要：在光伏系统最大功率点跟踪过程中,针对太阳辐射强度改变时,粒子群算法易出现收敛速度慢、陷入局部最优等问题,提出了一种惯性权重对数递减粒子群(LOGPSO)算法,该算法将惯性权重以对数形式递减,并加入了对数调整因子,使运行初期的MPPT能够较快地确定极大功率值点所对应的电压,运行中期的惯性权重迅速减小,运行后期的MPPT能够精确地搜索到最大功率点所对应的电压。仿真结果表明,在不同的太阳辐射强度条件下,LOGPSO算法能够显著改善光伏系统MPPT中存在的收敛速度慢、收敛精度低等问题。In the process of tracking the maximum power point of the PV system, the particle swarm optimization algorithm is prone to slow convergence and easy to fall into the local optimum for the solar radiation intensity change, We use a Logarithm Particle Swarm Optimization（LOGPSO）algorithm. The algorithm reduces the inertia weight as a logarithmic form and adds a logarithmic adjustment factor.So that the early MPPT can quickly determine the extreme point voltage position,and inertia weight decreases rapidly in the medium-term, the latter can accurately search for the maximum power point voltage. Simulation analysis shows that, under different lighting conditions,using LOGPSO algorithm can significantly improve the maximum power point tracking PV system during slow speed and low accuracy.

关 键 词：光伏系统 MPPT 局部阴影 太阳辐射强度突变 惯性权重对数递减粒子群算法 

分 类 号：TK513.4[动力工程及工程热物理—热能工程]