基于改进PSO算法在光伏阵列多峰MPPT的研究

针对传统的最大功率点跟踪算法在光伏阵列出现局部阴影时,其输出P-U特性曲线表现出的多峰现象,导致跟踪不能完成真正的最大功率点跟踪,从而造成系统的输出功率降低的问题;粒子群算法(PSO)在全局搜索具有很好的作用,把PSO应用在MPPT之中,但其收敛速度与精度方面具有一定的缺点,为了提高PSO算法的跟踪精度和收敛速度,提出了把非线性控制策略与PSO算法相结合;通过Matlab/Simulink进行仿真验证,结果表明:改进后的粒子群算法在有无阴影和环境发生变化的情况下均可快速且稳定准确地跟踪到最大功率点的有效性,提高了光伏系统的发电效率。

Research on Multi-peak MPPT of Photovoltaic Array Based on Improved PSO Algorithm

In the traditional maximum power point tracking (MMPT) algorithm, the multi-peak phenomenon of the P-U characteristic curve occurs when the local shadow appears in the photovoltaic array, which leads to a failure of the true maximum power point tracking, thus reducing the system output rate. Particle swarm optimization (PSO) works well in global search. PSO is used in MPPT, but it has some disadvantages in convergence speed and precision. In order to improve the tracking accuracy and convergence speed of the PSO Algorithm, a method of combining the nonlinear control theory strategy with the PSO algorithm is proposed, and Matlab/Simulink is used to do the simulation to verify its feasibility in this paper. The simulation results show that the improved PSO algorithm can track the maximum power point rapidly, stably and accurately under the condition of no shadow and environmental changes, which improves the power generation efficiency of the photovoltaic system.