基于改进多元宇宙优化算法的光伏系统最大功率点跟踪

在局部遮蔽条件下，光伏阵列的功率输出曲线呈现多峰特性，传统控制算法无法持续准确地跟踪最大功率输出点，该文提出一种基于改进多元宇宙优化(MVO)算法跟踪全局最大功率点的方法(IMVO)。引入螺旋更新和自适应压缩因子，增强了算法的全局搜索能力；改变旅行距离率的更新方式，加快了算法的收敛速度，3方面改进有效提高了算法的寻优能力。仿真结果表明:在均匀光照、局部遮蔽和变光照强度3种条件下，改进多元宇宙优化算法均能持续稳定地跟踪最大功率点，在收敛时间和收敛精度上均有较大提高，由此验证了该算法在最大功率点跟踪控制中的可行性。

Maximum Power Point Tracking for Photovoltaic System Based on Improved Multi-Verse Optimization

The power output curve of the photovoltaic array exhibits multi-peak characteristics under partial shading conditions, and the traditional control algorithm can not track the maximum power point continuously and accurately. A method for tracking the global maximum power point based on the Improved Multi-Verse Optimization (IMVO) algorithm is proposed. Spiral update and adaptive compression factor are introduced to enhance the algorithm's global search capability. Travelling distance rate update method is changed, and the convergence speed of algorithm is accelerated, so the optimization ability of the algorithm is improved. The simulation results show that the improved Multi-Verse Optimization (MVO) algorithm can track the maximum power point continuously and stably under the three conditions of uniform irradiance, partial shading and variable irradiance, and the convergence time and convergence accuracy are greatly improved, thus the feasibility of the algorithm is verified in the maximum power point tracking control.