在局部阴影情况下,光伏阵列输出的功率-电压曲线会出现多个极值,传统最大功率点追踪(Maximum power point tracking, MPPT)方法容易陷入局部最优而失效。为了提高MPPT的追踪效率和准确性,提出了一种基于改进灰狼优化算法的控制方法。在灰狼优化算法的基础上,改进算法在迭代过程中不断缩小搜索区间,提高算法的收敛速度和求解精度；同时,采用反向优化策略增大搜索过程的多样性,帮助算法跳出局部最优。仿真统计结果表明,相较于基本算法,改进算法具有更高的追踪成功率、追踪准确性和更短的追踪时间。
英文摘要:
Under a partial shading condition, the P-U curve of the photovoltaic array output will have multiple peaks. The conventional Maximum Power Point Tracking (MPPT) method is prone to stagnation in local optimum and fail. In order to improve the tracking efficiency and accuracy of MPPT, a control method based on improved grey wolf optimization algorithm is proposed. Based on the grey wolf optimization algorithm, the improved algorithm continuously decreases the search interval during the iterative process to improve the algorithm"s convergence speed and solution accuracy. At the same time, the reverse optimization strategy is used to increase the diversity of the search process and help the algorithm jump out of the local optimum. Statistics of simulation show that the improved algorithm has higher tracking success rate, accuracy and less tracking time than the basic algorithm.
