光伏阵列在复杂遮荫环境下的P-U曲线呈现多个峰值导致最大功率跟踪（MPPT）算法失效,为此提出双层控制模型,在上层模型中将Levy飞行和多项式变异策略嵌入灰狼算法,构建Levy-变异灰狼优化算法（LPGWO）搜索全局最大功率点;在下层模型中采用扰动观察法对最大功率点进行局部跟踪,进而有效降低复杂遮荫环境下的功率振荡。仿真结果表明,在多峰MPPT控制中,所提模型具有跟踪速度快、收敛精度高、整体功率振荡小等特点,能有效提升复杂遮荫环境下光伏阵列的最大功率跟踪效率和精度。
Abstract
The P-U curve of photovoltaic array presents multiple peak values in complex shading environment, resulting in the failure of maximum power point tracking (MPPT) algorithm. Therefore, a two-layer control model is proposed. In the upper model, Levy flight and polynomial mutation strategies are introduced into GWO algorithm to form a Levy-polynomial grey wolf optimization algorithm (LPGWO) to search for the global maximum power points. In the underlying model, the perturbation observation method is used to partly track the maximum power points to stabilize the power oscillation in the dynamic process. Simulation results show that in the multi-peak MPPT control, the proposed dual-layer control model has the characteristics of fast-tracking speed, high convergence accuracy and small overall power oscillation, thus improving the tracking efficiency and accuracy of maximum power output of photovoltaic array in complex shading environment.
关键词
光伏阵列 /
最大功率点跟踪 /
灰狼优化算法 /
扰动观察法 /
复杂遮荫
Key words
photovoltaic arrays /
maximum power point tracking (MPPT) /
grey wolf optimizer /
perturbation and observation /
complex shade
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基金
国家自然科学基金（51741907）; 梯级水电站运行与控制湖北省重点实验室开放基金（2017KJX06）
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