局部阴影条件下光伏电池多峰值最大功率点控制策略

Multi- peak PV array control strategy under the conditon of partial shade

局部阴影条件下,光伏阵列的P-V曲线会呈现多个局域峰值,影响最大功率点跟踪(MPPT),传统MPPT算法只能跟踪单个功率峰值,在局部阴影输出功率多峰值条件下,该算法不能完成有效跟踪。粒子群算法(PSO)有较强多极点寻优能力,但易陷入局部最优解。针对此问题,在粒子群算法中引入模拟退火算法的Metropolis选择机制,在简化所需设置参数同时帮助粒子群算法有效跳出局部最优解。在控制过程中,采用主程序加嵌套迭代双重判定条件,保证粒子稳定前提下,收敛在最大功率点(MPP)附近。通过MATLAB对比仿真验证,表明该算法在局部遮阴情况下能较精确、快速地跟踪到最大功率点,有效提高光伏电池输出效率。

On the condition of partial shade, the PV curve of PV array will show multiple local peaks, impacting the maximum power point tracking （maximum power point tracking, MPPT）. Traditional MPPT algorithm can only track a single power peak output power of more than partial shade in peak condition next, the algorithm could not be completed effectively tracked. Particle swarm optimization （particle swarm optimization, PSO） had good multi-pole optimization capability, but it was easy to fall into local optimal solution for this problem, the introduction of Metropolis simulated annealing algorithm selection mechanism in particle swarm algorithm, at the same time simplifying the help needed to set the parameters of particle swarm algorithm effectively out of local optima. In the control process, the proposed main plus nested iteration of this new thinking ahead to avoid particle convergence, to ensure the convergence of particles can be near to the maximum power point （MPP）. Ultimately through MATLAB simulation of the algorithm showed that the algorithm in the case of partial shading could be more accurately and quickly track the maximum power point, effectively improve the output efficiency of photovoltaic cells.