论文部分内容阅读
最大功率点的跟踪控制是光伏发电系统的关键技术,针对传统方法在局部阴影条件下易出现多峰值现象,输出功率损失严重的难题,提出了改进粒子群算法的光伏最大功率点跟踪控制方法。首先建立局部遮挡条件下的光伏最大功率点跟踪数学模型,然后根据粒子群算法找到最优光伏最大功率点,并对标准粒子群算法进行改进,克服其得到局部最优功率点的缺陷,最后采用仿真实验验证该方法的有效性和越性。结果表明,改进粒子群算法可以准确实现光伏最大功率点的跟踪,改善了光伏发电系统的性能。
The maximum power point tracking control is the key technology of photovoltaic power generation system. Aiming at the problem that the traditional method is prone to multi-peak phenomenon and the output power loss is serious under local shadow conditions, an improved particle swarm optimization algorithm is proposed. Firstly, the mathematical model of maximum power point tracking under partial occlusion is established. Then, the optimal PV maximum power point is found based on Particle Swarm Optimization (PSO), and the standard PSO algorithm is improved to overcome the defect of obtaining the local optimum power point. Finally, Simulation results show the effectiveness and feasibility of the proposed method. The results show that the improved particle swarm optimization algorithm can accurately track the maximum power point of PV and improve the performance of photovoltaic power generation system.