局部阴影下农业光伏系统MPPT算法研究综述

Research Overview of MPPT Algorithm of Agricultural Photovoltaic System under Local Shadow

农业光伏系统发展前景广阔,在现代农业发展、能源体系转型中起着重要的作用。但在实际应用中,光伏阵列会受到局部阴影遮挡,其输出曲线存在多个峰值点,传统的单峰值算法易陷入局部极值,造成功率浪费。为提高农业光伏系统的发电效率,对最大功率点跟踪算法展开研究。首先,阐述最大功率点跟踪原理;然后,介绍传统单峰值算法的工作原理和适用范围;最后,分析粒子群算法、神经网络算法、萤火虫算法和细菌觅食算法等智能算法的工作原理及其改进方法,从而更好地应用于光伏最大功率点追踪。

Agricultural photovoltaic systems have broad prospects for development and play an important role in the development of modern agriculture and the transformation of energy systems. However, in practical applications, the photovoltaic array will be blocked by local shadows, and there are multiple peak points in its output curve, so the traditional single peak algorithm is easy to fall into the local extremum, resulting in power waste. In order to improve the power generation efficiency of agricultural photovoltaic system, the Maximum Power Point Tracking(MPPT) algorithm is studied.Firstly, the principle of maximum power point tracking is described;then, the working principle and applicable scope of traditional single peak algorithm are introduced;finally, the working principle and improved methods of intelligent algorithms such as particle swarm optimization algorithm, neural network algorithm, firefly algorithm and bacterial foraging algorithm are analyzed, which can be better applied to photovoltaic maximum power point tracking.