%0 Journal Article
%T 改进的金豺优化算法在光伏MPPT中的研究<br>Improved Golden Jackal Optimization Algorithm in PV MPPT
%A 师尚
%A 孔令刚
%J Modeling and Simulation
%P 3525-3534
%@ 2324-870X
%D 2024
%I Hans Publishing
%R 10.12677/mos.2024.133321
%X 光伏发电系统在实际生活中，易受到天气条件、阴影效应、污染物等多种因素的干扰，影响光伏发电系统的发电效率、稳定性、维护成本以及美观度。光伏发电系统在理想情况下输出的P-U曲线是单峰值的，当光伏组件处于光照遮荫的情况下，光伏发电系统输出的P-U曲线会出现多个峰值点。这种情况下，最大功率点追踪(MPP)由单峰值寻优变为多峰值寻优，降低了光伏系统的发电效率。针对常规的MPPT控制算法响应速度慢、早熟、震荡的问题，引入了金豺优化算法(Golden jackal optimization, GJO)。针对GJO算法收敛速度慢、跟踪效率差、追踪精确度低的问题，本文提出了一种优化的金豺优化算法(P-GJO)，提高了光伏发电的效率。<br />
Photovoltaic (PV) power generation systems are susceptible to interference from a variety of factors, such as weather conditions, shading effects, and pollutants, which affect the power generation efficiency, stability, maintenance costs, and aesthetics of PV power generation systems in real life. The P-U curve of PV power generation system output is single peaked under ideal conditions, when the PV module is under light shading, the P-U curve of PV power generation system output will have multiple peak points. In this case, the maximum power point tracking (MPP) changes from single-peak seeking to multi-peak seeking, which reduces the power generation efficiency of the PV system. Based on the existing algorithms, this paper proposes a golden jackal optimization (GJO) algorithm to improve the efficiency of PV power generation.
%K 光伏发电系统，最大功率点追踪，金豺优化算法<br>Photovoltaic Power System
%K Maximum Power Point Tracking
%K Golden Jackal Optimization Algorithm
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=88338