MPPT of solar PV systems using PSO memetic algorithm considering the effect of change in tilt angle

被引:0
|
作者
Loganathan, V [1 ]
Swaroopan, Jothi N. M. [1 ]
机构
[1] Anna Univ, RMK Engn Coll, Dept EEE, Chennai 601206, India
来源
SCIENTIFIC REPORTS | 2025年 / 15卷 / 01期
关键词
Maximum power point tracking (MPPT); Particle swarm optimization (PSO); Particle swarm optimization memetic algorithm (PSOMA); Tilt angle; Photovoltaic (PV) system; POWER POINT TRACKING; PERTURB-AND-OBSERVE; OPTIMIZATION;
D O I
10.1038/s41598-025-92598-1
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Tracking the peak power output of solar photovoltaic modules poses a significant challenge in contemporary times, that too under variable climatic conditions. Despite the availability of various Maximum Power Point Tracking (MPPT) methods, each method carries its own set of limitations. Many of these constraints can be effectively addressed by leveraging a suitable metaheuristic algorithm. In this context, a Particle Swarm Optimization Memetic Algorithm (PSOMA) is proposed as a powerful tool for accelerating convergence towards the maximum power point and enhancing the tracking process. Furthermore, the proposed algorithm incorporates the impact of changes in tilt angle, thereby augmenting its efficacy. Simulation results demonstrate that the proposed method exhibits superior tracking capabilities compared to conventional MPPT methods and various other MPPT algorithms. The convergence time is also greatly reduced by the proposed method. An efficiency of 99.91% and a convergence time of 8.5 ms is achieved by this algorithm. The efficiency remains almost constant for different irradiance levels which is demonstrated by simulation results. Additionally, hardware experimentation validates the robustness of the developed algorithm.
引用
收藏
页数:17
相关论文
empty
未找到相关数据