返回
A Lipschitz Optimization-Based MPPT Algorithm for Photovoltaic System Under Partial Shading Condition
DOI:10.1109/ACCESS.2019.2939095.png)
摘要
En 中文
The power-voltage curve of a photovoltaic (PV) array shows multiple power peaks under partially shading conditions (PSCs). Hence, conventional maximum power point tracking (MPPT) algorithms can not guarantee the maximum power output of the PV array. In this study, a novel Lipschitz optimization (LIPO) MPPT algorithm, which is effective under PSCs, is proposed and analyzed. Its tracking speed is very fast and tracking efficiency is above 98%. The characteristics of a PV array under PSCs are first analyzed and then the working principle of the proposed LIPO MPPT algorithm is explained. In order to validate the performance of the proposed algorithm, two popular MPPT algorithms, i.e., the modified particle swarm optimization (M-PSO) algorithm and the modified firefly optimization (M-firefly) algorithm, are chosen to compare with it. All three algorithms are fulfilled and compared with each other through both simulations and experiments and the results show that the proposed MPPT algorithm has good performance.
Keyword:
Global maximum power point (GMPP)
Lipschitz optimization (LIPO)
maximum power point tracking (MPPT)
partially shaded condition (PSC)
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
A New MPPT Design Using Grey Wolf Optimization Technique for Photovoltaic System Under Partial Shading Conditions基于灰狼优化技术的局部阴影条件下光伏系统MPPT设计
An Overall Distribution Particle Swarm Optimization MPPT Algorithm for Photovoltaic System Under Partial Shading局部阴影下光伏系统整体分布粒子群优化MPPT算法
Modified Perturb and Observe MPPT Algorithm for Drift Avoidance in Photovoltaic Systems改进的扰动和观察MPPT算法可避免光伏系统中的漂移
MPPT of PV Systems Under Partial Shaded Conditions Through a Colony of Flashing Fireflies通过闪烁的萤火虫群体在部分阴影条件下对PV系统的MPPT

