一种新的全球MPPT方法,基于对复杂的部分遮阳下的光伏系统的灰天优化
Mohammed Taha Kaaitan1, Rashid Ali Fayadh1, Zuhair S Al-Sagar2
1Electrical Power Engineering, Middle Technical University, Baghdad, Iraq.
Scientific reports
|July 27, 2025
概括
一个新的Sooty Tern优化算法 (STOA) 有效地追踪在部分遮阳下的光伏系统的最大功率点. 与传统算法相比,这种生物灵感的方法提高了能源产量和稳定性.
科学领域:
- 可再生能源系统可再生能源系统
- 优化算法 优化算法
- 光伏发电是光伏发电的发电方式.
背景情况:
- 光伏 (PV) 系统的全球扩张需要先进的最大功率点跟踪 (MPPT) 算法.
- 部分遮阳条件 (PSC) 创建多个局部最大值,降低光伏能源产量,并带来重大跟踪挑战.
- 现有的MPPT方法往往在融合速度方面扎,并且在复杂的阴影场景中避免局部最佳.
研究的目的:
- 提出并评估一种新的MPPT策略,使用生物灵感的全球最大功率点跟踪 (GMPPT) 的Sooty Tern优化算法 (STOA).
- 为了提高追踪精度,融合速度和光伏系统在非均辐射下动态稳定性.
- 为了证明STOA在具有挑战性的PSC下最大限度地提高能源产量,在传统优化算法上的优越性.
主要方法:
- 为MPPT应用程序调整和优化了Sooty Tern优化算法 (STOA).
- 在MATLAB/Simulink中实现了一个模拟框架,配有3x3光伏阵列 (3千瓦) 和增压转换器.
- 在四个不同的PSC场景下测试了基于STOA的MPPT对Perturb & Observe (P&O),粒子群优化 (PSO) 和灰狼优化 (GWO).
主要成果:
- 与P&O,PSO和GWO相比,STOA在融合速度,跟踪精度和动态稳定性方面表现出卓越的表现.
- 在最具挑战性的PSC (模式4) 下,STOA实现了99.94%的跟踪效率,1676W的平均功率和0.5秒的响应时间.
- 在所有测试的阴影模式中,STOA保持了最小的功率振荡,确保了稳定的运行和减少了组件磨损.
结论:
- 拟议的基于STOA的GMPPT战略为太阳能采集提供了显著的进步,在复杂的PSC下表现优于基准算法.
- STOA在勘探和开采之间提供了更好的平衡,加速了融合,避免了非线性光伏系统中的局部最佳情况.
- 它的计算简单性和高精度使STOA成为分布式太阳能系统中实时嵌入式应用程序的可扩展,高效和可靠的解决方案.
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