在复杂条件下对光伏MPPT的研究基于先进的大墙建筑算法方法
Liming Wei1, Linghao Cao2, Hongdan Jia1
1School of Electrical and Computer Engineering, Jilin Jianzhu University, Changchun, 130118, Jilin, China.
Scientific reports
|November 14, 2024
概括
结合长城建设算法 (LGWGCA) 和扰乱和观测 (P&O) 的新方法在部分遮阳下提高光伏 (PV) 系统效率. 这种LGWGCA-P&O方法提高了跟踪速度,并最大限度地减少了功耗损失,以实现最佳的能源采集.
科学领域:
- 可再生能源系统可再生能源系统
- 电气工程 电气工程
- 优化算法 优化算法
背景情况:
- 光伏 (PV) 系统在部分遮阳下表现出复杂的非线性,多峰电压特性.
- 传统的最大功率点跟踪 (MPPT) 算法在这些具有挑战性的条件下努力实现最佳性能.
- 低于最佳的MPPT会导致显著的能量损耗和整体系统效率的降低.
研究的目的:
- 开发一种新的MPPT算法,克服部分阴影下现有方法的局限性.
- 为了提高光伏系统的MPPT的跟踪速度和准确性.
- 为了最大限度地减少功耗损失,并最大限度地提高光伏系统的能量转换效率.
主要方法:
- 介绍LGWGCA-P&O方法,一种混合方法,将修改后的长城建筑算法 (LGWGCA) 与扰乱和观察 (P&O) 技术相结合.
- 根据LGWGCA的说法,它采用了一种由灰狼优化 (GWO) 启发的位置更新机制,以及利维的飞行策略,以改善代理分配和加速跟踪.
- 算法无地过渡到P&O方法在最大功率点附近的精确识别.
主要成果:
- 通过LGWGCA-P&O方法实现了超过99.96%的光伏转换效率,大大降低了功耗损失.
- 与传统的GWO-P&O方法相比,收速度提高了约40%.
- 拟议的方法在极端条件下展示了优越的性能,计算效率和对粒子群优化和子搜索优化的稳定性.
结论:
- 开发的LGWGCA-P&O方法有效地解决了MPPT在光伏系统中部分遮阳条件下的挑战.
- 这种混合方法在跟踪速度,准确性和整体能量转换效率方面提供了显著的改进.
- 该LGWGCA-P&O方法为优化光伏系统性能提供了强大的和计算效率高的解决方案.
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