使用加权领导搜索算法的单,双和三二极管光伏模型的参数提取
1Department of Electrical and Electronics Engineering Faculty of Engineering and Architecture Eskişehir Osmangazi University Eskişehir 26480 Turkey.
Global challenges (Hoboken, NJ)
|May 15, 2024
概括
权重领导者搜索 (WLS) 算法准确地提取光伏 (PV) 模型的参数. WLS的性能优于其他方法,提高了光伏设备的性能和经济效益.
科学领域:
- 可再生能源工程可再生能源工程
- 计算智能是一种计算智能.
- 材料科学 材料科学 材料科学
背景情况:
- 精确的光伏 (PV) 设备建模对于最大化技术和经济效益至关重要.
- 单,双和三二极管光伏模型的参数提取存在重大挑战.
研究的目的:
- 通过使用加权领导搜索 (WLS) 算法提取参数来开发准确的光伏模型.
- 评估和选择最适合PV参数提取的优化算法.
主要方法:
- 使用公开可用的实验数据开发了24个光伏模型 (光伏电池6个,光伏模块18个).
- 测试了七个新的元启发算法,包括WLS,用于PV参数提取.
- 采用先进的统计测试 (弗里德曼,威尔科克森签名等级) 来进行算法比较.
主要成果:
- 权重领导者搜索 (WLS) 算法实现了最低的最小值,平均值,RMSE和标准偏差值.
- 与其他六种算法相比,WLS在PV参数提取方面表现出卓越的性能.
- 统计测试证实了WLS的显著优势,基于144次对对比.
结论:
- 权重领导者搜索 (WLS) 算法对光伏参数提取非常有效.
- 通过WLS,可以开发精确的光伏模型,从而提高性能和经济成果.
- WLS被认为是复杂的光伏建模任务的优化技术.
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