基于重组机制的有效QUATRE算法及其在改进的光伏模块中用于参数估计的应用
Fei-Fei Liu1, Shu-Chuan Chu1,2, Chia-Cheng Hu3
1College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, 266590, China.
Heliyon
|July 7, 2023
概括
本研究引入了一种新的光伏 (PV) 模块参数估计方法,独立于参考条件. 改进的RQUATRE算法提高了光伏模块分析的准确性和收性.
科学领域:
- 电气工程 电气工程
- 可再生能源系统可再生能源系统
- 计算智能是一种计算智能.
背景情况:
- 传统的光伏 (PV) 模块参数估计方法受到参考标准的限制.
- 双二极管模型 (DDM) 是一个常见的框架,但参数提取可能具有挑战性.
- 像QUATRE这样的现有算法可能会受到缓慢的融合和局部最佳的影响.
研究的目的:
- 开发一个修改后的光伏模块模型,用于独立于参考条件的参数估计.
- 增强QUATRE算法,以提高光伏模块参数提取的精度和趋同.
- 为了验证拟议的RQUATRE算法的有效性与其他元启发方法相比.
主要方法:
- 修改双二极管模型 (DDM) 进行参考独立的光伏模块参数化.
- 将重组机制集成到QUATRE算法中,创建RQUATRE算法.
- 在CEC2017测试套件中对RQUATRE与FMO,PIO,QUATRE,PSO和GWO进行比较分析.
- 对RQUATRE算法用于光伏模块参数提取的实验验证.
主要成果:
- RQUATRE算法表现出卓越的性能,在CEC2017测试套件上的众多比较中超过了其他算法.
- 在光伏模块参数提取中实现了2.99 × 10-3的根平均平方误差 (RMSE),超过了相比算法.
- 在强度分析方程 (IAE) 中达到10%以下的最终安装值,满足了安装要求.
结论:
- 拟议的修改光伏模块模型和RQUATRE算法为准确的参数估计提供了强大的解决方案.
- RQUATRE算法提供了增强的融合和精度,克服了传统方法的局限性.
- 开发的方法适用于光伏模块转换和重新配置任务.
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