通过改进的Sinh Cosh优化器与三角形运算符进行精细的光伏参数估计
Ala Saleh Alluhaidan1, Diaa Salama AbdElminaam2, Taraggy M Ghanim3
1Departmemt of Information Systems, College of Computer and Information Science, Princess Nourah Bint Abdulrahman University, Riyadh, 11671, Saudi Arabia.
这项研究引入了一种增强的Sinh Cosh Optimizer (I_SCHO),用于准确的太阳能电池模型参数估计. I_SCHO在光伏系统模拟中表现出卓越的性能,提高了可靠性和效率.
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
- 计算优化计算优化
背景情况:
- 准确的参数估计对于光伏 (PV) 系统的模拟和设计至关重要.
- 常见的太阳能电池模型包括单二极管,双二极管和三二极管配置.
- 参数估计是作为一个优化挑战,以尽量减少测量和模拟数据之间的差异.
研究的目的:
- 开发和评估一个增强的Sinh Cosh优化器 (I_SCHO),用于精确的光伏参数估计.
- 为了改善复杂的搜索空间的导航和优化算法的融合速度.
- 与现有方法相比,评估I_SCHO的准确性和可靠性.
主要方法:
- 从Sine Cosine算法 (SCA) 集成的三角函数运算符到Sinh Cosh优化器 (SCHO).
- 应用增强的I_SCHO算法来估计五种不同的太阳能电池模型的参数.
- 使用诸如根平均平方误差 (RMSE),标准偏差 (SD),运行时间和收行为等指标进行比较分析.
主要成果:
- I_SCHO算法在参数估计中始终取得了卓越的准确性和可靠性.
- 与其他算法相比,证明了避免局部最佳和更快的收能力的提高.
- 在多种太阳能电池类型中验证,包括RTC France,Photowatt-PWP201,Kyocera KC200GT,Ultra 85-P和STM6-40/36模块.
结论:
- 拟议的I_SCHO是太阳能电池参数估计的高效和可靠方法.
- I_SCHO在光伏建模的计算效率和准确性方面提供了显著的优势.
- 改进的算法显示了推进太阳能系统设计和模拟的巨大潜力.
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