对光伏模型的参数提取进行分类突变的差异演变
Yong-Gang Chen1,2, Yan Cao1, Kai Lu1
1School of Information Engineering, Xuchang University, Xuchang, China.
PloS one
|October 9, 2025
概括
一种名为分类突变差异进化 (DECM) 的新方法增强了光伏 (PV) 参数提取. 这种方法可以提高复杂的太阳能电池模型的精度和效率.
科学领域:
- 电气工程 电气工程
- 计算科学 计算科学
背景情况:
- 光伏 (PV) 参数提取对于太阳能电池建模至关重要.
- 现有的算法在平衡精度和计算效率方面面临挑战,特别是在复杂的光伏模型中.
研究的目的:
- 引入一种新的算法,分类突变的微分进化 (DECM),以改进PV参数提取.
- 为了提高复杂的光伏模型的参数提取的可扩展性和精度.
主要方法:
- DECM采用多群体方法,将个人分为具有当地最佳位置的子群体.
- 它使用不同的,角色特定的突变策略,用于不同的粒子位置.
- 该算法省略了交叉操作和参数调整,以提高简单性和效率.
主要成果:
- 在实验评估中,DECM在与流行的算法相比显示出更高的性能.
- 该算法实现了更高的解决方案准确性和计算效率.
- 在光伏参数提取中,DECM显示了增强的稳定性.
结论:
- DECM在光伏参数提取方面提供了显著的进步.
- 提出的方法有效地解决了现有算法的局限性.
- 对于复杂的光伏模型,DECM提供了一个更准确,更高效,更强大的解决方案.
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