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回应混沌增长优化器用于新型直流弧模型的参数提取
Zhendong Yin1, Li Wang2, Xianqun Qiu1
1College of Electrical, Energy and Power Engineering, Yangzhou University, Yangzhou 225127, China.
ISA transactions
|July 22, 2025
概括
光伏 (PV) 系统中的直流 (DC) 弧形故障是火灾风险. 一个新的指数细分噪声模型和反混乱增长优化器 (FCGRO) 算法提高了直流弧故障建模和检测准确度.
科学领域:
- 电气工程 电气工程
- 材料科学 材料科学 材料科学
- 计算科学 计算科学
背景情况:
- 直流 (DC) 弧断在光伏 (PV) 系统中构成重大火灾危险.
- 准确的DC弧故障建模对于理解它们的行为和开发有效的检测方法至关重要.
研究的目的:
- 为直流弧故障提出一个新的指数分割噪声模型.
- 介绍一个新的元启发算法,反混乱增长优化器 (FCGRO),用于精确的参数提取.
- 评估拟议模型和算法的性能与现有方法相比.
主要方法:
- 开发指数分割噪声模型,通过频率和光谱能量之间的指数关系来表征弧噪声.
- 引入反混乱增长优化器 (FCGRO),通过反和混乱机制增强传统的增长优化器 (GRO).
- 使用基准问题和实验光伏弧故障数据对八种最先进的算法进行FCGRO的比较评估.
主要成果:
- FCGRO实现了0.0418的平均根平均平方误差 (RMSE),标准偏差为0.00818,在精度和稳定性方面表现优于其他算法.
- 与现有模型相比,提出的指数分割噪声模型平均减少了53.26%的RMSE.
- FCGRO展示了具有竞争力的计算效率,平均处理时间为9.969秒.
结论:
- 提出的指数细分噪声模型为模拟直流弧故障提供了卓越的能力.
- FCGRO为DC弧故障分析中的参数提取提供了更准确,更稳定,更具计算竞争力的方法.
- 这些发现有助于提高光伏系统的安全性和可靠性.
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