改进的人工生态系统优化器在中小型配电变压器参数识别方面的能力
Abdelmonem Draz1, Hossam Ashraf2, Ahmed R El Shamy3,4
1Electrical Power and Machines Department, Faculty of Engineering, Zagazig University, Zagazig, 44519, Egypt. aaderaz@zu.edu.eg.
Scientific reports
|September 12, 2025
概括
本研究介绍了一种改进的人工生态系统优化器 (IAEO),用于准确的分配变压器建模. IAEO在参数估计方面表现优于其他方法,实现更低的误差和更好的效率和电压调节预测.
科学领域:
- 电气工程 电气工程
- 计算智能是一种计算智能.
- 电力系统 电力系统
背景情况:
- 分配变压器 (TX) 的准确建模对于电力系统分析和运行至关重要.
- 现有的优化算法可能无法为TX参数估计提供足够的准确性.
研究的目的:
- 提出和验证一个改进的人工生态系统优化器 (IAEO),用于准确的分布TXs的参数估计.
- 将IAEO的性能与各种已建立的优化算法进行比较.
主要方法:
- 实施IAEO算法用于TX参数估计.
- 使用绝对错误总和 (SAE) 作为目标函数进行比较分析.
- 评估TX性能指标,包括效率和电压调节 (VR).
主要成果:
- IAEO在4kVA (1.12e-5) 和15kVA (0.0322) 的TX中取得了最低的SAE,表现优于竞争对手.
- IAEO准确地预测了TX稳定状态特征,例如在36.2%的负载下 (112.5kVA TX) 的峰值效率.
- 在额定领先功率因子条件下,对167kVA TX观察到高达-8%的负VR.
结论:
- 拟议的IAEO在分布TX参数估计方面表现出卓越的表现.
- IAEO提供了对TX运行特征的准确见解,包括效率和电压调节.
- 统计分析证实了IAEO强而高效的优化趋势.
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