张义涛;王泽忠;刘丽平;邓春宇;孙云超;王新迎;韩笑;

• 1:华北电力大学电气与电子工程学院
• 2:中国电力科学研究院有限公司

摘要(Abstract)：

为更全面、准确地评估10 kV配电网线损水平,提出了一种基于灰色关联分析和改进神经网络的10kV配电网线线损预测方法。通过灰色关联分析方法定量分析了15个电气指标与10 kV配电网线损的关联性,再经过实际10 kV配电网数据的预测校验,最终确定了最佳的电气特征指标体系;其次使用十折交叉验证法结合试凑法计算分析不同神经网络结构下的模型预测性能,确定了最佳的网络结构,解决了BP神经网络(BPNN)隐含层节点数目多凭经验确定的缺点。考虑到传统的BP神经网络收敛速度慢、易陷入局部极小等缺点,采用自适应遗传算法改进BP神经网络(AGABPNN)的方法,进行学习和预测,并对比分析了该方法和径向基神经网络(RBFNN)、传统的BP神经网络的收敛性和预测准确性。通过某地区329条10kV线路实例计算,3种方法最小预测误差分别为6.71%、12.95%、17.05%,验证了AGA-BPNN具有更好的收敛性和泛化能力。

关键词(KeyWords)： 10kV配电网线损;灰色关联分析;神经网络;自适应遗传算法

Abstract:

Keywords:

基金项目(Foundation): 国家电网公司科技项目(面向同期线损管理的多专业数据治理技术与挖掘应用研究(XT71-17-027))~~

作者(Author): 张义涛;王泽忠;刘丽平;邓春宇;孙云超;王新迎;韩笑;

Email:

DOI: 10.13335/j.1000-3673.pst.2018.1193

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