[1]许爱东,李昊飞,程乐峰,等.PCA-PSO-ELM配网供电可靠性预测模型[J].哈尔滨工程大学学报,2018,39(06):1116-1122.[doi:10.11990/jheu.201611088]
 XU Aidong,LI Haofei,CHENG Lefeng,et al.Prediction model for power supply reliability of distribution network using PCA-PSO-ELM[J].hebgcdxxb,2018,39(06):1116-1122.[doi:10.11990/jheu.201611088]
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《哈尔滨工程大学学报》[ISSN:1006-6977/CN:61-1281/TN]

卷:
39
期数:
2018年06期
页码:
1116-1122
栏目:
出版日期:
2018-06-05

文章信息/Info

Title:
Prediction model for power supply reliability of distribution network using PCA-PSO-ELM
作者:
许爱东1 李昊飞2 程乐峰2 余涛2
1. 南方电网科学研究院有限责任公司, 广东 广州 510080;
2. 华南理工大学 电力学院, 广东 广州 510640
Author(s):
XU Aidong1 LI Haofei2 CHENG Lefeng2 YU Tao2
1. Electric Power Research Institute, China Southern Power Grid, Guangzhou 510080, China;
2. School of Electric Power, South China University of Technology, Guangzhou 510640, China
关键词:
配网供电可靠性主成分分析极限学习机粒子群优化算法供电可靠性评价指标预测模型
分类号:
V438
DOI:
10.11990/jheu.201611088
文献标志码:
A
摘要:
为了提升配网供电可靠性的预测精度,提出了基于主成分分析和粒子群优化极限学习机的配网供电可靠性预测模型。从多方面分析影响供电可靠性的指标,利用主成分分析得到综合变量,实现对数据的降维。在此基础上,构建人工神经网络并利用粒子群算法优化极限学习机的输入权值和阈值,完成对训练供电可靠性预测模型的训练。以某大型电网的47个供电局样本30种影响供电可靠性因素为例进行仿真分析,并将PCA-PSO-ELM算法与3种回归拟合算法对比,验证了该方法的有效性。模型充分考虑了多方面的供电可靠性影响因素,适用于多输入变量的情况,对于引导供电企业制定可靠性提升策略提供了科学有效的参考依据。

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2016-11-28。
基金项目:国家重点基础研究发展计划(2013CB-228205);国家自然科学基金项目(51177051,51477055);中国南方电网公司重点科技项目(KY2014-2-0018).
作者简介:许爱东(1977-),男,教授级高级工程师;程乐峰(1990-),男,博士研究生;余涛(1974-),男,教授,博士生导师.
通讯作者:程乐峰,E-mail:chenglf_scut@163.com
更新日期/Last Update: 2018-06-01