第39卷第6期2018年6月哈 尔 滨 工 程 大 学 学 报Journal of Harbin Engineering University Vol．39?．6Jun．2018
PCA-PSO-ELM 配网供电可靠性预测模型
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)
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三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,实现对数据的降维三在此基础上,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三以某大型电网的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三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三
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
DOI :10．11990/jheu．201611088
网络出版地址:http ://www．cnki．net /kcms /detail /23．1390．u．20180326．180４．0４0．html
中图分类号:V４38 文献标志码:A 文章编号:1006-70４3(2018)06-1116-00Prediction model for power supply reliability of distribution network using PCA-PSO-ELM
XU Aidong 1，ＬI Haofei 2，CHENG Ｌefeng 2，YU Tao 2
(1．Electric Power Research Institute，China Southern Power Grid，Guangzhou 510080，China;2．School of Electric Power，South Chi-na University of Technology，Guangzhou 5106４0，China)
Abstract :To enhance the predictive precision of power supply reliability in a distribution grid，a prediction model of power supply reliability in a distribution grid was proposed via principal component analysis (PCA)and particle swarm optimization extremity learning machine (PSO-EＬM)．First，the impact factors of power supply reliability were analyzed from various aspects．The linear combinations of the original variables were used to obtain the com-prehensive variables for realizing the dimension reduction of the data．On the basis of data pretreatment，the artifi-cial neural network was established，and PSO was applied to optimize the input weights and threshold values of EＬM to complete model training．Finally，30kinds of impact factors of power supply reliability of the samples，which were obtained from ４7power supply bureaus of a large power grid，were used for simulative analysis．The PCA-PSO-EＬM algorithm was compared with three kinds of regressive fitting algorithms to verify the validity of the method．The prediction model could fully consider the impact factors of power supply reliability in many aspects．It is applicable for multiple input variables and can provide a scientific and effective reference to guide power supply enterprises in working out a reliability lifting strategy．Keywords :power supply reliability of distribution network;principal component analysis;extreme learning ma-chine;particle swarm optimization;evaluation index of power supply reliability;prediction model
收稿日期:2016－11－28．网络出版日期:2018－03－27．
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．通信作者:程乐峰，E-mail:chenglf scut@163．com． 配电网是电力系统的重要组成部分，其供电的安全可靠程度直接影响着国民经济的发展和人民生
活水平的提升[1]三进一步提升配网的供电可靠性，不仅可以最大限度满足电力用户的用电需求，同时也有利于促进电网建设的进一步完善和发展[2]三我国自1992年以后城市供电可靠性进入了迅速发展阶段，供电可靠性达到了99%以上三近几年供电可靠性水平有了显著提升，越来越多的地区供电可靠率达到99．9%三如何开展供电可靠性评估是目前可靠性领域的万方数据