引用本文:闫志雄,张宁,宋红芳,等.基于DEA的电网绩效评估方法[J].电力系统保护与控制,2014,42(7):67-72.
YAN Zhi-xiong,ZHANG Ning,SONG Hong-fang,et al.A grid performance assessment method based on DEA[J].Power System Protection and Control,2014,42(7):67-72
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基于DEA的电网绩效评估方法
闫志雄1, 张宁2, 宋红芳2, 马蕾2, 方大川1, 杨莉1
1.浙江大学电气工程学院，浙江 杭州 310027;2.浙江省电力公司，浙江 杭州 310007
摘要:
在分析电力企业绩效研究现状，并综合考虑电网运营特点、绩效分析要求、实际数据等问题的基础上，提出了一种基于DEA的电网绩效分析方法。该方法以R聚类技术进行指标精选，以Q聚类技术对不同电网进行分类，并对所选取指标和分类的有效性进行统计检验。对同类电网采用DEA绩效分析，并利用松弛变量对非DEA有效的电网进行投影分析，从而得到提升电网绩效的最佳路径，是一种精细化的绩效分析方法。以中电联提供的“十一五”及2011年统计数据进行了省级电网绩效实证分析，验证了所提出方法的有效性和实用性。
关键词:  R型聚类  Q型聚类  DEA  电网  绩效评估
DOI：10.7667/j.issn.1674-3415.2014.07.010
分类号:
基金项目:国家高技术研究发展计划863计划（2012AA050204）；国网科技项目(“十一五”期间及2011年重点省市电网统计调查)
A grid performance assessment method based on DEA
YAN Zhi-xiong1, ZHANG Ning2, SONG Hong-fang2, MA Lei2, FANG Da-chuan1, YANG Li1
1.College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China;2.Zhejiang Electric Power Corporation, Hangzhou 310007, China
Abstract:
This paper studies the performance assessment and regulation for power enterprise, and proposes a grid performance assessment method based on Data Envelopment Analysis (DEA) considering the power grid operation characteristics, the performance assessment requirements, and the data availability. In the method, R-clustering technology is used for input and output selection. Based on the input and output index, Q-clustering technology is used to classify the power grids. And then the validity of the classification is tested by statistical criterions. Furthermore, the power grids belonging to the same cluster are treated by DEA. The grids which can not be analyzed effectively by DEA are projected by introducing the slack variables to illustrate the optimal route for the performance improvement, which is a delicacy DEA performance method. In the end, real data of the 11th-Five-Year Plan period and 2011 provided by China Electricity Council are used to conduct an empirical analysis of provincial-level power grid performance and it illustrates the effectiveness and practicability of the proposed method.
Key words:  R-clustering  Q-clustering  DEA  grid  performance assessment
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