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基于改进模糊物元法的电力自供区最优收购策略

Optimal acquisition strategy for electricity self-supply area based on the improved fuzzy matter-element method

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【作者】 张刚李芳锋张江滨王永庆张靠社陈斐刘福潮

【Author】 ZHANG Gang;LI Fangfeng;ZHANG Jiangbin;WANG Yongqing;ZHANG Kaoshe;CHEN Fei;LIU Fuchao;School of Water Resources and Hydroelectric Engineering,Xi’an University of Technology;State Grid Shaanxi Electric Power Company,Shaanxi Electric Power Research Institute;State Grid Shaanxi Electric Power Trading Center Co.,Ltd;State Grid Gansu Electric Power Company,Gansu Electric Power Research Institute;

【机构】 西安理工大学水利水电学院国网陕西省电力公司电力科学研究院国网陕西电力交易中心有限公司国网甘肃省电力公司电力科学研究院

【摘要】 2015年新一轮电力体制改革背景下,为使电网公司在市场竞争中处于优势地位,选择优质电力自供区进行收购,保证存量市场十分重要。本文重点考虑影响电力自供区收购的因素,构建了电力自供区资产价值收购评价指标体系,利用信息熵赋权法确定资产价值收购评价指标权重,并在此基础上,对模糊物元法进行改进,提出一种基于改进模糊物元法的电力自供区客户价值评价模型。以某省8个自供区为例进行研究,结果表明,该方法可以客观有效的对自供区客户进行评价,提供最优收购策略,从而为电网公司资产收购提供参考和依据。

【Abstract】 In the new round of power system reform in 2015,in order to enable grid companies to take a dominant position in the market competition,it is of importance to choose high-quality electricity acquired from the self-supplying area to ensure the stock market.This article focuses on the factors affecting the acquisition of electricity from the self-supplying area,builds the evaluation index system of assets acquisition from the power self-supplying area,and uses the information entropy method to determine the weight of the evaluation index of the assets value acquisition.Based on this,the fuzzy matter-element method is improved.This paper proposes a customer value evaluation model based on the improved fuzzy matter-element method.As for the province eight self-supplying area as an example application,the results show that this method can be the effective and objective evaluation on the supply area customers,and provides the best acquisition strategy,so as to present a reference and basis for the assets acquisition of power grid companies.

【基金】 国家自然科学基金资助项目(51507141)
  • 【文献出处】 西安理工大学学报 ,Journal of Xi’an University of Technology , 编辑部邮箱 ,2018年02期
  • 【分类号】F271;F426.61
  • 【被引频次】2
  • 【下载频次】121
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