新电改背景下电力用户信用风险预警模型与评价方法
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作者单位:

(1. 华北电力大学 新能源电力系统国家重点实验室,北京 102206; 2. 国网上海市电力公司 市北供电公司,上海 200072)

作者简介:

余培(1993),女,贵州毕节人,研究生,研究方向为电动汽车能量管理与电力市场营销;刘其辉(1974),男,山东济南人,博士,副教授,研究方向为新能源发电与并网技术与电力系统柔性交直流输电。

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基金项目:

国家重点研发计划项目(2018YFB0904000);国家电网公司科技项目(SGJB0000TKJS1801242)


Warning model and user credit risk evaluation method under the background ofnew power grid reform
Author:
Affiliation:

(1. State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North ChinaElectric Power University, Beijing 102206, China;2. Shibei Electricity Supply Company, State Grid ShanghaiMunicipal Electric Power Company, Shanghai 200072, China)

Fund Project:

This work is supported by National Key Research and Development Program of China(No.2018YFB0904000);Science and Technology Project of State Grid(No.SGJB0000TKJS1801242)

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    摘要:

    在新电改背景下,正确合理地评估电力用户的信用风险及提出预警,是决定供电企业进一步发展的重要因素。为了进一步地开展电力用户履约信用评价,帮助供电企业权衡电力交易时的风险水平,研究了电力用户信用风险评价原则和指标,并从该指标入手,基于随机森林算法构建了电力用户的信用风险预警模型,从企业市场风险、财务风险、信用风险、运营风险和结算管理风险对电力用户的信用风险进行了评价,有望完善电力市场交易机制,促进资源合理高效分配,使得电力行业在信用体系的保障下健康发展。

    Abstract:

    In the background of the new power reform, correct and reasonable assessment of the credit risk of power usersand early warning are important factors that restrict the further development of power supply enterprises. In order to carry out creditevaluation of power users and help power supply enterprises to balance the risk level of power trading, based on random forest algorithm, the evaluation principles and indicators of power users arestudied accroding to the evaluation indicators of credit risk in power market. The early warning model of power users evaluates thecredit risk of power users from enterprise market risk, financialrisk, credit risk, operational risk and settlement management risk.It is expected to improve the trading mechanism of electricity market and promote the rational and efficient allocation of resources,help power industry develope healthily under the protection of credit system.

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余 培,刘其辉,石 城.新电改背景下电力用户信用风险预警模型与评价方法[J].电力需求侧管理,2020,22(2):34-38

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  • 最后修改日期:2019-11-25
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  • 在线发布日期: 2020-03-30
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