Credit ability evaluation system of power selling enterprises based on big data
DOI:
https://doi.org/10.54097/tgmrb370Keywords:
big data; Key indicators; Credit ability evaluation; Performance ability.Abstract
With the gradual relaxation of the electricity market access threshold, the development pattern of market-oriented electricity sales has brought great challenges to the power grid business development. It is of great significance to select the right electricity selling enterprises in the market-oriented electric power marketing mode to ensure the practical demand of electricity customers and the operating efficiency of power grid enterprises. First, the basic characteristics of power big data are analyzed. Secondly, it classifies and analyzes the important factors that affect the performance credit of electricity selling enterprises under the new electricity transformation environment. By normalizing different types of key index data and assigning index weights, a credit ability evaluation model of electricity selling enterprises based on matter-element extension-TOPSIS is established. Finally, taking eight electricity selling enterprises in a province as an example, the credit ability evaluation model is applied to analyze and calculate the performance ability of different electricity selling enterprises. The results prove the practicability of the evaluation system proposed in this paper.
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Zhu Jialin, Zhang Min, Li Kai, et al. Research on Key Technologies of QoS Differentiation Service Based on 4/5G Converged Network [J]. Application of Electronic Technique, 202,48(06): 54-57+63.
Qiao Zhimin. Research on Enterprise Credit Evaluation and Application Based on Big Data [J]. Information Technology, 2022(05): 128-134+139.
Xia Jiajia, Ma Jing. Research on Credit Evaluation System of Small and Medium-sized Enterprises in Yangtze River Delta -- Based on AHP algorithm [J]. Journal of Guiyang University (Natural Science Edition), 202,17(01): 35-37+42.
XU Fangji. Power Equipment Supply enterprise credit evaluation model and model [J]. Enterprise Management, 2021(S1): 170-171.
Sun Yu, Niu Yanfang, Bi Xiuling. Credit evaluation of small and micro enterprises in cloud platform based on weighted iterative clustering method [J]. Journal of Shandong University of Finance and Economics, 2021, 33(06): 86-97.
Zhang Changzhen, Ma Zhanyou, Liu Lin, et al. Performance analysis of Hybrid peer-to-peer Networks with Differentiated Services [J]. Systems Engineering and Electronics: 1-10.
Guo Xin. Research on Credit Evaluation System of Science and technology project participants in Power supply and electricity enterprises [J]. China New Technology and New Products, 2020(12): 125-127.
GUO Yujie. Construction and Application of Chinese wind power enterprise Credit evaluation System [D]. Hebei University of Geosciences, 2020.
Liu Tong. Research on Credit Evaluation of power generation enterprises and electricity selling Enterprises under the background of new electricity reform [D]. Xi'an University of Technology, 2019.
Liu Jun. Research on Credit Evaluation of Internet financial Enterprises based on GA-BP neural network [D]. Henan University of Economics and Law, 2019.
Wang Haichao. Research on Credit Evaluation and Differentiated Service Management of Electricity selling Enterprises under the New electricity Transformation Environment [D]. North China Electric Power University (Beijing), 2019.
Wen Shu-min. Application of Differentiated Service in Power Quality Service [J]. Building Materials & Decoration, 2018(44): 232-233. (In Chinese)
Yang Yunlu. Research on Differentiated Service Strategy of Z Province Power Grid Company [D]. Northwest University, 2018.
Ding J. Credit evaluation of electricity enterprises based on AHP-Fuzzy Comprehensive evaluation method [J]. Science and Technology Industry, 2012, 12(02): 77-81.
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