Electric power customer credit comprehensive evaluation method based on grey relational degree

Abstract

The invention relates to an electric power customer credit comprehensive evaluation method based on the grey relational degree, and belongs to the field of electric power analysis. The new electric power customer credit evaluation indexes including big customer direct-purchase electricity contract breach electric quantity ratio and the new energy power generation grid connection quantity are taken into consideration, and an electric power customer credit rating evaluation index system is established in the seven aspects of electricity utilization payment credit, the electric power law and regulation credit, the electric power cooperation credit, the operation capacity credit, the social communication credit, the mortgage credit guarantee and development prospect credit of the electric power customers. Three evaluation methods with different attributes including a layer analysis method, an entropy weight method and a neural network method are integrated, combined weight is adopted, linear combination coefficients are determined by minimizing the deviation between single evaluation weights and combination weights, the potential information of an evaluated object is fully extracted, and the one-sidedness of a single evaluation method is avoided. Compared with the prior art, the electric power customer credit comprehensive evaluation method based on the grey relational degree has the advantages that a grey relational degree analysis method is adopted, operation is easy, efficiency is high, and the quantity of needed data is small.

Description

technical field [0001] The invention belongs to the field of electric power analysis, and in particular relates to a comprehensive evaluation method for electric power customer credit. Background technique [0002] According to statistics, in 2013, my country's power generation was 5.32 trillion kwh, a year-on-year increase of about 7.5%, and the electricity consumption elasticity was 0.974. Among them: 870 billion kWh of hydropower generation; 4.2 trillion kWh of thermal power generation; 110 billion kWh of nuclear power generation; 134 billion kWh of wind power generation; 7 billion kWh of solar power generation; 42 billion kWh of biomass power generation Time. In order to rationally allocate these increasingly large power generation supplies and monitor the use of electricity, the work of power customer credit evaluation is becoming more and more important. [0003] At the same time, the indicator of the amount of grid-connected new energy power generation reflects the ...

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Problems solved by technology

Cluster analysis is greatly affected by singular values ​​and is sensitive to initial value selection. The number of clusters needs to be specified in advance, and the efficiency is low when the samples are insufficient and the data is inaccurate.

The method of approximating the ideal point distance is simple and easy to understand, but it cannot solve the problem of information duplication caused by the correlation between indicators

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