Comprehensive evaluation method of smart power grid construction based on principal component cluster analysis

Abstract

The invention relates to a comprehensive evaluation method of smart power grid construction based on principal component cluster analysis, which is technologically characterized by comprising the steps that at the step 1, a generally approved comprehensive evaluation index system of the smart power grid construction is established or selected; at the step 2, index data is processed by standardization; at the step 3, an index data correlation coefficient matrix is established, an eigenvalue and an eigenvector of the matrix are solved, and a principal component expression is generated; at the step 4, a principal component variance contribution rate and a cumulative variance contribution rate are calculated, and quantity of principal components is determined; at the step 5, a comprehensive principal component evaluation index function is established, and a comprehensive evaluation result of a development and construction level of a smart power grid is given; and at the step 6, a principal component factor load matrix is established, and the cluster analysis is carried out to comprehensive evaluation indexes of the smart power grid. The comprehensive evaluation method of the smart power grid construction based on the principal component cluster analysis provided by the invention combines principal component analysis and the cluster analysis in order to simplify and reconstruct the evaluation index system of the smart power grid construction and provides suggestions for the smart power grid construction is laggard areas.

Description

technical field [0001] The invention belongs to the technical field of smart grids, in particular to a comprehensive evaluation method for smart grid construction based on principal component clustering analysis. Background technique [0002] The smart grid has pointed out the direction for the development of the future power grid. It is imperative to scientifically and accurately evaluate the overall development and construction level of the smart grid and measure the degree of differentiation of smart grids in different regions. [0003] Principal Component Analysis (PCA) and Cluster Analysis (ClusterAnalysis) are one of the most convenient and quick methods for dealing with multivariate and high-dimensional systems in the discipline of modern multivariate statistical analysis. Principal component analysis is a statistical analysis method that converts multiple variables (indicators) in the system into several comprehensive indicators. Cluster analysis is a multivariate an...

AI Technical Summary

Problems solved by technology

[0004] At present, the research on the evaluation method of smart grid construction mainly focuses on the evaluation methods of the dynamic comprehensive evaluation method entropy method and production function method to evaluate the smart grid as a whole, but the combination of principal component analysis and cluster analysis The research on comprehensive evaluation in the construction stage of smart grid is still slightly insufficient

In addition, the current research on smart grid mainly focuses on the evaluation of other fields (such as benefits, etc.) based on "smart grid", and there are few studies on the construction stage of smart grid.

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