Investment effectiveness key factor optimization method and system based on power transmission and distribution price supervision

Abstract

The invention provides an investment effectiveness key factor optimization method and system based on power transmission and distribution price supervision, and the method comprises the steps: calculating the correlation degree of factors according to a trend curve of factor quantification data; calculating a correlation coefficient according to the multistage hierarchical structure model; judgingthe influence relationship of factors according to the correlation coefficient; constructing a reachable matrix according to the influence relationship of the factors; screening a result factor groupand a driving factor group according to the reachable matrix; and outputting the achievement factor group and the driving factor group to obtain key factors influencing investment effectiveness. According to the invention, key factors of investment effectiveness are screened more objectively, comprehensively and effectively by determining the related performance among the factors.

Description

technical field [0001] The invention relates to the field of electric power market technology, in particular to a method and system for optimizing key factors of investment effectiveness based on power transmission and distribution price supervision. Background technique [0002] The investment environment of power grid enterprises is complex, including the influence of external economic and policy environments, as well as the influence of internal strategic objectives and development priorities. Therefore, it is necessary to determine the key factors affecting investment effectiveness and help power grid enterprises improve investment efficiency. [0003] At present, there are mainly two methods for investment judgment. The first one is principal component analysis, which is to delete repeated variables or closely related variables for all variables originally proposed, control the number of new variables, and make the relationship between these new variables These new vari...

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Problems solved by technology

[0003] At present, there are mainly two methods for investment judgment. The first one is principal component analysis, which is to delete repeated variables or closely related variables for all variables originally proposed, control the number of new variables, and make the relationship between these new variables These new variables are recombined into a new set of unrelated comprehensive factors to replace the original factors; however, due to the deletion of repeated variables or closely related variables, the physical meaning or practical meaning of the principal element has no meaning. The original variable is so clear, and the meaning of the comprehensive evaluation function is not clear when the eigenvalue obtained in the analysis process is negative.

Another method is the TOPSIS method, which sorts by detecting the distance between the evaluation object and the optimal solution and the worst solution. If the evaluation object is the closest to the optimal solution and the farthest away from the worst solution, it is the best; Inferior solution, in which the value of each factor of the optimal solution reaches the optimal value of each evaluation factor, and the value of each factor of the worst solution reaches the worst value of each evaluation factor; however, the weight of this method is given in advance, and there is a certain subjectivity, and in the application process, because the new scheme is prone to reverse sequence problems, more in-depth analysis is required

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