Extra-high voltage drop point plan optimal selection method based on cloud model

Abstract

The invention belongs to the field of electric power system planning, and particularly relates to an extra-high voltage drop point plan optimal selection method based on a cloud model. The method includes the steps that (1), an extra-high voltage drop point evaluation index system about safety, regional characteristics and perspective adaptability of drop points is set up; (2), an evaluation index weighting method based on a variance maximization model is set up; (3), the extra-high voltage drop point plan optimal selection comprehensive evaluation method based on the cloud model is set up. The requirement for the complete, comprehensive and effective evaluation index system for evaluating the extra-high voltage drop points is met, an effective tool is supplied to eliminate the influence on determination of evaluation index weights by using the single weighting method, and a reference basis is provided for adding the new extra-high voltage drop point plan optimal selection method and applying the cloud model to comprehensive evaluation of extra-high voltage drop point plan optimal selection.

Description

Technical field [0001] The invention belongs to the field of power system planning, in particular to a method for establishing a cloud model-based UHV drop point planning optimization. Background technique [0002] UHV drop point planning is an indispensable part of UHV power grid construction. It aims to strengthen the grid structure, improve power supply quality and power supply reliability. The optimal planning of location selection is a complex multi-attribute decision-making problem. It is very important to scientifically and reasonably establish a comprehensive evaluation index system, and use weighting methods and evaluation methods. [0003] The methods for establishing the index system are often divided into two categories, one is the subjective evaluation method of experts, the other is the comparative judgment method and the data statistical analysis method. The former is suitable for the evaluated objects with limited data and is mainly determined based on the rich expe...

AI Technical Summary

Problems solved by technology

Among these methods, there are also some problems in the application of system evaluation. For example, the choice of evaluation method is very random, and different methods may give different results; the evaluation method itself also has many shortcomings. For example, the gray relational degree analysis method only To solve the uncertainty of the system, the fuzzy comprehensive evaluation method only solves the fuzziness of the system

However, in the process of UHV drop point optimization, uncertainty and ambiguity often exist at the same time

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