Power distribution network three-dimensional simulation training credibility evaluation method based on cloud matter-element model

Abstract

The invention relates to a power distribution network three-dimensional simulation training credibility evaluation method based on a cloud matter-element model. A correlation function of a matter-element model is expressed with a normal cloud model with randomness and fuzziness considered, the relation between various simulation training reliability evaluation indexes and the evaluation intervals of various evaluation result levels is quantified with the correlation function, conversion between quantitative calculation and the qualitative concept is achieved, and finally a power distribution network three-dimensional simulation training credibility evaluation result is worked out according to the maximum membership degree principle. Finally, with a power outage cable replacement subsystem as the embodiment, the credibility of the power outage cable replacement subsystem is evaluated, which shows the superiority and feasibility of the cloud matter-element algorithm. The cloud matter-element algorithm with the cloud model and the matter-element model combined is adopted to evaluate the credibility of power distribution network training simulation, wherein the correlation function of the matter-element model is expressed with the normal cloud model, expert scoring uncertainty is considered, and qualitative index quantification is achieved.

Description

technical field [0001] The invention relates to the evaluation of the credibility of distribution network three-dimensional simulation training, in particular to a method for evaluating the reliability of distribution network three-dimensional simulation training based on a cloud matter-element model. Background technique [0002] Distribution network training simulation is a relatively new field of power training simulation research in the past two years, and the research on the reliability of distribution network training simulation is still in its infancy. Distribution network training simulation is different from numerical simulation. It does not only look at the error between the simulated value and the actual value, but also includes the visual experience brought by the animation performance, the auditory experience brought by the sound, and the impact of the operating environment on the response speed. , Whether the setting of operation steps is standardized, whether ...

AI Technical Summary

Problems solved by technology

However, fuzzy similarity requires the participation of experts, which is inevitably accompanied by a large number of subjective factors. For distribution network training simulation, there are too many corresponding actual system evaluation indicators, resulting in too many similar elements, which brings certain problems to the calculation. Difficulty, resulting in distortion of evaluation results

[0004] In the process of credibility evaluation, the selection of evaluation indicators, the division of status levels, etc. are all selected and formulated by experts in this field, and different people have different evaluation results due to their different knowledge and experience levels, which is inevitable. Introduce human subjective factors, with strong uncertainty

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