Trend fitting-based wind resource scene reduction method

Abstract

The invention discloses a trend fitting-based wind resource scene reduction method. The method is characterized by comprising the following steps of analyzing wind resource scene process lines and performing trend fitting; performing trend fitting on each wind resource scene process line in a wind resource scene process cluster to obtain a corresponding global trend sequence; performing scene reduction parameter assignment; calculating a distance between the global trend sequences in the wind resource scene process cluster before a current round of scene reduction; and finally performing scene reduction and scene probability updating until a scene set meeting a scene reduction quantity requirement and a scene probability are obtained. By automatically extracting the trends of the wind resource scene process lines, the similarity between wind resource scenes is judged and similar scenes are reduced, so that the purpose of scene reduction is achieved, random interference of wind resources is avoided, the similarity between the wind resource scenes can be conveniently judged, and the typical wind resource scene extraction effect is enhanced; and the method is of important significance for wind energy development and utilization.

Description

technical field [0001] The invention belongs to the technical field of wind resource characteristic analysis, in particular to a method for reducing wind resource scenarios based on trend fitting. Background technique [0002] The research on wind resource scene reduction is mainly used to extract typical wind resource scenes, reduce the workload of wind resource analysis, improve analysis efficiency, and provide technical support for wind energy development and utilization. Improving the reduction effect of wind resource scenarios will help to strengthen the ability to identify typical scenarios of wind resources and improve the technical level of wind resource analysis. At present, wind resource scene reduction technologies both at home and abroad directly process the time series of wind resources, identify scenes with close time series distances as similar scenes, and delete similar scenes to achieve the purpose of scene reduction. Similar scenarios mean scenarios with s...

AI Technical Summary

Problems solved by technology

The existing technology in this field has not considered the randomness of wind resources to interfere with the calculation of wind resource time series distance, which affects the recognition effect of similar wind resource scenarios

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