Bus peak load prediction method considering complex meteorological influence

Abstract

The invention relates to a bus peak load prediction method considering complex meteorological influence, and belongs to the technical field of bus peak load prediction. According to the method, the feature importance degree result of the condition mutual information on the to-be-selected features in the original feature set is used as the basis, and an IPSO-ELM serves as a predictor, forward feature selection is performed, an optimal characteristic set of bus peak load prediction is determined; the influence of characteristic redundancy on the prediction precision during bus peak load prediction is reduced; and optimal prediction models are constructed for different buses, so that the prediction precision of different buses is effectively improved, an improved particle swarm optimization extreme learning machine is introduced to be combined with a linear method, peak load prediction in different scenes is carried out, and the prediction requirements in small-sample or sample-free scenes are met.

Description

technical field [0001] The invention belongs to the technical field of busbar peak load forecasting, and in particular relates to a busbar peak load forecasting method considering complex meteorological influences. Background technique [0002] The historical data of busbar peak load is limited, fluctuates violently and presents nonlinear and random characteristics, and the problem of low forecasting accuracy and difficult forecasting has become an urgent problem to be solved. How to improve the forecasting accuracy of busbar peak load has become an urgent problem to be solved. Bus peak load forecasting is an important basis for ensuring reliable and stable operation of power systems. It is of great significance to analyze and study methods to improve the accuracy of bus peak load forecasting. [0003] At present, there have been many studies on the bus load forecasting, which optimized the bus load forecast according to the characteristics of the bus load, but did not fully...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a bus peak load forecasting method that takes into account the influence of complex weather to solve the problem of small samples that have not yet been addressed in peak load forecasting, peak load fluctuations and limited historical data in the prior art Technical Issues for Conducting Targeted Analysis

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