Short-term power load prediction method based on multiple factors and improved feature screening strategy

Abstract

The invention provides a short-term power load prediction method based on multiple factors and an improved feature screening strategy. The short-term power load prediction method comprises the following steps of S1, importing an original multi-factor data set and performing data preprocessing; S2, constructing a candidate feature variable set; s3, performing hour granularity feature screening based on data set reconstruction and an RReliefF algorithm; S4, introducing a k-means clustering label based on cosine similarity; S5, determining a final input variable set; and S6, carrying out model training and prediction. The method pays attention to front-end data processing of short-term power load prediction, can be used in combination with various current mainstream prediction models, can remarkably improve the prediction precision of the model, and has wide universality. According to the method, the problem of characteristic variable selection rules based on the hour granularity can be effectively solved, the shape and mode information of the load curve is added into the characteristic variables, and the prediction performance of the short-term power load is remarkably improved by improving the quality of front-end input data.

Description

technical field [0001] The invention belongs to the field of electric load forecasting, and relates to short-term electric load forecasting, in particular to a short-term electric load forecasting method based on multi-factor and improved feature screening strategies. Background technique [0002] Short-term load forecasting is of great significance in the operation of the power system. It is the guarantee for the safe and economical operation of the power grid and the basis for formulating power supply plans. As a bridge connecting energy and demand side, load forecasting involves all aspects of orderly power consumption, energy conservation and emission reduction. Accurate short-term load forecasting can not only meet the requirements of refined management of power load, but also promote demand-side reform, improve An important support for residents' electricity experience. [0003] Because the power load fluctuation trend will be affected by various external factors such...

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Problems solved by technology

[0004]Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a short-term power load forecasting method based on multi-factor and improved feature screening strategies to solve the current There are technical problems that the accuracy of short-term power load forecasting needs to be further improved

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