Short-term household electrical load prediction method and system, storage medium and equipment

Abstract

The invention discloses a short-term household electrical load prediction method and system, a storage medium and equipment. The method comprises the following steps: determining the architecture of a BP neural network, and selecting a training set sample, a test set sample and related parameters; then initializing the particle swarm; determining a particle individual historical extreme value and a group historical extreme value according to the initialized parameters; updating the position and the speed of the particle according to the fitness value F obtained by calculation, and completing iteration when a preset error range is reached or the maximum number of iterations is completed, at the moment, the gbest position being the optimal weight and threshold; performing BP neural network training on the obtained optimal weight and threshold; and comparing the actual load value with the predicted load value, calculating an average relative error of the prediction day, stopping iteration and ending training when the average relative error meets a preset error allowable range, and outputting a prediction result through error judgment to complete load prediction. The structure is simple, and the reliability of the prediction result is enhanced.

Description

technical field [0001] The invention belongs to the technical field of electric charge forecasting, and in particular relates to a short-term household electric load forecasting method, system, storage medium and equipment. Background technique [0002] With the gradual deepening of reforms in my country's power system and mechanism, and continuous innovation and practice in power platform construction, the era of digital and information-based power grids has entered the right track, and smart grids have entered thousands of households. Subsequently, the field of power load forecasting has also made great progress. Because of its own uniqueness, short-term load forecasting has an important impact on the safe and stable operation of the power network, so the prediction of the next few hours or even days Electric energy load, formulate corresponding short-term scheduling plan, and be able to respond in time when unexpected situations occur, which will play an important role in...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to provide a short-term household electricity load forecasting method, system, storage medium and equipment to solve the problem of low short-term household load forecasting accuracy

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