Short-term load prediction method based on frequency domain decomposition and artificial intelligence algorithm

Abstract

The invention provides a short-term load prediction method based on frequency domain decomposition and an artificial intelligence algorithm, to solve the problems that an existing short-term load prediction method is single in prediction method and low in prediction precision. The method comprises the following steps: decomposing a load time sequence of original load data by using a frequency domain decomposition algorithm to obtain a daily period component, a weekly period component, a low-frequency component and a high-frequency component; predicting a day period and a weekly period by adopting a neural network algorithm; predicting the low-frequency component by adopting a random forest algorithm; and carrying out secondary decomposition on the high-frequency component, and predicting the decomposed low-frequency part by adopting a neural network algorithm. According to the short-term load prediction model based on frequency domain decomposition provided by the invention, compared with an Elman neural network and a random forest prediction result, the prediction result has higher prediction precision.

Description

technical field [0001] The present invention relates to the relevant technical field of power system forecasting, in particular to a short-term load forecasting method based on frequency domain decomposition and artificial intelligence algorithm. Background technique [0002] Load forecasting can be divided into long-term forecasting (annual forecasting), medium-term forecasting (monthly forecasting), short-term forecasting (daily forecasting) and ultra-short-term forecasting (hourly forecasting) according to the forecasting period. Short-term load forecasting is of great significance to how to arrange dispatching plan, tie-line exchange power, unit optimization combination and so on. Electric load is highly volatile and random in the short term, so short-term load forecasting is more difficult. With the gradual implementation of my country's energy-saving and emission-reduction policies, improving the accuracy of load forecasting has become an increasingly important resear...

AI Technical Summary

Problems solved by technology

[0007] The present invention aims at the problems that existing short-term load forecasting methods have single forecasting methods and low forecasting accuracy, and provides a short-term load forecasting method based on frequency domain decomposition and artificial intelligence algorithm

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