Waveform feature-based electricity sale quantity prediction method and system

Abstract

The invention discloses an electricity sale quantity prediction method and system based on waveform characteristics. The method comprises the following steps: acquiring a historical temperature-time function change curve and a historical electricity sale quantity-time function change curve; according to a temperature-time change curve of four days before a to-be-predicted time period in a preset period, determining a temperature characteristic value of the temperature-time change curve; determining the electric quantity similarity of the electric quantity sale-time change curve according to the electric quantity sale-time change curve of the first four days of the to-be-predicted time period in the preset period; according to the temperature characteristic value and the electric quantity similarity, determining the change rate of the electricity sale quantity; and calculating the predicted electric quantity according to the change rate of the electric quantity sale. By means of the mode, the requirement for the data size can be reduced, the implementation time is short, the calculated amount is reduced, and the cost of power enterprises can be reduced.

Description

technical field [0001] The invention relates to the technical field of electricity market electricity forecasting, and in particular, to a method and system for forecasting electricity sales based on waveform characteristics. Background technique [0002] With the rapid development of the current society, the electricity consumption of all walks of life has increased sharply, and energy conservation and emission reduction is a major subject of our country's research. Therefore, the forecast of electricity sales is particularly important. In electricity marketing, electricity sales is an important part of it, and it is of great significance for electricity companies to continuously improve electricity forecasting methods and improve forecasting accuracy. Through the forecast and analysis of electricity sales, power companies can rationally arrange resources and avoid excessive waste, which is of great significance to promoting the development and construction of the electric...

AI Technical Summary

Problems solved by technology

Most of the research focuses on external uncertain factors to improve the forecasting accuracy of electricity sales of electricity sales companies, but does not consider the number of users. Many existing models have shortcomings such as long training time and large amount of calculation.

The announcement number is CN109190820 A, which is a patent document titled a method for in-depth forecasting of electric power market sales considering customer churn rate. It proposes a calculation method for power customer churn rate based on survival analysis. Significantly improved, but due to the large number of users involved, the computational efficiency decreases

The announcement number is CN 112435054 A, and the patent document titled the prediction method of electricity sales of nuclear extreme learning machine based on the generalized maximum correlation entropy criterion is proposed to use the generalized maximum correlation entropy criterion as the cost function of the prediction model, and the prediction effect is better, but due to The amount of data is large, and the model training time is long

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