Power grid power sale quantity prediction method based on season time sequence analysis

Abstract

The invention provides a power grid power sale quantity prediction method based on season time sequence analysis. Firstly, the historical monthly power sale quantity is decomposed into trend cyclic variables, season variables and random variables of the monthly power sale quantity through an X12 season adjusting method, the trend cyclic variables with the obvious rule are predicted through a time sequence method, the defects generated when only the time sequence method is used for predicting the monthly power sale quantity can be overcome to a large degree, the prediction accuracy of the monthly power sale quantity is remarkably improved, the monthly power sale quantity within the prediction period can be well predicted, and the method is used for guiding and planning the power yield of a power system in all months within the prediction period so as to solve the problems that in the prior art, due to the fact that the prediction accuracy of the future monthly power sale quantity is not high, power yield planning is inaccurate, power supply is seriously insufficient, or supply is excess, and energy is wasted. Multiple prediction calculating processes can be achieved simply through Eviews software in the prior art, high practicality is achieved, and application and popularization are convenient.

Description

technical field [0001] The invention relates to the technical field of power system electricity forecasting, in particular to a method for predicting power grid sales in the power system based on seasonal time series analysis. Background technique [0002] As an important part of my country's social market economy, the electricity market has a significant impact on the sustainable development of the national economy. In electricity marketing, electricity sales is one of the important contents, and it is of great significance for electric power enterprises to continuously improve electricity forecasting methods and improve forecasting accuracy. Through the forecast and analysis of electricity sales, power companies can more reasonably determine the total sales quota, so as to make relevant decisions to guide the rational operation of power plants and transmission and distribution networks; power companies can grasp the peak and valley distribution in the future power grid ope...

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Problems solved by technology

[0004] Aiming at the above-mentioned deficiencies in the prior art, the purpose of the present invention is to provide a forecasting method for grid electricity sales based on seasonal time series analysis. The method first adopts the X12 seasonal adjustment method to decompose the historical electricity sales data before the forecast cycle to obtain the historical data. The trend cycle variables and seasonal variables corresponding to each month in the data, and then use the time series method to predict the monthly electricity sales corresponding to each month in the forecast period according to the obtained trend cycle variables and seasonal variables, so as to guide the planning of the power system in the forecast period In order to solve the problems of inaccurate power production planning due to low prediction accuracy of future monthly electricity sales in the existing technology, serious shortage of power supply or excess supply and waste of energy, etc.

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