Method for predicting annual power consumption based on elastic coefficient

Abstract

The invention provides a method for predicting annual power consumption based on an elastic coefficient. The method comprises the following steps: (1) selecting a base year and reading historical data; (2) calculating the electric elastic coefficient of each year in a historical sample interval based on the base year comparable price; (3) calculating the added value ratios of two of three main industries of each year in the historical sample interval; (4) establishing a regression model of the electric elastic coefficient of the added value ratios of the two main industries; (5) predicting the electric elastic coefficient of a target year via the regression model; (6) calculating the social power consumption of the target year via the predicted electric elastic coefficient and the GDP (Gross Domestic Product). According to the method, a new electric elastic coefficient is calculated based on the base year comparable price, the regression model is established by using the electric elastic coefficient and the added value ratios of two of three main industries, and the prediction of the social power consumption of the target year is based on a theoretical model, so that the prediction accuracy is increased.

Description

technical field [0001] The invention relates to the technical field of power grid electricity forecasting, in particular to an annual electricity forecasting method based on an elastic coefficient. [0002] Background technique [0003] The power elasticity coefficient is the ratio of the year-on-year growth rate of electricity consumption in the whole society to the year-on-year growth rate of GDP, which can reflect the relationship between power consumption and economic growth. Changes in factors such as energy consumption structure, industrial structure, technology, and living standards will lead to changes in the power elasticity coefficient. [0004] In the calculation formula of the electric power elasticity coefficient in the prior art, the year-on-year growth rate of electricity consumption and the year-on-year growth rate of GDP in the whole society are compared with the current value and the previous value. The power elasticity coefficient obtained in this way flu...

AI Technical Summary

Problems solved by technology

[0004] In the calculation formula of the electric power elasticity coefficient in the prior art, the year-on-year growth rate of electricity consumption and the year-on-year growth rate of GDP in the whole society are compared with the current value and the previous value. The power elasticity coefficient obtained in this way fluctuates greatly, and it is not easy to find out which Therefore, it cannot be used to predict the annual electricity consumption of the whole society

[0005] At present, scholars at home and abroad focus on its application in single-sequence power consumption forecasting, and compare the prediction method based on the power elasticity coefficient with other power forecasting methods, generally through theoretical experience and qualitative analysis. Analyzing and judging the influencing factors of the power elasticity coefficient, there is no demonstration of the specific influencing mechanism of these factors through empirical evidence, the elasticity coefficient itself fluctuates greatly, and it is difficult to predict accurately, so it is also difficult to apply it to power forecasting

Images