A Method of Power Demand Forecasting and Early Warning Based on Leading Industries

Abstract

The invention relates to a leading industry based electricity demand prediction and early warning method, and belongs to the field of electricity system electricity demand analysis. The method includes performing time difference correlation analysis on industrial electricity consumption and a total electricity consumption sequence; predicting electricity consumption growth rates of each early-warning leading industry in following months virtually according to historical electricity consumption; calculating early warning success rate of each early-warning leading industry in history virtually; calculating early warning accuracy and coverage of each early-warning leading industry; calculating a mutual information value between each early-warning leading industry and the total electricity consumption sequence, and determining an electricity-demand-oriented early-warning leading industry set; calculating early warning threshold values of electricity demand growth rates of the early-warning leading industries; when the growth rates exceed the early warning numerical value range, sending out early warning signals, and performing rolling correction on follow-up electricity demand prediction. By the leading industry based electricity demand prediction and early warning method, electricity demand prediction accuracy can be improved, and supply and operation risks of a power grid can be reduced.

Description

technical field [0001] The invention belongs to the field of electric power demand analysis of electric power systems, and in particular relates to a method for forecasting and early warning of electric power demand based on leading industries. Background technique [0002] Power demand forecasting is an important business link in the power system. Improve the accuracy of power demand forecasting, and provide accurate early warnings when abnormal conditions such as power demand growth or decline occur. It is important for scientifically arranging power system maintenance and power generation plans, and optimizing power grids. It is of great significance to start an orderly electricity consumption work in a timely manner when the power supply and demand are tight, and reduce the supply risk and operation risk of the power grid. [0003] Most of the existing power demand forecasting methods are based on the trend extrapolation of historical data, and the correlation of externa...

AI Technical Summary

Problems solved by technology

However, when a major social event occurs or an "inflection point" occurs in the economic situation, it will be difficult to make accurate predictions through trend extrapolation, and in the face of a large number of complex external factors, it is also difficult to extract truly meaningful Early warning signals; therefore, in this case, traditional methods will face greater difficulties in forecasting and early warning of power demand

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