Monthly electric quantity prediction method based on correction of business expansion growth curve and season adjustment

Abstract

The invention discloses a monthly electric quantity prediction method based on correction of a business expansion growth curve and season adjustment. The monthly electric quantity prediction method utilizes different modes to realize prediction of the monthly electric quantity curve of an individual user and an overall industry, and can extract the corresponding key parameters by means of the power utilization growth curve for the individual user to correct the overall business expansion growth curve of the industry so as to accurately predict the overall electric quantity of the industry. The monthly electric quantity prediction method performs empirical analysis of the monthly electric quantity prediction of the iron and steel industry in a region, and the prediction result shows that the prediction method provided by the invention can accurately predict the monthly electric quantity for the individual user and the overall industry, and guarantees the effectiveness of the prediction method.

Description

technical field [0001] The invention belongs to the field of electric power, and in particular relates to a monthly electricity forecasting method based on correcting industry expansion growth curves and seasonal adjustments. Background technique [0002] Power sales forecasting is an important basis for power companies to plan and operate power systems, and the accuracy of power forecasting directly affects the business decisions and economic benefits of power companies. The development and change of power demand urgently requires power companies to deeply analyze the internal change mechanism and laws of the electricity sales market, and improve the scientificity, foresight and accuracy of power forecasting. [0003] Industrial expansion equipment is a direct reflection of the relationship between power companies and users in terms of power supply and consumption. The capacity of industrial expansion equipment is closely related to the level of electricity consumption of u...

AI Technical Summary

Problems solved by technology

[0004] At present, although a lot of research and exploration have been carried out on electricity forecasting, most of the relevant research focuses on the complexity of the algorithm, and neglects the in-depth analysis of the regularity of the electricity sales market itself.

Especially for the relationship between the installed capacity and electricity consumption of industrial expansion, the existing research pays less attention and is not deep enough

Literature [1] "Ge Fei, Li Zhou, Yang Xin, et al. Research on the forecasting method of power consumption in the whole society based on industry expansion report [J]. Journal of Anhui Electrical Engineering Vocational and Technical College. 2013 (04): 31-34." Analysis The correlation between industrial electricity consumption and industrial expansion report was established, but the forecast model established directly takes the capacity of industrial expansion report as an independent variable, without considering the influence of the unstable stage of power consumption on the prediction results in the initial stage of industrial expansion report Influence; literature [2] "Yu Xiangqian, Wang Linxin, Zhang Weijing, et al. Research on the trend of industry expansion and electricity consumption based on growth curve [J]. Power Demand Side Management. 2014,16(2):21-25." Exploration According to the changing trend of electricity consumption after the user's business expansion and installation, the power consumption curve of the industry's business expansion is fitted, but the prediction model established is relatively simple, and the separation of electricity generated by the user's multiple business expansion and installation is not considered. At the same time, the influence of seasonal characteristics and related factors on the power consumption curve is not considered.

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