Conference proceeding
About designing an intelligent system for forecasting electric power consumption based on artificial neural networks


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CEUR Workshop Proceedings
Publication Details
Author list: Neudakhina Y., Trofimov V.
Publisher: CEUR-WS
Publication year: 2021
Volume number: 2843

Abstract

This article examines the problem of forecasting electric power consumption of central heating stations based on the data of a Moscow heating supply company. The features of the proposed neural-network forecasting model include historical data of electricity consumption, and average monthly temperature as a meteorological variable. The intelligent system for forecasting total electricity consumption of central heating supply stations proposed in this work is based on the dual forecasting method. The system consists of three predictor units, which allow to produce several complementary projection variants that can be combined, so the most rational of them can be selected.


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Last updated on 2021-17-12 at 13:06