Neuro-Cybernetic System for Forecasting Electricity Consumption in the Bulgarian National Power System

Kostadin Yotov, Emil Hadzhikolev, Stanka Hadzhikoleva () and Stoyan Cheresharov
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Kostadin Yotov: Faculty of Mathematics and Informatics, University of Plovdiv Paisii Hilendarski, 236 Bulgaria Blvd., 4027 Plovdiv, Bulgaria
Emil Hadzhikolev: Faculty of Mathematics and Informatics, University of Plovdiv Paisii Hilendarski, 236 Bulgaria Blvd., 4027 Plovdiv, Bulgaria
Stanka Hadzhikoleva: Faculty of Mathematics and Informatics, University of Plovdiv Paisii Hilendarski, 236 Bulgaria Blvd., 4027 Plovdiv, Bulgaria
Stoyan Cheresharov: Faculty of Mathematics and Informatics, University of Plovdiv Paisii Hilendarski, 236 Bulgaria Blvd., 4027 Plovdiv, Bulgaria

Sustainability, 2022, vol. 14, issue 17, 1-18

Abstract: Making forecasts for the development of a given process over time, which depends on many factors, is in some cases a difficult task. The choice of appropriate methods—mathematical, statistical, or artificial intelligence methods—is also not obvious, given their great variety. This paper presented a model of a forecasting system by comparing the errors in the use of time series on the one hand, and artificial neural networks on the other. The model aims at multifactor predictions based on forecast data on significant factors, which were obtained by automated testing of different methods and selection of the methods with the highest accuracy. Successful experiments were conducted to forecast energy consumption in Bulgaria, including for household consumption; industry consumption, the public sector and services; and total final energy consumption.

Keywords: electricity consumption; forecast energy consumption; forecasting system (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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