International Journal of Scientific & Technology Research

Home About Us Scope Editorial Board Blog/Latest News Contact Us
10th percentile
Powered by  Scopus
Scopus coverage:
Nov 2018 to May 2020


IJSTR >> Volume 9 - Issue 4, April 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Forecasting Electricity Consumption In Bulgaria By Studying Its Dependence On Socio-Economic And Demographic Variables

[Full Text]



Kostadin Yotov, Emil Hadzhikolev, Stanka Hadzhikoleva



electricity consumption prediction, forecasting electricity consumption, relationship between electricity consumption and socio-economic and demographic factors.



The tendency of continuous increase in electricity consumption cannot continue forever. Many countries are actively conducting policies to reduce electricity consumption and increase energy efficiency. Their efforts are targeted in several directions - renovation of residential and industrial buildings, use of energy-saving appliances in households, optimization of electricity consumption in industry, etc. The application of new technologies and the energy generation from renewable sources have created a mix of factors that have an unpredictable impact on electricity consumption. This greatly complicates the estimation of its dependence on the other factors as well as its long-term prediction. The article presents the results of conducted research on the relationship between electricity consumption in Bulgaria and six socio-economic and demographic factors – GDP, Energy intensity, Population, Annual income, Electricity price for the industry and Electricity price for households. The results presented are part of a larger study to create a comprehensive model for forecasting electricity consumption in Bulgaria.



[1] European Commission, Energy policy: generalprinciples, available at https://www.europarl.europa.eu/factsheets/en/sheet/68/energy-policy-general-principles, April 2019.
[2] European Commission, EU 2020 target for energy efficiency, available at https://ec.europa.eu/energy/en/topics/energy-efficiency/ targets-directive-and-rules/eu-targets-energy-efficiency#20-energy-savings-by-2020, published 23 October 2014, last update: 13 February 2020.
[3] Risk Menagement Lab., Forecast of the Electricity Balance of the Republic of Bulgaria 2025, available at https://www.bia-bg.com/uploads/files/events/Energy_balans_BG2025.pdf, 2014.
[4] Preparation of a National Energy Strategy (focusing on electricity), Report of the Bulgarian Academy of Sciences, 31 October 2017, available at http://www.bas.bg/IR1.pdf.
[5] M. Kankal, A. Akpınar, M. Kömürcü, et al., “Modeling and forecasting of Turkey’s energy consumption using socio-economicand demographic variables”, Appl Energy (2010), doi:10.1016/j.apenergy.2010.12.005.
[6] U. Kumar, V. K. Jain, “Time series models (Grey-Markov, Grey Model with rolling mechanism and singular spectrum analysis) to forecast energy consumption in India”, Energy, Vol. 35 (4), April 2010, pp. 1709-1716, doi: 10.1016/j.energy.2009.12.021.
[7] Z.-X. Wang, P. Hao, “An improved grey multivariable model for predicting industrial energy consumption in China”, Applied Mathematical Modelling, Vol. 40 (11–12), June 2016, pp. 5745-5758, doi: 10.1016/j.apm.2016.01.012.
[8] G. Ogcu, O. F. Demirel, and S. Zaim, “Forecasting Electricity Consumption with Neural Networks and Support Vector Regression”, Procedia - Social and Behavioral Sciences, Vol. 58 (2012), pp. 1576 – 1585. doi: 10.1016/j.sbspro.2012.09.1144.
[9] A. S. Ahmad, M. Y. Hassan, M. P. Abdullah, et al. “A review on applications of ANN and SVM for building electrical energy consumption forecasting”, Renewable and Sustainable Energy Reviews, Volume 33, May 2014, Pages 102-109, https://doi.org/10.1016/j.rser.2014.01.069.
[10] InfoStat, available at https://infostat.nsi.bg/infostat.
[11] National Statistical Institute, available at https://www.nsi.bg.
[12] The World Bank, Electric power consumption (kWh per capita) – Bulgaria, available at https://data.worldbank.org/indicator /EG.USE.ELEC.KH.PC?contextual=default&end=2014&locations=BG&start=1997&view=chart.
[13] Matlab Documentation, available at https://www.mathworks.com/help/.