Abstract
This paper presents results of electricity consumption forecasting in the Western Balkan countries. Electricity consumption forecasting in the Western Balkan countries Bosnia and Herzegovina, Serbia, Montenegro, Albania, Kosovo and North Macedonia are done using conventional techniques based on extrapolation techniques using correlation between gross domestic product and electricity power consumption. Also, for electricity consumption forecasting is used advanced technique artificial neural intelligence. Inputs for training artificial neural network are for the first test case gross domestic product, population and decomposed time series of electricity consumption using Huang’s Empirical Mode Decomposition. The forecasting results using time series of electricity consumption processed with Discrete Wavelet Transform as input for training artificial neural network are also presented. Results of all used techniques are also presented, compared and discussed. Forecasted results of electricity consumption in Western Balkan for 2035 year indicate increase of about 20% of electricity consumption compared to 2017 year.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Feilat, E.A., Talal Al-Sha’abi, D., Momani, M.A.: Long-term load forecasting using neural network approach for Jordan’s power system. Engineering Press (2017)
Dinesh Reddy, M., Valley, R.K., Vishali, N.: Load forecasting using linear regression analysis in time series model for RGUKT, R.K. valley campus HT feeder. Int. J. Eng. Res. Technol. 6(5). ISSN: 2278-0181 (2017)
Muftić-Dedović, M., Dautbašić, N., Mujezinović, A.: Application of artificial neural network and empirical mode decomposition for predications of hourly values of active power consumption. In: 28th DAAAM International Symposium on Intelligent Manufacturing and Automation. https://doi.org/10.2507/28th.daaam.proceedings.xxx
Tačković, K., Nikolovski, S., Boras, V.: Kratkoročnoprognoziranjeopterećenjaprimjenommodelaumjetneneuronskemreže, Energija 5, Zagreb (2008)
Mansouri, V., Akbari, M.E.: Neural networks in electric load forecasting: a comprehensive survey. J. Artif. Intell. Electr. Eng. 3(10), 37–50 (2014)
Hadžić, A., Dautbašić, N., Konjić, T., Bećirović, E.: Prognozadnevnogdijagramaopterećenjaprimjenomneuronskihmrežai ARIMA modela, BosanskohercegovačkikomitetMeđunarodnogvijećazavelikeelektričnesisteme – BH K Cigre, Sarajevo (2017)
Bai, W., Liu, Z., Zhou, D., Wang, Q., Research of the load forecasting model base on HHT and combination of ANN. In: Power and Energy Engineering Conference, APPEEC (2009)
Khandelwal, I., Adhikari, R., Verma, G.: Time series forecasting using hybrid ARIMA and ANN models based on DWT decomposition. Procedia Comput. Sci. 48, 173–179 (2015)
Deka, P.C., Haque, L., Banhatti, A.G.: Discrete wavelet-ANN approach in time series flow forecasting - a case study of Brahmaputra river. Int. J. Earth Sci. Eng. 5(4), 673–685 (2012)
Zhang, W., Mu, G., Yan, G., An, J.: A power load forecast approach based on spatial-temporal clustering of load data. National Natural Science Foundation of China, Grant/Award Number: NSFC-51437003, 21 October 2017
Lee, K.Y., Park, J.H.: Short-term load forecasting using an artificial neural network. Trans. Power Syst. 7(1), 124–132 (1992)
Huang, H.E., Shen, Z., Long, S.R., Wu, M.C., Shih, H.H., Zheng, Q., Yen, N.-C., Tung, C.C., Liu, H.H.: The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proc. R. Soc. Lond. A 454, 903–995 (1998)
Dedovic, M.M., Avdakovic, S., Dautbasic, N.: Impact of air temperature on active and reactive power consumption - Sarajevo case study. Bosanskohercegovačkaelektrotehnika, under revision
Dedovic, M.M., Avdakovic, S., Turkovic, I., Dautbasic, N., Konjic, T.: Forecasting PM10 concentrations using neural networks and system for improving air quality. In: 2016 XI International Symposium on Telecommunications (BIHTEL), pp. 1–6 (2016)
Avdakovic, S., Nuhanovic, A., Kusljugic, M.: Wavelet theory and applications for estimation of active power unbalance in power system. Advances in Wavelet Theory and Their Applications in Engineering, Physics and Technology. IN-TECH. ISBN 979-953-307-538-8 (2012)
Avdaković, S., Čišija, N.: Wavelets as a tool for power system dynamic events analysis – state-of-the-art and future applications. J. Electr. Syst. Inf. Technol. 2(1), 47–57 (2015)
Avdakovic, S., Ademovic, A., Nuhanovic, A.: Insight into the properties of the UK power consumption using a linear regression and wavelet transform approach. Elektrotehniški Vestnik/Electrotech. Rev. 79(5), 278–283 (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Dedović, M.M. et al. (2020). Electricity Consumption Forecasting in the Western Balkan Countries. In: Avdaković, S., Mujčić, A., Mujezinović, A., Uzunović, T., Volić, I. (eds) Advanced Technologies, Systems, and Applications IV -Proceedings of the International Symposium on Innovative and Interdisciplinary Applications of Advanced Technologies (IAT 2019). IAT 2019. Lecture Notes in Networks and Systems, vol 83. Springer, Cham. https://doi.org/10.1007/978-3-030-24986-1_11
Download citation
DOI: https://doi.org/10.1007/978-3-030-24986-1_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-24985-4
Online ISBN: 978-3-030-24986-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)