ABSTRACT
In this study, the overall energy status of Turkey in the early stage of the COVID-19 pandemic was analyzed. The situation in the energy market and electricity demand in the pandemic period as global issues were investigated in Turkey as a developing country. In addition to this general overview using limited data for the early period of the pandemic, energy demand and energy generation values were modeled utilizing machine learning approaches. Daily energy demand values were modeled and forecasted by utilizing Nonlinear Autoregression Neural Network (NARNN), Auto-Regressive Integrated Moving Average (ARIMA), and Long-Short Term Memory (LSTM) techniques. According to the results of the first stage of the modeling process, the LSTM approach was found as the most accurate model. In the second step of the modeling and forecasting analysis, monthly electricity generation values from natural gas and coal were predicted. In the energy generation forecasting analysis for April-December 2020 period, contraction in energy generation by natural gas and coal were obtained as 6.27% and 7.19%, respectively in comparison to 2019. Finally, the energy market during and after the pandemic was evaluated and the strategies to be implemented in the post-pandemic process were discussed.
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Notes on contributors
Adnan Sözen
Adnan Sözen is a Professor in Department of Energy Systems Engineering at Gazi University. His research focuses principally on renewable energy systems, heat transfer analysis, nanofluids/nanorefrigerants, fluid mechanics, absorption refrigeration systems, heat recovery systems, heat exchangers, nuclear power plants, energy planning and management, energy policy, artificial intelligence techniques and data envelopment analysis.
M. Mustafa İzgeç
M. Mustafa İzgeç is a board member of Energy Market Regulatory Authority (EMRA) of Republic of Turkey. He received his Ph.D. degree from Gazi University. His research focuses principally on energy planning and management, energy policy, financial analysis of energy systems and renewable energy systems.
İsmail Kırbaş
İsmail Kırbaş is an Associate Professor in Department of Computer Engineering at Burdur Mehmet Akif Ersoy University. He received his Ph.D. degree from Sakarya University. His research focuses principally on machine learning approaches, statistical data analysis, wireless systems design and analysis, signal and image processing, time series analysis and renewable energy forecasting.
F. Şinasi Kazancıoğlu
F. Şinasi Kazancıoğlu is an Associate Professor and Deputy Director-General of Turkish State Railways. He received his Ph.D. degree from Gazi University. His research focuses principally on solar energy systems, absorption cooling systems, energy management, energy policy and energy system modeling.
Azim Doğuş Tuncer
Azim Doğuş Tuncer is a Research Assistant in Department of Energy Systems Engineering at Burdur Mehmet Akif Ersoy University. He is a Ph.D. candidate in Gazi University. His research focuses principally on solar-thermal systems, CFD simulation, PVT systems, energy system modeling, energy storage, heat exchangers and nanofluids.