Abstract
Energy is an essential requirement for sustainable development, society, and the world. Turkey has been trying to increase the use of renewable sources in electricity energy production with the incentive policies it has implemented in recent years. Accordingly, in the 2019–2023 Strategic Plan of the Ministry of Energy and Natural Resources, targets to increase the installed capacity of renewable energy sources have been determined. In this context, this article examines fort the first time, the effect of installed capacity of renewable energy sources on sectoral electricity demand. Thus, the study aims to evaluate the renewable energy policies implemented in Turkey. For this purpose, firstly, sectoral electricity demands were estimated for the period 1988–2017 using the autoregressive distributed lag bound testing approach. Then, forecasts were made for the period 2019–2023 with the econometric simulation method. The findings show that the Installed Capacity variable significantly and negatively affects electricity demand in all sectors in the long run. According to the forecast results made in the second stage of the study, it was observed that the higher the increase rate in the installed capacity of renewable energy sources, the faster the electricity demand would decrease. According to these results, Turkey needs to increase the share of renewable energy sources in electricity production in terms of economic and environmental sustainability.
Graphical Abstract
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
Data can be shared with third parties at any time.
References
Agboola P O, Hossain M, Gyamfi B A & Bekun FV (2022). Environmental consequences of foreign direct investment influx and conventional energy consumption: evidence from dynamic ARDL simulation for Turkey. Environ Sci Pollut Res 1–14. https://doi.org/10.1007/s11356-022-19656-3
Akan, Y. & Tak, S. (2003). Türkiye Elektrik Enerjisi Ekonometrik Talep Analizi. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi 17 (1–2). https://doi.org/10.1016/j.renene.2020.08.062
Alkan Ö, Albayrak ÖK (2020) Ranking of renewable energy sources for regions in Turkey by fuzzy entropy based fuzzy COPRAS and fuzzy MULTIMOORA. Renew Energy 162:712–726
Arisoy I, Ozturk I (2014) Estimating industrial and residential electricity demand in Turkey: A time varying parameter approach. Energy 66:959–964. https://doi.org/10.1016/j.energy.2014.01.016
Aslani A, Helo P, Naaranoja M (2014) Role of renewable energy policies in energy dependency in Finland: System dynamics approach. Appl Energy 113:758–765. https://doi.org/10.1016/j.apenergy.2013.08.015
Banerjee A, Dolado JJ, Hendry DF, Smith GW (1986) Exploring equilibrium relationships in econometrics through static models: some monte-carlo evidence. Oxf Bull Econ Stat 48:253–277. https://doi.org/10.1111/j.1468-0084.1986.mp48003005.x
Baris K, Kucukali S (2012) Availibility of renewable energy sources in Turkey: current situation, potential, government policies and the EU perspective. Energy Policy 42:377–391. https://doi.org/10.1016/j.enpol.2011.12.002
Basaran ST, Dogru AO, Balcik FB, Ulugtekin NN, Goksel C, Sozen S (2015) Assessment of renewable energy potential and policy in Turkey-Toward the acquisition period in European Union. Environ Sci Policy 46:82–94. https://doi.org/10.1016/j.envsci.2014.08.016
Bilgili M, Sahin B, Yasar A, Simsek E (2012) Electric energy demands of Turkey in residential and industrial sectors. Renew Sustain Energy Rev 16(1):404–414. https://doi.org/10.1016/j.rser.2011.08.005
Boran FE (2018) A new approach for evaluation of renewable energy resources: a case of Turkey. Energy Sources Part B 13(3):196–204. https://doi.org/10.1080/15567249.2017.1423414
Boran F, Boran K, Dizdar E (2012a) A fuzzy multi criteria decision making to evaluate energy policy based on an information axiom: a case study in Turkey. Energy Sources Part B 7(3):230–240. https://doi.org/10.1080/15567240902839294
Boran F, Boran K, Menlik T (2012b) The evaluation of renewable energy technologies for electricity generation in Turkey using intuitionistic fuzzy TOPSIS. Energy Sources Part B 7(1):81–90. https://doi.org/10.1080/15567240903047483
BP (2019). British Petroleum. Retrieved from https://www.bp.com/content/dam/bp/business-sites/en/global/corporate/pdfs/energy-economics/statistical-review/bp-stats-review 2019-full-report.pdf. [accessed 25 December 2019].
Brown RL, Durbin J, Evans JM (1975) Techniques for testing the constancy of regression relationships over time. J Roy Stat Soc: Ser B (methodol) 37(2):149–163. https://doi.org/10.1111/j.2517-6161.1975.tb01532.x
Büyüközkan G, Güleryüz S (2016) An integrated DEMATEL-ANP approach for renewable energy resources selection in Turkey. Int J Prod Econ 182:435–448. https://doi.org/10.1016/j.ijpe.2016.09.015
Büyüközkan G, Güleryüz S (2017) Evaluation of Renewable Energy Resources in Turkey using an integrated MCDM approach with linguistic interval fuzzy preference relations. Energy 123:149–163. https://doi.org/10.1016/j.energy.2017.01.137
Çelikbilek Y, Tüysüz F (2016) An integrated grey based multi-criteria decision making approach for the evaluation of renewable energy sources. Energy 115:1246–1258. https://doi.org/10.1016/j.energy.2016.09.091
Cialani C, Mortazavi R (2018) Household and industrial electricity demand in Europe. Energy Policy 122:592–600. https://doi.org/10.1016/j.enpol.2018.07.060
Csereklyei Z (2020) Price and income elasticities of residential and industrial electricity demand in the European Union. Energy Policy 137:111079. https://doi.org/10.1016/j.enpol.2019.111079
de Oliveira EM, Oliveira FLC (2018) Forecasting mid-long term electric energy consumption through bagging ARIMA and exponential smoothing methods. Energy 144:776–788. https://doi.org/10.1016/j.energy.2017.12.049
Demir C, Cergibozan R (2020) Does alternative energy usage converge across Oecd countries? Renew Energy 146:559–567. https://doi.org/10.1016/j.renene.2019.06.180
Dilaver Z, Hunt LC (2011a) Industrial electricity demand for Turkey: a structural time series analysis. Energy Econ 33(3):426–436. https://doi.org/10.1016/j.eneco.2010.10.001
Dilaver Z, Hunt LC (2011b) Modelling and forecasting Turkish residential electricity demand. Energy Policy 39(6):3117–3127. https://doi.org/10.1016/j.enpol.2011.02.059
Dogan E (2015) The relationship between economic growth and electricity consumption from renewable and non-renewable sources: a study of Turkey. Renew Sustain Energy Rev 52:534–546. https://doi.org/10.1016/j.rser.2015.07.130
Dogan E (2016) Analyzing the linkage between renewable and non-renewable energy consumption and economic growth by considering structural break in time-series data. Renew Energy 99:1126–1136. https://doi.org/10.1016/j.renene.2016.07.078
Dong B, Li Z, Rahman SM, Vega R (2016) A hybrid model approach for forecasting future residential electricity consumption. Energy Build 117:341–351. https://doi.org/10.1016/j.enbuild.2015.09.033
El-Shazly A (2013) Electricity demand analysis and forecasting: a panel cointegration approach. Energy Econ 40:251–258. https://doi.org/10.1016/j.eneco.2013.07.003
Engle RF & Granger CW (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: J Econ Soc 251–276. https://doi.org/10.2307/1913236
EPDK (2015). Enerji Piyasası Düzenleme Kurumu. Dağıtım Lisansı Sahibi Tüzel Kişiler ve Görevli Tedarik Şirketlerinin Tarife Uygulamalarına İlişkin Usul ve Esaslar. T.C. Resmi Gazete, 29579, 31. Aralık. https://www.epdk.gov.tr/Detay/Icerik/3-1994/dagitim-lisansi-sahibi-tuzel-kisiler-ve-gorevli-t.
ETKB (2019). Enerji ve Tabii Kaynaklar Bakanlığı. Retrieved from https://sp.enerji.gov.tr/ETKB_2019_2023_Stratejik_Plani.pdf. [accessed 11 December 2019].
ETKB (2020). Enerji ve Tabii Kaynaklar Bakanlığı. Retrieved from https://enerji.gov.tr/enerji-isleri-genel-mudurlugu-denge-tablolari. [accessed 5 August 2020].
Gautam TK, Paudel KP (2018) Estimating sectoral demands for electricity using the pooled mean group method. Appl Energy 231:54–67. https://doi.org/10.1016/j.apenergy.2018.09.023
Gerrard W, Godfrey L (1998) Diagnostic checks for single-equation error-correction and autoregressive distributed lag models. Manch Sch 66(2):222–237. https://doi.org/10.1111/1467-9957.00098
Gomes JG, Pinto JMXu, Zhao H, C. & Hashim, H. (2020) Modeling and planning of the electricity energy system with a high share of renewable supply for Portugal. Energy 211:118713. https://doi.org/10.1016/j.energy.2020.118713
Gregory AW, Hansen BE (1996) Residual-based tests for cointegration in models with regime shifts. J Econ 70(1):99–126. https://doi.org/10.1016/0304-4076(69)41685-7
Guefano S, Tamba JG, Azong TEW, Monkam L (2021) Forecast of electricity consumption in the Cameroonian residential sector by Grey and vector autoregressive models. Energy 214:118791. https://doi.org/10.1016/j.energy.2020.118791
Günay ME (2016) Forecasting annual gross electricity demand by artificial neural networks using predicted values of socio-economic indicators and climatic conditions: Case of Turkey. Energy Policy 90:92–101. https://doi.org/10.1016/j.enpol.2015.12.019
Guven D, Kayalica MO, Kayakutlu G, Isikli E (2021) Impact of climate change on sectoral electricity demand in Turkey. Energy Sources Part B 16(3):235–257. https://doi.org/10.1080/15567249.2021.1883772
Guzović Z, Duic N, Piacentino A, Markovska N, Mathiesen BV & Lund H (2022). Recent advances in methods, policies and technologies at sustainable energy systems development. Energy 123276. https://doi.org/10.1016/j.energy.2022.123276
Halicioglu F (2007) Residential electricity demand dynamics in Turkey. Energy Econ 29(2):199–210. https://doi.org/10.1016/j.eneco.2006.11.007
Holtedahl P, Joutz FL (2004) Residential electricity demand in Taiwan. Energy Econ 26(2):201–224. https://doi.org/10.1016/j.eneco.2003.11.001
IEA. (2019). International Energy Agency. Retrieved from https://www.iea.org/data-and-statistics. [accessed 15 November 2019].
IMF. (2019). International Monetary Fund. Retrieved from https://www.imf.org/en/Publications/CR/Issues/2019/12/26/Turkey-2019-Article-IV-Consultation-Press-Release-Staff-Report-and-Statement-by-the-48920. [accessed 12 February 2020].
Jamil F, Ahmad E (2011) Income and price elasticities of electricity demand: Aggregate and sector-wise analyses. Energy Policy 39(9):5519–5527. https://doi.org/10.1016/j.enpol.2011.05.010
Johansen S, Juselius K (1990) Maximum likelihood estimation and inference on cointegration—with appucations to the demand for money. Oxford Bull Econ Stat 52(2):169–210
Kavaz I (2020) Analysing the Industrial Electricity Demand for Turkey. Bingöl Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 4(2):187–218. https://doi.org/10.33399/biibfad.761687
Kaytez F, Taplamacioglu MC, Cam E, Hardalac F (2015) Forecasting electricity consumption: A comparison of regression analysis, neural networks and least squares support vector machines. Int J Electr Power Energy Syst 67:431–438. https://doi.org/10.1016/j.ijepes.2014.12.036
Kilickaplan A, Bogdanov D, Peker O, Caldera U, Aghahosseini A, Breyer C (2017) An energy transition pathway for Turkey to achieve 100% renewable energy powered electricity, desalination and non-energetic industrial gas demand sectors by 2050. Sol Energy 158:218–235. https://doi.org/10.1016/j.solener.2017.09.030
Kucukali S, Baris K (2011) Renewable energy policy in Turkey. World Renewable Energy Congress-Sweden, Linköping
Kumar D, Tewary T (2022) Techno-economic assessment and optimization of a standalone residential hybrid energy system for sustainable energy utilization. Int J Energy Res 46(8):10020–10039. https://doi.org/10.1002/er.6389
Lenzen M, Dey C, Foran B (2004) Energy requirements of Sydney households. Ecol Econ 49(3):375–399. https://doi.org/10.1016/j.ecolecon.2004.01.019
Lewis CD (1982). Industrial and business forecasting methods: a practical guide to exponential smoothing and curve fitting. Butterworth-Heinemann
Lin W, Chen B, Luo S, Liang L (2014) Factor analysis of residential energy consumption at the provincial level in China. Sustainability 6(11):7710–7724. https://doi.org/10.3390/su6117710
Lumsdaine RL, Papell DH (1997) Multiple trend breaks and the unit-root hypothesis. Rev Econ Stat 79(2):212–218. https://doi.org/10.1162/003465397556791
MacMackin N, Miller L, Carriveau R (2019) Modeling and disaggregating hourly effects of weather on sectoral electricity demand. Energy 188:115956. https://doi.org/10.1016/j.energy.2019.115956
Mah JS (2000) An empirical examination of the disaggregated import demand of Korea—the case of information technology products. J Asian Econ 11(2):237–244. https://doi.org/10.1016/S1049-0078(00)00053-1
Melikoglu M (2016) The role of renewables and nuclear energy in Turkey׳ s Vision 2023 energy targets: Economic and technical scrutiny. Renew Sustain Energy Rev 62:1–12. https://doi.org/10.1016/j.rser.2016.04.029
MGM (2020) Meteoroloji Genel Müdürlüğü. Retrieved from https://www.mgm.gov.tr/FILES/resmi-istatistikler/parametreAnalizi/Turkiye-Ortalama-Sicaklik-2020.pdf. Accessed 18 Oct 2020
Moreno JJM, Pol AP, Abad AS, Blasco BC (2013) Using the R-MAPE index as a resistant measure of forecast accuracy. Psicothema 25(4):500–506 http://hdl.handle.net/11162/98545 [accessed 23 December 2021]
Narayan PK, Smyth R (2005a) Structural breaks and unit roots in Australian macroeconomic time series. Pac Econ Rev 10(4):421–437. https://doi.org/10.1111/j.1468-0106.2005.00283.x
Narayan PK, Smyth R (2005b) The residential demand for electricity in Australia: an application of the bounds testing approach to cointegration. Energy Policy 33(4):467–474. https://doi.org/10.1016/j.enpol.2003.08.011
Narayan PK, Smyth R, Prasad A (2007) Electricity consumption in G7 countries: A panel cointegration analysis of residential demand elasticities. Energy Policy 35(9):4485–4494. https://doi.org/10.1016/j.enpol.2007.03.018
Ndiritu SW, Engola MK (2020) The effectiveness of feed-in-tariff policy in promoting power generation from renewable energy in Kenya. Renew Energy 161:593–605. https://doi.org/10.1016/j.renene.2020.07.082
Nwulua NI, Agboolab OP (2011) Utilizing renewable energy resources to solve Nigeria’s electricity generation problem. Int J Thermal Environ Eng 3(1):15–20
Othman NS, Hariri NHM (2021) Estimating the causality and elasticities of residential electricity consumption for Malaysia. Int J Energy Econ Policy 11(6):335. https://doi.org/10.32479/ijeep.11727
Ozturk HK, Ceylan H (2005) Forecasting total and industrial sector electricity demand based on genetic algorithm approach: Turkey case study. Int J Energy Res 29(9):829–840. https://doi.org/10.1002/er.1092
Papapostolou A, Karakosta C, Doukas H (2017) Analysis of policy scenarios for achieving renewable energy sources targets: A fuzzy TOPSIS approach. Energy Environ 28(1–2):88–109. https://doi.org/10.1177/0958305X16685474
Pata UK (2018) Renewable energy consumption, urbanization, financial development, income and CO2 emissions in Turkey: testing EKC hypothesis with structural breaks. J Clean Prod 187:770–779. https://doi.org/10.1016/j.jclepro.2018.03.236
Pata UK, Balsalobre-Lorente D (2022) Exploring the impact of tourism and energy consumption on the load capacity factor in Turkey: a novel dynamic ARDL approach. Environ Sci Pollut Res 29(9):13491–13503. https://doi.org/10.1007/s11356-021-16675-4
Pata UK, Kahveci S (2018) A multivariate causality analysis between electricity consumption and economic growth in Turkey. Environ Dev Sustain 20(6):2857–2870. https://doi.org/10.1007/s10668-017-0020-z
Perron P (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica: J Econ Soc 1361–1401
Pesaran MH, Shin Y, Smith RJ (2001) Bounds testing approaches to the analysis of level relationships. J Appl Economet 16(3):289–326. https://doi.org/10.1002/jae.616
Pourazarm E, Cooray A (2013) Estimating and forecasting residential electricity demand in Iran. Econ Model 35:546–558. https://doi.org/10.1016/j.econmod.2013.08.006
Pourazarm, Elham, Electricity demand analysis in different sectors: a case study of Iran, Doctor of Philosophy thesis, School of Economics, University of Wollongong, 2012. http://ro.uow.edu.au/theses/3786
Sadeghi H, Zolfaghari M, Heydarizade M (2011) Estimation of electricity demand in residential sector using genetic algorithm approach. Int J Indust Eng Prod Res 22(1):43–50
Sakkas N, Yfanti S, Daskalakis C, Barbu E, Domnich M (2021) Interpretable forecasting of energy demand in the residential sector. Energies 14(20):6568. https://doi.org/10.3390/en14206568
Şekercioğlu S, Yılmaz M (2012) Renewable energy perspectives in the frame of Turkey’s and the EU’s energy policies. Energy Convers Manage 63:233–238. https://doi.org/10.1016/j.enconman.2012.01.039
Serim N, Oran FC (2017) The renewable energy policy convergence in the EU: a comparison on Germany and Turkey’s incentives for the wind and solar energy resources. Int J Energ Econ Policy 7(3):308–320. Retrieved from https://dergipark.org.tr/en/pub/ijeeep/issue/31922/351255
Shirani-Fakhr Z, Khoshakhlagh R, Sharifi A (2015) Estimating demand function for electricity in industrial sector of Iran using structural time series model (Stsm). Appl Econ Int Dev 15(1):143–160
Silva S, Soares I, Pinho C (2018) Electricity residential demand elasticities: urban versus rural areas in Portugal. Energy 144:627–632. https://doi.org/10.1016/j.energy.2017.12.070
Sirin SM, Ege A (2012) Overcoming problems in Turkey’s renewable energy policy: How can EU contribute? Renew Sustain Energy Rev 16(7):4917–4926. https://doi.org/10.1016/j.rser.2012.03.067
Sözen A, Isikan O, Menlik T, Arcaklioglu E (2011) The forecasting of net electricity consumption of the consumer groups in Turkey. Energy Sources Part B 6(1):20–46. https://doi.org/10.1080/15567240802459201
Tatli H (2017) Short-and long-term determinants of residential electricity demand in Turkey. Int J Econ Manag Account 25(3):443–464
TEİAŞ (2018) Türkiye Elektrik İletim A.Ş. Genel Müdürlüğü. Retrieved from https://www.teias.gov.tr/tr-TR/turkiye-elektrik-uretim-iletim-istatistikleri. Accessed 17 Nov 2018
Topcu I, Ülengin F, Kabak Ö, Isik M, Unver B, Ekici SO (2019) The evaluation of electricity generation resources: The case of Turkey. Energy 167:417–427. https://doi.org/10.1016/j.energy.2018.10.126
Tserkezos ED (1992) Forecasting residential electricity consumption in Greece using monthly and quarterly data. Energy Econ 14(3):226–232. https://doi.org/10.1016/0140-9883(92)90016-7
TSKB (2019) Sektörel Görünüm: Enerji. Retrieved from https://www.tskb.com.tr/i/assets/document/pdf/enerji-sektorel-gorunumu.pdf. Accessed 10 Mar 2019
TUİK (2020a) Türkiye İstatistik Kurumu. Retrieved from https://data.tuik.gov.tr/Kategori/GetKategori?p=cevre-ve-enerji-103&dil=1. Accessed 20 Sep 2020
TUİK (2020b) Türkiye İstatistik Kurumu. Retrieved from https://data.tuik.gov.tr/Kategori/GetKategori?p=Ulastirma-ve-Haberlesme-112. Accessed 20 Sep 2020
UN (2015) Transforming our world: the 2030 Agenda for Sustainable Development. Retrieved from https://www.un.org/en/development/desa/population/migration/generalassembly/docs/globalcompact/A_RES_70_1_E.pdf. Accessed 18 Sep 2022
UN (2020) Affordable and clean energy: why it matters. Retrieved from https://www.un.org/sustainabledevelopment/wp-content/uploads/2016/08/7_Why-It-Matters-2020.pdf. Accessed 10 Sep 2022
Wang N, Mogi G (2017) Industrial and residential electricity demand dynamics in Japan: How did price and income elasticities evolve from 1989 to 2014? Energy Policy 106:233–243. https://doi.org/10.1016/j.enpol.2017.03.066
WB (2020) World Bank. Retrieved from https://www.worldbank.org/tr/country/turkey. Accessed 05 Jun 2020
Yarbay RZ, Güler AŞ, Yaman E (2011) Renewable energy sources and policies in Turkey. In 6th International Advanced Technologies Symposium (IATS’11), pp 16–18
Yekdem (2005) Yenilenebilir Enerji kaynaklarının elektrik enerjisi üretimi amaçlı kullanımına ilişkin kanun. T.C. Resmi Gazete, 5346, 18 Mayıs 2005. https://www.mevzuat.gov.tr/mevzuatmetin/1.5.5346.pdf. Accessed 10 Oct 2019
Yüksel I (2010) Energy production and sustainable energy policies in Turkey. Renew Energy 35(7):1469–1476
Zhang Q, Ishihara KN, Mclellan BC, Tezuka T (2012) Scenario analysis on future electricity supply and demand in Japan. Energy 38(1):376–385. https://doi.org/10.1016/j.energy.2011.11.046
Zhang Y, Jin W, Xu M (2021) Total factor efficiency and convergence analysis of renewable energy in Latin American countries. Renew Energy 170:785–795. https://doi.org/10.1016/j.renene.2021.02.016
Zivot E, Andrews DWK (1992) Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. J Bus Econ Stat 10(3):251
Author information
Authors and Affiliations
Contributions
Fatih Soğukpınar: conceptualization, methodology, formal analysis, ınvestigation, resources, writing—original draft, writing—review and editing, visualization. Gökhan Erkal: conceptualization, methodology, writing—review and editing, supervision. Hüseyin Özer: conceptualization, methodology, writing—review and editing, project administration.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no competing interests.
Ethical approval
Ethical approval is not required as this study uses data shared with the public.
Consent to participate
Not applicable.
Consent for publication
Not applicable.
Additional information
Responsible Editor: Arshian Sharif
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This paper derived from the doctoral dissertation performed by Fatih Soğukpınar under the supervision of Gökhan Erkal and Hüseyin Özer.
Highlights
• Renewable energy policies in Turkey have a negative impact on electricity demand.
• Renewable energy policies in Turkey are most effective in the lighting and residential sectors.
• Residential electricity demand in Turkey will be between 61.734 and 69.899 GWh in 2023.
• In 2023, the electricity demand of the Turkish industry is expected to be 148.606–150.417 GWh.
• The price elasticity of electricity demand in residentials in Turkey is less than 1.
Appendices
Appendix 1
Cusum and CusumSQ test results
Appendix 2
Comparison of actual and estimated values
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Soğukpınar, F., Erkal, G. & Özer, H. Evaluation of renewable energy policies in Turkey with sectoral electricity demand forecasting. Environ Sci Pollut Res 30, 35891–35912 (2023). https://doi.org/10.1007/s11356-022-24673-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-022-24673-3