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Türkiye'nin Toplam Petrol Talebi ve Ulaştırma SektörüPetrol Talebinin Arıma Modeli İle Tahmin Edilmesi

Yıl 2013, Cilt: 18 Sayı: 3, 131 - 142, 01.09.2013

Öz

Turkey's high growth rate in the last years resulted with significant increase in energy consumption. Policy makers should give critical decisions for meeting this growing energy demand. Forecasting of energy demand is one of the most important policy tools used by the decision makers. In this study, focused on forecasting of total petroleum demand and transport petroleum demand of Turkey from 2012 to 2020 using the Autoregressive Integrated Moving Average (ARIMA) model. Turkey’s total and transport petroleum demand will increase to value of 30,58 mtep and 20,73 mtep by 2020, respectively

Kaynakça

  • 1. AKAY, Diyar ve Mehmet Atak (2007), "Grey Prediction with Rolling Mechanism for Electricity Demand Forecasting of Turkey", Energy, Volume 32, Issue 9, p.1670-1675.
  • 2. ALBAYRAK, Ali Sait (2010), "ARIMA Forecasting of Primary Energy Production and Consumption in Turkey: 1923–2006", Enerji, Piyasa ve Düzenleme, Cilt 1, Sayı 1, s.24-50.
  • 3. ALTINAY, Galip (2007), Short-run and Long-run Elasticities of Import Demand for Crude Oil in Turkey, Energy Policy, Volume 35, Issue 11, p.5829-5835.
  • 4. ALTINAY, Galip (2010), "Aylık Elektrik Talebinin Mevsimsel Model ile Orta Dönem Öngörüsü", Enerji, Piyasa ve Düzenleme, Cilt 1, Sayı 1, s.1-23.
  • 5. BİLGİLİ, Mehmet, Beşir Şahin, Abdulkadir Yaşar ve Erdoğan Şimşek (2012), "Electric Energy Demands of Turkey in Residential and Industrial Sectors", Renewable and Sustainable Energy Reviews, Volume 16, Issue 1, p.404-414.
  • 6. BOX, George E. P. ve Gwilym Jenkins (1976), Time Series Analysis: Forecasting and Control, 2nd edition, San Francisco: Holden-Day.
  • 7. CANYURT, Olcay Ersel ve Harun Kemal Öztürk (2006), "Three Different Applications of Genetic Algorithm (GA) Search Techniques on Oil Demand Estimation", Energy Conversion and Management, Volume 47, Issue 18-19, p.3138-3148.
  • 8. CEYLAN, Halim ve Harun Kemal Öztürk (2004), "Estimating Energy Demand of Turkey Based on Economic Indicators Using Genetic Algorithm Approach", Energy Conversion and Management, Volume 45, Issue15-16, p.2525-2537.
  • 9. DİLAVER, Zafer ve Lester C. Hunt (2011a), "Industrial Electricity Demand for Turkey: A Structural Time Series Analysis", Energy Economics, Volume 33, Issue 3, p.426-436.
  • 10. DİLAVER, Zafer ve Lester C. Hunt (2011b), "Modeling and Forecasting Turkish Residential Electricity Demand", Energy Policy, Volume 39, ıssue 6, p.3117–3127.
  • 11. DÜNYA ENERJİ KONSEYİ TÜRK MİLLİ KOMİTESİ (2013), http://www.dektmk.org.tr/incele.php?id=MTAw, 21.01.2013.
  • 12. EDİGER, Volkan Ş. ve Sertaç Akar (2007), "ARIMA Forecasting of Primary Energy Demand by Fuel in Turkey", Energy Policy, Volume 35, Issue 3, p.1701-1708.
  • 13. ENERJİ VE TABİİ KAYNAKLAR BAKANLIĞI (2013), http://www.enerji.gov.tr/index.php?dil=tr&sf=webpages&b=y_istatistik &bn=244&hn=244&id=398, 21.01.2013.
  • 14. EPDK (2012), Petrol Piyasası Sektör Raporu, Ankara.
  • 15. ERDOĞDU, Erkan (2007), "Electricity Demand Analysis Using Cointegration and ARIMA Modelling: A Case Study of Turkey", Energy Policy, Volume 35, Issue 2, p.1129-1146.
  • 16. HALDENBİLEN, Soner ve Halim Ceylan (2005), "Genetic Algorithm Approach to Estimate Transport Energy Demand in Turkey", Energy Policy, Volume 33, Issue 1, p.89-98.
  • 17. HAMZAÇEBİ, Coşkun (2007), "Forecasting of Turkey’s Net Electricity Energy Consumption on Sectoral Bases", Energy Policy, Volume 35, Issue 3, p.2009-2016.
  • 18. HO, S. L., M. Xie ve T. N. Goh (2002), "A Comparative Study of Neural Network and Box-Jenkins ARIMA Modeling in Time Series Prediction", Computers & Industrial Engineering, Volume 42, Issues 2–4, p.371– 375.
  • 19. HOTUNLUOĞLU, Hakan ve Etem KARAKAYA (2011), "Forecasting Turkey’s Energy Demand Using Artificial Neural Networks: Three Scenario Applications", Ege Akademik Bakış, Cilt 11, Özel Sayı, s.87-94.
  • 20. KALKINMA BAKANLIĞI (2013), http://www.kalkinma.gov.tr/ PortalDesign/PortalControls/WebIcerikGosterim.aspx?Enc=83D5A6FF0 3C7B4FC5A73E5CFAD2D9676, 30.12.2012.
  • 21. KAVAKLIOĞLU, Kadir, Halim Ceylan, Harun Kemal Özturk ve Olcay Ersel Canyurt (2009), "Modeling and Prediction of Turkey’s Electricity Consumption Using Artificial Neural Networks", Energy Conversion and Management, Volume 50, Issue 1, p.2719-2727.
  • 22. KÜÇÜKALİ, Serhat ve Kemal Barış (2010), "Turkey’s Short-Term Gross Annual Electricity Demand Forecast By Fuzzy Logic Approach", Energy Policy, Volume 38, Issue 5, p.2438-2445.
  • 23. MURAT, Yetiş Sazi ve Halim Ceylan (2006), "Use of Artificial Neural Networks for Transport Energy Demand Modeling", Energy Policy, Volume 34, Issue 1, p.3165-3172.
  • 24. ÖZTÜRK, Harun Kemal, Halim Ceylan, Olcay Ersel Canyurt ve Arif Hepbaşlı (2005), "Electricity Estimation Using Genetic Algorithm Approach: A Case Study of Turkey", Energy, Volume 30, Issue 7, p.1003-1012.
  • 25. SEVÜKTEKİN, Mustafa ve Mehmet Nargeleçekenler (2010), Ekonometrik Zaman Serileri Analizi, 3. Baskı, Nobel Yayın Dağıtım, Ankara.
  • 26. SOLAK, Ali Osman ve Ahmet Beşkaya (2013), "Türkiye’nin Net Petrol İthalatının Fiyat ve Gelir Esneklikleri: ARDL Modelleme Yaklaşımı ile Eşbütünleşme Analizi", Ul
  • 27. TOKSARI, M. Duran (2009), "Estimating the Net Electricity Energy Generation and Demand Using the Ant Colony Optimization Approach: Case of Turkey", Energy Policy, Volume 37, Issue 3, p.1181-1187.
  • 28. YİĞİT, Vecihi (2011), "Genetik Algoritma ile Türkiye Net Elektrik Enerjisi Tüketiminin 2020 Yılına Kadar Tahmini", International Journal of Engineering Research and Development, Volume 3, No 2, p.37-41.
  • 29. YUMURTACI, Zehra ve Ercan Asmaz (2004), "Electric Energy Demand of Turkey for the Year 2050", Energy Sources, Volume 26, Issue 12, p.1157-1164.
  • 30. ZHANG, G. Peter (2004), Neural Networks in Business Forecasting, Idea Group Inc., Hershey

TÜRKİYE'NİN TOPLAM PETROL TALEBİ VE ULAŞTIRMA SEKTÖRÜ PETROL TALEBİNİN ARIMA MODELİ İLE TAHMİN EDİLMESİ

Yıl 2013, Cilt: 18 Sayı: 3, 131 - 142, 01.09.2013

Öz

Türkiye'nin son yıllardaki yüksek büyüme rakamları, enerji tüketiminin önemli ölçüde artması ile sonuçlanmıştır. Artan enerji talebinin karşılanması karar vericiler açısından önemli konulardan biridir. Enerji talebinin tahmin edilmesi, enerji stratejileri ve politikalarını belirleyen karar vericiler için önemli bir araç olarak kullanılmaktadır. Bu çalışmada, Türkiye'nin toplam petrol talebi ve ulaştırma sektörü petrol talebi 2012-2020 dönemi için Otoregresif Entegre Hareketli Ortalama (ARIMA) modeli ile tahmin edilmiştir. Elde edilen tahmin değerlerine göre, 2020 yılında toplam petrol talebinin 30,58 mtep olması, ulaştırma sektörü petrol talebinin 20,73 mtep olması beklenmektedir

Kaynakça

  • 1. AKAY, Diyar ve Mehmet Atak (2007), "Grey Prediction with Rolling Mechanism for Electricity Demand Forecasting of Turkey", Energy, Volume 32, Issue 9, p.1670-1675.
  • 2. ALBAYRAK, Ali Sait (2010), "ARIMA Forecasting of Primary Energy Production and Consumption in Turkey: 1923–2006", Enerji, Piyasa ve Düzenleme, Cilt 1, Sayı 1, s.24-50.
  • 3. ALTINAY, Galip (2007), Short-run and Long-run Elasticities of Import Demand for Crude Oil in Turkey, Energy Policy, Volume 35, Issue 11, p.5829-5835.
  • 4. ALTINAY, Galip (2010), "Aylık Elektrik Talebinin Mevsimsel Model ile Orta Dönem Öngörüsü", Enerji, Piyasa ve Düzenleme, Cilt 1, Sayı 1, s.1-23.
  • 5. BİLGİLİ, Mehmet, Beşir Şahin, Abdulkadir Yaşar ve Erdoğan Şimşek (2012), "Electric Energy Demands of Turkey in Residential and Industrial Sectors", Renewable and Sustainable Energy Reviews, Volume 16, Issue 1, p.404-414.
  • 6. BOX, George E. P. ve Gwilym Jenkins (1976), Time Series Analysis: Forecasting and Control, 2nd edition, San Francisco: Holden-Day.
  • 7. CANYURT, Olcay Ersel ve Harun Kemal Öztürk (2006), "Three Different Applications of Genetic Algorithm (GA) Search Techniques on Oil Demand Estimation", Energy Conversion and Management, Volume 47, Issue 18-19, p.3138-3148.
  • 8. CEYLAN, Halim ve Harun Kemal Öztürk (2004), "Estimating Energy Demand of Turkey Based on Economic Indicators Using Genetic Algorithm Approach", Energy Conversion and Management, Volume 45, Issue15-16, p.2525-2537.
  • 9. DİLAVER, Zafer ve Lester C. Hunt (2011a), "Industrial Electricity Demand for Turkey: A Structural Time Series Analysis", Energy Economics, Volume 33, Issue 3, p.426-436.
  • 10. DİLAVER, Zafer ve Lester C. Hunt (2011b), "Modeling and Forecasting Turkish Residential Electricity Demand", Energy Policy, Volume 39, ıssue 6, p.3117–3127.
  • 11. DÜNYA ENERJİ KONSEYİ TÜRK MİLLİ KOMİTESİ (2013), http://www.dektmk.org.tr/incele.php?id=MTAw, 21.01.2013.
  • 12. EDİGER, Volkan Ş. ve Sertaç Akar (2007), "ARIMA Forecasting of Primary Energy Demand by Fuel in Turkey", Energy Policy, Volume 35, Issue 3, p.1701-1708.
  • 13. ENERJİ VE TABİİ KAYNAKLAR BAKANLIĞI (2013), http://www.enerji.gov.tr/index.php?dil=tr&sf=webpages&b=y_istatistik &bn=244&hn=244&id=398, 21.01.2013.
  • 14. EPDK (2012), Petrol Piyasası Sektör Raporu, Ankara.
  • 15. ERDOĞDU, Erkan (2007), "Electricity Demand Analysis Using Cointegration and ARIMA Modelling: A Case Study of Turkey", Energy Policy, Volume 35, Issue 2, p.1129-1146.
  • 16. HALDENBİLEN, Soner ve Halim Ceylan (2005), "Genetic Algorithm Approach to Estimate Transport Energy Demand in Turkey", Energy Policy, Volume 33, Issue 1, p.89-98.
  • 17. HAMZAÇEBİ, Coşkun (2007), "Forecasting of Turkey’s Net Electricity Energy Consumption on Sectoral Bases", Energy Policy, Volume 35, Issue 3, p.2009-2016.
  • 18. HO, S. L., M. Xie ve T. N. Goh (2002), "A Comparative Study of Neural Network and Box-Jenkins ARIMA Modeling in Time Series Prediction", Computers & Industrial Engineering, Volume 42, Issues 2–4, p.371– 375.
  • 19. HOTUNLUOĞLU, Hakan ve Etem KARAKAYA (2011), "Forecasting Turkey’s Energy Demand Using Artificial Neural Networks: Three Scenario Applications", Ege Akademik Bakış, Cilt 11, Özel Sayı, s.87-94.
  • 20. KALKINMA BAKANLIĞI (2013), http://www.kalkinma.gov.tr/ PortalDesign/PortalControls/WebIcerikGosterim.aspx?Enc=83D5A6FF0 3C7B4FC5A73E5CFAD2D9676, 30.12.2012.
  • 21. KAVAKLIOĞLU, Kadir, Halim Ceylan, Harun Kemal Özturk ve Olcay Ersel Canyurt (2009), "Modeling and Prediction of Turkey’s Electricity Consumption Using Artificial Neural Networks", Energy Conversion and Management, Volume 50, Issue 1, p.2719-2727.
  • 22. KÜÇÜKALİ, Serhat ve Kemal Barış (2010), "Turkey’s Short-Term Gross Annual Electricity Demand Forecast By Fuzzy Logic Approach", Energy Policy, Volume 38, Issue 5, p.2438-2445.
  • 23. MURAT, Yetiş Sazi ve Halim Ceylan (2006), "Use of Artificial Neural Networks for Transport Energy Demand Modeling", Energy Policy, Volume 34, Issue 1, p.3165-3172.
  • 24. ÖZTÜRK, Harun Kemal, Halim Ceylan, Olcay Ersel Canyurt ve Arif Hepbaşlı (2005), "Electricity Estimation Using Genetic Algorithm Approach: A Case Study of Turkey", Energy, Volume 30, Issue 7, p.1003-1012.
  • 25. SEVÜKTEKİN, Mustafa ve Mehmet Nargeleçekenler (2010), Ekonometrik Zaman Serileri Analizi, 3. Baskı, Nobel Yayın Dağıtım, Ankara.
  • 26. SOLAK, Ali Osman ve Ahmet Beşkaya (2013), "Türkiye’nin Net Petrol İthalatının Fiyat ve Gelir Esneklikleri: ARDL Modelleme Yaklaşımı ile Eşbütünleşme Analizi", Ul
  • 27. TOKSARI, M. Duran (2009), "Estimating the Net Electricity Energy Generation and Demand Using the Ant Colony Optimization Approach: Case of Turkey", Energy Policy, Volume 37, Issue 3, p.1181-1187.
  • 28. YİĞİT, Vecihi (2011), "Genetik Algoritma ile Türkiye Net Elektrik Enerjisi Tüketiminin 2020 Yılına Kadar Tahmini", International Journal of Engineering Research and Development, Volume 3, No 2, p.37-41.
  • 29. YUMURTACI, Zehra ve Ercan Asmaz (2004), "Electric Energy Demand of Turkey for the Year 2050", Energy Sources, Volume 26, Issue 12, p.1157-1164.
  • 30. ZHANG, G. Peter (2004), Neural Networks in Business Forecasting, Idea Group Inc., Hershey
Toplam 30 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

  Yrd.Doç.Dr.Ali Osman Solak Bu kişi benim

Yayımlanma Tarihi 1 Eylül 2013
Yayımlandığı Sayı Yıl 2013 Cilt: 18 Sayı: 3

Kaynak Göster

APA Solak, .O. (2013). TÜRKİYE’NİN TOPLAM PETROL TALEBİ VE ULAŞTIRMA SEKTÖRÜ PETROL TALEBİNİN ARIMA MODELİ İLE TAHMİN EDİLMESİ. Süleyman Demirel Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 18(3), 131-142.