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Forecasting Turkey’s Natural Gas Consumption by Using Time Series Methods

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Abstract (2. Language): 
Strategic energy planning processes, which include natural gas demand, are commonly used as a tool to design the regional and local energy system and encourage renewable energy development. The oil and natural gas market plays a very important role in the strategic energy planning process in a country. In recent years, natural gas consumption has become the fastest growing primary energy source in Turkey. In this study, natural gas consumptions of Turkey in different time periods are forecasted by using various time series methods such as exponential smoothing, winters’ forecasting and Box-Jenkins methods. These methods are compared with each other in terms of the superiority in forecasting performance. The findings reveal that in the yearly data set, double exponential smoothing model outperforms the other alternative forecasting models. On the other hand, in term of monthly data set, SARIMA model provides the better results than the others.
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REFERENCES

References: 

Al-Fattah, S.M. 2006. “Time Series Modeling for U.S. Natural Gas Forecasting”. EJournal
of Petroleum Management Economics. Vol.1.
Aras, H. and Aras, N. 2004. “Forecasting Residential Natural Gas Demand”. Energy
Sources, Part A: Recovery, Utilization, and Environmental Effects. Vol. 26:5,
pp.463-472.
BOTAS Annual Report. 2005. Boru Hatlar1 ile Petrol Tasima A.S (BOTAS),
http://www.botas.gov.tr/icerik/docs/faalrapor/2005/fr2005_full.pdf.
BOTAS Annual Report. 2006. Boru Hatlar1 ile Petrol Tasima A.S (BOTAS),
http://www.botas.gov.tr/icerik/docs/faalrapor/2006/fr2006_full.pdf.
BOTAS Annual Report. 2007. Boru Hatlar1 ile Petrol Tasima A.S (BOTAS),
http://www.botas.gov.tr/icerik/docs/faalrapor/2007/fr2007_full.pdf.
Box, G.E.P. and Jenkins, G.M. 1970. Time Series Analysis, Forecasting and Control, San
Francisco: Holden-Day (revised edn. published 1976).
Brown, R.H. and Matin, I. 1995. “Development of Artificial Neural Network Models to
Predict Daily Gas Consumption”, Proceedings of the 1995 IEEE IECON 21st
International Conference, Orlando, Vol.2, pp.1389-1394.
Brown, R.H., Marx, B.M and Corliss, G.F. 2005. Mathematical Models for Gas
Forecasting, GasDay Report No.129.
Chatfield, C. 1996. The Analyses of Time Series: An Introduction, Fifth Edition.
Chapman & Hall.
Durmayaz, A., Kadioglu, M. and Sen, Z. 2000. “An Application of the Degree-Hours
Method to Estimate the Residential Heating Energy Requirement and Fuel
Consumption in Istanbul”. Energy. Vol.25. pp.1245-1256.
Ediger, V.S. and Akar, S. 2007. “ARIMA Forecasting of Primary Energy Demand by
Fuel in Turkey”. Energy Policy. Vol.35. pp.1701-1708.
Gumrah, F., Katircioglu, D., Aykan, Y., Okumus, S. and Kilincer, N. “Modeling of Gas
Demand Using Degree-Day Concept: Case Study for Ankara”. Energy Sources,
Part A.
Kenisarian, M. and Kenisarina, K. 2007. “Energy Saving Potential in the Residential
Sector of Uzbekistan”. Energy. Vol.32. pp.1319-1325.
Khotanzad, A., Elragal, H. and Lu, T.L. 2000. “Combination of Artificial Neural-Network
Forecasters for Prediction of Natural Gas Consumption”. IEEE Transactions on
Neural Networks. Vol.11. pp. 464-473.
Kilic, A.M. 2006. “Turkey’s Natural Gas Necessity, Consumption and Future
Perspectives”. Energy Policy. Vol.34. pp.1928-1934.
Kizilaslan R. and Karlik B. 2009. “Combination of Neural Networks Forecasters For
Monthly Natural Gas Consumption Prediction”. Neural Network World. Vol. 19.
pp. 191-199.
Liu, H., Liu, H., Zheng, G., Liang, Y. and Ni, Y. 2004. “Research on Natural Gas Load
Forecasting Based on Support Vector Regression”. Fifth World Congress on
Intelligent Control and Automation. 15-19 June 2004. Vol.4, 3591A-3595.
Liu, L.M. and Lin, M.W. 1991. “Forecasting Residential Consumption of Natural Gas
Using Monthly and Quarterly Time Series”. International Journal of Forecasting.
Vol.7. pp.3-16.
Ozturk, H.K. and Hepbasli, A. 2003. “The Place of Natural Gas in Turkey’s Energy
Sources and Future Perspectives”. Energy Sources, Part A: Recovery,
Utilization, and Environmental Effects. Vol.25. pp.293-307.
Potocnik, P., Thaler, M., Govekar, E., Grabec, I., Poredos, A. 2007. “Forecasting Risks
of Natural Gas Consumption in Slovenia”. Energy Policy. Vol.35. pp.4271-4282.
Sanchez-Ubeda, E. and Berzosa, A. 2007. “Modeling and Forecasting Industrial End-
Use Natural Gas Consumption”. Energy Economics. Vol.29. pp.710-742.
Sarak, H. and Satman, A. 2003. “The Degree-Day Method to Estimate the Residential
Heating Natural Gas Consumption in Turkey: A Case Study”. Energy. Vol.28.
pp.929-939.
Siemek, J., Nagy, S., and Rychlicki, S. 2003. “Estimation of Natural-Gas Consumption in
Poland Based on the Logistic-Curve Interpretation”. Applied Energy. Vol.75.
pp.1-7.
Goktas, O. 2005. Teorik ve Uygulamal1 Zaman Serileri Analizi. Besir Kitabevi.
Viet, N.H., and Mandziuk, J. 2003. “Neural and Fuzzy Neural Networks for Natural Gas
Consumption Prediction”. IEEE 13th Workshop on Neural Networks for Signal
Processing. 17-19 September 2003. pp.759-768.
Wong-Parodi, G., Dale, L. and Lekov, A. 2006. “Comparing Price Forecast Accuracy of
Natural Gas Models and Futures Markets”. Energy Policy. Vol.34. pp.4115-4122.

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