IDEAS home Printed from https://ideas.repec.org/a/eco/journ2/2018-03-28.html
   My bibliography  Save this article

Forecasting Natural Gas: A Literature Survey

Author

Listed:
  • Jean Gaston Tamba

    (Department of Thermal and Energy Engineering, University Institute of Technology, University of Douala, PO Box 8698 Douala, Cameroon)

  • Salom Ndjakomo Essiane

    (Laboratory of Technologies and Applied Science, University Institute of Technology, University of Douala, PO Box 8698 Douala, Cameroon,)

  • Emmanuel Flavian Sapnken

    (Laboratory of Technologies and Applied Science, University Institute of Technology, University of Douala, PO Box 8698 Douala, Cameroon,)

  • Francis Djanna Koffi

    (Department of Thermal and Energy Engineering, University Institute of Technology, University of Douala, PO Box 8698 Douala, Cameroon,)

  • Jean Luc Nsouand l

    (Department of Renewable Energy, Higher Institute of the Sahel, University of Maroua, PO Box 46, Maroua, Cameroon)

  • Bozidar Soldo

    (HEP-Plin Ltd., Cara Hadrijana 7, HR-31000 Osijek, Croatia,)

  • Donatien Njomo

    (Environmental Energy Technologies Laboratory, University of Yaound I, PO Box 812, Yaound , Cameroon.)

Abstract

This work presents a state-of-the-art survey of published papers that forecast natural gas production, consumption or demand, prices and income elasticity, market volatility and hike in prices. New models and techniques that have recently been applied in the field of natural gas forecasting have discussed with highlights on various methodologies, their specifics, data type, data size, data source, results and conclusions. Moreover, we undertook the difficult task of classifying existing models that have been applied in this field by giving their performance for instance. Our objective is to provide a synthesis of published papers in the field of natural gas forecasting, insights on modeling issues to achieve usable results, and the future research directions. This work will help future researchers in the area of forecasting no matter the methodological approach and nature of energy source used.

Suggested Citation

  • Jean Gaston Tamba & Salom Ndjakomo Essiane & Emmanuel Flavian Sapnken & Francis Djanna Koffi & Jean Luc Nsouand l & Bozidar Soldo & Donatien Njomo, 2018. "Forecasting Natural Gas: A Literature Survey," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 216-249.
  • Handle: RePEc:eco:journ2:2018-03-28
    as

    Download full text from publisher

    File URL: https://www.econjournals.com/index.php/ijeep/article/download/6269/3721
    Download Restriction: no

    File URL: https://www.econjournals.com/index.php/ijeep/article/view/6269/3721
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Siemek, Jakub & Nagy, Stanislaw & Rychlicki, Stanislaw, 2003. "Estimation of natural-gas consumption in Poland based on the logistic-curve interpretation," Applied Energy, Elsevier, vol. 75(1-2), pages 1-7, May.
    2. Satman, A & Yalcinkaya, N, 1999. "Heating and cooling degree-hours for Turkey," Energy, Elsevier, vol. 24(10), pages 833-840.
    3. Ernst R. Berndt & G. Campbell Watkins, 1977. "Demand for Natural Gas: Residential and Commercial Markets in Ontario and British Columbia," Canadian Journal of Economics, Canadian Economics Association, vol. 10(1), pages 97-111, February.
    4. Yoo, Seung-Hoon & Lim, Hea-Jin & Kwak, Seung-Jun, 2009. "Estimating the residential demand function for natural gas in Seoul with correction for sample selection bias," Applied Energy, Elsevier, vol. 86(4), pages 460-465, April.
    5. Paltsev, Sergey, 2014. "Scenarios for Russia's natural gas exports to 2050," Energy Economics, Elsevier, vol. 42(C), pages 262-270.
    6. Yu, Feng & Xu, Xiaozhong, 2014. "A short-term load forecasting model of natural gas based on optimized genetic algorithm and improved BP neural network," Applied Energy, Elsevier, vol. 134(C), pages 102-113.
    7. Sailor, David J. & Muñoz, J.Ricardo, 1997. "Sensitivity of electricity and natural gas consumption to climate in the U.S.A.—Methodology and results for eight states," Energy, Elsevier, vol. 22(10), pages 987-998.
    8. Gómez, Antonio & Dopazo, César & Fueyo, Norberto, 2015. "The future of energy in Uzbekistan," Energy, Elsevier, vol. 85(C), pages 329-338.
    9. Solarin, Sakiru Adebola & Ozturk, Ilhan, 2016. "The relationship between natural gas consumption and economic growth in OPEC members," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1348-1356.
    10. Wadud, Zia & Dey, Himadri S. & Kabir, Md. Ashfanoor & Khan, Shahidul I., 2011. "Modeling and forecasting natural gas demand in Bangladesh," Energy Policy, Elsevier, vol. 39(11), pages 7372-7380.
    11. Herbert, John H. & Sitzer, Scott & Eades-Pryor, Yvonne, 1987. "A statistical evaluation of aggregate monthly industrial demand for natural gas in the U.S.A," Energy, Elsevier, vol. 12(12), pages 1233-1238.
    12. Özge Dilaver & Zafer Dilaver & Lester C Hunt, 2013. "What Drives Natural Gas Consumption in Europe? Analysis and Projections," Surrey Energy Economics Centre (SEEC), School of Economics Discussion Papers (SEEDS) 143, Surrey Energy Economics Centre (SEEC), School of Economics, University of Surrey.
    13. Vondrácek, Jirí & Pelikán, Emil & Konár, Ondrej & Cermáková, Jana & Eben, Krystof & Malý, Marek & Brabec, Marek, 2008. "A statistical model for the estimation of natural gas consumption," Applied Energy, Elsevier, vol. 85(5), pages 362-370, May.
    14. Zhu, L. & Li, M.S. & Wu, Q.H. & Jiang, L., 2015. "Short-term natural gas demand prediction based on support vector regression with false neighbours filtered," Energy, Elsevier, vol. 80(C), pages 428-436.
    15. Maggio, G. & Cacciola, G., 2009. "A variant of the Hubbert curve for world oil production forecasts," Energy Policy, Elsevier, vol. 37(11), pages 4761-4770, November.
    16. Erdogdu, Erkan, 2010. "Natural gas demand in Turkey," Applied Energy, Elsevier, vol. 87(1), pages 211-219, January.
    17. Lin, Boqiang & Wang, Ting, 2012. "Forecasting natural gas supply in China: Production peak and import trends," Energy Policy, Elsevier, vol. 49(C), pages 225-233.
    18. Brabec, Marek & Konár, Ondrej & Pelikán, Emil & Malý, Marek, 2008. "A nonlinear mixed effects model for the prediction of natural gas consumption by individual customers," International Journal of Forecasting, Elsevier, vol. 24(4), pages 659-678.
    19. Jiang, BinBin & Wenying, Chen & Yuefeng, Yu & Lemin, Zeng & Victor, David, 2008. "The future of natural gas consumption in Beijing, Guangdong and Shanghai: An assessment utilizing MARKAL," Energy Policy, Elsevier, vol. 36(9), pages 3286-3299, September.
    20. Lee, Ray-Shine & Singh, Nirvikar, 1994. "Patterns in Residential Gas and Electricity Consumption: An Econometric Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 233-241, April.
    21. S. M. Tinic & B. M. Harnden & C. T. L. Janssen, 1973. "Estimation of Rural Demand for Natural Gas," Management Science, INFORMS, vol. 20(4-Part-II), pages 604-616, December.
    22. Narjes Zamani, 2016. "How the Crude Oil Market Affects the Natural Gas Market? Demand and Supply Shocks," International Journal of Energy Economics and Policy, Econjournals, vol. 6(2), pages 217-221.
    23. Philip Ejoor Agbonifo, 2016. "Natural Gas Distribution Infrastructure and the Quest for Environmental Sustainability in the Niger Delta: The Prospect of Natural Gas Utilization in Nigeria," International Journal of Energy Economics and Policy, Econjournals, vol. 6(3), pages 442-448.
    24. Marek Brabec & Ondřej Konár & Marek Malý & Emil Pelikán & Jiří Vondráček, 2009. "A statistical model for natural gas standardized load profiles," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(1), pages 123-139, February.
    25. Forouzanfar, Mehdi & Doustmohammadi, Ali & Menhaj, M. Bagher & Hasanzadeh, Samira, 2010. "Modeling and estimation of the natural gas consumption for residential and commercial sectors in Iran," Applied Energy, Elsevier, vol. 87(1), pages 268-274, January.
    26. Sarak, H & Satman, A, 2003. "The degree-day method to estimate the residential heating natural gas consumption in Turkey: a case study," Energy, Elsevier, vol. 28(9), pages 929-939.
    27. Fan, Ying & Xia, Yan, 2012. "Exploring energy consumption and demand in China," Energy, Elsevier, vol. 40(1), pages 23-30.
    28. Tahat, M. A. & Al-Hinai, H. & Probert, S. D., 2002. "Performance of a low-energy-consumption house experiencing a Mediterranean climate," Applied Energy, Elsevier, vol. 71(1), pages 1-13, January.
    29. Thaler, Marko & Grabec, Igor & Poredoš, Alojz, 2005. "Prediction of energy consumption and risk of excess demand in a distribution system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 46-53.
    30. Darda, Md Abud & Guseo, Renato & Mortarino, Cinzia, 2015. "Nonlinear production path and an alternative reserves estimate for South Asian natural gas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 654-664.
    31. Huntington, Hillard G., 2007. "Industrial natural gas consumption in the United States: An empirical model for evaluating future trends," Energy Economics, Elsevier, vol. 29(4), pages 743-759, July.
    32. Potocnik, Primoz & Thaler, Marko & Govekar, Edvard & Grabec, Igor & Poredos, Alojz, 2007. "Forecasting risks of natural gas consumption in Slovenia," Energy Policy, Elsevier, vol. 35(8), pages 4271-4282, August.
    33. Chkili, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory," Energy Economics, Elsevier, vol. 41(C), pages 1-18.
    34. Bartels, Robert & Fiebig, Denzil G & Nahm, Daehoon, 1996. "Regional End-Use Gas Demand in Australia," The Economic Record, The Economic Society of Australia, vol. 72(219), pages 319-331, December.
    35. Yu, Yihua & Zheng, Xinye & Han, Yi, 2014. "On the demand for natural gas in urban China," Energy Policy, Elsevier, vol. 70(C), pages 57-63.
    36. Wang, Jianliang & Feng, Lianyong & Zhao, Lin & Snowden, Simon, 2013. "China's natural gas: Resources, production and its impacts," Energy Policy, Elsevier, vol. 55(C), pages 690-698.
    37. Liu, Lon-Mu & Lin, Maw-Wen, 1991. "Forecasting residential consumption of natural gas using monthly and quarterly time series," International Journal of Forecasting, Elsevier, vol. 7(1), pages 3-16, May.
    38. Szoplik, Jolanta, 2015. "Forecasting of natural gas consumption with artificial neural networks," Energy, Elsevier, vol. 85(C), pages 208-220.
    39. Voudouris, Vlasios & Matsumoto, Ken'ichi & Sedgwick, John & Rigby, Robert & Stasinopoulos, Dimitrios & Jefferson, Michael, 2014. "Exploring the production of natural gas through the lenses of the ACEGES model," Energy Policy, Elsevier, vol. 64(C), pages 124-133.
    40. Kovačič, Miha & Šarler, Božidar, 2014. "Genetic programming prediction of the natural gas consumption in a steel plant," Energy, Elsevier, vol. 66(C), pages 273-284.
    41. Potočnik, Primož & Soldo, Božidar & Šimunović, Goran & Šarić, Tomislav & Jeromen, Andrej & Govekar, Edvard, 2014. "Comparison of static and adaptive models for short-term residential natural gas forecasting in Croatia," Applied Energy, Elsevier, vol. 129(C), pages 94-103.
    42. Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2002. "Comparison of forecast performance for homogeneous, heterogeneous and shrinkage estimators: Some empirical evidence from US electricity and natural-gas consumption," Economics Letters, Elsevier, vol. 76(3), pages 375-382, August.
    43. Sanchez-Ubeda, Eugenio Fco. & Berzosa, Ana, 2007. "Modeling and forecasting industrial end-use natural gas consumption," Energy Economics, Elsevier, vol. 29(4), pages 710-742, July.
    44. Azadeh, A. & Asadzadeh, S.M. & Ghanbari, A., 2010. "An adaptive network-based fuzzy inference system for short-term natural gas demand estimation: Uncertain and complex environments," Energy Policy, Elsevier, vol. 38(3), pages 1529-1536, March.
    45. Douglas B. Reynolds & Marek Kolodziej, 2009. "North American Natural Gas Supply Forecast: The Hubbert Method Including the Effects of Institutions," Energies, MDPI, vol. 2(2), pages 1-38, May.
    46. Mount, Tim & Tyrrell, Timothy J., 1977. "Energy Demand: Conservation, Taxation, and Growth," Staff Papers 184442, Cornell University, Department of Applied Economics and Management.
    47. Xiong, Ping-ping & Dang, Yao-guo & Yao, Tian-xiang & Wang, Zheng-xin, 2014. "Optimal modeling and forecasting of the energy consumption and production in China," Energy, Elsevier, vol. 77(C), pages 623-634.
    48. Bianco, Vincenzo & Scarpa, Federico & Tagliafico, Luca A., 2014. "Scenario analysis of nonresidential natural gas consumption in Italy," Applied Energy, Elsevier, vol. 113(C), pages 392-403.
    49. Parikh, Jyoti & Purohit, Pallav & Maitra, Pallavi, 2007. "Demand projections of petroleum products and natural gas in India," Energy, Elsevier, vol. 32(10), pages 1825-1837.
    50. Shekarchian, M. & Moghavvemi, M. & Motasemi, F. & Zarifi, F. & Mahlia, T.M.I., 2012. "Energy and fuel consumption forecast by retrofitting absorption cooling in Malaysia from 2012 to 2025," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 6128-6141.
    51. Ozturk, Ilhan & Al-Mulali, Usama, 2015. "Natural gas consumption and economic growth nexus: Panel data analysis for GCC countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 998-1003.
    52. Gutiérrez, R. & Nafidi, A. & Gutiérrez Sánchez, R., 2005. "Forecasting total natural-gas consumption in Spain by using the stochastic Gompertz innovation diffusion model," Applied Energy, Elsevier, vol. 80(2), pages 115-124, February.
    53. Beierlein, James G & Dunn, James W & McConnon, James C, Jr, 1981. "The Demand for Electricity and Natural Gas in the Northeastern United States," The Review of Economics and Statistics, MIT Press, vol. 63(3), pages 403-408, August.
    54. Rahim, Khalid Abdul & Liwan, Audrey, 2012. "Oil and gas trends and implications in Malaysia," Energy Policy, Elsevier, vol. 50(C), pages 262-271.
    55. Kialashaki, Arash & Reisel, John R., 2013. "Modeling of the energy demand of the residential sector in the United States using regression models and artificial neural networks," Applied Energy, Elsevier, vol. 108(C), pages 271-280.
    56. Aydinalp-Koksal, Merih & Ugursal, V. Ismet, 2008. "Comparison of neural network, conditional demand analysis, and engineering approaches for modeling end-use energy consumption in the residential sector," Applied Energy, Elsevier, vol. 85(4), pages 271-296, April.
    57. Lv, Xiaodong & Shan, Xian, 2013. "Modeling natural gas market volatility using GARCH with different distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(22), pages 5685-5699.
    58. Durmayaz, Ahmet & Kadıoǧlu, Mikdat & Şen, Zekai, 2000. "An application of the degree-hours method to estimate the residential heating energy requirement and fuel consumption in Istanbul," Energy, Elsevier, vol. 25(12), pages 1245-1256.
    59. Melikoglu, Mehmet, 2013. "Vision 2023: Forecasting Turkey's natural gas demand between 2013 and 2030," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 393-400.
    60. Askari, S. & Montazerin, N. & Zarandi, M.H. Fazel, 2015. "Forecasting semi-dynamic response of natural gas networks to nodal gas consumptions using genetic fuzzy systems," Energy, Elsevier, vol. 83(C), pages 252-266.
    61. Kani, Alireza H. & Abbasspour, Madjid & Abedi, Zahra, 2014. "Estimation of demand function for natural gas in Iran: Evidences based on smooth transition regression models," Economic Modelling, Elsevier, vol. 36(C), pages 341-347.
    62. Soldo, Božidar, 2012. "Forecasting natural gas consumption," Applied Energy, Elsevier, vol. 92(C), pages 26-37.
    63. Merve Karacaer-Ulusoy & Ayhan Kapusuzoglu, 2017. "The Dynamics of Financial and Macroeconomic Determinants in Natural Gas and Crude Oil Markets: Evidence from Organization for Economic Cooperation and Development/Gulf Cooperation Council/Organization," International Journal of Energy Economics and Policy, Econjournals, vol. 7(3), pages 167-187.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dimitri Lalas & Nikolaos Gakis & Sebastian Mirasgedis & Elena Georgopoulou & Yannis Sarafidis & Haris Doukas, 2021. "Energy and GHG Emissions Aspects of the COVID Impact in Greece," Energies, MDPI, vol. 14(7), pages 1-22, April.
    2. Jonathan Berrisch & Florian Ziel, 2022. "Distributional modeling and forecasting of natural gas prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1065-1086, September.
    3. Yifei Chen & Zhihan Fu, 2023. "Multi-Step Ahead Forecasting of the Energy Consumed by the Residential and Commercial Sectors in the United States Based on a Hybrid CNN-BiLSTM Model," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    4. Qiao, Weibiao & Liu, Wei & Liu, Enbin, 2021. "A combination model based on wavelet transform for predicting the difference between monthly natural gas production and consumption of U.S," Energy, Elsevier, vol. 235(C).
    5. Oana Vlăduţ & George Eduard Grigore & Dumitru Alexandru Bodislav & Gabriel Ilie Staicu & Raluca Iuliana Georgescu, 2024. "Analysing the Connection between Economic Growth, Conventional Energy, and Renewable Energy: A Comparative Analysis of the Caspian Countries," Energies, MDPI, vol. 17(1), pages 1-30, January.
    6. Dimitrios Mouchtaris & Emmanouil Sofianos & Periklis Gogas & Theophilos Papadimitriou, 2021. "Forecasting Natural Gas Spot Prices with Machine Learning," Energies, MDPI, vol. 14(18), pages 1-13, September.
    7. Mohamed Jaouad Malzi & Aziz Ettahir & Sa d Hanchane, 2019. "Responsiveness of Residential Natural Gas Demand to Elderly, Urban Population and Density: Evidence from Organization for Economic Co-operation and Development Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 9(4), pages 388-395.
    8. Drachal, Krzysztof, 2021. "Forecasting selected energy commodities prices with Bayesian dynamic finite mixtures," Energy Economics, Elsevier, vol. 99(C).
    9. Bartłomiej Gaweł & Andrzej Paliński, 2021. "Long-Term Natural Gas Consumption Forecasting Based on Analog Method and Fuzzy Decision Tree," Energies, MDPI, vol. 14(16), pages 1-26, August.
    10. Athanasios Anagnostis & Elpiniki Papageorgiou & Dionysis Bochtis, 2020. "Application of Artificial Neural Networks for Natural Gas Consumption Forecasting," Sustainability, MDPI, vol. 12(16), pages 1-29, August.
    11. Konstantinos Papageorgiou & Elpiniki I. Papageorgiou & Katarzyna Poczeta & Dionysis Bochtis & George Stamoulis, 2020. "Forecasting of Day-Ahead Natural Gas Consumption Demand in Greece Using Adaptive Neuro-Fuzzy Inference System," Energies, MDPI, vol. 13(9), pages 1-32, May.
    12. Sofia Dahlgren & Jonas Ammenberg, 2021. "Sustainability Assessment of Public Transport, Part II—Applying a Multi-Criteria Assessment Method to Compare Different Bus Technologies," Sustainability, MDPI, vol. 13(3), pages 1-30, January.
    13. Svoboda, Radek & Kotik, Vojtech & Platos, Jan, 2021. "Short-term natural gas consumption forecasting from long-term data collection," Energy, Elsevier, vol. 218(C).
    14. Soltanisarvestani, A. & Safavi, A.A., 2021. "Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map," Utilities Policy, Elsevier, vol. 72(C).
    15. Su, Huai & Zio, Enrico & Zhang, Jinjun & Xu, Mingjing & Li, Xueyi & Zhang, Zongjie, 2019. "A hybrid hourly natural gas demand forecasting method based on the integration of wavelet transform and enhanced Deep-RNN model," Energy, Elsevier, vol. 178(C), pages 585-597.
    16. Ivan Borisov Todorov & Fernando Sánchez Lasheras, 2022. "Forecasting Applied to the Electricity, Energy, Gas and Oil Industries: A Systematic Review," Mathematics, MDPI, vol. 10(21), pages 1-15, October.
    17. Bartłomiej Gaweł & Andrzej Paliński, 2024. "Global and Local Approaches for Forecasting of Long-Term Natural Gas Consumption in Poland Based on Hierarchical Short Time Series," Energies, MDPI, vol. 17(2), pages 1-25, January.
    18. Wei, Nan & Yin, Lihua & Li, Chao & Li, Changjun & Chan, Christine & Zeng, Fanhua, 2021. "Forecasting the daily natural gas consumption with an accurate white-box model," Energy, Elsevier, vol. 232(C).
    19. Jinyuan Liu & Shouxi Wang & Nan Wei & Yi Yang & Yihao Lv & Xu Wang & Fanhua Zeng, 2023. "An Enhancement Method Based on Long Short-Term Memory Neural Network for Short-Term Natural Gas Consumption Forecasting," Energies, MDPI, vol. 16(3), pages 1-14, January.
    20. Nan Wei & Changjun Li & Jiehao Duan & Jinyuan Liu & Fanhua Zeng, 2019. "Daily Natural Gas Load Forecasting Based on a Hybrid Deep Learning Model," Energies, MDPI, vol. 12(2), pages 1-15, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Soldo, Božidar, 2012. "Forecasting natural gas consumption," Applied Energy, Elsevier, vol. 92(C), pages 26-37.
    2. Szoplik, Jolanta, 2015. "Forecasting of natural gas consumption with artificial neural networks," Energy, Elsevier, vol. 85(C), pages 208-220.
    3. Sen, Doruk & Günay, M. Erdem & Tunç, K.M. Murat, 2019. "Forecasting annual natural gas consumption using socio-economic indicators for making future policies," Energy, Elsevier, vol. 173(C), pages 1106-1118.
    4. Ravnik, J. & Hriberšek, M., 2019. "A method for natural gas forecasting and preliminary allocation based on unique standard natural gas consumption profiles," Energy, Elsevier, vol. 180(C), pages 149-162.
    5. Potočnik, Primož & Soldo, Božidar & Šimunović, Goran & Šarić, Tomislav & Jeromen, Andrej & Govekar, Edvard, 2014. "Comparison of static and adaptive models for short-term residential natural gas forecasting in Croatia," Applied Energy, Elsevier, vol. 129(C), pages 94-103.
    6. Ergun Yukseltan & Ahmet Yucekaya & Ayse Humeyra Bilge & Esra Agca Aktunc, 2020. "Forecasting Models for Daily Natural Gas Consumption Considering Periodic Variations and Demand Segregation," Papers 2003.13385, arXiv.org.
    7. Yukseltan, Ergun & Yucekaya, Ahmet & Bilge, Ayse Humeyra & Agca Aktunc, Esra, 2021. "Forecasting models for daily natural gas consumption considering periodic variations and demand segregation," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
    8. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
    9. Mustafa Akpinar & Nejat Yumusak, 2016. "Year Ahead Demand Forecast of City Natural Gas Using Seasonal Time Series Methods," Energies, MDPI, vol. 9(9), pages 1-17, September.
    10. Reza Hafezi & Amir Naser Akhavan & Mazdak Zamani & Saeed Pakseresht & Shahaboddin Shamshirband, 2019. "Developing a Data Mining Based Model to Extract Predictor Factors in Energy Systems: Application of Global Natural Gas Demand," Energies, MDPI, vol. 12(21), pages 1-22, October.
    11. Tomasz Cieślik & Piotr Narloch & Adam Szurlej & Krzysztof Kogut, 2022. "Indirect Impact of the COVID-19 Pandemic on Natural Gas Consumption by Commercial Consumers in a Selected City in Poland," Energies, MDPI, vol. 15(4), pages 1-18, February.
    12. Askari, S. & Montazerin, N. & Fazel Zarandi, M.H., 2016. "Gas networks simulation from disaggregation of low frequency nodal gas consumption," Energy, Elsevier, vol. 112(C), pages 1286-1298.
    13. Li, Wei & Lu, Can, 2019. "The multiple effectiveness of state natural gas consumption constraint policies for achieving sustainable development targets in China," Applied Energy, Elsevier, vol. 235(C), pages 685-698.
    14. Soltanisarvestani, A. & Safavi, A.A., 2021. "Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map," Utilities Policy, Elsevier, vol. 72(C).
    15. Zhu, L. & Li, M.S. & Wu, Q.H. & Jiang, L., 2015. "Short-term natural gas demand prediction based on support vector regression with false neighbours filtered," Energy, Elsevier, vol. 80(C), pages 428-436.
    16. Bartłomiej Gaweł & Andrzej Paliński, 2021. "Long-Term Natural Gas Consumption Forecasting Based on Analog Method and Fuzzy Decision Tree," Energies, MDPI, vol. 14(16), pages 1-26, August.
    17. Spoladore, Alessandro & Borelli, Davide & Devia, Francesco & Mora, Flavio & Schenone, Corrado, 2016. "Model for forecasting residential heat demand based on natural gas consumption and energy performance indicators," Applied Energy, Elsevier, vol. 182(C), pages 488-499.
    18. Azadeh, A. & Asadzadeh, S.M. & Saberi, M. & Nadimi, V. & Tajvidi, A. & Sheikalishahi, M., 2011. "A Neuro-fuzzy-stochastic frontier analysis approach for long-term natural gas consumption forecasting and behavior analysis: The cases of Bahrain, Saudi Arabia, Syria, and UAE," Applied Energy, Elsevier, vol. 88(11), pages 3850-3859.
    19. Konstantinos Papageorgiou & Elpiniki I. Papageorgiou & Katarzyna Poczeta & Dionysis Bochtis & George Stamoulis, 2020. "Forecasting of Day-Ahead Natural Gas Consumption Demand in Greece Using Adaptive Neuro-Fuzzy Inference System," Energies, MDPI, vol. 13(9), pages 1-32, May.
    20. Askari, S. & Montazerin, N. & Zarandi, M.H. Fazel, 2015. "Forecasting semi-dynamic response of natural gas networks to nodal gas consumptions using genetic fuzzy systems," Energy, Elsevier, vol. 83(C), pages 252-266.

    More about this item

    Keywords

    Forecasting natural gas; Existing forecasting models; Models categorization.;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eco:journ2:2018-03-28. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ilhan Ozturk (email available below). General contact details of provider: http://www.econjournals.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.