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Energy models for demand forecasting—A review

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Cited by:

  1. Liu, Xuewei & Yuan, Zengwei & Xu, Yuan & Jiang, Songyan, 2017. "Greening cement in China: A cost-effective roadmap," Applied Energy, Elsevier, vol. 189(C), pages 233-244.
  2. Azadeh, Ali & Vafa Arani, Hamed, 2016. "Biodiesel supply chain optimization via a hybrid system dynamics-mathematical programming approach," Renewable Energy, Elsevier, vol. 93(C), pages 383-403.
  3. Woo, C.K. & Liu, Y. & Zarnikau, J. & Shiu, A. & Luo, X. & Kahrl, F., 2018. "Price elasticities of retail energy demands in the United States: New evidence from a panel of monthly data for 2001–2016," Applied Energy, Elsevier, vol. 222(C), pages 460-474.
  4. Koppelaar, Rembrandt H.E.M. & Keirstead, James & Shah, Nilay & Woods, Jeremy, 2016. "A review of policy analysis purpose and capabilities of electricity system models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1531-1544.
  5. Figueiredo, Nuno Carvalho & Silva, Patrícia Pereira da & Bunn, Derek, 2016. "Weather and market specificities in the regional transmission of renewable energy price effects," Energy, Elsevier, vol. 114(C), pages 188-200.
  6. Vu, D.H. & Muttaqi, K.M. & Agalgaonkar, A.P., 2015. "A variance inflation factor and backward elimination based robust regression model for forecasting monthly electricity demand using climatic variables," Applied Energy, Elsevier, vol. 140(C), pages 385-394.
  7. Wu, Junqi & Niu, Zhibin & Li, Xiang & Huang, Lizhen & Nielsen, Per Sieverts & Liu, Xiufeng, 2023. "Understanding multi-scale spatiotemporal energy consumption data: A visual analysis approach," Energy, Elsevier, vol. 263(PD).
  8. Aydin, Gokhan, 2014. "Modeling of energy consumption based on economic and demographic factors: The case of Turkey with projections," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 382-389.
  9. Kumar, Rajesh & Agarwala, Arun, 2016. "Renewable energy technology diffusion model for techno-economics feasibility," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1515-1524.
  10. Liao, Hua & Cai, Jia-Wei & Yang, Dong-Wei & Wei, Yi-Ming, 2016. "Why did the historical energy forecasting succeed or fail? A case study on IEA's projection," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 90-96.
  11. Hossein Iranmanesh & Majid Abdollahzade & Arash Miranian, 2011. "Mid-Term Energy Demand Forecasting by Hybrid Neuro-Fuzzy Models," Energies, MDPI, vol. 5(1), pages 1-21, December.
  12. Adom, Philip Kofi & Bekoe, William, 2012. "Conditional dynamic forecast of electrical energy consumption requirements in Ghana by 2020: A comparison of ARDL and PAM," Energy, Elsevier, vol. 44(1), pages 367-380.
  13. Wang, Delu & Wang, Yadong & Song, Xuefeng & Liu, Yun, 2018. "Coal overcapacity in China: Multiscale analysis and prediction," Energy Economics, Elsevier, vol. 70(C), pages 244-257.
  14. Engeland, Kolbjørn & Borga, Marco & Creutin, Jean-Dominique & François, Baptiste & Ramos, Maria-Helena & Vidal, Jean-Philippe, 2017. "Space-time variability of climate variables and intermittent renewable electricity production – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 600-617.
  15. Franco, Sainu & Mandla, Venkata Ravibabu & Ram Mohan Rao, K., 2017. "Urbanization, energy consumption and emissions in the Indian context A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 898-907.
  16. Shahbaz, Muhammad & Zakaria, Muhammad & Shahzad, Syed Jawad Hussain & Mahalik, Mantu Kumar, 2018. "The energy consumption and economic growth nexus in top ten energy-consuming countries: Fresh evidence from using the quantile-on-quantile approach," Energy Economics, Elsevier, vol. 71(C), pages 282-301.
  17. Genovese, P.V. & Zoure, A.N., 2023. "Architecture trends and challenges in sub-Saharan Africa's construction industry: A theoretical guideline of a bioclimatic architecture evolution based on the multi-scale approach and circular economy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
  18. Wang, Qiang & Li, Shuyu & Li, Rongrong, 2018. "Forecasting energy demand in China and India: Using single-linear, hybrid-linear, and non-linear time series forecast techniques," Energy, Elsevier, vol. 161(C), pages 821-831.
  19. Woo, C.K. & Shiu, A. & Liu, Y. & Luo, X. & Zarnikau, J., 2018. "Consumption effects of an electricity decarbonization policy: Hong Kong," Energy, Elsevier, vol. 144(C), pages 887-902.
  20. Spandagos, Constantine & Ng, Tze Ling, 2018. "Fuzzy model of residential energy decision-making considering behavioral economic concepts," Applied Energy, Elsevier, vol. 213(C), pages 611-625.
  21. Wu, Da-Chun & Amini, Amin & Razban, Ali & Chen, Jie, 2018. "ARC algorithm: A novel approach to forecast and manage daily electrical maximum demand," Energy, Elsevier, vol. 154(C), pages 383-389.
  22. Le Cam, M. & Daoud, A. & Zmeureanu, R., 2016. "Forecasting electric demand of supply fan using data mining techniques," Energy, Elsevier, vol. 101(C), pages 541-557.
  23. Ameyaw, Bismark & Yao, Li & Oppong, Amos & Agyeman, Joy Korang, 2019. "Investigating, forecasting and proposing emission mitigation pathways for CO2 emissions from fossil fuel combustion only: A case study of selected countries," Energy Policy, Elsevier, vol. 130(C), pages 7-21.
  24. Yuehjen E. Shao & Yi-Shan Tsai, 2018. "Electricity Sales Forecasting Using Hybrid Autoregressive Integrated Moving Average and Soft Computing Approaches in the Absence of Explanatory Variables," Energies, MDPI, vol. 11(7), pages 1-22, July.
  25. El-Sayed, Ahmed Hassan A. & Khalil, Adel & Yehia, Mohamed, 2023. "Modeling alternative scenarios for Egypt 2050 energy mix based on LEAP analysis," Energy, Elsevier, vol. 266(C).
  26. Sharifzadeh, Mahdi & Sikinioti-Lock, Alexandra & Shah, Nilay, 2019. "Machine-learning methods for integrated renewable power generation: A comparative study of artificial neural networks, support vector regression, and Gaussian Process Regression," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 513-538.
  27. Jasiński, Tomasz, 2022. "A new approach to modeling cycles with summer and winter demand peaks as input variables for deep neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
  28. Emami Javanmard, M. & Tang, Y. & Wang, Z. & Tontiwachwuthikul, P., 2023. "Forecast energy demand, CO2 emissions and energy resource impacts for the transportation sector," Applied Energy, Elsevier, vol. 338(C).
  29. Llorca, Manuel & Jamasb, Tooraj, 2017. "Energy efficiency and rebound effect in European road freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 98-110.
  30. Shao, Zhen & Gao, Fei & Yang, Shan-Lin & Yu, Ben-gong, 2015. "A new semiparametric and EEMD based framework for mid-term electricity demand forecasting in China: Hidden characteristic extraction and probability density prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 876-889.
  31. Cao, K.H. & Qi, H.S. & Li, R. & Woo, C.K. & Tishler, A. & Zarnikau, J., 2023. "An experiment in own-price elasticity estimation for non-residential electricity demand in the U.S," Utilities Policy, Elsevier, vol. 81(C).
  32. Kumar Sahu, Bikash, 2015. "A study on global solar PV energy developments and policies with special focus on the top ten solar PV power producing countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 621-634.
  33. Chen, Jun & Rabiti, Cristian, 2017. "Synthetic wind speed scenarios generation for probabilistic analysis of hybrid energy systems," Energy, Elsevier, vol. 120(C), pages 507-517.
  34. Colmenar, J.M. & Hidalgo, J.I. & Salcedo-Sanz, S., 2018. "Automatic generation of models for energy demand estimation using Grammatical Evolution," Energy, Elsevier, vol. 164(C), pages 183-193.
  35. Chaturvedi, Shobhit & Rajasekar, Elangovan & Natarajan, Sukumar & McCullen, Nick, 2022. "A comparative assessment of SARIMA, LSTM RNN and Fb Prophet models to forecast total and peak monthly energy demand for India," Energy Policy, Elsevier, vol. 168(C).
  36. Hu, Yusha & Man, Yi, 2023. "Energy consumption and carbon emissions forecasting for industrial processes: Status, challenges and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
  37. Zhu, Jizhong & Dong, Hanjiang & Zheng, Weiye & Li, Shenglin & Huang, Yanting & Xi, Lei, 2022. "Review and prospect of data-driven techniques for load forecasting in integrated energy systems," Applied Energy, Elsevier, vol. 321(C).
  38. Barja-Martinez, Sara & Aragüés-Peñalba, Mònica & Munné-Collado, Íngrid & Lloret-Gallego, Pau & Bullich-Massagué, Eduard & Villafafila-Robles, Roberto, 2021. "Artificial intelligence techniques for enabling Big Data services in distribution networks: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
  39. Ackah, Ishmael & Kizys, Renatas, 2015. "Green growth in oil producing African countries: A panel data analysis of renewable energy demand," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 1157-1166.
  40. Hou, Jin & Xu, Peng & Lu, Xing & Pang, Zhihong & Chu, Yiyi & Huang, Gongsheng, 2018. "Implementation of expansion planning in existing district energy system: A case study in China," Applied Energy, Elsevier, vol. 211(C), pages 269-281.
  41. Yang, Xiu'e & Liu, Shuli & Zou, Yuliang & Ji, Wenjie & Zhang, Qunli & Ahmed, Abdullahi & Han, Xiaojing & Shen, Yongliang & Zhang, Shaoliang, 2022. "Energy-saving potential prediction models for large-scale building: A state-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
  42. García-Gusano, Diego & Suárez-Botero, Jasson & Dufour, Javier, 2018. "Long-term modelling and assessment of the energy-economy decoupling in Spain," Energy, Elsevier, vol. 151(C), pages 455-466.
  43. Yildiz, B. & Bilbao, J.I. & Sproul, A.B., 2017. "A review and analysis of regression and machine learning models on commercial building electricity load forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 1104-1122.
  44. Espinoza, Vicente Sebastian & Fontalvo, Javier & Martí-Herrero, Jaime & Miguel, Luis Javier & Mediavilla, Margarita, 2022. "Analysis of energy future pathways for Ecuador facing the prospects of oil availability using a system dynamics model. Is degrowth inevitable?," Energy, Elsevier, vol. 259(C).
  45. Shao, Zhen & Chao, Fu & Yang, Shan-Lin & Zhou, Kai-Le, 2017. "A review of the decomposition methodology for extracting and identifying the fluctuation characteristics in electricity demand forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 123-136.
  46. Vanegas Cantarero, María Mercedes, 2018. "Reviewing the Nicaraguan transition to a renewable energy system: Why is “business-as-usual” no longer an option?," Energy Policy, Elsevier, vol. 120(C), pages 580-592.
  47. Marcillo-Delgado, J.C. & Ortego, M.I. & Pérez-Foguet, A., 2019. "A compositional approach for modelling SDG7 indicators: Case study applied to electricity access," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 388-398.
  48. de Oliveira, Erick Meira & Cyrino Oliveira, Fernando Luiz, 2018. "Forecasting mid-long term electric energy consumption through bagging ARIMA and exponential smoothing methods," Energy, Elsevier, vol. 144(C), pages 776-788.
  49. Alipour, M. & Hafezi, R. & Amer, M. & Akhavan, A.N., 2017. "A new hybrid fuzzy cognitive map-based scenario planning approach for Iran's oil production pathways in the post–sanction period," Energy, Elsevier, vol. 135(C), pages 851-864.
  50. Gomez, Juan A. & Anjos, Miguel F., 2017. "Power capacity profile estimation for building heating and cooling in demand-side management," Applied Energy, Elsevier, vol. 191(C), pages 492-501.
  51. Le Cam, M. & Zmeureanu, R. & Daoud, A., 2017. "Cascade-based short-term forecasting method of the electric demand of HVAC system," Energy, Elsevier, vol. 119(C), pages 1098-1107.
  52. Gu, Haifei & Li, Yang & Yu, Jie & Wu, Chen & Song, Tianli & Xu, Jinzhou, 2020. "Bi-level optimal low-carbon economic dispatch for an industrial park with consideration of multi-energy price incentives," Applied Energy, Elsevier, vol. 262(C).
  53. Mahumane, Gilberto & Mulder, Peter, 2016. "Introducing MOZLEAP: An integrated long-run scenario model of the emerging energy sector of Mozambique," Energy Economics, Elsevier, vol. 59(C), pages 275-289.
  54. Gils, Hans Christian & Simon, Sonja, 2017. "Carbon neutral archipelago – 100% renewable energy supply for the Canary Islands," Applied Energy, Elsevier, vol. 188(C), pages 342-355.
  55. Vidoza, Jorge A. & Gallo, Waldyr L.R., 2016. "Projection of fossil fuels consumption in the Venezuelan electricity generation industry," Energy, Elsevier, vol. 104(C), pages 237-249.
  56. al Irsyad, M. Indra & Halog, Anthony & Nepal, Rabindra, 2018. "Estimating the impacts of financing support policies towards photovoltaic market in Indonesia: A social-energy-economy-environment (SE3) model simulation," Working Papers 2018-09, University of Tasmania, Tasmanian School of Business and Economics.
  57. Deb, Chirag & Zhang, Fan & Yang, Junjing & Lee, Siew Eang & Shah, Kwok Wei, 2017. "A review on time series forecasting techniques for building energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 902-924.
  58. Foroni, Claudia & Ravazzolo, Francesco & Rossini, Luca, 2023. "Are low frequency macroeconomic variables important for high frequency electricity prices?," Economic Modelling, Elsevier, vol. 120(C).
  59. Li, Raymond & Woo, Chi-Keung & Tishler, Asher & Zarnikau, Jay, 2022. "Price responsiveness of commercial demand for natural gas in the US," Energy, Elsevier, vol. 256(C).
  60. Tang, Lei & Wang, Xifan & Wang, Xiuli & Shao, Chengcheng & Liu, Shiyu & Tian, Shijun, 2019. "Long-term electricity consumption forecasting based on expert prediction and fuzzy Bayesian theory," Energy, Elsevier, vol. 167(C), pages 1144-1154.
  61. Riva, Fabio & Gardumi, Francesco & Tognollo, Annalisa & Colombo, Emanuela, 2019. "Soft-linking energy demand and optimisation models for local long-term electricity planning: An application to rural India," Energy, Elsevier, vol. 166(C), pages 32-46.
  62. Wu, Jie & Wang, Zhi-Xin & Wang, Guo-Qiang, 2014. "The key technologies and development of offshore wind farm in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 453-462.
  63. Yukseltan, E. & Kok, A. & Yucekaya, A. & Bilge, A. & Aktunc, E. Agca & Hekimoglu, M., 2022. "The impact of the COVID-19 pandemic and behavioral restrictions on electricity consumption and the daily demand curve in Turkey," Utilities Policy, Elsevier, vol. 76(C).
  64. Serkan Yilmaz Kandir & Ahmet Erismis & Ilhan Ozturk, 2015. "Investigating Exchange Rate Exposure of Energy Firms: Evidence from Turkey," Prague Economic Papers, Prague University of Economics and Business, vol. 2015(6), pages 729-743.
  65. Panapakidis, Ioannis P. & Dagoumas, Athanasios S., 2017. "Day-ahead natural gas demand forecasting based on the combination of wavelet transform and ANFIS/genetic algorithm/neural network model," Energy, Elsevier, vol. 118(C), pages 231-245.
  66. Zhao, Deyin & Zhong, Ming & Zhang, Xu & Su, Xing, 2016. "Energy consumption predicting model of VRV (Variable refrigerant volume) system in office buildings based on data mining," Energy, Elsevier, vol. 102(C), pages 660-668.
  67. Agüero, J. & Rodríguez, F. & Giménez, A., 2013. "Energy management based on productiveness concept," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 92-100.
  68. Pinheiro, Marco G. & Madeira, Sara C. & Francisco, Alexandre P., 2023. "Short-term electricity load forecasting—A systematic approach from system level to secondary substations," Applied Energy, Elsevier, vol. 332(C).
  69. Yu, Dongwei & Tan, Hongwei, 2016. "Application of ‘potential carbon’ in energy planning with carbon emission constraints," Applied Energy, Elsevier, vol. 169(C), pages 363-369.
  70. Qudrat-Ullah, Hassan, 2014. "Green power in Ontario: A dynamic model-based analysis," Energy, Elsevier, vol. 77(C), pages 859-870.
  71. Guerra, Omar J. & Tejada, Diego A. & Reklaitis, Gintaras V., 2016. "An optimization framework for the integrated planning of generation and transmission expansion in interconnected power systems," Applied Energy, Elsevier, vol. 170(C), pages 1-21.
  72. Mondal, Md Alam Hossain & Bryan, Elizabeth & Ringler, Claudia & Mekonnen, Dawit & Rosegrant, Mark, 2018. "Ethiopian energy status and demand scenarios: Prospects to improve energy efficiency and mitigate GHG emissions," Energy, Elsevier, vol. 149(C), pages 161-172.
  73. 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.
  74. Lobo, Benjamin J. & Brown, Donald E. & Grazaitis, Peter J., 2019. "Long-term forecasting of fuel demand at theater entry points," International Journal of Forecasting, Elsevier, vol. 35(2), pages 502-520.
  75. Baratsas, Stefanos G. & Niziolek, Alexander M. & Onel, Onur & Matthews, Logan R. & Floudas, Christodoulos A. & Hallermann, Detlef R. & Sorescu, Sorin M. & Pistikopoulos, Efstratios N., 2022. "A novel quantitative forecasting framework in energy with applications in designing energy-intelligent tax policies," Applied Energy, Elsevier, vol. 305(C).
  76. Berger, Matthias & Worlitschek, Jörg, 2018. "A novel approach for estimating residential space heating demand," Energy, Elsevier, vol. 159(C), pages 294-301.
  77. Hall, Lisa M.H. & Buckley, Alastair R., 2016. "A review of energy systems models in the UK: Prevalent usage and categorisation," Applied Energy, Elsevier, vol. 169(C), pages 607-628.
  78. Prado, Francisco & Minutolo, Marcel C. & Kristjanpoller, Werner, 2020. "Forecasting based on an ensemble Autoregressive Moving Average - Adaptive neuro - Fuzzy inference system – Neural network - Genetic Algorithm Framework," Energy, Elsevier, vol. 197(C).
  79. Oreshkin, Boris N. & Dudek, Grzegorz & Pełka, Paweł & Turkina, Ekaterina, 2021. "N-BEATS neural network for mid-term electricity load forecasting," Applied Energy, Elsevier, vol. 293(C).
  80. Klemm, Christian & Vennemann, Peter, 2021. "Modeling and optimization of multi-energy systems in mixed-use districts: A review of existing methods and approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
  81. Alobaidi, Mohammad H. & Chebana, Fateh & Meguid, Mohamed A., 2018. "Robust ensemble learning framework for day-ahead forecasting of household based energy consumption," Applied Energy, Elsevier, vol. 212(C), pages 997-1012.
  82. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
  83. Peng, Jieyang & Kimmig, Andreas & Niu, Zhibin & Wang, Jiahai & Liu, Xiufeng & Ovtcharova, Jivka, 2021. "A flexible potential-flow model based high resolution spatiotemporal energy demand forecasting framework," Applied Energy, Elsevier, vol. 299(C).
  84. Chanthawong, Anuman & Dhakal, Shobhakar & Jongwanich, Juthathip, 2016. "Supply and demand of biofuels in the fuel market of Thailand: Two stage least square and three least square approaches," Energy, Elsevier, vol. 114(C), pages 431-443.
  85. Afees A. Salisu & Oluwatomisinn Oyewole & Lateef O. Akanni, 2018. "Modeling the residential electricity demand in the US," Working Papers 042, Centre for Econometric and Allied Research, University of Ibadan.
  86. He, Yongda & Lin, Boqiang, 2018. "Forecasting China's total energy demand and its structure using ADL-MIDAS model," Energy, Elsevier, vol. 151(C), pages 420-429.
  87. Zhao, Guangling & Guerrero, Josep M. & Jiang, Kejun & Chen, Sha, 2017. "Energy modelling towards low carbon development of Beijing in 2030," Energy, Elsevier, vol. 121(C), pages 107-113.
  88. Guo, Peiyang & Lam, Jacqueline C.K. & Li, Victor O.K., 2019. "Drivers of domestic electricity users’ price responsiveness: A novel machine learning approach," Applied Energy, Elsevier, vol. 235(C), pages 900-913.
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  90. Yang, Yang & Xue, Dingyü, 2016. "Continuous fractional-order grey model and electricity prediction research based on the observation error feedback," Energy, Elsevier, vol. 115(P1), pages 722-733.
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  93. Yukseltan, Ergun & Yucekaya, Ahmet & Bilge, Ayse Humeyra, 2017. "Forecasting electricity demand for Turkey: Modeling periodic variations and demand segregation," Applied Energy, Elsevier, vol. 193(C), pages 287-296.
  94. Salisu, Afees A. & Ayinde, Taofeek O., 2016. "Modeling energy demand: Some emerging issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1470-1480.
  95. Zhang, Chi & Zhou, Kaile & Yang, Shanlin & Shao, Zhen, 2017. "On electricity consumption and economic growth in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 353-368.
  96. Bhandari, Ramchandra & Subedi, Subodh, 2023. "Evaluation of surplus hydroelectricity potential in Nepal until 2040 and its use for hydrogen production via electrolysis," Renewable Energy, Elsevier, vol. 212(C), pages 403-414.
  97. Bhandari, Ramchandra, 2022. "Green hydrogen production potential in West Africa – Case of Niger," Renewable Energy, Elsevier, vol. 196(C), pages 800-811.
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  100. Murat Yalçıntaş & Melih Bulu & Murat Küçükvar & Hamidreza Samadi, 2015. "A Framework for Sustainable Urban Water Management through Demand and Supply Forecasting: The Case of Istanbul," Sustainability, MDPI, vol. 7(8), pages 1-18, August.
  101. Pirlogea, Corina & Cicea, Claudiu, 2012. "Econometric perspective of the energy consumption and economic growth relation in European Union," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5718-5726.
  102. Yi-Chung Hu, 2017. "A genetic-algorithm-based remnant grey prediction model for energy demand forecasting," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-11, October.
  103. Widera, Barbara, 2021. "Comparative analysis of user comfort and thermal performance of six types of vernacular dwellings as the first step towards climate resilient, sustainable and bioclimatic architecture in western sub-S," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
  104. Hocaoglu, Fatih Onur & Karanfil, Fatih, 2013. "A time series-based approach for renewable energy modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 204-214.
  105. Wu, Zhibin & Xu, Jiuping, 2013. "Predicting and optimization of energy consumption using system dynamics-fuzzy multiple objective programming in world heritage areas," Energy, Elsevier, vol. 49(C), pages 19-31.
  106. Maaouane, Mohamed & Zouggar, Smail & Krajačić, Goran & Zahboune, Hassan, 2021. "Modelling industry energy demand using multiple linear regression analysis based on consumed quantity of goods," Energy, Elsevier, vol. 225(C).
  107. Nieves, J.A. & Aristizábal, A.J. & Dyner, I. & Báez, O. & Ospina, D.H., 2019. "Energy demand and greenhouse gas emissions analysis in Colombia: A LEAP model application," Energy, Elsevier, vol. 169(C), pages 380-397.
  108. De Giorgi, M.G. & Malvoni, M. & Congedo, P.M., 2016. "Comparison of strategies for multi-step ahead photovoltaic power forecasting models based on hybrid group method of data handling networks and least square support vector machine," Energy, Elsevier, vol. 107(C), pages 360-373.
  109. Tziolis, Georgios & Spanias, Chrysovalantis & Theodoride, Maria & Theocharides, Spyros & Lopez-Lorente, Javier & Livera, Andreas & Makrides, George & Georghiou, George E., 2023. "Short-term electric net load forecasting for solar-integrated distribution systems based on Bayesian neural networks and statistical post-processing," Energy, Elsevier, vol. 271(C).
  110. Shakouri, Mahmoud & Lee, Hyun Woo & Kim, Yong-Woo, 2017. "A probabilistic portfolio-based model for financial valuation of community solar," Applied Energy, Elsevier, vol. 191(C), pages 709-726.
  111. Yu, Miao & Zhao, Xintong & Gao, Yuning, 2019. "Factor decomposition of China’s industrial electricity consumption using structural decomposition analysis," Structural Change and Economic Dynamics, Elsevier, vol. 51(C), pages 67-76.
  112. Kialashaki, Arash & Reisel, John R., 2014. "Development and validation of artificial neural network models of the energy demand in the industrial sector of the United States," Energy, Elsevier, vol. 76(C), pages 749-760.
  113. Chou, Jui-Sheng & Tran, Duc-Son, 2018. "Forecasting energy consumption time series using machine learning techniques based on usage patterns of residential householders," Energy, Elsevier, vol. 165(PB), pages 709-726.
  114. Ozoegwu, C.G. & Eze, C. & Onwosi, C.O. & Mgbemene, C.A. & Ozor, P.A., 2017. "Biomass and bioenergy potential of cassava waste in Nigeria: Estimations based partly on rural-level garri processing case studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 625-638.
  115. Harris, Tyler M. & Devkota, Jay P. & Khanna, Vikas & Eranki, Pragnya L. & Landis, Amy E., 2018. "Logistic growth curve modeling of US energy production and consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 46-57.
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