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Models for forecasting growth trends in renewable energy

Citations

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Cited by:

  1. Mohd Chachuli, Fairuz Suzana & Ahmad Ludin, Norasikin & Md Jedi, Muhamad Alias & Hamid, Norul Hisham, 2021. "Transition of renewable energy policies in Malaysia: Benchmarking with data envelopment analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
  2. Alonso-Montesinos, J. & Polo, Jesús & Ballestrín, Jesús & Batlles, F.J. & Portillo, C., 2019. "Impact of DNI forecasting on CSP tower plant power production," Renewable Energy, Elsevier, vol. 138(C), pages 368-377.
  3. Zhao, Lu-Tao & Wang, Yi & Guo, Shi-Qiu & Zeng, Guan-Rong, 2018. "A novel method based on numerical fitting for oil price trend forecasting," Applied Energy, Elsevier, vol. 220(C), pages 154-163.
  4. Vadim A. Golubev & Viktoria A. Verbnikova & Ilia A. Lopyrev & Daria D. Voznesenskaya & Rashid N. Alimov & Olga V. Novikova & Evgenii A. Konnikov, 2021. "Energy Evolution: Forecasting the Development of Non-Conventional Renewable Energy Sources and Their Impact on the Conventional Electricity System," Sustainability, MDPI, vol. 13(22), pages 1-19, November.
  5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  6. Rajaeifar, Mohammad Ali & Sadeghzadeh Hemayati, Saeed & Tabatabaei, Meisam & Aghbashlo, Mortaza & Mahmoudi, Seyed Bagher, 2019. "A review on beet sugar industry with a focus on implementation of waste-to-energy strategy for power supply," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 423-442.
  7. Zhong, Chao-Yun & Cai, Qiran & Creutzig, Felix & Qing, Jing & Xu, Qingyang & Liang, Qiao-Mei, 2025. "Techno-environmental and economic impacts of EV charging strategies on urban power systems under fleet heterogeneity and electrification uncertainty," Energy, Elsevier, vol. 336(C).
  8. Anca Mehedintu & Mihaela Sterpu & Georgeta Soava, 2018. "Estimation and Forecasts for the Share of Renewable Energy Consumption in Final Energy Consumption by 2020 in the European Union," Sustainability, MDPI, vol. 10(5), pages 1-22, May.
  9. Xianxun Wang & Lihua Chen & Qijuan Chen & Yadong Mei & Hao Wang, 2018. "Model and Analysis of Integrating Wind and PV Power in Remote and Core Areas with Small Hydropower and Pumped Hydropower Storage," Energies, MDPI, vol. 11(12), pages 1-24, December.
  10. Shamsi, Meisam & Babazadeh, Reza, 2022. "Estimation and prediction of Jatropha cultivation areas in China and India," Renewable Energy, Elsevier, vol. 183(C), pages 548-560.
  11. Xiaoye Jin & Meiying Li & Fansheng Meng, 2019. "Comprehensive Evaluation of the New Energy Power Generation Development at the Regional Level: An Empirical Analysis from China," Energies, MDPI, vol. 12(23), pages 1-15, December.
  12. Suat Ozturk & Feride Ozturk, 2018. "Forecasting Energy Consumption of Turkey by Arima Model," Journal of Asian Scientific Research, Asian Economic and Social Society, vol. 8(2), pages 52-60, February.
  13. Anuman Chanthawong & Therdchai Choibamroong, 2022. "Dynamic Linkages of Carbon Emissions, Economic Growth, Energy Consumption, Tourism Indicators and Population: Evidence from Second-tier Cities in Thailand," International Journal of Energy Economics and Policy, Econjournals, vol. 12(5), pages 61-72, September.
  14. Ofosu-Adarkwa, Jeffrey & Xie, Naiming & Javed, Saad Ahmed, 2020. "Forecasting CO2 emissions of China's cement industry using a hybrid Verhulst-GM(1,N) model and emissions' technical conversion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
  15. Wu, Lifeng & Gao, Xiaohui & Xiao, Yanli & Yang, Yingjie & Chen, Xiangnan, 2018. "Using a novel multi-variable grey model to forecast the electricity consumption of Shandong Province in China," Energy, Elsevier, vol. 157(C), pages 327-335.
  16. Sheraz Syed & Asad Arfeen & Riaz Uddin & Umaima Haider, 2021. "An Analysis of Renewable Energy Usage by Mobile Data Network Operators," Sustainability, MDPI, vol. 13(4), pages 1-15, February.
  17. Krzysztof Księżopolski & Grzegorz Maśloch, 2021. "Time Delay Approach to Renewable Energy in the Visegrad Group," Energies, MDPI, vol. 14(7), pages 1-18, March.
  18. Liu, Tianhao & Shan, Linke & Jiang, Meihui & Li, Fangning & Kong, Fannie & Du, Pengcheng & Zhu, Hongyu & Goh, Hui Hwang & Kurniawan, Tonni Agustiono & Huang, Chao & Zhang, Dongdong, 2025. "Multi-dimensional data processing and intelligent forecasting technologies for renewable energy generation," Applied Energy, Elsevier, vol. 398(C).
  19. Mihaela Simionescu & Carmen Beatrice Păuna & Tiberiu Diaconescu, 2020. "Renewable Energy and Economic Performance in the Context of the European Green Deal," Energies, MDPI, vol. 13(23), pages 1-19, December.
  20. Hu, Huanling & Wang, Lin & Lv, Sheng-Xiang, 2020. "Forecasting energy consumption and wind power generation using deep echo state network," Renewable Energy, Elsevier, vol. 154(C), pages 598-613.
  21. Mihaela Simionescu & Yuriy Bilan & Emília Krajňáková & Dalia Streimikiene & Stanisław Gędek, 2019. "Renewable Energy in the Electricity Sector and GDP per Capita in the European Union," Energies, MDPI, vol. 12(13), pages 1-15, June.
  22. R. Rajesh, 2022. "A novel advanced grey incidence analysis for investigating the level of resilience in supply chains," Annals of Operations Research, Springer, vol. 308(1), pages 441-490, January.
  23. Wenting Zhao & Juanjuan Zhao & Xilong Yao & Zhixin Jin & Pan Wang, 2019. "A Novel Adaptive Intelligent Ensemble Model for Forecasting Primary Energy Demand," Energies, MDPI, vol. 12(7), pages 1-28, April.
  24. Mohammad Mahdi Forootan & Iman Larki & Rahim Zahedi & Abolfazl Ahmadi, 2022. "Machine Learning and Deep Learning in Energy Systems: A Review," Sustainability, MDPI, vol. 14(8), pages 1-49, April.
  25. Du, Xiaoyi & Wu, Dongdong & Yan, Yabo, 2023. "Prediction of electricity consumption based on GM(1,Nr) model in Jiangsu province, China," Energy, Elsevier, vol. 262(PA).
  26. Mihaela Simionescu & Wadim Strielkowski & Manuela Tvaronavičienė, 2020. "Renewable Energy in Final Energy Consumption and Income in the EU-28 Countries," Energies, MDPI, vol. 13(9), pages 1-18, May.
  27. Feng Li & Li Zhou & Guangshu Xu & Hui Lu & Kai Wang & Sang-Bing Tsai, 2018. "An empirical study on solving an integrated production and distribution problem with a hybrid strategy," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-23, November.
  28. Lovato, Giovanna & Kovalovszki, Adam & Alvarado-Morales, Merlin & Arjuna Jéglot, Arnaud Tristan & Rodrigues, José Alberto Domingues & Angelidaki, Irini, 2021. "Modelling bioaugmentation: Engineering intervention in anaerobic digestion," Renewable Energy, Elsevier, vol. 175(C), pages 1080-1087.
  29. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
  30. Lopion, Peter & Markewitz, Peter & Robinius, Martin & Stolten, Detlef, 2018. "A review of current challenges and trends in energy systems modeling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 156-166.
  31. Wang, Lu & Wu, Jiangbin & Cao, Yang & Hong, Yanran, 2022. "Forecasting renewable energy stock volatility using short and long-term Markov switching GARCH-MIDAS models: Either, neither or both?," Energy Economics, Elsevier, vol. 111(C).
  32. Zheng, Hong-Hao & Wang, Zheng-Xin, 2019. "Measurement and comparison of export sophistication of the new energy industry in 30 countries during 2000–2015," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 140-158.
  33. Ahmad, Tanveer & Huanxin, Chen & Zhang, Dongdong & Zhang, Hongcai, 2020. "Smart energy forecasting strategy with four machine learning models for climate-sensitive and non-climate sensitive conditions," Energy, Elsevier, vol. 198(C).
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