IDEAS home Printed from https://ideas.repec.org/r/eee/rensus/v77y2017icp1169-1178.html
   My bibliography  Save this item

Models for forecasting growth trends in renewable energy

Citations

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


Cited by:

  1. 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.
  2. 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).
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 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.
  10. Krzysztof Księżopolski & Grzegorz Maśloch, 2021. "Time Delay Approach to Renewable Energy in the Visegrad Group," Energies, MDPI, vol. 14(7), pages 1-18, March.
  11. 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.
  12. 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.
  13. 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.
  14. 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.
  15. 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.
  16. 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.
  17. 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.
  18. 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.
  19. 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.
  20. 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.
  21. 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).
  22. 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.
  23. 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.
  24. 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.
  25. Debnath, Kumar Biswajit & Mourshed, Monjur, 2018. "Forecasting methods in energy planning models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 297-325.
  26. 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.
  27. 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.
  28. 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).
  29. 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.
  30. 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).
  31. 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).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.