A Comparative Study of AI Methods on Renewable Energy Prediction for Smart Grids: Case of Turkey
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Ahmed, Adil & Khalid, Muhammad, 2019. "A review on the selected applications of forecasting models in renewable power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 100(C), pages 9-21.
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.- Ahmed, R. & Sreeram, V. & Mishra, Y. & Arif, M.D., 2020. "A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
- Wang, Yun & Zou, Runmin & Liu, Fang & Zhang, Lingjun & Liu, Qianyi, 2021. "A review of wind speed and wind power forecasting with deep neural networks," Applied Energy, Elsevier, vol. 304(C).
- Polleux, Louis & Guerassimoff, Gilles & Marmorat, Jean-Paul & Sandoval-Moreno, John & Schuhler, Thierry, 2022. "An overview of the challenges of solar power integration in isolated industrial microgrids with reliability constraints," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
- Muhammad Aslam & Jae-Myeong Lee & Hyung-Seung Kim & Seung-Jae Lee & Sugwon Hong, 2019. "Deep Learning Models for Long-Term Solar Radiation Forecasting Considering Microgrid Installation: A Comparative Study," Energies, MDPI, vol. 13(1), pages 1-15, December.
- Wolfram Rozas & Rafael Pastor-Vargas & Angel Miguel García-Vico & José Carpio, 2023. "Consumption–Production Profile Categorization in Energy Communities," Energies, MDPI, vol. 16(19), pages 1-27, October.
- Nemanja Mišljenović & Matej Žnidarec & Goran Knežević & Damir Šljivac & Andreas Sumper, 2023. "A Review of Energy Management Systems and Organizational Structures of Prosumers," Energies, MDPI, vol. 16(7), pages 1-32, March.
- Wen, Xin & Heinisch, Verena & Müller, Jonas & Sasse, Jan-Philipp & Trutnevyte, Evelina, 2023. "Comparison of statistical and optimization models for projecting future PV installations at a sub-national scale," Energy, Elsevier, vol. 285(C).
- Nakıp, Mert & Çopur, Onur & Biyik, Emrah & Güzeliş, Cüneyt, 2023. "Renewable energy management in smart home environment via forecast embedded scheduling based on Recurrent Trend Predictive Neural Network," Applied Energy, Elsevier, vol. 340(C).
- Marta Poncela-Blanco & Pilar Poncela, 2021. "Improving Wind Power Forecasts: Combination through Multivariate Dimension Reduction Techniques," Energies, MDPI, vol. 14(5), pages 1-16, March.
- Abhnil Amtesh Prasad & Merlinde Kay, 2021. "Prediction of Solar Power Using Near-Real Time Satellite Data," Energies, MDPI, vol. 14(18), pages 1-20, September.
- Phathutshedzo Mpfumali & Caston Sigauke & Alphonce Bere & Sophie Mulaudzi, 2019. "Day Ahead Hourly Global Horizontal Irradiance Forecasting—Application to South African Data," Energies, MDPI, vol. 12(18), pages 1-28, September.
- Ma, Chao & Xu, Ximeng & Pang, Xiulan & Li, Xiaofeng & Zhang, Pengfei & Liu, Lu, 2024. "Scenario-based ultra-short-term rolling optimal operation of a photovoltaic-energy storage system under forecast uncertainty," Applied Energy, Elsevier, vol. 356(C).
- Samu, Remember & Calais, Martina & Shafiullah, G.M. & Moghbel, Moayed & Shoeb, Md Asaduzzaman & Nouri, Bijan & Blum, Niklas, 2021. "Applications for solar irradiance nowcasting in the control of microgrids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
- Lu, Peng & Ye, Lin & Tang, Yong & Zhao, Yongning & Zhong, Wuzhi & Qu, Ying & Zhai, Bingxu, 2021. "Ultra-short-term combined prediction approach based on kernel function switch mechanism," Renewable Energy, Elsevier, vol. 164(C), pages 842-866.
- Gulay, Emrah & Sen, Mustafa & Akgun, Omer Burak, 2024. "Forecasting electricity production from various energy sources in Türkiye: A predictive analysis of time series, deep learning, and hybrid models," Energy, Elsevier, vol. 286(C).
- Zhenhua Xiong & Yan Chen & Guihua Ban & Yixin Zhuo & Kui Huang, 2022. "A Hybrid Algorithm for Short-Term Wind Power Prediction," Energies, MDPI, vol. 15(19), pages 1-11, October.
- Endemaño-Ventura, Lázaro & Serrano González, Javier & Roldán Fernández, Juan Manuel & Burgos Payán, Manuel & Riquelme Santos, Jesús Manuel, 2021. "Optimal energy bidding for renewable plants: A practical application to an actual wind farm in Spain," Renewable Energy, Elsevier, vol. 175(C), pages 1111-1126.
- Li, Binghui & Feng, Cong & Siebenschuh, Carlo & Zhang, Rui & Spyrou, Evangelia & Krishnan, Venkat & Hobbs, Benjamin F. & Zhang, Jie, 2022. "Sizing ramping reserve using probabilistic solar forecasts: A data-driven method," Applied Energy, Elsevier, vol. 313(C).
- Sewdien, V.N. & Preece, R. & Torres, J.L. Rueda & Rakhshani, E. & van der Meijden, M., 2020. "Assessment of critical parameters for artificial neural networks based short-term wind generation forecasting," Renewable Energy, Elsevier, vol. 161(C), pages 878-892.
- Olatunji, Kehinde O. & Ahmed, Noor A. & Madyira, Daniel M. & Adebayo, Ademola O. & Ogunkunle, Oyetola & Adeleke, Oluwatobi, 2022. "Performance evaluation of ANFIS and RSM modeling in predicting biogas and methane yields from Arachis hypogea shells pretreated with size reduction," Renewable Energy, Elsevier, vol. 189(C), pages 288-303.
More about this item
Keywords
renewable energy; smart grid; deep learning; ANN; LSTM; CNN; LightGBM; GBR; RF;All these keywords.
Statistics
Access and download statisticsCorrections
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:gam:jsusta:v:16:y:2024:i:7:p:2894-:d:1367360. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.