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Benefits of solar forecasting for energy imbalance markets

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  1. Hugo Bezerra Menezes Leite & Hamidreza Zareipour, 2023. "Six Days Ahead Forecasting of Energy Production of Small Behind-the-Meter Solar Sites," Energies, MDPI, vol. 16(3), pages 1-14, February.
  2. Logothetis, Stavros-Andreas & Salamalikis, Vasileios & Wilbert, Stefan & Remund, Jan & Zarzalejo, Luis F. & Xie, Yu & Nouri, Bijan & Ntavelis, Evangelos & Nou, Julien & Hendrikx, Niels & Visser, Lenna, 2022. "Benchmarking of solar irradiance nowcast performance derived from all-sky imagers," Renewable Energy, Elsevier, vol. 199(C), pages 246-261.
  3. Terrén-Serrano, G. & Martínez-Ramón, M., 2023. "Kernel learning for intra-hour solar forecasting with infrared sky images and cloud dynamic feature extraction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
  4. Alessandro Niccolai & Seyedamir Orooji & Andrea Matteri & Emanuele Ogliari & Sonia Leva, 2022. "Irradiance Nowcasting by Means of Deep-Learning Analysis of Infrared Images," Forecasting, MDPI, vol. 4(1), pages 1-11, March.
  5. Singh Doorga, Jay Rovisham & Dhurmea, Kumar Ram & Rughooputh, Soonil & Boojhawon, Ravindra, 2019. "Forecasting mesoscale distribution of surface solar irradiation using a proposed hybrid approach combining satellite remote sensing and time series models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 69-85.
  6. Verbois, Hadrien & Blanc, Philippe & Huva, Robert & Saint-Drenan, Yves-Marie & Rusydi, Andrivo & Thiery, Alexandre, 2020. "Beyond quadratic error: Case-study of a multiple criteria approach to the performance assessment of numerical forecasts of solar irradiance in the tropics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
  7. Lasemi, Mohammad Ali & Arabkoohsar, Ahmad, 2020. "Optimal operating strategy of high-temperature heat and power storage system coupled with a wind farm in energy market," Energy, Elsevier, vol. 210(C).
  8. Liao, Zhouyi & Coimbra, Carlos F.M., 2024. "Hybrid solar irradiance nowcasting and forecasting with the SCOPE method and convolutional neural networks," Renewable Energy, Elsevier, vol. 232(C).
  9. Rafati, Amir & Joorabian, Mahmood & Mashhour, Elaheh & Shaker, Hamid Reza, 2021. "High dimensional very short-term solar power forecasting based on a data-driven heuristic method," Energy, Elsevier, vol. 219(C).
  10. Olubayo M. Babatunde & Josiah L. Munda & Yskandar Hamam, 2020. "Exploring the Potentials of Artificial Neural Network Trained with Differential Evolution for Estimating Global Solar Radiation," Energies, MDPI, vol. 13(10), pages 1-18, May.
  11. Elsinga, Boudewijn & van Sark, Wilfried G.J.H.M., 2017. "Short-term peer-to-peer solar forecasting in a network of photovoltaic systems," Applied Energy, Elsevier, vol. 206(C), pages 1464-1483.
  12. Rodríguez, Fermín & Galarza, Ainhoa & Vasquez, Juan C. & Guerrero, Josep M., 2022. "Using deep learning and meteorological parameters to forecast the photovoltaic generators intra-hour output power interval for smart grid control," Energy, Elsevier, vol. 239(PB).
  13. Tawsif Ahmad & Ning Zhou & Ziang Zhang & Wenyuan Tang, 2024. "Enhancing Probabilistic Solar PV Forecasting: Integrating the NB-DST Method with Deterministic Models," Energies, MDPI, vol. 17(10), pages 1-19, May.
  14. Carneiro, Tatiane C. & Rocha, Paulo A.C. & Carvalho, Paulo C.M. & Fernández-Ramírez, Luis M., 2022. "Ridge regression ensemble of machine learning models applied to solar and wind forecasting in Brazil and Spain," Applied Energy, Elsevier, vol. 314(C).
  15. Bouzgou, Hassen & Gueymard, Christian A., 2019. "Fast short-term global solar irradiance forecasting with wrapper mutual information," Renewable Energy, Elsevier, vol. 133(C), pages 1055-1065.
  16. 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.
  17. Cheng, Lilin & Zang, Haixiang & Wei, Zhinong & Zhang, Fengchun & Sun, Guoqiang, 2022. "Evaluation of opaque deep-learning solar power forecast models towards power-grid applications," Renewable Energy, Elsevier, vol. 198(C), pages 960-972.
  18. Benali, L. & Notton, G. & Fouilloy, A. & Voyant, C. & Dizene, R., 2019. "Solar radiation forecasting using artificial neural network and random forest methods: Application to normal beam, horizontal diffuse and global components," Renewable Energy, Elsevier, vol. 132(C), pages 871-884.
  19. Dillon, Trent & Maurer, Benjamin & Lawson, Michael & Polagye, Brian, 2024. "Forecast-based stochastic optimization for a load powered by wave energy," Renewable Energy, Elsevier, vol. 226(C).
  20. Notton, Gilles & Nivet, Marie-Laure & Voyant, Cyril & Paoli, Christophe & Darras, Christophe & Motte, Fabrice & Fouilloy, Alexis, 2018. "Intermittent and stochastic character of renewable energy sources: Consequences, cost of intermittence and benefit of forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 87(C), pages 96-105.
  21. Chu, Yinghao & Wang, Yiling & Yang, Dazhi & Chen, Shanlin & Li, Mengying, 2024. "A review of distributed solar forecasting with remote sensing and deep learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 198(C).
  22. Behzadi, Amirmohammad & Sadrizadeh, Sasan, 2023. "Grid-tied solar and biomass hybridization for multi-family houses in Sweden: An optimal rule-based control framework through machine learning approach," Renewable Energy, Elsevier, vol. 218(C).
  23. Keeratimahat, Kanyawee & Bruce, Anna & MacGill, Iain, 2021. "Analysis of short-term operational forecast deviations and controllability of utility-scale photovoltaic plants," Renewable Energy, Elsevier, vol. 167(C), pages 343-358.
  24. Khoodaruth, A. & Oree, V. & Elahee, M.K. & Clark, Woodrow W., 2017. "Exploring options for a 100% renewable energy system in Mauritius by 2050," Utilities Policy, Elsevier, vol. 44(C), pages 38-49.
  25. Paletta, Quentin & Arbod, Guillaume & Lasenby, Joan, 2023. "Omnivision forecasting: Combining satellite and sky images for improved deterministic and probabilistic intra-hour solar energy predictions," Applied Energy, Elsevier, vol. 336(C).
  26. Kaur, Amanpreet & Nonnenmacher, Lukas & Coimbra, Carlos F.M., 2016. "Net load forecasting for high renewable energy penetration grids," Energy, Elsevier, vol. 114(C), pages 1073-1084.
  27. Jayesh Thaker & Robert Höller, 2023. "Evaluation of High Resolution WRF Solar," Energies, MDPI, vol. 16(8), pages 1-13, April.
  28. Marco Pierro & David Moser & Richard Perez & Cristina Cornaro, 2020. "The Value of PV Power Forecast and the Paradox of the “Single Pricing” Scheme: The Italian Case Study," Energies, MDPI, vol. 13(15), pages 1-27, August.
  29. Yang, Dazhi & Wang, Wenting & Gueymard, Christian A. & Hong, Tao & Kleissl, Jan & Huang, Jing & Perez, Marc J. & Perez, Richard & Bright, Jamie M. & Xia, Xiang’ao & van der Meer, Dennis & Peters, Ian , 2022. "A review of solar forecasting, its dependence on atmospheric sciences and implications for grid integration: Towards carbon neutrality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
  30. Hafize Nurgul Durmus Senyapar & Ahmet Aksoz, 2024. "Empowering Sustainability: A Consumer-Centric Analysis Based on Advanced Electricity Consumption Predictions," Sustainability, MDPI, vol. 16(7), pages 1-23, April.
  31. Yang, Dazhi & van der Meer, Dennis, 2021. "Post-processing in solar forecasting: Ten overarching thinking tools," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
  32. Yang, Dazhi & Wu, Elynn & Kleissl, Jan, 2019. "Operational solar forecasting for the real-time market," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1499-1519.
  33. Gandhi, Oktoviano & Zhang, Wenjie & Kumar, Dhivya Sampath & Rodríguez-Gallegos, Carlos D. & Yagli, Gokhan Mert & Yang, Dazhi & Reindl, Thomas & Srinivasan, Dipti, 2024. "The value of solar forecasts and the cost of their errors: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
  34. Carpentieri, A. & Folini, D. & Nerini, D. & Pulkkinen, S. & Wild, M. & Meyer, A., 2023. "Intraday probabilistic forecasts of surface solar radiation with cloud scale-dependent autoregressive advection," Applied Energy, Elsevier, vol. 351(C).
  35. Pierro, Marco & De Felice, Matteo & Maggioni, Enrico & Moser, David & Perotto, Alessandro & Spada, Francesco & Cornaro, Cristina, 2020. "Residual load probabilistic forecast for reserve assessment: A real case study," Renewable Energy, Elsevier, vol. 149(C), pages 508-522.
  36. Oprea, Simona-Vasilica & Bâra, Adela & Ciurea, Cristian-Eugen, 2022. "A novel cost-revenue allocation computation for the competitiveness of balancing responsible parties, including RES. Insights from the electricity market," Renewable Energy, Elsevier, vol. 199(C), pages 881-894.
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