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Energy forecasting: A review and outlook

Citations

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Cited by:

  1. Yang, Dazhi, 2022. "Correlogram, predictability error growth, and bounds of mean square error of solar irradiance forecasts," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
  2. Brusaferri, Alessandro & Ballarino, Andrea & Grossi, Luigi & Laurini, Fabrizio, 2025. "On-line conformalized neural networks ensembles for probabilistic forecasting of day-ahead electricity prices," Applied Energy, Elsevier, vol. 398(C).
  3. Bergsteinsson, Hjörleifur G. & Sørensen, Mikkel Lindstrøm & Møller, Jan Kloppenborg & Madsen, Henrik, 2023. "Heat load forecasting using adaptive spatial hierarchies," Applied Energy, Elsevier, vol. 350(C).
  4. Cornell, Cameron & Dinh, Nam Trong & Pourmousavi, S. Ali, 2024. "A probabilistic forecast methodology for volatile electricity prices in the Australian National Electricity Market," International Journal of Forecasting, Elsevier, vol. 40(4), pages 1421-1437.
  5. Daniel Foronda-Pascual & Andrés M. Alonso, 2023. "Prediction of Matching Prices in Electricity Markets through Curve Representation," Energies, MDPI, vol. 16(23), pages 1-20, November.
  6. Dariusz Borkowski & Michał Jaśkiewicz, 2025. "Forecasting Electricity Prices Three Days in Advance: Comparison Between Multilayer Perceptron and Support Vector Machine Networks," Energies, MDPI, vol. 18(17), pages 1-25, September.
  7. Shadi Tehrani & Jesús Juan & Eduardo Caro, 2022. "Electricity Spot Price Modeling and Forecasting in European Markets," Energies, MDPI, vol. 15(16), pages 1-23, August.
  8. Eric Cebekhulu & Adeiza James Onumanyi & Sherrin John Isaac, 2022. "Performance Analysis of Machine Learning Algorithms for Energy Demand–Supply Prediction in Smart Grids," Sustainability, MDPI, vol. 14(5), pages 1-26, February.
  9. Jonathan Roth & Jayashree Chadalawada & Rishee K. Jain & Clayton Miller, 2021. "Uncertainty Matters: Bayesian Probabilistic Forecasting for Residential Smart Meter Prediction, Segmentation, and Behavioral Measurement and Verification," Energies, MDPI, vol. 14(5), pages 1-22, March.
  10. Bianca Goia & Tudor Cioara & Ionut Anghel, 2022. "Virtual Power Plant Optimization in Smart Grids: A Narrative Review," Future Internet, MDPI, vol. 14(5), pages 1-22, April.
  11. Xiaoxun, Zhu & Huan, Xiao & Lin, Zhu & Yuxuan, Li & Xiaoxia, Gao & Qiang, Sun & Haiqiang, Wang, 2025. "A graph neural model for predicting wind speed behavior based on the effect of wind speed point coupling," Energy, Elsevier, vol. 336(C).
  12. van Zyl, Corne & Ye, Xianming & Naidoo, Raj, 2024. "Harnessing eXplainable artificial intelligence for feature selection in time series energy forecasting: A comparative analysis of Grad-CAM and SHAP," Applied Energy, Elsevier, vol. 353(PA).
  13. Serafin, Tomasz & Marcjasz, Grzegorz & Weron, Rafał, 2022. "Trading on short-term path forecasts of intraday electricity prices," Energy Economics, Elsevier, vol. 112(C).
  14. Maciej Kostrzewski & Jadwiga Kostrzewska, 2021. "The Impact of Forecasting Jumps on Forecasting Electricity Prices," Energies, MDPI, vol. 14(2), pages 1-17, January.
  15. Pellini, Elisabetta, 2021. "Estimating income and price elasticities of residential electricity demand with Autometrics," Energy Economics, Elsevier, vol. 101(C).
  16. Lago, Jesus & Marcjasz, Grzegorz & De Schutter, Bart & Weron, Rafał, 2021. "Forecasting day-ahead electricity prices: A review of state-of-the-art algorithms, best practices and an open-access benchmark," Applied Energy, Elsevier, vol. 293(C).
  17. Park, Jungyeon & Alvarenga, Estêvão & Jeon, Jooyoung & Li, Ran & Petropoulos, Fotios & Kim, Hokyun & Ahn, Kwangwon, 2024. "Probabilistic forecast-based portfolio optimization of electricity demand at low aggregation levels," Applied Energy, Elsevier, vol. 353(PB).
  18. Yang, Dazhi & Yang, Guoming & Liu, Bai, 2023. "Combining quantiles of calibrated solar forecasts from ensemble numerical weather prediction," Renewable Energy, Elsevier, vol. 215(C).
  19. Maciej Jakub Walczewski & Hendrik Wöhrle, 2024. "Prediction of Electricity Generation Using Onshore Wind and Solar Energy in Germany," Energies, MDPI, vol. 17(4), pages 1-27, February.
  20. Zhang, Hanyu & Zandehshahvar, Reza & Tanneau, Mathieu & Van Hentenryck, Pascal, 2025. "Weather-informed probabilistic forecasting and scenario generation in power systems," Applied Energy, Elsevier, vol. 384(C).
  21. Ciarreta, Aitor & Martinez, Blanca & Nasirov, Shahriyar, 2023. "Forecasting electricity prices using bid data," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1253-1271.
  22. Grothe, Oliver & Kächele, Fabian & Krüger, Fabian, 2023. "From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecasting," Energy Economics, Elsevier, vol. 120(C).
  23. Arne Vogler & Florian Ziel, 2021. "Event-Based Evaluation of Electricity Price Ensemble Forecasts," Forecasting, MDPI, vol. 4(1), pages 1-21, December.
  24. Sheybanivaziri, Samaneh & Le Dréau, Jérôme & Kazmi, Hussain, 2024. "Forecasting price spikes in day-ahead electricity markets: techniques, challenges, and the road ahead," Discussion Papers 2024/1, Norwegian School of Economics, Department of Business and Management Science.
  25. Bartosz Uniejewski, 2023. "Smoothing Quantile Regression Averaging: A new approach to probabilistic forecasting of electricity prices," Papers 2302.00411, arXiv.org, revised Nov 2024.
  26. Runyao Yu & Derek W. Bunn & Julia Lin & Jochen Stiasny & Fabian Leimgruber & Tara Esterl & Yuchen Tao & Lianlian Qi & Yujie Chen & Wentao Wang & Jochen L. Cremer, 2026. "Deep Learning for Electricity Price Forecasting: A Review of Day-Ahead, Intraday, and Balancing Electricity Markets," Papers 2602.10071, arXiv.org, revised May 2026.
  27. Katarzyna Maciejowska, 2022. "A portfolio management of a small RES utility with a Structural Vector Autoregressive model of German electricity markets," Papers 2205.00975, arXiv.org.
  28. Llinet Benavides Cesar & Rodrigo Amaro e Silva & Miguel Ángel Manso Callejo & Calimanut-Ionut Cira, 2022. "Review on Spatio-Temporal Solar Forecasting Methods Driven by In Situ Measurements or Their Combination with Satellite and Numerical Weather Prediction (NWP) Estimates," Energies, MDPI, vol. 15(12), pages 1-23, June.
  29. Dumas, Jonathan & Wehenkel, Antoine & Lanaspeze, Damien & Cornélusse, Bertrand & Sutera, Antonio, 2022. "A deep generative model for probabilistic energy forecasting in power systems: normalizing flows," Applied Energy, Elsevier, vol. 305(C).
  30. Qin, Dalin & Wu, Xian & Sun, Dayan & Liang, Zhifeng & Zhang, Ning, 2025. "Load forecasting under distribution shift: An online quantile ensembling approach," Applied Energy, Elsevier, vol. 401(PC).
  31. George Fragiadakis & Evangelia Filiopoulou & Christos Michalakelis & Thomas Kamalakis & Mara Nikolaidou, 2023. "Applying Machine Learning in Cloud Service Price Prediction: The Case of Amazon IaaS," Future Internet, MDPI, vol. 15(8), pages 1-19, August.
  32. Wang, Wenting & Guo, Yufeng & Yang, Dazhi & Zhang, Zili & Kleissl, Jan & van der Meer, Dennis & Yang, Guoming & Hong, Tao & Liu, Bai & Huang, Nantian & Mayer, Martin János, 2024. "Economics of physics-based solar forecasting in power system day-ahead scheduling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
  33. Depoortere, Joris & Driesen, Johan & Suykens, Johan & Kazmi, Hussain Syed, 2025. "SolNet: Open-source deep learning models for photovoltaic power forecasting across the globe," International Journal of Forecasting, Elsevier, vol. 41(3), pages 1223-1236.
  34. Yagli, Gokhan Mert & Yang, Dazhi & Srinivasan, Dipti, 2022. "Ensemble solar forecasting and post-processing using dropout neural network and information from neighboring satellite pixels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
  35. Mayer, Martin János & Yang, Dazhi, 2023. "Calibration of deterministic NWP forecasts and its impact on verification," International Journal of Forecasting, Elsevier, vol. 39(2), pages 981-991.
  36. Verdone, Alessio & Panella, Massimo & De Santis, Enrico & Rizzi, Antonello, 2025. "A review of solar and wind energy forecasting: From single-site to multi-site paradigm," Applied Energy, Elsevier, vol. 392(C).
  37. 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.
  38. Mikkel L. Sørensen & Peter Nystrup & Mathias B. Bjerregård & Jan K. Møller & Peder Bacher & Henrik Madsen, 2023. "Recent developments in multivariate wind and solar power forecasting," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 12(2), March.
  39. Jonathan Berrisch & Florian Ziel, 2022. "Distributional modeling and forecasting of natural gas prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1065-1086, September.
  40. Wang, Yi & Von Krannichfeldt, Leandro & Zufferey, Thierry & Toubeau, Jean-François, 2021. "Short-term nodal voltage forecasting for power distribution grids: An ensemble learning approach," Applied Energy, Elsevier, vol. 304(C).
  41. Wang, Sen & Sun, Yonghui & Zhang, Wenjie & Srinivasan, Dipti, 2025. "Optimization of deterministic and probabilistic forecasting for wind power based on ensemble learning," Energy, Elsevier, vol. 319(C).
  42. Hu, Zehuan & Gao, Yuan & Sun, Luning & Mae, Masayuki, 2025. "A novel attention-enhanced LLM approach for accurate power demand and generation forecasting," Renewable Energy, Elsevier, vol. 252(C).
  43. Weronika Nitka & Rafał Weron, 2023. "Combining predictive distributions of electricity prices. Does minimizing the CRPS lead to optimal decisions in day-ahead bidding?," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 33(3), pages 105-118.
  44. Marcjasz, Grzegorz & Narajewski, Michał & Weron, Rafał & Ziel, Florian, 2023. "Distributional neural networks for electricity price forecasting," Energy Economics, Elsevier, vol. 125(C).
  45. Agakishiev, Ilyas & Härdle, Wolfgang Karl & Kopa, Milos & Kozmik, Karel & Petukhina, Alla, 2025. "Multivariate probabilistic forecasting of electricity prices with trading applications," Energy Economics, Elsevier, vol. 141(C).
  46. 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).
  47. Markovics, Dávid & Mayer, Martin János, 2022. "Comparison of machine learning methods for photovoltaic power forecasting based on numerical weather prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
  48. Bergsteinsson, Hjörleifur G. & Møller, Jan Kloppenborg & Nystrup, Peter & Pálsson, Ólafur Pétur & Guericke, Daniela & Madsen, Henrik, 2021. "Heat load forecasting using adaptive temporal hierarchies," Applied Energy, Elsevier, vol. 292(C).
  49. Ignacio Mauleón, 2021. "Aggregated World Energy Demand Projections: Statistical Assessment," Energies, MDPI, vol. 14(15), pages 1-13, July.
  50. Mayer, Martin János & Yang, Dazhi, 2022. "Probabilistic photovoltaic power forecasting using a calibrated ensemble of model chains," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
  51. Wen, Honglin & Pinson, Pierre & Gu, Jie & Jin, Zhijian, 2024. "Wind energy forecasting with missing values within a fully conditional specification framework," International Journal of Forecasting, Elsevier, vol. 40(1), pages 77-95.
  52. Tawn, R. & Browell, J., 2022. "A review of very short-term wind and solar power forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
  53. Cirac, Gabriel & Botechia, Vinicius Eduardo & Schiozer, Denis José & Martínez, Víctor & Werneck, Rafael de Oliveira & Rocha, Anderson, 2025. "Few-shot and continuous online learning for forecasting in the energy industry," Energy, Elsevier, vol. 336(C).
  54. Billé, Anna Gloria & Gianfreda, Angelica & Del Grosso, Filippo & Ravazzolo, Francesco, 2023. "Forecasting electricity prices with expert, linear, and nonlinear models," International Journal of Forecasting, Elsevier, vol. 39(2), pages 570-586.
  55. Li, Jin & Wen, Xin & Jia, Li & Cao, Ruochen & Zhang, Xiao & Hao, Yanrong & Gao, Chengxin & Cao, Rui, 2025. "A Transformer-based model fusing temporal dependence and variable correlation for short and medium-term electricity price forecasting," Energy, Elsevier, vol. 338(C).
  56. Max Kleinebrahm & Jonathan Berrisch & Philipp Eiser & Wolf Fichtner & Veit Hagenmeyer & Matthias Hertel & Nils Koster & Sebastian Lerch & Ralf Mikut & Jan Priesmann & Melanie Schienle & Benjamin Schae, 2026. "Energy-Arena: A Dynamic Benchmark for Operational Energy Forecasting," Papers 2604.24705, arXiv.org.
  57. Li, Yiyan & Zhang, Si & Hu, Rongxing & Lu, Ning, 2021. "A meta-learning based distribution system load forecasting model selection framework," Applied Energy, Elsevier, vol. 294(C).
  58. Jiaxin Zhang & Siyuan Shang, 2025. "Fast and Interpretable Probabilistic Solar Power Forecasting via a Multi-Observation Non-Homogeneous Hidden Markov Model," Energies, MDPI, vol. 18(10), pages 1-14, May.
  59. Ramos, Paulo Vitor B. & Villela, Saulo Moraes & Silva, Walquiria N. & Dias, Bruno H., 2023. "Residential energy consumption forecasting using deep learning models," Applied Energy, Elsevier, vol. 350(C).
  60. Monika Zielińska-Sitkiewicz & Mariola Chrzanowska & Konrad Furmańczyk & Kacper Paczutkowski, 2021. "Analysis of Electricity Consumption in Poland Using Prediction Models and Neural Networks," Energies, MDPI, vol. 14(20), pages 1-21, October.
  61. Wu, Thomas & Hu, Ruifeng & Zhu, Hongyu & Jiang, Meihui & Lv, Kunye & Dong, Yunxuan & Zhang, Dongdong, 2024. "Combined IXGBoost-KELM short-term photovoltaic power prediction model based on multidimensional similar day clustering and dual decomposition," Energy, Elsevier, vol. 288(C).
  62. Mayer, Martin János, 2022. "Impact of the tilt angle, inverter sizing factor and row spacing on the photovoltaic power forecast accuracy," Applied Energy, Elsevier, vol. 323(C).
  63. Pesantez, Jorge E. & Li, Binbin & Lee, Christopher & Zhao, Zhizhen & Butala, Mark & Stillwell, Ashlynn S., 2023. "A Comparison Study of Predictive Models for Electricity Demand in a Diverse Urban Environment," Energy, Elsevier, vol. 283(C).
  64. Stefano Bianchi & Allegra De Filippo & Sandro Magnani & Gabriele Mosaico & Federico Silvestro, 2021. "VIRTUS Project: A Scalable Aggregation Platform for the Intelligent Virtual Management of Distributed Energy Resources," Energies, MDPI, vol. 14(12), pages 1-31, June.
  65. Yu, Hanxin & Chen, Shanlin & Chu, Yinghao & Li, Mengying & Ding, Yueming & Cui, Rongxi & Zhao, Xin, 2024. "Self-attention mechanism to enhance the generalizability of data-driven time-series prediction: A case study of intra-hour power forecasting of urban distributed photovoltaic systems," Applied Energy, Elsevier, vol. 374(C).
  66. Katarzyna Chec & Bartosz Uniejewski & Rafal Weron, 2026. "From biased point forecasts of electricity demand to accurate predictive distributions: Using LASSO and GAMLSS," WORking papers in Management Science (WORMS) WORMS/26/01, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
  67. Pierre Pinson & Liyang Han & Jalal Kazempour, 2022. "Regression markets and application to energy forecasting," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(3), pages 533-573, October.
  68. 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.
  69. Bashyal, Atit & Bangre, Chidambar Prabhakar & Boroukhian, Tina & Wicaksono, Hendro, 2025. "Unsupervised domain adaptation framework for photovoltaic power forecasting using variational auto-encoders," Applied Energy, Elsevier, vol. 400(C).
  70. Qinghe Zhao & Xinyi Liu & Junlong Fang, 2023. "Extreme Gradient Boosting Model for Day-Ahead STLF in National Level Power System: Estonia Case Study," Energies, MDPI, vol. 16(24), pages 1-29, December.
  71. Arkadiusz Jędrzejewski & Grzegorz Marcjasz & Rafał Weron, 2021. "Importance of the Long-Term Seasonal Component in Day-Ahead Electricity Price Forecasting Revisited: Parameter-Rich Models Estimated via the LASSO," Energies, MDPI, vol. 14(11), pages 1-17, June.
  72. Siwei Cheng & Jing Shi & Qi Cheng & Xinmeng Zhou & Shuai Zeng, 2025. "Hybrid Model for Medium-Term Load Forecasting in Urban Power Grids," Energies, MDPI, vol. 18(16), pages 1-24, August.
  73. Yang, Mao & Huang, Yutong & Xu, Chuanyu & Liu, Chenyu & Dai, Bozhi, 2025. "Review of several key processes in wind power forecasting: Mathematical formulations, scientific problems, and logical relations," Applied Energy, Elsevier, vol. 377(PC).
  74. 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).
  75. Yang, Dazhi & Kleissl, Jan, 2023. "Summarizing ensemble NWP forecasts for grid operators: Consistency, elicitability, and economic value," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1640-1654.
  76. Hugo Radet & Bruno Sareni & Xavier Roboam, 2023. "Synthesis of Solar Production and Energy Demand Profiles Using Markov Chains for Microgrid Design," Energies, MDPI, vol. 16(23), pages 1-12, December.
  77. Jaweriya Naz & Dr. Mirza Faizan Ahmed & Prof. Dr. Raza Ali Khan, 2024. "Pakistan Energy Outlook for Next 25 Years," Bulletin of Business and Economics (BBE), Research Foundation for Humanity (RFH), vol. 13(2), pages 563-572.
  78. Serafin, Tomasz & Weron, Rafał, 2025. "Loss functions in regression models: Impact on profits and risk in day-ahead electricity trading," Energy Economics, Elsevier, vol. 148(C).
  79. Uniejewski, Bartosz & Weron, Rafał, 2021. "Regularized quantile regression averaging for probabilistic electricity price forecasting," Energy Economics, Elsevier, vol. 95(C).
  80. Lin, Fan & Zhang, Yao & Wang, Jianxue, 2023. "Recent advances in intra-hour solar forecasting: A review of ground-based sky image methods," International Journal of Forecasting, Elsevier, vol. 39(1), pages 244-265.
  81. Jing Wan & Jiehui Huang & Zhiyuan Liao & Chunquan Li & Peter X. Liu, 2022. "A Multi-View Ensemble Width-Depth Neural Network for Short-Term Wind Power Forecasting," Mathematics, MDPI, vol. 10(11), pages 1-20, May.
  82. Stienecker, Malte, 2024. "Impact of forecasted heat demand on day-ahead optimal scheduling and real time control of multi-energy systems," Energy, Elsevier, vol. 297(C).
  83. Gonca Gürses-Tran & Antonello Monti, 2022. "Advances in Time Series Forecasting Development for Power Systems’ Operation with MLOps," Forecasting, MDPI, vol. 4(2), pages 1-24, May.
  84. Kohút, Roman & Klaučo, Martin & Kvasnica, Michal, 2025. "Unified carbon emissions and market prices forecasts of the power grid," Applied Energy, Elsevier, vol. 377(PC).
  85. Nametala, Ciniro Aparecido Leite & Faria, Wandry Rodrigues & Lage, Guilherme Guimarães & Pereira, Benvindo Rodrigues, 2023. "Analysis of hourly price granularity implementation in the Brazilian deregulated electricity contracting environment," Utilities Policy, Elsevier, vol. 81(C).
  86. Jui-Tang Wang & Thi Anh Tuyet Nguyen & Yu-Hong Guo & Chau-Yun Hsu & Huang-Jun Xie, 2025. "An innovative cluster-based prediction approach for mass solar site management," Energy & Environment, , vol. 36(1), pages 212-230, February.
  87. Perera, Maneesha & De Hoog, Julian & Bandara, Kasun & Senanayake, Damith & Halgamuge, Saman, 2024. "Day-ahead regional solar power forecasting with hierarchical temporal convolutional neural networks using historical power generation and weather data," Applied Energy, Elsevier, vol. 361(C).
  88. Chȩć, Katarzyna & Uniejewski, Bartosz & Weron, Rafał, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Journal of Commodity Markets, Elsevier, vol. 37(C).
  89. Leonard Burg & Gonca Gürses-Tran & Reinhard Madlener & Antonello Monti, 2021. "Comparative Analysis of Load Forecasting Models for Varying Time Horizons and Load Aggregation Levels," Energies, MDPI, vol. 14(21), pages 1-16, November.
  90. 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).
  91. Mayer, Martin János, 2022. "Benefits of physical and machine learning hybridization for photovoltaic power forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
  92. Lauret, Philippe & Alonso-Suárez, Rodrigo & Amaro e Silva, Rodrigo & Boland, John & David, Mathieu & Herzberg, Wiebke & Le Gall La Salle, Josselin & Lorenz, Elke & Visser, Lennard & van Sark, Wilfried, 2024. "The added value of combining solar irradiance data and forecasts: A probabilistic benchmarking exercise," Renewable Energy, Elsevier, vol. 237(PB).
  93. Wen, Qianyun & Liu, Yang, 2025. "Feature engineering and selection for prosumer electricity consumption and production forecasting: A comprehensive framework," Applied Energy, Elsevier, vol. 381(C).
  94. Ayesha Siddiqa & Nadim Rana & Wazir Zada Khan & Fathe Jeribi & Ali Tahir, 2025. "Explaining solar forecasts with generative AI: A two-stage framework combining transformers and LLMs," PLOS ONE, Public Library of Science, vol. 20(9), pages 1-22, September.
  95. Terrén-Serrano, Guillermo & Martínez-Ramón, Manel, 2021. "Comparative analysis of methods for cloud segmentation in ground-based infrared images," Renewable Energy, Elsevier, vol. 175(C), pages 1025-1040.
  96. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
  97. Uniejewski, Bartosz, 2025. "Smoothing quantile regression averaging: A new approach to probabilistic forecasting of electricity prices," Journal of Commodity Markets, Elsevier, vol. 39(C).
  98. Dong, Xianzhou & Guo, Weiyong & Zhou, Cheng & Luo, Yongqiang & Tian, Zhiyong & Zhang, Limao & Wu, Xiaoying & Liu, Baobing, 2024. "Hybrid model for robust and accurate forecasting building electricity demand combining physical and data-driven methods," Energy, Elsevier, vol. 311(C).
  99. Katarzyna Chk{e}'c & Bartosz Uniejewski & Rafa{l} Weron, 2025. "Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market," Papers 2503.02518, arXiv.org.
  100. Kazmi, Hussain & Tao, Zhenmin, 2022. "How good are TSO load and renewable generation forecasts: Learning curves, challenges, and the road ahead," Applied Energy, Elsevier, vol. 323(C).
  101. Haben, Stephen & Arora, Siddharth & Giasemidis, Georgios & Voss, Marcus & Vukadinović Greetham, Danica, 2021. "Review of low voltage load forecasting: Methods, applications, and recommendations," Applied Energy, Elsevier, vol. 304(C).
  102. Yannik Pflugfelder & Aiko Schinke-Nendza & Jonathan Dumas & Christoph Weber, 2024. "Deriving multivariate probabilistic solar generation forecasts based on hourly imbalanced data," EWL Working Papers 2407, University of Duisburg-Essen, Chair for Management Science and Energy Economics, revised Nov 2024.
  103. Dai, Yeming & Yang, Xinyu & Leng, Mingming, 2022. "Forecasting power load: A hybrid forecasting method with intelligent data processing and optimized artificial intelligence," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
  104. Qi Cheng & Jing Shi & Siwei Cheng, 2025. "Short-Term Load Forecasting Based on Similar Day Theory and BWO-VMD," Energies, MDPI, vol. 18(9), pages 1-20, May.
  105. Nikolaos Kolokas & Dimosthenis Ioannidis & Dimitrios Tzovaras, 2021. "Multi-Step Energy Demand and Generation Forecasting with Confidence Used for Specification-Free Aggregate Demand Optimization," Energies, MDPI, vol. 14(11), pages 1-36, May.
  106. Stefenon, Stefano Frizzo & Seman, Laio Oriel & da Silva, Evandro Cardozo & Finardi, Erlon Cristian & Coelho, Leandro dos Santos & Mariani, Viviana Cocco, 2024. "Hypertuned wavelet convolutional neural network with long short-term memory for time series forecasting in hydroelectric power plants," Energy, Elsevier, vol. 313(C).
  107. Rahman, Tasmeea & Othman, Mohammad Lutfi & Mohd Noor, Samsul Bahari & Binti Wan Ahmad, Wan Fatinhamamah & Sulaima, Mohamad Fani, 2024. "Methods and attributes for customer-centric dynamic electricity tariff design: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
  108. Visser, L.R. & AlSkaif, T.A. & Khurram, A. & Kleissl, J. & van Sark, W.G.H.J.M., 2024. "Probabilistic solar power forecasting: An economic and technical evaluation of an optimal market bidding strategy," Applied Energy, Elsevier, vol. 370(C).
  109. Haicheng Ling & Pierre-Yves Massé & Thibault Rihet & Frédéric Wurtz, 2023. "Realistic Nudging through ICT Pipelines to Help Improve Energy Self-Consumption for Management in Energy Communities," Energies, MDPI, vol. 16(13), pages 1-24, July.
  110. Mayer, Martin János & Yang, Dazhi, 2023. "Pairing ensemble numerical weather prediction with ensemble physical model chain for probabilistic photovoltaic power forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
  111. 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).
  112. Voyant, Cyril & Notton, Gilles & Duchaud, Jean-Laurent & Gutiérrez, Luis Antonio García & Bright, Jamie M. & Yang, Dazhi, 2022. "Benchmarks for solar radiation time series forecasting," Renewable Energy, Elsevier, vol. 191(C), pages 747-762.
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