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Energy forecasting: A review and outlook

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Cited by:

  1. 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.
  2. 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).
  3. 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).
  4. 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.
  5. Mayer, Martin János, 2022. "Benefits of physical and machine learning hybridization for photovoltaic power forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
  6. 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.
  7. 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).
  8. 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.
  9. 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).
  10. 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.
  11. 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.
  12. 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).
  13. 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).
  14. 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).
  15. 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).
  16. 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.
  17. 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.
  18. Maciej Kostrzewski & Jadwiga Kostrzewska, 2021. "The Impact of Forecasting Jumps on Forecasting Electricity Prices," Energies, MDPI, vol. 14(2), pages 1-17, January.
  19. 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.
  20. 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.
  21. 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.
  22. 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.
  23. 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.
  24. 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).
  25. 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).
  26. Bartosz Uniejewski, 2023. "Smoothing Quantile Regression Averaging: A new approach to probabilistic forecasting of electricity prices," Papers 2302.00411, arXiv.org, revised Nov 2024.
  27. 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.
  28. Pellini, Elisabetta, 2021. "Estimating income and price elasticities of residential electricity demand with Autometrics," Energy Economics, Elsevier, vol. 101(C).
  29. 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).
  30. 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.
  31. 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).
  32. 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).
  33. 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.
  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. 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.
  36. Tadeusz A. Grzeszczyk & Michal K. Grzeszczyk, 2022. "Justifying Short-Term Load Forecasts Obtained with the Use of Neural Models," Energies, MDPI, vol. 15(5), pages 1-20, March.
  37. 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.
  38. 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.
  39. Uniejewski, Bartosz & Weron, Rafał, 2021. "Regularized quantile regression averaging for probabilistic electricity price forecasting," Energy Economics, Elsevier, vol. 95(C).
  40. 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.
  41. 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).
  42. 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.
  43. 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.
  44. 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.
  45. 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).
  46. Georgios Papazoglou & Pandelis Biskas, 2022. "Review of Methodologies for the Assessment of Feasible Operating Regions at the TSO–DSO Interface," Energies, MDPI, vol. 15(14), pages 1-24, July.
  47. 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.
  48. 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).
  49. 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.
  50. 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.
  51. 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).
  52. 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).
  53. Marcjasz, Grzegorz & Narajewski, Michał & Weron, Rafał & Ziel, Florian, 2023. "Distributional neural networks for electricity price forecasting," Energy Economics, Elsevier, vol. 125(C).
  54. 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).
  55. 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.
  56. 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).
  57. 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).
  58. Serafin, Tomasz & Marcjasz, Grzegorz & Weron, Rafał, 2022. "Trading on short-term path forecasts of intraday electricity prices," Energy Economics, Elsevier, vol. 112(C).
  59. 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).
  60. Massidda, Luca & Marrocu, Marino, 2023. "Total and thermal load forecasting in residential communities through probabilistic methods and causal machine learning," Applied Energy, Elsevier, vol. 351(C).
  61. 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).
  62. 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.
  63. 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.
  64. 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.
  65. 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).
  66. 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.
  67. 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).
  68. 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).
  69. Yang, Dazhi & Yang, Guoming & Liu, Bai, 2023. "Combining quantiles of calibrated solar forecasts from ensemble numerical weather prediction," Renewable Energy, Elsevier, vol. 215(C).
  70. 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.
  71. 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).
  72. 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.
  73. Ignacio Mauleón, 2021. "Aggregated World Energy Demand Projections: Statistical Assessment," Energies, MDPI, vol. 14(15), pages 1-13, July.
  74. 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).
  75. 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).
  76. Arne Vogler & Florian Ziel, 2021. "Event-Based Evaluation of Electricity Price Ensemble Forecasts," Forecasting, MDPI, vol. 4(1), pages 1-21, December.
  77. 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.
  78. Katarzyna Maciejowska & Bartosz Uniejewski & Rafa{l} Weron, 2022. "Forecasting Electricity Prices," Papers 2204.11735, arXiv.org.
  79. 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).
  80. Ciarreta, Aitor & Martinez, Blanca & Nasirov, Shahriyar, 2023. "Forecasting electricity prices using bid data," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1253-1271.
  81. 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).
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