The evolution of probabilistic price forecasting techniques: A review of the day-ahead, intra-day, and balancing markets
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Date
2026-04-16
Authors
O’Connor, Ciaran
Bahloul, Mohamed
Prestwich, Steven
Visentin, Andrea
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Abstract
Electricity price forecasting has become a critical tool for decision-making in energy markets, particularly as the increasing penetration of renewable energy has introduced greater volatility and uncertainty. Historically, research in this field has been dominated by point forecasting methods, which provide single-value predictions but fail to quantify uncertainty. However, as power markets evolve due to renewable integration, smart grids, and regulatory changes, the need for probabilistic forecasting has become more pronounced, offering a more comprehensive approach to risk assessment and market participation. This paper presents a review of probabilistic forecasting methods, tracing their evolution from Bayesian and distribution based approaches to quantile regression techniques to recent developments in conformal prediction. Particular emphasis is placed on advancements in probabilistic forecasting, including validity-focused methods that address key limitations in uncertainty estimation. Additionally, this review extends beyond the day-ahead market to include the intra-day and balancing markets, where forecasting challenges are intensified by higher temporal granularity and real-time operational constraints. We examine state-of-the-art methodologies, key evaluation metrics, and ongoing challenges, such as forecast validity, model selection, and the absence of standardised benchmarks, providing researchers and practitioners with a comprehensive and timely resource for navigating the complexities of modern electricity markets. © 2026 by the authors.
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© 2026, by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Keywords
Artificial Intelligence and Data Analytics , SDG 7 - Affordable and Clean Energy , Balancing market , Conformal prediction , Day-ahead market , Intra-day market , Probabilistic electricity price forecasting , Quantile regression , Costs , Decision making , Forecasting , [ComputerScience] , Regression analysis , [Insight Centre for Data Analytics]
Citation
O’Connor, C, Bahloul, M, Prestwich, S & Visentin, A 2026, 'The evolution of probabilistic price forecasting techniques: A review of the day-ahead, intra-day, and balancing markets', Energies, vol. 19, no. 8, 1929, pp. 1-39. https://doi.org/10.3390/en19081929
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