English
Related papers

Related papers: Adaptive probabilistic forecasting of French elect…

200 papers

Probabilistic electricity price forecasting (PEPF) is subject of increasing interest, following the demand for proper quantification of prediction uncertainty, to support the operation in complex power markets with increasing share of…

Machine Learning · Computer Science 2024-06-11 Alessandro Brusaferri , Andrea Ballarino , Luigi Grossi , Fabrizio Laurini

Electricity price forecasting (EPF) is a branch of forecasting on the interface of electrical engineering, statistics, computer science, and finance, which focuses on predicting prices in wholesale electricity markets for a whole spectrum…

Statistical Finance · Quantitative Finance 2022-04-26 Arkadiusz Jędrzejewski , Jesus Lago , Grzegorz Marcjasz , Rafał Weron

Large-scale renewable energy deployment introduces pronounced volatility into the electricity system, turning grid operation into a complex stochastic optimization problem. Accurate electricity price forecasting (EPF) is essential not only…

Machine Learning · Computer Science 2026-04-17 Jan Niklas Lettner , Hadeer El Ashhab , Veit Hagenmeyer , Benjamin Schäfer

Probabilistic electricity price forecasting (PEPF) is vital for short-term electricity markets, yet the multivariate nature of day-ahead prices - spanning 24 consecutive hours - remains underexplored. At the same time, real-time…

Machine Learning · Statistics 2026-04-27 Simon Hirsch

The integration of renewable energy into electricity markets poses significant challenges to price stability and increases the complexity of market operations. Accurate and reliable electricity price forecasting is crucial for effective…

Machine Learning · Computer Science 2025-02-10 Ciaran O'Connor , Mohamed Bahloul , Roberto Rossi , Steven Prestwich , Andrea Visentin

Forecasting electricity prices is a challenging task and an active area of research since the 1990s and the deregulation of the traditionally monopolistic and government-controlled power sectors. Although it aims at predicting both spot and…

Statistical Finance · Quantitative Finance 2025-07-23 Katarzyna Maciejowska , Bartosz Uniejewski , Rafał Weron

Electricity price forecasting has become a critical tool for decision-making in energy markets, particularly as the increasing penetration of renewable energy introduces greater volatility and uncertainty. Historically, research in this…

Statistical Finance · Quantitative Finance 2025-11-11 Ciaran O'Connor , Mohamed Bahloul , Steven Prestwich , Andrea Visentin

Accurate electricity price forecasting (EPF) is crucial for effective decision-making in power trading on the spot market. While recent advances in generative artificial intelligence (GenAI) and pre-trained large language models (LLMs) have…

Machine Learning · Computer Science 2025-08-21 Timothée Hornek Amir Sartipi , Igor Tchappi , Gilbert Fridgen

Electricity price forecasting (EPF) plays a critical role in power system operation and market decision making. While existing review studies have provided valuable insights into forecasting horizons, market mechanisms, and evaluation…

Computational Finance · Quantitative Finance 2026-05-13 Runyao Yu , Derek W. Bunn , Julia Lin , Jochen Stiasny , Fabian Leimgruber , Tara Esterl , Yuchen Tao , Lianlian Qi , Yujie Chen , Wentao Wang , Jochen L. Cremer

Electricity market price predictions enable energy market participants to shape their consumption or supply while meeting their economic and environmental objectives. By utilizing the basic properties of the supply-demand matching process…

Applications · Statistics 2019-06-11 Ana Radovanovic , Tommaso Nesti , Bokan Chen

Electricity price forecasting (EPF) is essential for energy markets stakeholders (e.g. grid operators, energy traders, policymakers) but remains challenging due to the inherent volatility and nonlinearity of price signals. Traditional…

Artificial Intelligence · Computer Science 2026-02-06 Kritchanat Ponyuenyong , Pengyu Tu , Jia Wei Tan , Wei Soon Cheong , Jamie Ng Suat Ling , Lianlian Jiang

The Optimal Power Flow (OPF) problem is pivotal for power system operations, guiding generator output and power distribution to meet demand at minimized costs, while adhering to physical and engineering constraints. The integration of…

Machine Learning · Computer Science 2023-11-27 Chen Li , Alexander Kies , Kai Zhou , Markus Schlott , Omar El Sayed , Mariia Bilousova , Horst Stoecker

Accurate electricity price forecasting (EPF) is increasingly difficult in markets characterised by extreme volatility, frequent price spikes, and rapid structural shifts. Deep learning (DL) has been increasingly adopted in EPF due to its…

Machine Learning · Computer Science 2026-02-16 Mohammed Osman Gani , Zhipeng He , Chun Ouyang , Sara Khalifa

The recent energy crisis starting in 2021 led to record-high gas, coal, carbon and power prices, with electricity reaching up to 40 times the pre-crisis average. This had dramatic consequences for operational and risk management prompting…

Applications · Statistics 2024-08-27 Paul Ghelasi , Florian Ziel

Accurate prediction of electricity prices plays an essential role in the electricity market. To reflect the uncertainty of electricity prices, price intervals are predicted. This paper proposes a novel prediction interval construction…

Machine Learning · Computer Science 2025-01-15 Xin Lu

This paper presents a novel approach to electricity price forecasting (EPF) using a pure Transformer model. As opposed to other alternatives, no other recurrent network is used in combination to the attention mechanism. Hence, showing that…

Machine Learning · Computer Science 2025-09-11 Oscar Llorente , Jose Portela

Electricity price forecasting is a critical tool for the efficient operation of power systems and for supporting informed decision-making by market participants. This paper explores a novel methodology aimed at improving the accuracy of…

Applications · Statistics 2025-01-13 Bartosz Uniejewski , Florian Ziel

Electricity load forecasting is a necessary capability for power system operators and electricity market participants. The proliferation of local generation, demand response, and electrification of heat and transport are changing the…

Motivated by the increasing integration among electricity markets, in this paper we propose two different methods to incorporate market integration in electricity price forecasting and to improve the predictive performance. First, we…

Statistical Finance · Quantitative Finance 2017-12-08 Jesus Lago , Fjo De Ridder , Peter Vrancx , Bart De Schutter

The accurate prediction of short-term electricity prices is vital for effective trading strategies, power plant scheduling, profit maximisation and efficient system operation. However, uncertainties in supply and demand make such…

Econometrics · Economics 2023-04-20 Mira Watermeyer , Thomas Möbius , Oliver Grothe , Felix Müsgens
‹ Prev 1 2 3 10 Next ›