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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

Electricity market prices exhibit extreme volatility, nonlinearity, and non-stationarity, making accurate forecasting a significant challenge. While cutting-edge time series foundation models (TSFMs) effectively capture temporal…

Machine Learning · Computer Science 2026-03-10 Yunzhong Qiu , Binzhu Li , Hao Wei , Shenglin Weng , Chen Wang , Zhongyi Pei , Mingsheng Long , Jianmin Wang

Renewable electricity generation has grown significantly across many European power systems, leading to a greener energy mix, but also additional complexity in balancing electricity supply and demand. Unexpected differences between…

Systems and Control · Electrical Eng. & Systems 2026-05-19 Arnaud Verstraeten , Maria Margarida Mascarenhas , Hussain Kazmi

The availability of historical data related to electricity day-ahead prices and to the underlying price formation process is limited. In addition, the electricity market in Europe is facing a rapid transformation, which limits the…

Applications · Statistics 2023-06-27 Raffaele Sgarlato

Energy forecasting is vital for grid reliability and operational efficiency. Although recent advances in time series forecasting have led to progress, existing benchmarks remain limited in spatial and temporal scope and lack multi-energy…

Machine Learning · Computer Science 2025-09-09 Chen Shao , Yue Wang , Zhenyi Zhu , Zhanbo Huang , Sebastian Pütz , Benjamin Schäfer , Tobais Käfer , Michael Färber

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) 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

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

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

Energy is a critical driver of modern economic systems. Accurate energy price forecasting plays an important role in supporting decision-making at various levels, from operational purchasing decisions at individual business organizations to…

Machine Learning · Computer Science 2024-11-07 Alexandru-Victor Andrei , Georg Velev , Filip-Mihai Toma , Daniel Traian Pele , Stefan Lessmann

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

The energy transition is well underway in most European countries. It has a growing impact on electric power systems as it dramatically modifies the way electricity is produced. To ensure a safe and smooth transition towards a pan-European…

Physics and Society · Physics 2018-10-17 Laurent Pagnier , Philippe Jacquod

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

As global energy systems transit to clean energy, accurate renewable generation and renewable demand forecasting is imperative for effective grid management. Foundation Models (FMs) can help improve forecasting of renewable generation and…

Systems and Control · Electrical Eng. & Systems 2025-08-01 Md Meftahul Ferdaus , Tanmoy Dam , Md Rasel Sarkar , Moslem Uddin , Sreenatha G. Anavatti

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

This work presents ensemble forecasting of monthly electricity demand using pattern similarity-based forecasting methods (PSFMs). PSFMs applied in this study include $k$-nearest neighbor model, fuzzy neighborhood model, kernel regression…

Machine Learning · Computer Science 2020-04-02 Paweł Pełka , Grzegorz Dudek

Accurately forecasting electricity price volatility is crucial for effective risk management and decision-making. Traditional forecasting models often fall short in capturing the complex, non-linear dynamics of electricity markets,…

Computational Engineering, Finance, and Science · Computer Science 2025-05-20 Haochen Xue , Chenghao Liu , Chong Zhang , Yuxuan Chen , Angxiao Zong , Zhaodong Wu , Yulong Li , Jiayi Liu , Kaiyu Liang , Zhixiang Lu , Ruobing Li , Jionglong Su

Accurate forecasts of electricity prices are crucial for the management of electric power systems and the development of smart applications. European electricity prices have risen substantially and became highly volatile after the Russian…

High-quality wind power forecasting is crucial for the operation of modern power grids. However, prevailing data-driven paradigms either train a site-specific model which cannot generalize to other locations or rely on fine-tuning of…

Machine Learning · Computer Science 2025-09-09 Hang Fan , Yu Shi , Zongliang Fu , Shuo Chen , Wei Wei , Wei Xu , Jian Li

Foundation models (FMs) currently dominate news headlines. They employ advanced deep learning architectures to extract structural information autonomously from vast datasets through self-supervision. The resulting rich representations of…

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