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The South Australia region of the Australian National Electricity Market (NEM) displays some of the highest levels of price volatility observed in modern electricity markets. This paper outlines an approach to probabilistic forecasting…

Machine Learning · Computer Science 2023-12-13 Cameron Cornell , Nam Trong Dinh , S. Ali Pourmousavi

We examine the problem of modeling and forecasting European Day-Ahead and Month-Ahead natural gas prices. For this, we propose two distinct probabilistic models that can be utilized in risk- and portfolio management. We use daily pricing…

Applications · Statistics 2023-02-13 Jonathan Berrisch , Florian Ziel

We use three ensemble members of the EURO-CORDEX project and their data on surface wind speeds, solar irradiation as well as water runoff with a spatial resolution of 12 km and a temporal resolution of 3 hours under representative…

Physics and Society · Physics 2018-11-09 Markus Schlott , Alexander Kies , Tom Brown , Stefan Schramm , Martin Greiner

We present a new model for the electricity spot price dynamics, which is able to capture seasonality, low-frequency dynamics and the extreme spikes in the market. Instead of the usual purely deterministic trend we introduce a non-stationary…

Applications · Statistics 2012-01-06 Fred Espen Benth , Claudia Klüppelberg , Gernot Müller , Linda Vos

In electricity markets, locational marginal price (LMP) forecasting is particularly important for market participants in making reasonable bidding strategies, managing potential trading risks, and supporting efficient system planning and…

Machine Learning · Computer Science 2021-07-28 Yuyun Yang , Zhenfei Tan , Haitao Yang , Guangchun Ruan , Haiwang Zhong

Energy system models require a large amount of technical and economic data, the quality of which significantly influences the reliability of the results. Some of the variables on the important data source ENTSO-E transparency platform, such…

General Economics · Economics 2023-02-23 Thomas Möbius , Mira Watermeyer , Oliver Grothe , Felix Müsgens

The increase of renewables in the grid and the volatility of the load create uncertainties in the day-ahead prices of electricity markets. Adaptive robust optimization (ARO) and stochastic optimization have been used to make commitment and…

Optimization and Control · Mathematics 2023-09-18 Dimitris Bertsimas , Angelos G. Koulouras

Accurate price predictions are essential for market participants in order to optimize their operational schedules and bidding strategies, especially in the current context where electricity prices become more volatile and less predictable…

Computational Engineering, Finance, and Science · Computer Science 2025-09-26 Naga Venkata Sai Jitin Jami , Juraj Kardoš , Olaf Schenk , Harald Köstler

The implementation of electricity markets based on locational marginal pricing in a multi-settlement process has allowed wholesale competition, with pricing mechanisms that incentivize the optimal allocation of generation, transmission, and…

Systems and Control · Electrical Eng. & Systems 2020-12-29 Veronica R. Bosquezfoti , Andrew L. Liu

In contemporary power systems, energy consumption prediction plays a crucial role in maintaining grid stability and resource allocation enabling power companies to minimize energy waste and avoid overloading the grid. While there are…

Machine Learning · Computer Science 2025-03-20 Aayam Bansal , Keertan Balaji , Zeus Lalani

Climate and energy policy targets of the European Commission aim to make Europe the first climate-neutral continent by 2050. For low-carbon and net-neutral energy systems primarily based on variable renewable power generation, issues…

General Economics · Economics 2025-06-06 Diana Böttger , Philipp Härtel

The United States' power market is featured by the lack of judicial power at the federal level. The market thus provides a unique testing environment for the market organization structure. At the same time, the econometric modeling and…

Econometrics · Economics 2018-06-13 Chelsea Sun

Calibration sample selection and forecast combination are two simple yet powerful tools used in forecasting. They can be combined with a variety of models to significantly improve prediction accuracy, at the same time offering easy…

Applications · Statistics 2025-10-20 Tomasz Serafin , Weronika Nitka

Prediction of stock prices plays a significant role in aiding the decision-making of investors. Considering its importance, a growing literature has emerged trying to forecast stock prices with improved accuracy. In this study, we introduce…

Statistical Finance · Quantitative Finance 2023-11-14 Md Sabbirul Haque , Md Shahedul Amin , Jonayet Miah , Duc Minh Cao , Ashiqul Haque Ahmed

Currently the UK Electric market is guided by load (demand) forecasts published every thirty minutes by the regulator. A key factor in predicting demand is weather conditions, with forecasts published every hour. We present HYENA: a hybrid…

Machine Learning · Computer Science 2022-05-24 Maria Eleni Athanasopoulou , Justina Deveikyte , Alan Mosca , Ilaria Peri , Alessandro Provetti

Structural transformation, the shift from agrarian economies to more diversified industrial and service-based systems, is a key driver of economic development. However, in low- and middle-income countries (LMICs), data scarcity and…

Applications · Statistics 2025-10-02 Ronald Katende

Power systems face increasing challenges in maintaining resource adequacy due to lower operating margins, rising renewable energy uncertainty, and demand variability. Forecasting the probability distribution of peak demand on shorter…

Systems and Control · Electrical Eng. & Systems 2025-10-28 Buyi Yu , Wenyuan Tang

In an electric power system, demand fluctuations may result in significant ancillary cost to suppliers. Furthermore, in the near future, deep penetration of volatile renewable electricity generation is expected to exacerbate the variability…

Optimization and Control · Mathematics 2012-07-13 John N. Tsitsiklis , Yunjian Xu

Middle-term horizon (months to a year) power consumption prediction is a main challenge in the energy sector, in particular when probabilistic forecasting is considered. We propose a new modelling approach that incorporates trend,…

Methodology · Statistics 2022-01-04 Michele Azzone , Roberto Baviera

This working paper presents a comprehensive study on the development and analysis of various electricity market models, focusing on continuous, discrete, and fractional-order approaches. The continuous model captures the ongoing…

Optimization and Control · Mathematics 2024-07-29 Ioannis Dassios