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In a growing renewable based energy system, accurate and reliable wind power forecasts are crucial for grid stability, balancing supply and demand and market risk management. Even though short-term weather forecasts have been thoroughly…

Machine Learning · Computer Science 2026-04-22 Eloi Lindas , Yannig Goude , Philippe Ciais

We study short-term prediction of wind speed and wind power (every 10 minutes up to 4 hours ahead). Accurate forecasts for these quantities are crucial to mitigate the negative effects of wind farms' intermittent production on energy…

The planning and operation of renewable energy, especially wind power, depend crucially on accurate, timely, and high-resolution weather information. Coarse-grid global numerical weather forecasts are typically downscaled to meet these…

Uncertainty analysis in the form of probabilistic forecasting can provide significant improvements in decision-making processes in the smart power grid for better integrating renewable energies such as wind. Whereas point forecasting…

Machine Learning · Statistics 2018-03-30 Kostas Hatalis , Shalinee Kishore , Katya Scheinberg , Alberto Lamadrid

The paper introduces a new methodology for assessing on-line the prediction risk of short-term wind power forecasts. The first part of this methodology consists in computing confidence intervals with a confidence level defined by the…

Data Analysis, Statistics and Probability · Physics 2023-10-05 Georges Kariniotakis , Pierre Pinson

Short-term probabilistic wind power forecasting can provide critical quantified uncertainty information of wind generation for power system operation and control. As the complicated characteristics of wind power prediction error, it would…

Machine Learning · Computer Science 2017-02-14 You Lin , Ming Yang , Can Wan , Jianhui Wang , Yonghua Song

Renewable energy sources provide a constantly increasing contribution to the total energy production worldwide. However, the power generation from these sources is highly variable due to their dependence on meteorological conditions.…

Applications · Statistics 2019-03-05 Thordis Thorarinsdottir , Anders Løland , Alex Lenkoski

The volatile nature of wind power generation creates challenges in achieving secure power grid operations. It is, therefore, necessary to make accurate wind power prediction and its uncertainty quantification. Wind power forecasting usually…

Applications · Statistics 2020-09-29 Jingxing Wang , Abdullah Alshelahi , Mingdi You , Eunshin Byon , Romesh Saigal

Wind power plays an increasingly significant role in achieving the 2050 Net Zero Strategy. Despite its rapid growth, its inherent variability presents challenges in forecasting. Accurately forecasting wind power generation is one key demand…

Applications · Statistics 2025-05-13 Tao Shen , Jethro Browell , Daniela Castro-Camilo

The share of wind energy in total installed power capacity has grown rapidly in recent years around the world. Producing accurate and reliable forecasts of wind power production, together with a quantification of the uncertainty, is…

Applications · Statistics 2017-04-26 Amanda Lenzi , Ingelin Steinsland , Pierre Pinson

Accurate production forecasts are essential to continue facilitating the integration of renewable energy sources into the power grid. This paper illustrates how to obtain probabilistic day-ahead forecasts of wind power generation via…

Machine Learning · Computer Science 2026-02-16 Max Bruninx , Diederik van Binsbergen , Timothy Verstraeten , Ann Nowé , Jan Helsen

The transition from conventional methods of energy production to renewable energy production necessitates better prediction models of the upcoming supply of renewable energy. In wind power production, error in forecasting production is…

Machine Learning · Computer Science 2021-08-24 Alagappan Swaminathan , Venkatakrishnan Sutharsan , Tamilselvi Selvaraj

Despite the increasing importance of forecasts of renewable energy, current planning studies only address a general estimate of the forecast quality to be expected and selected forecast horizons. However, these estimates allow only a…

Applications · Statistics 2019-06-03 Jens Schreiber , Artjom Buschin , Bernhard Sick

Wind energy is becoming an increasingly crucial component of a sustainable grid, but its inherent variability and limited predictability present challenges for grid operators. The energy sector needs novel forecasting techniques that can…

Applications · Statistics 2023-12-05 Zheng Dong , Hanyu Zhang , Shixiang Zhu , Yao Xie , Pascal Van Hentenryck

Wind farms can be regarded as complex systems that are, on the one hand, coupled to the nonlinear, stochastic characteristics of weather and, on the other hand, strongly influenced by supervisory control mechanisms. One crucial problem in…

Applications · Statistics 2021-01-22 Tobias Braun , Matthias Waechter , Joachim Peinke , Thomas Guhr

Uncertainty analysis in the form of probabilistic forecasting can significantly improve decision making processes in the smart power grid for better integrating renewable energy sources such as wind. Whereas point forecasting provides a…

Machine Learning · Statistics 2017-10-05 Kostas Hatalis , Alberto J. Lamadrid , Katya Scheinberg , Shalinee Kishore

This paper introduces a new approach to quantify the impact of forward propagated demand and weather uncertainty on power system planning and operation models. Recent studies indicate that such sampling uncertainty, originating from demand…

Applications · Statistics 2020-11-17 Adriaan P Hilbers , David J Brayshaw , Axel Gandy

Wind energy plays a critical role in the transition towards renewable energy sources. However, the uncertainty and variability of wind can impede its full potential and the necessary growth of wind power capacity. To mitigate these…

Machine Learning · Computer Science 2026-01-13 Stefan Jonas , Kevin Winter , Bernhard Brodbeck , Angela Meyer

To forecast wind power generation in the scale of years to decades, outputs from climate models are often used. However, one major limitation of the data projected by these models is their coarse temporal resolution - usually not finer than…

Applications · Statistics 2023-09-19 Nina Effenberger , Nicole Ludwig , Rachel H. White

Photovoltaic (PV) power is affected by weather conditions, making the power generated from the PV systems uncertain. Solving this problem would help improve the reliability and cost effectiveness of the grid, and could help reduce reliance…

Machine Learning · Computer Science 2020-10-07 Yahya Al Lawati , Jack Kelly , Dan Stowell
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