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Accurate prediction of wind ramp events is critical for ensuring the reliability and stability of the power systems with high penetration of wind energy. This paper proposes a classification based approach for estimating the future class of…

Machine Learning · Computer Science 2016-10-18 Saurav Gupta , Nitin Anand Shrivastava , Abbas Khosravi , Bijaya Ketan Panigrahi

Globally, wind energy has lessened the burden on conventional fossil fuel based power generation. Wind resource assessment for onshore and offshore wind farms aids in accurate forecasting and analyzing nature of ramp events. From an…

Signal Processing · Electrical Eng. & Systems 2020-12-01 Harsh S. Dhiman , Dipankar Deb

Authors: Yifan Xu Abstract: Conventional wind power prediction methods often struggle to provide accurate and reliable predictions in the presence of sudden changes in wind speed and power output. To address this challenge, this study…

Machine Learning · Computer Science 2025-02-19 Yifan Xu

Decision support systems are essential for maintaining grid stability in low-carbon power systems, such as wind power plants, by providing real-time alerts to control room operators regarding potential events, including Wind Power Ramp…

The wind power ramp events threaten the power grid safety significantly. To improve the ramp prediction accuracy, a hybrid wavelet deep belief network algorithm with adaptive feature selection (WDBNAFS) is proposed. First, the wind power…

Systems and Control · Electrical Eng. & Systems 2022-02-14 Zhenhao Tang , Qingyu Meng , Shengxian Cao , Yang Li , Zhongha Mu , Xiaoya Pang

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

With the rising costs of conventional sources of energy, the world is moving towards sustainable energy sources including wind energy. Wind turbines consist of several electrical and mechanical components and experience an enormous amount…

Machine Learning · Computer Science 2020-01-13 Joyjit Chatterjee , Nina Dethlefs

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…

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

This letter proposes a data-driven method for estimating the probability of wind ramping events without exploiting the exact probability distribution function (PDF) of wind power. Actual wind data validates the proposed method.

Optimization and Control · Mathematics 2016-03-23 Cheng Wang , Wei Wei , Jianhui Wang , Feng Qiu

Accurate prediction of wind power is essential for the grid integration of this intermittent renewable source and aiding grid planners in forecasting available wind capacity. Spatial differences lead to discrepancies in climatological data…

Machine Learning · Computer Science 2024-05-21 Md Saiful Islam Sajol , Md Shazid Islam , A S M Jahid Hasan , Md Saydur Rahman , Jubair Yusuf

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

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

The energy market relies on forecasting capabilities of both demand and power generation that need to be kept in dynamic balance. Today, when it comes to renewable energy generation, such decisions are increasingly made in a liberalized…

Machine Learning · Computer Science 2022-03-15 Odin Foldvik Eikeland , Finn Dag Hovem , Tom Eirik Olsen , Matteo Chiesa , Filippo Maria Bianchi

Accurate wind speed prediction is crucial for designing and selecting sites for offshore wind farms. This paper investigates the effectiveness of various machine learning models in predicting offshore wind power for a site near the Gulf of…

Signal Processing · Electrical Eng. & Systems 2025-03-19 Linhan Fang , Fan Jiang , Ann Mary Toms , Xingpeng Li

With the fast growth of wind power penetration, power systems need additional flexibility to cope with wind power ramping. Several electricity markets have established requirements for flexible ramping capacity (FRC) reserves. This paper…

Physics and Society · Physics 2017-12-05 Zhiwen Wang , Chen Shen , Feng Liu , Jianhui Wang , Xiangyu Wu

Achieving net zero carbon emissions by 2050 requires the integration of increasing amounts of wind power into power grids. This energy source poses a challenge to system operators due to its variability and uncertainty. Therefore, accurate…

Machine Learning · Computer Science 2024-02-23 Julie Keisler , Etienne Le Naour

Wind power forecasting plays a critical role in modern energy systems, facilitating the integration of renewable energy sources into the power grid. Accurate prediction of wind energy output is essential for managing the inherent…

Machine Learning · Computer Science 2024-12-18 Ali Forootani , Danial Esmaeili Aliabadi , Daniela Thraen

The rapid growth of the wind energy sector underscores the urgent need to optimize turbine operations and ensure effective maintenance through early fault detection systems. While traditional empirical and physics-based models offer…

In recent years, probabilistic forecasts techniques were proposed in research as well as in applications to integrate volatile renewable energy resources into the electrical grid. These techniques allow decision makers to take the…

Machine Learning · Statistics 2024-10-30 Jens Schreiber , Bernhard Sick
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