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Ambitious decarbonisation targets are rapidly increasing the commission of new offshore wind farms. For these newly commissioned plants to run, accurate power forecasts are needed from the onset. These allow grid stability, good reserve…

Machine Learning · Computer Science 2026-04-27 Dominic Weisser , Chloé Hashimoto-Cullen , Benjamin Guedj

In the last decades wind power became the second largest energy source in the EU covering 16% of its electricity demand. However, due to its volatility, accurate short range wind power predictions are required for successful integration of…

Applications · Statistics 2022-06-22 Sándor Baran , Ágnes Baran

In this paper we propose a framework for automated forecasting of energy-related time series using open access data from European Network of Transmission System Operators for Electricity (ENTSO-E). The framework provides forecasts for…

Applications · Statistics 2016-11-17 Gergo Barta , Gabor Nagy , Gabor Simon , Gyozo Papp

This work presents the evolution of a solution for predictive maintenance to a Big Data environment. The proposed adaptation aims for predicting failures on wind turbines using a data-driven solution deployed in the cloud and which is…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-09-22 Mikel Canizo , Enrique Onieva , Angel Conde , Santiago Charramendieta , Salvador Trujillo

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

The integration of large-scale wind farms and large-scale charging stations for electric vehicles with the electricity grids necessitate energy storage support for both technologies. Matching the energy variability of the wind farms with…

Signal Processing · Electrical Eng. & Systems 2020-04-28 Fuad Noman , Ammar Al-Kahtani , Vassilios Agelidis , Sieh Kiong Tiong

To cater the rapidly growing demand for electricity leading to the integration of renewable energy sources in power system. Due to intermittent nature of renewables, it also brings challenges for research community during the planning and…

Systems and Control · Electrical Eng. & Systems 2021-05-14 Rustam Kumar

Wind power and other forms of renewable energy sources play an ever more important role in the energy supply of today's power grids. Forecasting renewable energy sources has therefore become essential in balancing the power grid. While a…

Machine Learning · Computer Science 2022-02-18 Nina Effenberger , Nicole Ludwig

Tidal energy is one of the key components in increasing the penetration of renewable energy. High tidal energy penetration into the electrical grid depends on accurate tidal current speed forecasting. Model inaccuracies hinder forecast…

Machine Learning · Computer Science 2026-03-03 Tengfei Cheng , Yangdi Huang , Ling Xiao , Yunxuan Dong

The future energy system will largely depend on volatile renewable energy sources and temperature-dependent loads, which makes the weather a central influencing factor. This article presents a novel approach for simulating weather scenarios…

Systems and Control · Electrical Eng. & Systems 2024-05-31 Jan Peper , David Kröger , Jonathan Kipp , Florian Ziel , Christian Rehtanz

The growing penetration of intermittent, renewable generation in US power grids, especially wind and solar generation, results in increased operational uncertainty. In that context, accurate forecasts are critical, especially for wind…

Wind power forecasting is essential to power system operation and electricity markets. As abundant data became available thanks to the deployment of measurement infrastructures and the democratization of meteorological modelling, extensive…

Applications · Statistics 2023-11-30 Honglin Wen , Pierre Pinson , Jie Gu , Zhijian Jin

Energy (load, wind, photovoltaic) forecasting is significant in the power industry as it can provide a reference for subsequent tasks such as power grid dispatch, thus bringing huge economic benefits. However, there are many differences…

Machine Learning · Computer Science 2024-10-07 Zhixian Wang , Qingsong Wen , Chaoli Zhang , Liang Sun , Leandro Von Krannichfeldt , Shirui Pan , Yi Wang

In the wind energy industry, it is of great importance to develop models that accurately forecast the power output of a wind turbine, as such predictions are used for wind farm location assessment or power pricing and bidding, monitoring,…

Applications · Statistics 2022-07-13 Sándor Kolumbán , Stella Kapodistria , Nazanin Nooraee

Energy forecasting is pivotal in energy systems, by providing fundamentals for operation, with different horizons and resolutions. Though energy forecasting has been widely studied for capturing temporal information, very few works…

Signal Processing · Electrical Eng. & Systems 2024-01-12 Chenxi Wang , Pierre Pinson , Yi Wang

Accurate and reliable energy forecasting is essential for power grid operators who strive to minimize extreme forecasting errors that pose significant operational challenges and incur high intra-day trading costs. Incorporating planning…

Computers and Society · Computer Science 2026-05-13 Raffael Theiler , Leandro Von Krannichfeldt , Giovanni Sansavini , Michael F. Howland , Olga Fink

Wind energy resource assessment typically requires numerical models, but such models are too computationally intensive to consider multi-year timescales. Increasingly, unsupervised machine learning techniques are used to identify a small…

Machine Learning · Statistics 2023-02-14 Mariana C A Clare , Simon C Warder , Robert Neal , B Bhaskaran , Matthew D Piggott

The prediction of near surface wind speed is becoming increasingly vital for the operation of electrical energy grids as the capacity of installed wind power grows. The majority of predictive wind speed modeling has focused on point-based…

Machine Learning · Computer Science 2017-12-15 Jianan Cao , David J. Farnham , Upmanu Lall

Short-term wind speed prediction is essential for economical wind power utilization. The real-world wind speed data is typically intermittent and fluctuating, presenting great challenges to existing shallow models. In this paper, we present…

Machine Learning · Computer Science 2023-05-08 Hailong Shu

The growth of wind generation capacities in the past decades has shown that wind energy can contribute to the energy transition in many parts of the world. Being highly variable and complex to model, the quantification of the…

Signal Processing · Electrical Eng. & Systems 2022-07-19 Federico Amato , Fabian Guignard , Alina Walch , Nahid Mohajeri , Jean-Louis Scartezzini , Mikhail Kanevski