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Accurate and reliable prediction of Photovoltaic (PV) power output is critical to electricity grid stability and power dispatching capabilities. However, Photovoltaic (PV) power generation is highly volatile and unstable due to different…

Machine Learning · Computer Science 2022-10-04 Sarah Almaghrabi , Mashud Rana , Margaret Hamilton , Mohammad Saiedur Rahaman

The output of solar power generation is significantly dependent on the available solar radiation. Thus, with the proliferation of PV generation in the modern power grid, forecasting of solar irradiance is vital for proper operation of the…

Applications · Statistics 2022-09-05 Kwasi Opoku , Svetlana Lucemo , Qun Zhou Sun , Aleksandar Dimitrovski

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…

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

Due to the stochastic nature of photovoltaic (PV) power generation, there is high demand for forecasting PV output to better integrate PV generation into power grids. Systematic knowledge regarding the factors influencing forecast accuracy…

Applications · Statistics 2021-11-04 Thi Ngoc Nguyen , Felix Müsgens

Renewable Energies (RES) penetration is progressing rapidly: in France, the installed capacity of photovoltaic (PV) power rose from 26MW in 2007 to 8GW in 2017 [1]. Power generated by PV plants being highly dependent on variable weather…

Applications · Statistics 2019-10-15 Kevin Bellinguer , Robin Girard , Guillaume Bontron , Georges Kariniotakis

Several energy management applications rely on accurate photovoltaic generation forecasts. Common metrics like mean absolute error or root-mean-square error, omit error-distribution details needed for stochastic optimization. In addition,…

Machine Learning · Computer Science 2026-03-05 Philipp Danner , Hermann de Meer

While power systems research relies on the availability of real-world network datasets, data owners (e.g., system operators) are hesitant to share data due to security and privacy risks. To control these risks, we develop privacy-preserving…

Cryptography and Security · Computer Science 2023-03-21 Vladimir Dvorkin , Audun Botterud

Given the advancements in data-driven modeling for complex engineering and scientific applications, this work utilizes a data-driven predictive control method, namely subspace predictive control, to coordinate hybrid power plant components…

Systems and Control · Electrical Eng. & Systems 2025-02-20 Manavendra Desai , Himanshu Sharma , Sayak Mukherjee , Sonja Glavaski

Wind energy plays an increasing role in the supply of energy world-wide. The energy output of a wind farm is highly dependent on the weather condition present at the wind farm. If the output can be predicted more accurately, energy…

Artificial Intelligence · Computer Science 2011-09-12 Katya Vladislavleva , Tobias Friedrich , Frank Neumann , Markus Wagner

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…

Electricity is difficult to store, except at prohibitive cost, and therefore the balance between generation and load must be maintained at all times. Electricity is traditionally managed by anticipating demand and intermittent production…

Machine Learning · Computer Science 2024-09-26 Julie Keisler , Margaux Bregere

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 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

Ahead-of-time forecasting of the output power of power plants is essential for the stability of the electricity grid and ensuring uninterrupted service. However, forecasting renewable energy sources is difficult due to the chaotic behavior…

Computer Vision and Pattern Recognition · Computer Science 2023-10-27 Anas Al-lahham , Obaidah Theeb , Khaled Elalem , Tariq A. Alshawi , Saleh A. Alshebeili

Large-scale integration of photovoltaics (PV) into electricity grids is challenged by the intermittent nature of solar power. Sky-image-based solar forecasting using deep learning has been recognized as a promising approach to predicting…

Computer Vision and Pattern Recognition · Computer Science 2022-07-05 Yuhao Nie , Xiatong Li , Andea Scott , Yuchi Sun , Vignesh Venugopal , Adam Brandt

The prediction of electrical power in combined cycle power plants is a key challenge in the electrical power and energy systems field. This power output can vary depending on environmental variables, such as temperature, pressure, and…

Signal Processing · Electrical Eng. & Systems 2019-08-06 Jesus L. Lobo , Igor Ballesteros , Izaskun Oregi , Javier Del Ser

With the recent interest in net-zero sustainability for commercial buildings, integration of photovoltaic (PV) assets becomes even more important. This integration remains a challenge due to high solar variability and uncertainty in the…

Systems and Control · Computer Science 2018-08-28 Chaitanya Poolla , Abraham K. Ishihara

The increasing penetration level of energy generation from renewable sources is demanding for more accurate and reliable forecasting tools to support classic power grid operations (e.g., unit commitment, electricity market clearing or…

Machine Learning · Computer Science 2020-07-17 Michela Moschella , Mauro Tucci , Emanuele Crisostomi , Alessandro Betti

In-situ measurements of the solar wind, a turbulent and anisotropic plasma flow originating at the Sun, are mostly carried out by single spacecraft, resulting in one-dimensional time series. The conversion of these measurements to the…

Solar and Stellar Astrophysics · Physics 2024-05-22 Norbert Magyar , Jaye Verniero , Adam Szabo , Jiyuan Zhang , Tom Van Doorsselaere