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Accurate renewable energy production forecasting has become a priority as the share of intermittent energy sources on the grid increases. Recent work has shown that convolutional deep learning models can successfully be applied to forecast…

Image and Video Processing · Electrical Eng. & Systems 2022-01-24 Sebastian Bosma , Negar Nazari

Wind energy is a widely distributed, renewable, and environmentally friendly energy source that plays a crucial role in mitigating global warming and addressing energy shortages. Nevertheless, wind power generation is characterized by…

Machine Learning · Computer Science 2023-09-06 Meiyu Jiang , Jun Shen , Xuetao Jiang , Lihui Luo , Rui Zhou , Qingguo Zhou

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…

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

Accurate forecasting of renewable energy generation is fundamental to enhancing the dynamic performance of modern power grids, especially under high renewable penetration. This paper presents Channel-Time Patch Time-Series Transformer…

Machine Learning · Computer Science 2026-01-23 Kuan Lu , Menghao Huo , Yuxiao Li , Qiang Zhu , Zhenrui Chen

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

Regional solar power forecasting, which involves predicting the total power generation from all rooftop photovoltaic systems in a region holds significant importance for various stakeholders in the energy sector. However, the vast amount of…

Machine Learning · Computer Science 2024-03-05 Maneesha Perera , Julian De Hoog , Kasun Bandara , Damith Senanayake , Saman Halgamuge

Accurate forecasting is critical for reliable power grid operations, particularly as the share of renewable generation, such as wind and solar, continues to grow. Given the inherent uncertainty and variability in renewable generation,…

Applications · Statistics 2025-10-20 Alireza Moradi , Mathieu Tanneau , Reza Zandehshahvar , Pascal Van Hentenryck

Accurate and reliable forecasting of renewable energy generation is crucial for the efficient integration of renewable sources into the power grid. In particular, probabilistic forecasts are becoming essential for managing the intrinsic…

Applications · Statistics 2025-02-12 Alireza Moradi , Mathieu Tanneau , Reza Zandehshahvar , Pascal Van Hentenryck

Wind power is playing an increasingly important role in electricity markets. However, it's inherent variability and uncertainty cause operational challenges and costs as more operating reserves are needed to maintain system reliability.…

Optimization and Control · Mathematics 2016-03-01 Yishen Wang , Zhi Zhou , Cong Liu , Audun Botterud

Accurate prediction of non-dispatchable renewable energy sources is essential for grid stability and price prediction. Regional power supply forecasts are usually indirect through a bottom-up approach of plant-level forecasts, incorporate…

Signal Processing · Electrical Eng. & Systems 2026-02-24 Eloi Lindas , Yannig Goude , Philippe Ciais

Accurate renewable energy forecasting is essential to reduce dependence on fossil fuels and enabling grid decarbonization. However, current approaches fail to effectively integrate the rich spatial context of weather patterns with their…

Machine Learning · Computer Science 2025-11-20 Federico Battini

Power supply from renewable resources is on a global rise where it is forecasted that renewable generation will surpass other types of generation in a foreseeable future. Increased generation from renewable resources, mainly solar and wind,…

Machine Learning · Statistics 2017-06-28 Mohana Alanazi , Mohsen Mahoor , Amin Khodaei

Renewable energy sources, such as wind and solar power, are increasingly being integrated into smart grid systems. However, when compared to traditional energy resources, the unpredictability of renewable energy generation poses significant…

Systems and Control · Electrical Eng. & Systems 2023-03-01 Arman Ghasemi , Amin Shojaeighadikolaei , Morteza Hashemi

The objective of the GreenPAD project is to use green energy (wind, solar and biomass) for powering data-centers that are used to run HPC jobs. As a part of this it is important to predict the Renewable (Wind) energy for efficient…

Machine Learning · Computer Science 2014-02-27 Ankur Sahai

Renewable energy sources, especially wind energy, are to play a larger role in providing electricity to industrial and domestic consumers. This is already the case today for a number of European countries, closely followed by the US and…

Methodology · Statistics 2013-12-24 Pierre Pinson

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

Generation and load balance is required in the economic scheduling of generating units in the smart grid. Variable energy generations, particularly from wind and solar energy resources, are witnessing a rapid boost, and, it is anticipated…

Machine Learning · Computer Science 2017-04-07 Mohamed Abuella , Badrul Chowdhury

As renewable distributed energy resources (DERs) penetrate the power grid at an accelerating speed, it is essential for operators to have accurate solar photovoltaic (PV) energy forecasting for efficient operations and planning. Generally,…

Machine Learning · Statistics 2017-09-26 Hossein Sangrody , Morteza Sarailoo , Ning Zhou , Nhu Tran , Mahdi Motalleb , Elham Foruzan

By the end of 2021, the renewable energy share of the global electricity capacity reached 38.3% and the new installations are dominated by wind and solar energy, showing global increases of 12.7% and 18.5%, respectively. However, both wind…

Machine Learning · Statistics 2024-09-18 Ágnes Baran , Sándor Baran
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