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Electricity generated from renewable energy sources has been established as an efficient remedy for both energy shortages and the environmental pollution stemming from conventional energy production methods. Solar and wind power are two of…

Machine Learning · Computer Science 2025-01-06 Charalampos Symeonidis , Nikos Nikolaidis

Wind power forecasting (WPF), as a significant research topic within renewable energy, plays a crucial role in enhancing the security, stability, and economic operation of power grids. However, due to the high stochasticity of…

Machine Learning · Computer Science 2025-04-16 Mingyi Zhu , Zhaoxin Li , Qiao Lin , Li Ding

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

Wind power is attracting increasing attention around the world due to its renewable, pollution-free, and other advantages. However, safely and stably integrating the high permeability intermittent power energy into electric power systems…

Machine Learning · Computer Science 2023-05-31 Yang Zhang , Lingbo Liu , Xinyu Xiong , Guanbin Li , Guoli Wang , Liang Lin

The main objective of this study is to propose an enhanced wind power forecasting (EWPF) transformer model for handling power grid operations and boosting power market competition. It helps reliable large-scale integration of wind power…

Systems and Control · Electrical Eng. & Systems 2023-04-24 Md Rasel Sarkar , Sreenatha G. Anavatti , Tanmoy Dam , Mahardhika Pratama , Berlian Al Kindhi

The increasing severity of climate change necessitates an urgent transition to renewable energy sources, making the large-scale adoption of wind energy crucial for mitigating environmental impact. However, the inherent uncertainty of wind…

Machine Learning · Computer Science 2024-10-18 Chongyang Wan , Shunbo Lei , Yuan Luo

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

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

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

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

Wind is one kind of high-efficient, environmentally-friendly and cost-effective energy source. Wind power, as one of the largest renewable energy in the world, has been playing a more and more important role in supplying electricity. Though…

Computational Engineering, Finance, and Science · Computer Science 2024-01-02 Wei Fan , Yanjie Fu , Shun Zheng , Jiang Bian , Yuanchun Zhou , Hui Xiong

Recent developments related to the energy transition pose particular challenges for distribution grids. Hence, precise load forecasts become more and more important for effective grid management. Novel modeling approaches such as the…

Machine Learning · Computer Science 2023-05-19 Elena Giacomazzi , Felix Haag , Konstantin Hopf

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

Wind power prediction is of vital importance in wind power utilization. There have been a lot of researches based on the time series of the wind power or speed, but In fact, these time series cannot express the temporal and spatial changes…

Machine Learning · Computer Science 2018-07-19 Ruiguo Yu , Zhiqiang Liu , Xuewei Li , Wenhuan Lu , Mei Yu , Jianrong Wang , Bin Li

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 prediction of wind speed and power is vital for enhancing the efficiency of wind energy systems. Numerous solutions have been implemented to date, demonstrating their potential to improve forecasting. Among these, deep learning is…

Machine Learning · Computer Science 2024-01-17 Mulomba Mukendi Christian , Yun Seon Kim , Hyebong Choi , Jaeyoung Lee , SongHee You

Integrated wind-solar-wave marine energy systems hold broad promise for supplying clean electricity in offshore and coastal regions. By leveraging the spatiotemporal complementarity of multiple resources, such systems can effectively…

Machine Learning · Computer Science 2025-10-01 Baoyi Xie , Shuiling Shi , Wenqi Liu

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
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