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High Durability Sliding TENG with Enhanced Output Achieved by Capturing Multiple Region Charges for Harvesting Wind Energy. [PDF]
Nanomicro LettHe W +7 more
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Enhancing stability in renewable energy transmission using multi-terminal HVDC systems with grid-forming controls for offshore and onshore wind integration. [PDF]
Sci RepShufian A +3 more
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Sensor Fusion-Based Machine Learning Algorithms for Meteorological Conditions Nowcasting in Port Scenarios. [PDF]
Sensors (Basel)Haruna M +4 more
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Expert elicitation survey predicts 37% to 49% declines in wind energy costs by 2050
Nature Energy, 2021 Ryan Wiser, Joseph Rand, Joachim Seel
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Climate change impacts on wind power generation
Nature Reviews Earth & Environment, 2020 Sara C Pryor +2 more
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Short-Term Wind Speed Interval Prediction Based on Ensemble GRU Model
IEEE Transactions on Sustainable Energy, 2020Wind speed interval prediction is playing an increasingly important role in wind power production. The intermittent and fluctuant characteristics of wind power make high-quality prediction interval challenging.
Chaoshun Li +4 more
semanticscholar +1 more source
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2007
From its rebirth in the early 1980s, the rate of development of wind energy has been dramatic. Today, other than hydropower, it is the most important of the renewable sources of power. The UK Government and the EU Commission have adopted targets for renewable energy generation of 10 and 12% of consumption, respectively. Much of this, by necessity, must
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From its rebirth in the early 1980s, the rate of development of wind energy has been dramatic. Today, other than hydropower, it is the most important of the renewable sources of power. The UK Government and the EU Commission have adopted targets for renewable energy generation of 10 and 12% of consumption, respectively. Much of this, by necessity, must
openaire +3 more sources
Spatio-Temporal Graph Deep Neural Network for Short-Term Wind Speed Forecasting
IEEE Transactions on Sustainable Energy, 2019Wind speed forecasting is still a challenge due to the stochastic and highly varying characteristics of wind. In this paper, a graph deep learning model is proposed to learn the powerful spatio-temporal features from the wind speed and wind direction ...
Mahdi Khodayar, Jianhui Wang
semanticscholar +1 more source