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1. Realistic simulations of the July 1, 2011 severe wind event over the Buffalo Ridge Wind Farm: Realistic simulations of a severe wind event over a wind farm

   https://doi.org/10.1002/we.2122  

   Hawbecker, Patrick ; Basu, Sukanta ; Manuel, Lance ( November 2017 , Wind Energy)
2. Prediction of Wind Speed, Potential Wind Power, and the Associated Uncertainties for Offshore Wind Farm Using Deep Learning

   https://doi.org/10.1115/POWER2020-16557  

   Choe, Do-Eun ; Talor, Gary ; Kim, Changkyu ( January 2020 , ASME 2020 Power Conference collocated with the 2020 International Conference on Nuclear Engineering)

   Floating offshore wind turbines hold great potential for future solutions to the growing demand for renewable energy production. Thereafter, the prediction of the offshore wind power generation became critical in locating and designing wind farms and turbines. The purpose of this research is to improve the prediction of the offshore wind power generation by the prediction of local wind speed using a Deep Learning technique. In this paper, the future local wind speed is predicted based on the historical weather data collected from National Oceanic and Atmospheric Administration. Then, the prediction of the wind power generation is performed usingmore »the traditional methods using the future wind speed data predicted using Deep Learning. The network layers are designed using both Long Short-Term Memory (LSTM) and Bi-directional LSTM (BLSTM), known to be effective on capturing long-term time-dependency. The selected networks are fine-tuned, trained using a part of the weather data, and tested using the other part of the data. To evaluate the performance of the networks, a parameter study has been performed to find the relationships among: length of the training data, prediction accuracy, and length of the future prediction that is reliable given desired prediction accuracy and the training size.

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3. Distribution of mean kinetic energy around an isolated wind turbine and a characteristic wind turbine of a very large wind farm

   https://doi.org/10.1103/PhysRevFluids.1.074402  

   Cortina, Gerard ; Calaf, Marc ; Cal, Raúl Bayoán ( November 2016 , Physical Review Fluids)
4. “Wind Theft” from Onshore Wind Turbine Arrays: Sensitivity to Wind Farm Parameterization and Resolution

   https://doi.org/10.1175/JAMC-D-19-0235.1  

   Pryor, Sara C. ; Shepherd, Tristan J. ; Volker, Patrick J. H. ; Hahmann, Andrea N. ; Barthelmie, Rebecca J. ( January 2020 , Journal of Applied Meteorology and Climatology)

   High-resolution simulations are conducted with the Weather Research and Forecasting Model to evaluate the sensitivity of wake effects and power production from two wind farm parameterizations [the commonly used Fitch scheme and the more recently developed Explicit Wake Parameterization (EWP)] to the resolution at which the model is applied. The simulations are conducted for a 9-month period for a domain encompassing much of the U.S. Midwest. The two horizontal resolutions considered are 4 km × 4 km and 2 km × 2 km grid cells, and the two vertical discretizations employ either 41 or 57 vertical layers (with themore »latter having double the number in the lowest 1 km). Higher wind speeds are observed close to the wind turbine hub height when a larger number of vertical layers are employed (12 in the lowest 200 m vs 6), which contributes to higher power production from both wind farm schemes. Differences in gross capacity factors for wind turbine power production from the two wind farm parameterizations and with resolution are most strongly manifest under stable conditions (i.e., at night). The spatial extent of wind farm wakes when defined as the area affected by velocity deficits near to wind turbine hub heights in excess of 2% of the simulation without wind turbines is considerably larger in simulations with the Fitch scheme. This spatial extent is generally reduced by increasing the horizontal resolution and/or increasing the number of vertical levels. These results have important applications to projections of expected annual energy production from new wind turbine arrays constructed in the wind shadow from existing wind farms.

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5. Atmospheric scattering effects on ground-based measurements of thermospheric vertical wind, horizontal wind, and temperature: SCATTERING EFFECTS ON WIND MEASUREMENTS

   https://doi.org/10.1002/2017JA023942  

   Harding, Brian. J. ; Makela, Jonathan J. ; Qin, Jianqi ; Fisher, Daniel J. ; Martinis, Carlos R. ; Noto, John ; Wrasse, Cristiano M. ( July 2017 , Journal of Geophysical Research: Space Physics)