Artigos de revistas sobre o tema "Wind farm estimation"
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Celeska, Maja. "EQUIVALENT WIND FARM POWER CURVE ESTIMATION". Journal of Electrical Engineering and Information Technologies 2, n.º 2 (2017): 105–11. http://dx.doi.org/10.51466/jeeit172105c.
Texto completo da fonteCeleska, Maja. "EQUIVALENT WIND FARM POWER CURVE ESTIMATION". Journal of Electrical Engineering and Information Technologies 2, n.º 2 (2017): 105–11. http://dx.doi.org/10.51466/jeeit172105c.
Texto completo da fonteAnnoni, Jennifer, Christopher Bay, Kathryn Johnson, Emiliano Dall'Anese, Eliot Quon, Travis Kemper e Paul Fleming. "Wind direction estimation using SCADA data with consensus-based optimization". Wind Energy Science 4, n.º 2 (20 de junho de 2019): 355–68. http://dx.doi.org/10.5194/wes-4-355-2019.
Texto completo da fonteARINAGA, Shinji, Masaaki SHIBATA, Shigeto HIRAI, Toshiya NANAHARA, Takamitsu SATO e Koji YAMAGUCHI. "Estimation of Fluctuating Output in Wind Farm". Proceedings of the JSME annual meeting 2004.3 (2004): 293–94. http://dx.doi.org/10.1299/jsmemecjo.2004.3.0_293.
Texto completo da fonteBecker, Marcus, Dries Allaerts e Jan-Willem van Wingerden. "Ensemble-Based Flow Field Estimation Using the Dynamic Wind Farm Model FLORIDyn". Energies 15, n.º 22 (16 de novembro de 2022): 8589. http://dx.doi.org/10.3390/en15228589.
Texto completo da fonteMeglic, Antun, e Ranko Goic. "Impact of Time Resolution on Curtailment Losses in Hybrid Wind-Solar PV Plants". Energies 15, n.º 16 (17 de agosto de 2022): 5968. http://dx.doi.org/10.3390/en15165968.
Texto completo da fonteTSUCHIYA, Manabu, Yukinari FUKUMOTO e Takeshi ISHIHARA. "The Wind Observation and Energy Production Estimation for Offshore Wind Farm". Wind Engineers, JAWE 2008, n.º 115 (2008): 119–22. http://dx.doi.org/10.5359/jawe.2008.119.
Texto completo da fonteS, Fredy H. Martínez, César A. Hernández S e Fernando Martínez S. "Multivariate Wind Speed Forecasting with LSTMs for Wind Farm Performance Estimation". International Journal of Engineering and Technology 10, n.º 6 (31 de dezembro de 2018): 1626–32. http://dx.doi.org/10.21817/ijet/2018/v10i6/181006025.
Texto completo da fontePetkovic, Dalibor. "Estimation of wind farm efficiency by ANFIS strategy". Godisnjak Pedagoskog fakulteta u Vranju, n.º 7 (2016): 91–105. http://dx.doi.org/10.5937/gufv1607091p.
Texto completo da fonteFarrell, W., T. Herges, D. Maniaci e K. Brown. "Wake state estimation of downwind turbines using recurrent neural networks for inverse dynamics modelling". Journal of Physics: Conference Series 2265, n.º 3 (1 de maio de 2022): 032094. http://dx.doi.org/10.1088/1742-6596/2265/3/032094.
Texto completo da fonteGrande, Olatz, Josune Cañizo, Itziar Angulo, David Jenn, Laith R. Danoon, David Guerra e David de la Vega. "Simplified Formulae for the Estimation of Offshore Wind Turbines Clutter on Marine Radars". Scientific World Journal 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/982508.
Texto completo da fonteMaheshwari, Priyank, Julien Haize e Maxime Pallud. "Modeling of Blockage and Wake Effect: Comparison with Field data". Journal of Physics: Conference Series 2767, n.º 9 (1 de junho de 2024): 092021. http://dx.doi.org/10.1088/1742-6596/2767/9/092021.
Texto completo da fonteDoekemeijer, Bart M., Sjoerd Boersma, Lucy Y. Pao, Torben Knudsen e Jan-Willem van Wingerden. "Online model calibration for a simplified LES model in pursuit of real-time closed-loop wind farm control". Wind Energy Science 3, n.º 2 (24 de outubro de 2018): 749–65. http://dx.doi.org/10.5194/wes-3-749-2018.
Texto completo da fonteBingöl, Ferhat. "Comparison of Weibull Estimation Methods for Diverse Winds". Advances in Meteorology 2020 (6 de julho de 2020): 1–11. http://dx.doi.org/10.1155/2020/3638423.
Texto completo da fonteFeijóo, Andrés, e Daniel Villanueva. "Contributions to wind farm power estimation considering wind direction-dependent wake effects". Wind Energy 20, n.º 2 (30 de junho de 2016): 221–31. http://dx.doi.org/10.1002/we.2002.
Texto completo da fonteMarti-Puig, Pere, Jose Ángel Hernández, Jordi Solé-Casals e Moises Serra-Serra. "Enhancing Reliability in Wind Turbine Power Curve Estimation". Applied Sciences 14, n.º 6 (15 de março de 2024): 2479. http://dx.doi.org/10.3390/app14062479.
Texto completo da fonteMirzaei, Mahmood, Tuhfe Göçmen, Gregor Giebel, Poul Ejnar Sørensen e Niels K. Poulsen. "Estimation of the Possible Power of a Wind Farm". IFAC Proceedings Volumes 47, n.º 3 (2014): 6782–87. http://dx.doi.org/10.3182/20140824-6-za-1003.02253.
Texto completo da fonteBadger, Jake, Helmut Frank, Andrea N. Hahmann e Gregor Giebel. "Wind-Climate Estimation Based on Mesoscale and Microscale Modeling: Statistical–Dynamical Downscaling for Wind Energy Applications". Journal of Applied Meteorology and Climatology 53, n.º 8 (agosto de 2014): 1901–19. http://dx.doi.org/10.1175/jamc-d-13-0147.1.
Texto completo da fonteKartal, Serkan, Sukanta Basu e Simon J. Watson. "A decision-tree-based measure–correlate–predict approach for peak wind gust estimation from a global reanalysis dataset". Wind Energy Science 8, n.º 10 (16 de outubro de 2023): 1533–51. http://dx.doi.org/10.5194/wes-8-1533-2023.
Texto completo da fonteVelázquez Medina, Sergio, José A. Carta e Ulises Portero Ajenjo. "Performance Sensitivity of a Wind Farm Power Curve Model to Different Signals of the Input Layer of ANNs: Case Studies in the Canary Islands". Complexity 2019 (26 de março de 2019): 1–11. http://dx.doi.org/10.1155/2019/2869149.
Texto completo da fonteRajeevan, A. K., P. V. Shouri e Usha Nair. "ARIMA Based Wind Speed Modeling for Wind Farm Reliability Analysis and Cost Estimation". Journal of Electrical Engineering and Technology 11, n.º 4 (1 de julho de 2016): 869–77. http://dx.doi.org/10.5370/jeet.2016.11.4.869.
Texto completo da fonteLiu, Li Yang, Jun Ji Wu e Shao Liang Meng. "The Application of Wind Speed Numerical Simulation in Wind Power Generation". Applied Mechanics and Materials 380-384 (agosto de 2013): 3370–73. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3370.
Texto completo da fontePaik, Chunhyun, Yongjoo Chung e Young Jin Kim. "Power Curve Modeling of Wind Turbines through Clustering-Based Outlier Elimination". Applied System Innovation 6, n.º 2 (15 de março de 2023): 41. http://dx.doi.org/10.3390/asi6020041.
Texto completo da fonteKelly, Mark, e Hans E. Jørgensen. "Statistical characterization of roughness uncertainty and impact on wind resource estimation". Wind Energy Science 2, n.º 1 (25 de abril de 2017): 189–209. http://dx.doi.org/10.5194/wes-2-189-2017.
Texto completo da fonteJiao, Chunlei, Zhao Pu zhi, Hou bing, Wang Zhen e Cai Yongjun. "Wind Farm Harmonic Impedance Estimation Based on Stochastic Subspace Method". IOP Conference Series: Earth and Environmental Science 371 (13 de dezembro de 2019): 022052. http://dx.doi.org/10.1088/1755-1315/371/2/022052.
Texto completo da fonteLingad, M. V., M. Rodrigues, S. Leonardi e A. Zare. "Three-dimensional stochastic dynamical modeling for wind farm flow estimation". Journal of Physics: Conference Series 2767, n.º 5 (1 de junho de 2024): 052065. http://dx.doi.org/10.1088/1742-6596/2767/5/052065.
Texto completo da fonteChristodoulou, Christos A., Vasiliki Vita, George-Calin Seritan e Lambros Ekonomou. "A Harmony Search Method for the Estimation of the Optimum Number of Wind Turbines in a Wind Farm". Energies 13, n.º 11 (1 de junho de 2020): 2777. http://dx.doi.org/10.3390/en13112777.
Texto completo da fonteBoersma, Sjoerd, Bart Doekemeijer, Mehdi Vali, Johan Meyers e Jan-Willem van Wingerden. "A control-oriented dynamic wind farm model: WFSim". Wind Energy Science 3, n.º 1 (6 de março de 2018): 75–95. http://dx.doi.org/10.5194/wes-3-75-2018.
Texto completo da fonteLuo, Yilan, Deniz Sezer, David Wood, Mingkuan Wu e Hamid Zareipour. "Estimation of the Daily Variability of Aggregate Wind Power Generation in Alberta, Canada". Energies 12, n.º 10 (24 de maio de 2019): 1998. http://dx.doi.org/10.3390/en12101998.
Texto completo da fonteDe Blasis, Riccardo, Giovanni Batista Masala e Filippo Petroni. "A Multivariate High-Order Markov Model for the Income Estimation of a Wind Farm". Energies 14, n.º 2 (12 de janeiro de 2021): 388. http://dx.doi.org/10.3390/en14020388.
Texto completo da fonteSales-Setién, Ester, e Ignacio Peñarrocha-Alós. "Robust estimation and diagnosis of wind turbine pitch misalignments at a wind farm level". Renewable Energy 146 (fevereiro de 2020): 1746–65. http://dx.doi.org/10.1016/j.renene.2019.07.133.
Texto completo da fonteBlondel, Frédéric. "Brief communication: A momentum-conserving superposition method applied to the super-Gaussian wind turbine wake model". Wind Energy Science 8, n.º 2 (8 de fevereiro de 2023): 141–47. http://dx.doi.org/10.5194/wes-8-141-2023.
Texto completo da fonteLoCascio, Michael J., Christopher J. Bay, Majid Bastankhah, Garrett E. Barter, Paul A. Fleming e Luis A. Martínez-Tossas. "FLOW Estimation and Rose Superposition (FLOWERS): an integral approach to engineering wake models". Wind Energy Science 7, n.º 3 (1 de junho de 2022): 1137–51. http://dx.doi.org/10.5194/wes-7-1137-2022.
Texto completo da fonteVollmer, Lukas, Gerald Steinfeld e Martin Kühn. "Transient LES of an offshore wind turbine". Wind Energy Science 2, n.º 2 (8 de dezembro de 2017): 603–14. http://dx.doi.org/10.5194/wes-2-603-2017.
Texto completo da fonteBhatt, Aditya H., Mireille Rodrigues, Federico Bernardoni, Stefano Leonardi e Armin Zare. "Stochastic Dynamical Modeling of Wind Farm Turbulence". Energies 16, n.º 19 (30 de setembro de 2023): 6908. http://dx.doi.org/10.3390/en16196908.
Texto completo da fonteGudmestad, Ove Tobias, e Anja Schnepf. "Design Basis Considerations for the Design of Floating Offshore Wind Turbines". Sustainable Marine Structures 5, n.º 2 (16 de setembro de 2023): 26–34. http://dx.doi.org/10.36956/sms.v5i2.913.
Texto completo da fonteLi, Jing, Ya Di Luo, Yan Sheng Lang, Cheng Long Dou, Yu Zou, Zi Ming Guo, Dong Sheng Wang e Xin Peng Li. "Research of Fine and Robust State Estimation". Advanced Materials Research 1008-1009 (agosto de 2014): 202–6. http://dx.doi.org/10.4028/www.scientific.net/amr.1008-1009.202.
Texto completo da fonteGupta, Deepak, Vikas Kumar, Ishan Ayus, M. Vasudevan e N. Natarajan. "Short-term prediction of wind power density using convolutional LSTM network". FME Transactions 49, n.º 3 (2021): 653–63. http://dx.doi.org/10.5937/fme2103653g.
Texto completo da fonteCañadillas, Beatriz, Richard Foreman, Gerald Steinfeld e Nick Robinson. "Cumulative Interactions between the Global Blockage and Wake Effects as Observed by an Engineering Model and Large-Eddy Simulations". Energies 16, n.º 7 (23 de março de 2023): 2949. http://dx.doi.org/10.3390/en16072949.
Texto completo da fonteRoy, Asish, e Kalyan Chatterjee. "Availability estimation of a multi-state wind farm in fuzzy environment". International Journal of Green Energy 15, n.º 2 (15 de janeiro de 2018): 80–95. http://dx.doi.org/10.1080/15435075.2018.1423977.
Texto completo da fonteJiang, Wang, e Jiping Lu. "Frequency estimation in wind farm integrated systems using artificial neural network". International Journal of Electrical Power & Energy Systems 62 (novembro de 2014): 72–79. http://dx.doi.org/10.1016/j.ijepes.2014.04.027.
Texto completo da fonteHamilton, Nicholas, Dennice Gayme e Raúl Bayoán Cal. "Wind plant controls". Journal of Renewable and Sustainable Energy 14, n.º 6 (novembro de 2022): 060401. http://dx.doi.org/10.1063/5.0133996.
Texto completo da fonteNikolić, Vlastimir, Shahaboddin Shamshirband, Dalibor Petković, Kasra Mohammadi, Žarko Ćojbašić, Torki A. Altameem e Abdullah Gani. "Wind wake influence estimation on energy production of wind farm by adaptive neuro-fuzzy methodology". Energy 80 (fevereiro de 2015): 361–72. http://dx.doi.org/10.1016/j.energy.2014.11.078.
Texto completo da fonteBusse, Przemysław. "Methodological Procedure For Pre-Investment Wind Farm Ornithological Monitoring Based On Collision Risk Estimation". Ring 35, n.º 1 (12 de março de 2014): 3–30. http://dx.doi.org/10.2478/ring-2013-0001.
Texto completo da fonteSantos, Francisco de N., Gregory Duthé, Imad Abdallah, Pierre-Élouan Réthoré, Wout Weijtjens, Eleni Chatzi e Christof Devriendt. "Multivariate prediction on wake-affected wind turbines using graph neural networks". Journal of Physics: Conference Series 2647, n.º 11 (1 de junho de 2024): 112006. http://dx.doi.org/10.1088/1742-6596/2647/11/112006.
Texto completo da fonteGalinos, Christos, Jonas Kazda, Wai Hou Lio e Gregor Giebel. "T2FL: An Efficient Model for Wind Turbine Fatigue Damage Prediction for the Two-Turbine Case". Energies 13, n.º 6 (11 de março de 2020): 1306. http://dx.doi.org/10.3390/en13061306.
Texto completo da fontePerdana, Abram, e Ola Carlson. "Factors Influencing Design of Dynamic Reactive Power Compensation for an Offshore Wind Farm". Wind Engineering 33, n.º 3 (maio de 2009): 273–85. http://dx.doi.org/10.1260/0309-524x.33.3.273.
Texto completo da fonteLuo, Ya Di, Jing Li, Zi Ming Guo, Gui Rong Shi, Dong Sheng Wang e Bo Yan. "Research of Robust State Estimation Method and Program Implementation Considering Large-Scale Wind Power Integration". Applied Mechanics and Materials 672-674 (outubro de 2014): 361–66. http://dx.doi.org/10.4028/www.scientific.net/amm.672-674.361.
Texto completo da fonteLi, Shuhui, Donald C. Wunsch, Edgar O’Hair e Michael G. Giesselmann. "Comparative Analysis of Regression and Artificial Neural Network Models for Wind Turbine Power Curve Estimation". Journal of Solar Energy Engineering 123, n.º 4 (1 de julho de 2001): 327–32. http://dx.doi.org/10.1115/1.1413216.
Texto completo da fonteSterle, Arnold, Christian A. Hans e Jörg Raisch. "Model predictive control of wakes for wind farm power tracking". Journal of Physics: Conference Series 2767, n.º 3 (1 de junho de 2024): 032005. http://dx.doi.org/10.1088/1742-6596/2767/3/032005.
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