Simplified model of offshore Airborne Wind Energy Converters
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DOI: 10.1016/j.renene.2015.11.063
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- Cherubini, Antonello & Papini, Andrea & Vertechy, Rocco & Fontana, Marco, 2015. "Airborne Wind Energy Systems: A review of the technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1461-1476.
- Babarit, A. & Hals, J. & Muliawan, M.J. & Kurniawan, A. & Moan, T. & Krokstad, J., 2012. "Numerical benchmarking study of a selection of wave energy converters," Renewable Energy, Elsevier, vol. 41(C), pages 44-63.
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- Luuk van Hagen & Kristian Petrick & Stefan Wilhelm & Roland Schmehl, 2023. "Life-Cycle Assessment of a Multi-Megawatt Airborne Wind Energy System," Energies, MDPI, vol. 16(4), pages 1-23, February.
- Wang, Yingguang & Wang, Lifu, 2018. "Towards realistically predicting the power outputs of wave energy converters: Nonlinear simulation," Energy, Elsevier, vol. 144(C), pages 120-128.
- Dragomir, George & Șerban, Alexandru & Năstase, Gabriel & Brezeanu, Alin Ionuț, 2016. "Wind energy in Romania: A review from 2009 to 2016," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 129-143.
- Salari, Mahdi Ebrahimi & Coleman, Joseph & Toal, Daniel, 2019. "Analysis of direct interconnection technique for offshore airborne wind energy systems under normal and fault conditions," Renewable Energy, Elsevier, vol. 131(C), pages 284-296.
- Pankaj Kumar & Yashwant Kashyap & Roystan Vijay Castelino & Anabalagan Karthikeyan & Manjunatha Sharma K. & Debabrata Karmakar & Panagiotis Kosmopoulos, 2023. "Laboratory-Scale Airborne Wind Energy Conversion Emulator Using OPAL-RT Real-Time Simulator," Energies, MDPI, vol. 16(19), pages 1-30, September.
- Helena Schmidt & Gerdien de Vries & Reint Jan Renes & Roland Schmehl, 2022. "The Social Acceptance of Airborne Wind Energy: A Literature Review," Energies, MDPI, vol. 15(4), pages 1-24, February.
- Mostafa A. Rushdi & Ahmad A. Rushdi & Tarek N. Dief & Amr M. Halawa & Shigeo Yoshida & Roland Schmehl, 2020. "Power Prediction of Airborne Wind Energy Systems Using Multivariate Machine Learning," Energies, MDPI, vol. 13(9), pages 1-23, May.
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Keywords
Floating; AWE; Wave energy; High altitude wind; Offshore renewable; Offshore platform;All these keywords.
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