IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v267y2020ics0306261920304347.html
   My bibliography  Save this item

Wave energy resource characterization and assessment for coastal waters of the United States

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Li, Ning & García Medina, Gabriel & Yang, Zhaoqing & Cheung, Kwok Fai & Hitzl, David & Chen, Yi-Leng, 2023. "Wave climate and energy resources in the Mariana Islands from a 42-year high-resolution hindcast," Renewable Energy, Elsevier, vol. 215(C).
  2. Ahn, Seongho & Neary, Vincent S. & Haas, Kevin A., 2022. "Global wave energy resource classification system for regional energy planning and project development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
  3. Wang, Yuhan & Dong, Sheng, 2022. "Array of concentric perforated cylindrical systems with torus oscillating bodies integrated on inner cylinders," Applied Energy, Elsevier, vol. 327(C).
  4. Brand, Matthew Willi & Huang, Yicheng & Yang, Zhaoqing & Wang, Taiping, 2025. "Tidal stream energy resource characterization for powering the blue economy applications for Southeastern Alaska," Renewable Energy, Elsevier, vol. 244(C).
  5. Seongho Ahn & Kevin A. Haas & Vincent S. Neary, 2020. "Dominant Wave Energy Systems and Conditional Wave Resource Characterization for Coastal Waters of the United States," Energies, MDPI, vol. 13(12), pages 1-26, June.
  6. Rusu, Liliana, 2020. "A projection of the expected wave power in the Black Sea until the end of the 21st century," Renewable Energy, Elsevier, vol. 160(C), pages 136-147.
  7. Kamranzad, Bahareh & Takara, Kaoru, 2020. "A climate-dependent sustainability index for wave energy resources in Northeast Asia," Energy, Elsevier, vol. 209(C).
  8. Beya, Ignacio & Buckham, Bradley & Robertson, Bryson, 2021. "Impact of tidal currents and model fidelity on wave energy resource assessments," Renewable Energy, Elsevier, vol. 176(C), pages 50-66.
  9. Shahriar, Tanvir & Habib, M. Ahsan, 2024. "A reconnaissance-level characterization of wave energy resource in the exclusive economic zones of Bay-of-Bengal," Renewable Energy, Elsevier, vol. 225(C).
  10. Cai, Qinlin & Zhu, Songye, 2021. "Applying double-mass pendulum oscillator with tunable ultra-low frequency in wave energy converters," Applied Energy, Elsevier, vol. 298(C).
  11. Coe, Ryan G. & Ahn, Seongho & Neary, Vincent S. & Kobos, Peter H. & Bacelli, Giorgio, 2021. "Maybe less is more: Considering capacity factor, saturation, variability, and filtering effects of wave energy devices," Applied Energy, Elsevier, vol. 291(C).
  12. Choupin, O. & Pinheiro Andutta, F. & Etemad-Shahidi, A. & Tomlinson, R., 2021. "A decision-making process for wave energy converter and location pairing," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
  13. Yang, Zhaoqing & Wang, Taiping & Branch, Ruth & Xiao, Ziyu & Deb, Mithun, 2021. "Tidal stream energy resource characterization in the Salish Sea," Renewable Energy, Elsevier, vol. 172(C), pages 188-208.
  14. Yang, Zhaoqing & García Medina, Gabriel & Neary, Vincent S. & Ahn, Seongho & Kilcher, Levi & Bharath, Aidan, 2023. "Multi-decade high-resolution regional hindcasts for wave energy resource characterization in U.S. coastal waters," Renewable Energy, Elsevier, vol. 212(C), pages 803-817.
  15. Zhang, Jincheng & Zhao, Xiaowei & Jin, Siya & Greaves, Deborah, 2022. "Phase-resolved real-time ocean wave prediction with quantified uncertainty based on variational Bayesian machine learning," Applied Energy, Elsevier, vol. 324(C).
  16. Joensen, Bárður & Niclasen, Bárður A. & Bingham, Harry B., 2021. "Wave power assessment in Faroese waters using an oceanic to nearshore scale spectral wave model," Energy, Elsevier, vol. 235(C).
  17. Shahroozi, Zahra & Göteman, Malin & Engström, Jens, 2024. "Neural network survivability approach of a wave energy converter considering uncertainties in the prediction of future knowledge," Renewable Energy, Elsevier, vol. 228(C).
  18. Ahn, Seongho & Neary, Vincent S. & Ha, Taemin, 2023. "A practical method for modeling temporally-averaged ocean wave frequency-directional spectra for characterizing wave energy climates," Renewable Energy, Elsevier, vol. 207(C), pages 499-511.
  19. Choupin, Ophelie & Del Río-Gamero, B. & Schallenberg-Rodríguez, Julieta & Yánez-Rosales, Pablo, 2022. "Integration of assessment-methods for wave renewable energy: Resource and installation feasibility," Renewable Energy, Elsevier, vol. 185(C), pages 455-482.
  20. Meng Qi & Xin Dai & Bei Zhang & Junjie Li & Bangfan Liu, 2023. "The Evolution and Future Prospects of China’s Wave Energy Policy from the Perspective of Renewable Energy: Facing Problems, Governance Optimization and Effectiveness Logic," Sustainability, MDPI, vol. 15(4), pages 1-25, February.
  21. Ahn, Seongho & Neary, Vincent S. & Allahdadi, Mohammad Nabi & He, Ruoying, 2021. "Nearshore wave energy resource characterization along the East Coast of the United States," Renewable Energy, Elsevier, vol. 172(C), pages 1212-1224.
  22. Han, Zhi & Cao, Feifei & Tao, Ji & Shi, Hongda, 2023. "Study on the energy capture spectrum (ECS) of a multi-DoF buoy under random waves," Energy, Elsevier, vol. 279(C).
  23. Anastas, Gael & Alfredo Santos, João & Fortes, C.J.E.M. & Pinheiro, Liliana V., 2022. "Energy assessment of potential locations for OWC instalation at the Portuguese coast," Renewable Energy, Elsevier, vol. 200(C), pages 37-47.
  24. Shao, Zhuxiao & Gao, Huijun & Liang, Bingchen & Lee, Dongyoung, 2022. "Potential, trend and economic assessments of global wave power," Renewable Energy, Elsevier, vol. 195(C), pages 1087-1102.
  25. Meduri, Aghamarshana & Kang, HeonYong, 2025. "Sequential design optimization with Bayesian approach for cost-competitive levelized cost of energy of a wave energy converter with adaptive resonance," Applied Energy, Elsevier, vol. 382(C).
  26. Ahn, Seongho & Neary, Vincent S., 2021. "Wave energy resource characterization employing joint distributions in frequency-direction-time domain," Applied Energy, Elsevier, vol. 285(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.