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Satellite-based wave data and wave energy resource assessment for South China Sea

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  • Yaakob, Omar
  • Hashim, Farah Ellyza
  • Mohd Omar, Kamaludin
  • Md Din, Ami Hassan
  • Koh, Kho King

Abstract

Wave energy has the potential to valuably contribute to the coastal states renewable energy mix. However, lack of data sources hinders the effort to deliberately assess this resource. This paper presents an assessment of wave energy resources in the South China Sea (Malaysian Exclusive Economic Zone) using satellite altimeter. Radar Altimeter Database System (RADS) provides data of significant wave height and wind speed from several satellite altimeters. The data were extracted for a space resolution of 0.25° × 0.25°, and within the time range from January 2001 to December 2010 and space range of 1.5°N – 10.0°N, 95.0°E − 116.0°E. For this study, fifteen 2° × 2° zones were considered around the east coast of Peninsular Malaysia and the coast of East Malaysia. The 10-year-data were validated with buoy measurements and presented as the probability distribution of wave height and wave period. The results indicate that bulk of the waves had peak period between 5s and 7s and significant wave height between 0.5 m and 1.5 m. The data were then used to calculate the theoretical available wave energy and power in the study areas. The results show that the average wave energy density of Malaysian seas facing the South China Sea is in the range of 1.41 kW/m to 7.92 kW/m, while the energy storage varies from 7.10 MW h/m to 69.41 MW h/m. This study also demonstrates the ability of satellite altimeter to provide an accurate and reliable data for more comprehensive and realistic estimate of the energy potential. The ability of satellite altimeter to provide wave data for all sea zones will enable more accurate identification of potential locations for wave energy development in Malaysia.

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  • Yaakob, Omar & Hashim, Farah Ellyza & Mohd Omar, Kamaludin & Md Din, Ami Hassan & Koh, Kho King, 2016. "Satellite-based wave data and wave energy resource assessment for South China Sea," Renewable Energy, Elsevier, vol. 88(C), pages 359-371.
    • Handle: RePEc:eee:renene:v:88:y:2016:i:c:p:359-371
    DOI: 10.1016/j.renene.2015.11.039
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    3. Sun, Ze & Zhang, Haicheng & Xu, Daolin & Liu, Xiaolong & Ding, Jun, 2020. "Assessment of wave power in the South China Sea based on 26-year high-resolution hindcast data," Energy, Elsevier, vol. 197(C).
    4. Zanous, Sina Pasha & Shafaghat, Rouzbeh & Alamian, Rezvan & Shadloo, Mostafa Safdari & Khosravi, Mohammad, 2019. "Feasibility study of wave energy harvesting along the southern coast and islands of Iran," Renewable Energy, Elsevier, vol. 135(C), pages 502-514.
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    6. Silva, R.N. & Nunes, M.M. & Oliveira, F.L. & Oliveira, T.F. & Brasil, A.C.P. & Pinto, M.S.S., 2023. "Dynamical analysis of a novel hybrid oceanic tidal-wave energy converter system," Energy, Elsevier, vol. 263(PD).
    7. Uti, Mat Nizam & Md Din, Ami Hassan & Yusof, Norhakim & Yaakob, Omar, 2023. "A spatial-temporal clustering for low ocean renewable energy resources using K-means clustering," Renewable Energy, Elsevier, vol. 219(P2).
    8. Liang, Bingchen & Shao, Zhuxiao & Wu, Yajie & Shi, Hongda & Liu, Zhen, 2017. "Numerical study to estimate the wave energy under Wave-Current Interaction in the Qingdao coast, China," Renewable Energy, Elsevier, vol. 101(C), pages 845-855.
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