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Citation:
　Mohua Das,M. Rafiqul Islam,Tariqul Islam Shazeeb.Analysis of Wave Energy Resources Around the Saint Martin Island in Bangladesh[J].Journal of Marine Science and Application,2021,(2):248-267.[doi:10.1007/s11804-021-00208-z]
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Analysis of Wave Energy Resources Around the Saint Martin Island in Bangladesh

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Title:
Analysis of Wave Energy Resources Around the Saint Martin Island in Bangladesh
Author(s):
Mohua Das;  M. Rafiqul Islam;  Tariqul Islam Shazeeb
Affilations:
Author(s):
Mohua Das;  M. Rafiqul Islam;  Tariqul Islam Shazeeb
Department of Naval Architecture and Marine Engineering, Bangladesh University of Engineering and Technology, Dhaka 1000, Bangladesh
Keywords:
Renewable energy; Ocean waves; Saint Martin Island; Delft3D; Wave power density; Stability
分类号:
-
DOI:
10.1007/s11804-021-00208-z
Abstract:
Saint Martin Island is the only coral island and one of the well-known tourist spots in Bangladesh. Because of its geographic location, electricity cannot be supplied from the mainland through the electricity grid. Diesel generators and solar power are the only means of electricity generation presently available there. Surrounded by the sea, Saint Martin Island has the ideal conditions for wave energy extraction. In this research, numerical models have been developed using the Delft3D simulation software to determine the wave characteristics of different locations around Saint Martin Island. The results have been calibrated and validated against the data obtained from well-known data sources. The wave power densities have been calculated using the data obtained from the simulation models. The findings of the research show that the wave power density increases significantly from shallow water to deep water and a large amount of wave energy can be extracted during the summer and rainy monsoon seasons. The maximum hourly average value of wave power in 2016 has been determined to be 6.90 kW/m at location with a water depth of 27.80 m. Wave energy resources are also observed to be sufficiently stable with the coefficients of variation of wave power density less than 0.62, except for December, January, and May of that particular year. Moreover, the annual effective energies have been determined to be within the range of 36.57 to 57.28 MWh/m, which will be sufficient to meet the electricity requirement of the island communities.

References:

Aboobacker VM, Shanas PR, Alsaafani MA, Albarakati AM (2017) Wave energy resource assessment for Red Sea. Renew Energy 114:46-58. https://doi.org/10.1016/j.renene.2016.09.073
Akp?nar A, Kömürcü M? (2013) Assessment of wave energy resource of the Black Sea based on 15-year numerical hindcast data. Appl Energy 101:502-512. https://doi.org/10.1016/j.apenergy.2012.06.005
Arinaga RA, Cheung KF (2012) Atlas of global wave energy from 10 years of reanalysis and hindcast data. Renew Energy 39(1):49-64. https://doi.org/10.1016/j.renene.2011.06.039
Besio G, Mentaschi L, Mazzino A (2016) Wave energy resource assessment in the Mediterranean Sea on the basis of a 35-year hindcast. Energy 94:50-63. https://doi.org/10.1016/j.energy.2015.10.044
Bouhrim H, El Marjani A (2019) Wave energy assessment along the Moroccan Atlantic coast. J Mar Sci Appl 18(2):142-152. https://doi.org/10.1007/s11804-018-00060-8
Cornett AM (2008) A global wave energy resource assessment. Proceedings of the Eighteenth International Offshore and Polar Engineering Conference, Vancouver
Das M, Shazeeb TI, Islam MR (2018) Numerical investigation of wave energy of Saint Martin region of Bangladesh. Proceedings of the 11th International Conference on Marine Technology (MARTEC), UTM, Kuala Lumpur, pp 39-44
Deltares (2017a) Delft3D-FLOW user manual:simulation of multidimensional hydrodynamic flows and transport phenomena, including sediments. Deltares:Delft, the Netherlands, version:3.15, SVN Revision:52614, 173-268
Deltares (2017b) Delft3D user manual:Delft3D, functional specifications. Deltares:Delft, the Netherlands, version:3.15, SVN Revision:52614, 1-20
Deltares (2017c) Delft3D-WAVE user manual:simulation of short-crested waves with SWAN. Deltares:Delft, The Netherlands, Version:3.15, SVN Revision:52614, 6
Espindola RL, Araújo AM (2017) Wave energy resource of Brazil:an analysis from 35 years of ERA-interim reanalysis data. PLoS One 12(8):e0183501. https://doi.org/10.1371/journal.pone.0183501
Hughes MG, Heap AD (2010) National-scale wave energy resource assessment for Australia. Renew Energy 35(8):1783-1791. https://doi.org/10.1016/j.renene.2009.11.001
Iglesias G, Carballo R (2010) Wave energy and nearshore hot spots:the case of the SE Bay of Biscay. Renew Energy 35(11):2490-2500. https://doi.org/10.1016/j.renene.2010.03.016
Islam S, Khan MZ (2017) A review of energy sector of Bangladesh. Energy Procedia 110:611-618. https://doi.org/10.1016/j.egypro.2017.03.193
Islam MT, Uddin MG, Chakma TB, Chowdhury MZ (2014) Feasibility study of ocean wave of the bay of Bengal to generate electricity as a renewable energy with a proposed design of energy conversion system. Int J Renew Energy Res (IJRER) 4(2):445-452
Jiang B, Wu G, Ding J, Ma C, Fang Y, Wang X (2019) Assessment of the wave energy resource in the South China Sea. Proc Instit Civil Eng-Mar Eng 172(1):23-33. https://doi.org/10.1680/jmaen.2018.29
Kim G, Jeong WM, Lee KS, Jun K, Lee ME (2011) Offshore and nearshore wave energy assessment around the Korean peninsula. Energy 36(3):1460-1469. https://doi.org/10.1016/j.energy.2011.01.023
Kumar VS, Anoop TR (2015) Wave energy resource assessment for the Indian shelf seas. Renew Energy 76:212-219. https://doi.org/10.1016/j.renene.2014.11.034
Kumar VS, Dubhashi KK, Nair TB, Singh J (2013) Wave power potential at a few shallow-water locations around Indian coast. Curr Sci 104(9):1219-1224
Lavidas G, Venugopal V, Friedrich D (2017) Wave energy extraction in Scotland through an improved nearshore wave atlas. Int J Mar Energy 17:64-83. https://doi.org/10.1016/j.ijome.2017.01.008
Liang B, Fan F, Liu F, Gao S, Zuo H (2014) 22-year wave energy hindcast for the China east adjacent seas. Renew Energy 71:200-207. https://doi.org/10.1016/j.renene.2014.05.027
Monteforte M, Re CL, Ferreri GB (2015) Wave energy assessment in Sicily (Italy). Renew Energy 78:276-287. https://doi.org/10.1016/j.renene.2015.01.006
Monteiro WM, Sarmento AJ, Fernandes AJ, Fernandes JM (2016) Statistical analysis of wave energy resources available for conversion at natural caves of cape-Verde Islands. Ocean Sci Discuss:1-23
Morim J, Cartwright N, Etemad-Shahidi A, Strauss D, Hemer M (2016) Wave energy resource assessment along the southeast coast of Australia on the basis of a 31-year hindcast. Appl Energy 184:276-297. https://doi.org/10.1016/j.apenergy.2016.09.064
Rahman H, Mahdy AT, Islam MR, Haque N (2018) A study for assessing wave energy of the bay of Bengal. Proceedings of the international conference on innovation in engineering and technology (ICIET), 1-5. https://doi.org/10.1109/CIET.2018.8660935
Rosales P, Ocampo-Torres FJ, Osuna P, Monbaliu J, Padilla-Hernández R (2008) Wave-current interaction in coastal waters:effects on the bottom-shear stress. J Mar Syst 71(1-2):131-148. https://doi.org/10.1016/j.jmarsys.2007.06.006
Sarker MT, Rahman MA, Mahmud PD (2017) Electricity demand load forecasting for a remote area of Bangladesh. Int J Sci Eng 8(1):265-277
Silva D, Rusu E, Guedes Soares C (2013) Evaluation of various technologies for wave energy conversion in the Portuguese nearshore. Energies 6(3):1344-1364. https://doi.org/10.3390/en6031344
Swain J, Umesh PA, Balchand AN, Bhaskaran PK (2017) Wave hindcasting using WAM and WAVEWATCH III:a comparison study utilizing oceansat-2 (OSCAT) winds. J Oceanogr Mar Res 5(2):2572-3103. https://doi.org/10.4172/2572-3103.1000166
Wan Y, Zhang J, Meng J, Wang J (2015) A wave energy resource assessment in the China’s seas based on multi-satellite merged radar altimeter data. Acta Oceanol Sin 34(3):115-124. https://doi.org/10.1007/s13131-015-0627-6
Wan Y, Fan C, Zhang J, Meng J, Dai Y, Li L, Sun W, Zhou P, Wang J, Zhang X (2017) Wave energy resource assessment off the coast of China around the Zhoushan Islands. Energies 10(9):1320. https://doi.org/10.3390/en10091320
Wan Y, Fan C, Dai Y, Li L, Sun W, Zhou P, Qu X (2018) Assessment of the joint development potential of wave and wind energy in the South China Sea. Energies 11(2):398. https://doi.org/10.3390/en11020398
Yaakob O, Hashim FE, Omar KM, Din AH, Koh KK (2016) Satellite-based wave data and wave energy resource assessment for South China Sea. Renew Energy 88:359-371. https://doi.org/10.1016/j.renene.2015.11.039
Zheng C, Zhuang H, Li X, Li X (2012) Wind energy and wave energy resources assessment in the East China Sea and South China Sea. Sci China Technol Sci 55(1):163-173. https://doi.org/10.1007/s11431-011-4646-z
Zheng CW, Pan J, Li JX (2013) Assessing the China Sea wind energy and wave energy resources from 1988 to 2009. Ocean Eng 65:39-48. https://doi.org/10.1016/j.oceaneng.2013.03.006
Zheng C, Shao L, Shi W, Su Q, Lin G, Li X, Chen X (2014) An assessment of global ocean wave energy resources over the last 45 a. Acta Oceanol Sin 33(1):92-101. https://doi.org/10.1007/s13131-014-0418-5

Memo

Memo:
Received date:2020-05-10;Accepted date:2021-02-14。
Corresponding author:Mohua Das, mohuadas@name.buet.ac.bd
Last Update: 2021-09-06