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AIMS Energy

2014, Volume 2, Issue 3: 295-320. doi: 10.3934/energy.2014.3.295
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Review Special Issues

A review of ocean energy converters, with an Australian focus

  • CSIRO Energy Technology, PO Box 330, Newcastle 2300, NSW, Australia
  • Received: 10 March 2014 Accepted: 18 August 2014 Published: 25 August 2014

  • The requirement to move away from carbon based fossil fuels has led to a renewed interest in unconventional energy sources. Of interest in this article are ocean waves and current and tidal flows. This paper reviews the numerous options for ocean energy conversion systems that are currently available. A basic nomenclature for the variety of systems is utilized to classify the devices. A variety of issues including competing use, boating, fishing, commercial shipping and tourism are discussed with respect to impacts on and from ocean renewable energy.

    Citation: Chris Knight, Scott McGarry, Jennifer Hayward, Peter Osman, Sam Behrens. A review of ocean energy converters, with an Australian focus[J]. AIMS Energy, 2014, 2(3): 295-320. doi: 10.3934/energy.2014.3.295

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    [1] Osman P, Behrens S, Griffin D, et al. Ocean Renewable Energy: 2015-2050. Commonwealth Scientific and Industrial Research Organisation (CSIRO), 2011. Available from: http://www.csiro.au/Organisation-Structure/Flagships/Energy-Flagship/Ocean-renewable-energy.aspx.
    [2] Behrens S, Hayward J, Hemer M, et al. (2012) Assessing the wave energy converter potential for Australian coastal regions. Renew Energ 43: 210-217. doi: 10.1016/j.renene.2011.11.031
    [3] Hemer M, Griffin D (2010) The wave energy resource along Australia's southern margin. J Renew Sust Energ 2: 043108. doi: 10.1063/1.3464753
    [4] Hayward J, Behrens S, McGarry S, et al. (2012) Economic modelling of the potential of wave energy. Renew Energ 48: 238-250. doi: 10.1016/j.renene.2012.05.007
    [5] Jones A, Finley W. Recent development in salinity gradient power; 2003 12 April 2004; San Francisco, USA. pp. 3.
    [6] Polinder H, Scuotto M. Wave Energy Converters and their Impact on power systems; 2005 18 November 2005; Amsterdam, Netherland. pp. 9.
    [7] Harris R, Johanning L, Wolfram J. Mooring systems for wave energy converters: A review of design issues and choices; 2004; Blyth, UK.
    [8] Drew B, Plummer A, Sahinkaya M (2009) A review of wave energy converter technology. Proc IMechE 223: 15. doi: 10.1243/09544097JRRT174
    [9] Falcao A (2010) Wave energy utilization: A review of the technologies Renew Sust Energ Rev 14: 19.
    [10] Muetze A, Vining J. Ocean Wave Energy Conversion - A Survey, 2006 8-12 October 2006; Tempa, USA. pp.1410-1417.
    [11] López I, Andreu J, Ceballos S, et al. (2013) Review of wave energy technologies and the necessary power-equipment. Renew Sust Energ Rev 27: 413-434. doi: 10.1016/j.rser.2013.07.009
    [12] Czech B, Bauer P (2012) Wave Energy Converter Concepts Design Challenges and Classification. Ieee Ind Electr Mag 6: 4-16.
    [13] Pelamis. Pelamis Brochure, 2010. Available from:
    http://www.pelamiswave.com/pelamis-technology.
    [14] Soerensen H, Friis-Madsen E, Panhauser W, et al. Development of Wave Dragon from Scale 1:50 to Prototype; 2003; Cork, Ireland.
    [15] IEA IEA Ocean Energy Systems Links. International Energy Agency (IEA). pp. International overview.
    [16] Wave Star Energy, The commercial 500 kW Wave Star machine. Wave Star Energy, 2014. Available from: http://www.wavestarenergy.com.
    [17] Previsic M, Bedard R, Hagerman G, et al. System Level Design, Performance and Costs for San Francisco California Pelamis Offshore Wave Power Plant. 2004. Available from:
    http://oceanenergy.epri.com/attachments/wave/reports/006_San_Francisco_Pelamis_Conceptual_Design_12-11-04.pdf.
    [18] Sea Generation The SeaGen Project. Sea Generation Ltd.
    [19] Atlantis Resources (2010) Atlantis Resources Corporation AK turbine illustration.
    [20] BioPower Systems. Technologies - BioSTREAM, 2010. Available from:
    http://www.biopowersystems.com/biostream.html.
    [21] Newcastle City Council, Newcastle City Council - Water. 2009. Available from:
    http://www.newcastle.nsw.gov.au/environment/flooding_and_waterways/urban_water_cycle.
    [22] Fane T (2011). Personal communication: UNESCO Centre for Membrane Science and Technology.
    [23] watertechnology.net, Tuas seawater desalination plant -, Singapore. Available from:
    http://www.water-technology.net/projects/tuas-seawater-desalination/.
    [24] watertechnology.net, Perth seawater desalination plant, Australia. Available from:
    http://www.water-technology.net/projects/perth/.
    [25] Tewari P, Hanra M, Ramani M (1987) Relative technoeconomics of multistage flash distillation and reverse osmosis for seawater desalination - a case study. Desalination 64: 203-210. doi: 10.1016/0011-9164(87)90096-8
    [26] Narmine H, El-Fiqi A (2003). Mechanical vapour compression desalination systems - a case study Desalination Malta 143-150.
    [27] Tsai CF, Tzong TJ, Wu FHY (1993) Wave powered desalination apparatus with turbine-driven pressurization. Google Patents.
    [28] watertechnology.net, Hadera desalination plant, Israel. Available from:
    http://www.water-technology.net/projects/hadera-desalination/.
    [29] watertechnology.net, Tampa Bay seawater desalinatin plant, United States of America. Available from: http://www.water-technology.net/projects/tampa/.
    [30] Folley M, Whittaker T (2009) The cost of water from an autonomous wave-powered desalination plant. Renew Energ 34: 6.
    [31] Sharmila N, Jalihal P, Swamy A, et al. (2004) Wave powered desalination system. Energ 29: 3.
    [32] Hicks D, Pleass C, Mitcheson G. DELBUOY: wave-powered seawater desalination system; 1988 31 Octpber-2 November 1988; Baltimore, USA. pp. 1049-1054.
    [33] O'Grady J, McInnes K (2010) Extreme wind waves and their relationship to storm surges in northeastern Bass Strait. Aust Meteorol Oceanogr J 60: 265-275.
    [34] Uppsala University Wave Power Project - Lysekil. Uppsala University. Available from:
    http://www.el.angstrom.uu.se/forskningsprojekt/WavePower/Lysekilsprojektet_E.html.
    [35] Clean Development Mechanism, Project 0349: Sihwa Tidal Power Plant. UNFCCC, 2004. Available from:
    http://cdm.unfccc.int/Projects/DB/DNV-CUK1143710269.08.
    [36] Langhamer O, Haikonen K, Sundberg J (2010) Wave power - sustainable energy or environmentally costly? A review with special emphasis on linear wave energy converters. Renew Sust Energ Rev 14: 1329-1335.
    [37] Boehlert G, Gill A (2010) Environmental and ecological effects of ocean renewable energy development: a current synthesis. Oceanography 23: 68-81. doi: 10.5670/oceanog.2010.46
    [38] Thorpe T, Picken M (1993) Wave energy devices and the marine environment. Sci Meas Tech 140: 63-70.
    [39] Hammons T (1993) Tidal power. P IEEE 81: 419-433. doi: 10.1109/5.241486
    [40] Pelc R, Fujita R (2002) Renewable energy from the ocean. Marine Policy 26: 471-479. doi: 10.1016/S0308-597X(02)00045-3
    [41] Dadswell M, Rulifson R (1994) Macrotidal estuaries: a region of collision between migratory marine animals and tidal power development. Biol J Linn Soc 51: 93-113. doi: 10.1111/j.1095-8312.1994.tb00947.x
    [42] Soerensen H, Naef S (2008) Report and technical specificatin of reference technologies (wave and tidal power plant). NEEDS Project Rep.
    [43] Hammar L, Andersson S, Eggertsen L, et al. (2013) Hydrokinetic Turbine Effects on Fish Swimming Behaviour. PLoS ONE 8: e84141. doi: 10.1371/journal.pone.0084141
    [44] Jacobson P, Amaral S, Castro-Santas T, et al. (2012) Environmental effects of hydrokinetic turbines on fish: desktop and laboratory flume studies. Electric Power Research Institute.
    [45] Vega L (1995) The 210 kW open cycle OTEC experimental apparatus: status report; 1995 9-12 October 1995; San Diego, USA. pp. 1110-1115.
    [46] Wilde P (2010) Environmental Monitoring and Assessment Program at Potential OTEC Sites. 6th Annual Ocean Thermal Energy Conversion Conference. Lawrence Berkley National Laboratory.
    [47] Myers E, Hoss D, Matsumoto W, et al. (1986) The potential impact of ocean thermal energy conversion (OTEC) on fisheries. NOAA Technical Report NMFS 40 1986.
    [48] Vega L, OTEC overview. OTEC News, 2011. Available from:
    http://www.otecnews.org/portal/otec-articles/ocean-thermal-energy-conversion-otec-by-l-a-vega-ph-d/.
    [49] Australian Fisheries Management Authority, 2014. Available from:
    http://www.afma.gov.au/managing-our-fisheries/environment-and-sustainability/marine-protected-areas/.
    [50] (IUCN) IUfCoN, Sustainable Fisheries Management, 2014. Available from:
    http://www.iucn.org/about/union/secretariat/offices/rowa/iucnwame_ourwork/iucnwame_marineprogramme/iucn_m_drosos/.
    [51] Dähne M, Gilles A, Lucke K, et al. (2013) Effects of pile-driving on harbour porpoises (Phocoena phocoena) at the first offshore wind farm in Germany. Environ Res Lett 8: 1-16.
    [52] Robinson S, Theobald P, Lepper P. Underwater noise generated from marine piling; 2014; Edinburgh, Scotland. pp. 070080.
    [53] Haikonen K, Sundberg J, Leijon M (2013) Characteristics of the operational noise from full scale wave energy converters in the Lyskil Project: estimation of potential environmental impacts. Energies 6: 2562-2582. doi: 10.3390/en6052562
    [54] Copping A, Battey H, Brown-Saracino J, et al. (2014) An international assessment of the environmental effects of marine energy development. Ocean Coast Manage: 1-11.
    [55] Bolin K, Almgren M, Ohlsson E, et al. (2014) Long term estimations of low frequency noise levels over water from an off-shore wind farm. J Acoust Soc Am 135: 1106-1114. doi: 10.1121/1.4863302
    [56] Hampton T, Hofford A (2011) West Coast Wave Energy Planning and Assessment Framework: Assessment of Information and Approaches for Ocean Renewable Energy Siting and Planning. Oregon Wave Energy Trust: Pacific Energy Ventures.
    [57] oregon.gov, Oregon Territorial Sea Plan (Part 5). Use of the Territorial Sea for the Development of Renewable Energy Faciliteis or Other Related Structures, Equipment or Facilites. 2014. Available at: http://wwworegongov/LCD/OCMP/Pages/Ocean_TSP.aspx.
    [58] Gonzalez-Santamaria R, Zou Q, Pan S (2013) Impacts of a wave farm on waves, currents and coastal morphology in South West England. Estuaries Coasts 1: 1-14.
    [59] Veigas M, Ramos V, Iglesias G (2014) A wave arm for an island: detailed effects on the nearshore wave climate. Energy In press.
    [60] Bento A, Rusu E, Martinho P, et al. (2014) Assessment of the changes induced by a wave energy farm in the nearshore wave conditions. Comput Geosci In press.
    [61] Copping A, Hanna L, Van Cleve B, et al. (2014) Environmental risk evaluation system - an approach to ranking risk of oean energy development on coastal and estuarine environments. Estuaries Coasts: 1-16.

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    57. Jummy David, Gabrielle Brankston, Idriss Sekkak, Sungju Moon, Xiaoyan Li, Sana Jahedi, Zahra Mohammadi, Ao Li, Martin Grunnil, Pengfei Song, Woldegebriel Assefa, Nicola Bragazzi, Jianhong Wu, 2023, Chapter 1, 978-3-031-40804-5, 1, 10.1007/978-3-031-40805-2_1
    58. Glenn Webb, Xinyue Evelyn Zhao, An Epidemic Model with Infection Age and Vaccination Age Structure, 2024, 16, 2036-7449, 35, 10.3390/idr16010004
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