Reducing variability in the cost of energy of ocean energy arrays

Mathew B.R. Topper; Vincenzo Nava; Adam J. Collin; David Bould; Francesco Ferri; Sterling S. Olson; Ann R. Dallman; Jesse D. Roberts; Pablo Ruiz-Minguela; Henry F. Jeffrey

doi:10.1016/j.rser.2019.05.032

Reducing variability in the cost of energy of ocean energy arrays

Mathew B.R. Topper, Vincenzo Nava, Adam J. Collin, David Bould, Francesco Ferri, Sterling S. Olson, Ann R. Dallman, Jesse D. Roberts, Pablo Ruiz-Minguela, Henry F. Jeffrey

Research output: Contribution to journal › Article › peer-review

20 Citations (Scopus)

Abstract

Variability in the predicted cost of energy of an ocean energy converter array is more substantial than for other forms of energy generation, due to the combined stochastic action of weather conditions and failures. If the variability is great enough, then this may influence future financial decisions. This paper provides the unique contribution of quantifying variability in the predicted cost of energy and introduces a framework for investigating reduction of variability through investment in components. Following review of existing methodologies for parametric analysis of ocean energy array design, the development of the DTOcean software tool is presented. DTOcean can quantify variability by simulating the design, deployment and operation of arrays with higher complexity than previous models, designing sub-systems at component level. A case study of a theoretical floating wave energy converter array is used to demonstrate that the variability in levelised cost of energy (LCOE) can be greatest for the smallest arrays and that investment in improved component reliability can reduce both the variability and most likely value of LCOE. A hypothetical study of improved electrical cables and connectors shows reductions in LCOE up to 2.51% and reductions in the variability of LCOE of over 50%; these minima occur for different combinations of components.

Original language	English
Pages (from-to)	263-279
Number of pages	17
Journal	Renewable and Sustainable Energy Reviews
Volume	112
DOIs	https://doi.org/10.1016/j.rser.2019.05.032
Publication status	Published - Sept 2019

Keywords

Financial
Variability
Energy
Ocean
Wave
Tidal
Arrays

Project and Funding Information

Project ID
info:eu-repo/grantAgreement/EC/FP7/608597/EU/Optimal Design Tools for Ocean Energy Arrays/DTOCEAN
info:eu-repo/grantAgreement/EC/H2020/785921/EU/Advanced Design Tools for Ocean Energy Systems Innovation, Development and Deployment/DTOceanPlus
Funding Info
The research leading to this publication is part of the DTOceanPlus project which has received funding from the EuropeanUnion's Horizon 2020 research and innovation programme under grant agreement No 785921. Funding was also received from the European Community's Seventh Framework Programme for the DTOcean Project (grant agreement No. 608597). The contribution of Sandia National Laboratories was funded by the U.S. Department of Energy's Water Power Technologies Office. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the Un

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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title = "Reducing variability in the cost of energy of ocean energy arrays",

abstract = "Variability in the predicted cost of energy of an ocean energy converter array is more substantial than for other forms of energy generation, due to the combined stochastic action of weather conditions and failures. If the variability is great enough, then this may influence future financial decisions. This paper provides the unique contribution of quantifying variability in the predicted cost of energy and introduces a framework for investigating reduction of variability through investment in components. Following review of existing methodologies for parametric analysis of ocean energy array design, the development of the DTOcean software tool is presented. DTOcean can quantify variability by simulating the design, deployment and operation of arrays with higher complexity than previous models, designing sub-systems at component level. A case study of a theoretical floating wave energy converter array is used to demonstrate that the variability in levelised cost of energy (LCOE) can be greatest for the smallest arrays and that investment in improved component reliability can reduce both the variability and most likely value of LCOE. A hypothetical study of improved electrical cables and connectors shows reductions in LCOE up to 2.51% and reductions in the variability of LCOE of over 50%; these minima occur for different combinations of components.",

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note = "The research leading to this publication is part of the DTOceanPlus project which has received funding from the EuropeanUnion's Horizon 2020 research and innovation programme under grant agreement No 785921. Funding was also received from the European Community's Seventh Framework Programme for the DTOcean Project (grant agreement No. 608597). The contribution of Sandia National Laboratories was funded by the U.S. Department of Energy's Water Power Technologies Office. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government. The image of the RM3 device, in Fig. 7, was reproduced with the permission of Sandia National Laboratories",

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doi = "10.1016/j.rser.2019.05.032",

language = "English",

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AU - Bould, David

AU - Ferri, Francesco

AU - Olson, Sterling S.

AU - Dallman, Ann R.

AU - Roberts, Jesse D.

AU - Ruiz-Minguela, Pablo

AU - Jeffrey, Henry F.

N1 - The research leading to this publication is part of the DTOceanPlus project which has received funding from the EuropeanUnion's Horizon 2020 research and innovation programme under grant agreement No 785921. Funding was also received from the European Community's Seventh Framework Programme for the DTOcean Project (grant agreement No. 608597). The contribution of Sandia National Laboratories was funded by the U.S. Department of Energy's Water Power Technologies Office. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525. This paper describes objective technical results and analysis. Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the U.S. Department of Energy or the United States Government. The image of the RM3 device, in Fig. 7, was reproduced with the permission of Sandia National Laboratories

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AB - Variability in the predicted cost of energy of an ocean energy converter array is more substantial than for other forms of energy generation, due to the combined stochastic action of weather conditions and failures. If the variability is great enough, then this may influence future financial decisions. This paper provides the unique contribution of quantifying variability in the predicted cost of energy and introduces a framework for investigating reduction of variability through investment in components. Following review of existing methodologies for parametric analysis of ocean energy array design, the development of the DTOcean software tool is presented. DTOcean can quantify variability by simulating the design, deployment and operation of arrays with higher complexity than previous models, designing sub-systems at component level. A case study of a theoretical floating wave energy converter array is used to demonstrate that the variability in levelised cost of energy (LCOE) can be greatest for the smallest arrays and that investment in improved component reliability can reduce both the variability and most likely value of LCOE. A hypothetical study of improved electrical cables and connectors shows reductions in LCOE up to 2.51% and reductions in the variability of LCOE of over 50%; these minima occur for different combinations of components.

KW - Financial

KW - Variability

KW - Energy

KW - Ocean

KW - Wave

KW - Tidal

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KW - Financial

KW - Variability

KW - Energy

KW - Ocean

KW - Wave

KW - Tidal

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DO - 10.1016/j.rser.2019.05.032

M3 - Article

SN - 1364-0321

VL - 112

SP - 263

EP - 279

JO - Renewable and Sustainable Energy Reviews

JF - Renewable and Sustainable Energy Reviews

ER -

Reducing variability in the cost of energy of ocean energy arrays

Abstract

Keywords

Project and Funding Information

UN SDGs

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