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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 formore » different combinations of components.« less

Authors:
; ; ; ; ; ; ; ; ;
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1531034
Alternate Identifier(s):
OSTI ID: 1570292
Report Number(s):
SAND-2019-10077J
Journal ID: ISSN 1364-0321; S1364032119303454; PII: S1364032119303454
Grant/Contract Number:  
AC04-94AL85000
Resource Type:
Published Article
Journal Name:
Renewable and Sustainable Energy Reviews
Additional Journal Information:
Journal Name: Renewable and Sustainable Energy Reviews Journal Volume: 112 Journal Issue: C; Journal ID: ISSN 1364-0321
Publisher:
Elsevier
Country of Publication:
United Kingdom
Language:
English
Subject:
16 TIDAL AND WAVE POWER; Financial; Variability; Energy; Ocean; Wave; Tidal; Arrays

Citation Formats

Topper, Mathew B. R., Nava, Vincenzo, Collin, Adam J., Bould, David, Ferri, Francesco, Olson, Sterling S., Dallman, Ann R., Roberts, Jesse D., Ruiz-Minguela, Pablo, and Jeffrey, Henry F. Reducing variability in the cost of energy of ocean energy arrays. United Kingdom: N. p., 2019. Web. doi:10.1016/j.rser.2019.05.032.
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Topper, Mathew B. R., Nava, Vincenzo, Collin, Adam J., Bould, David, Ferri, Francesco, Olson, Sterling S., Dallman, Ann R., Roberts, Jesse D., Ruiz-Minguela, Pablo, & Jeffrey, Henry F. Reducing variability in the cost of energy of ocean energy arrays. United Kingdom. https://doi.org/10.1016/j.rser.2019.05.032
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Topper, Mathew B. R., Nava, Vincenzo, Collin, Adam J., Bould, David, Ferri, Francesco, Olson, Sterling S., Dallman, Ann R., Roberts, Jesse D., Ruiz-Minguela, Pablo, and Jeffrey, Henry F. Sun . "Reducing variability in the cost of energy of ocean energy arrays". United Kingdom. https://doi.org/10.1016/j.rser.2019.05.032.
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@article{osti_1531034,
title = {Reducing variability in the cost of energy of ocean energy arrays},
author = {Topper, Mathew B. R. and Nava, Vincenzo and Collin, Adam J. and Bould, David and Ferri, Francesco and Olson, Sterling S. and Dallman, Ann R. and Roberts, Jesse D. and Ruiz-Minguela, Pablo and Jeffrey, Henry F.},
abstractNote = {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.},
doi = {10.1016/j.rser.2019.05.032},
journal = {Renewable and Sustainable Energy Reviews},
number = C,
volume = 112,
place = {United Kingdom},
year = {Sun Sep 01 00:00:00 EDT 2019},
month = {Sun Sep 01 00:00:00 EDT 2019}
}
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Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1016/j.rser.2019.05.032
Copyright Statement
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Citation Metrics:
Cited by: 9 works
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Figures / Tables:

Table 1 Table 1 : Simulation scope and modelling assumptions of the DTOcean software.
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Works referenced in this record:

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    Figures / Tables found in this record:

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