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dc.contributor.authorRuiz Minguela, Pablo
dc.contributor.authorNoble, Donald R.
dc.contributor.authorNava, Vincenzo
dc.contributor.authorPennock, Shona
dc.contributor.authorBlanco Ilzarbe, Jesús María ORCID
dc.contributor.authorJeffrey, Henry
dc.date.accessioned2023-01-10T17:34:05Z
dc.date.available2023-01-10T17:34:05Z
dc.date.issued2022-12-23
dc.identifier.citationSustainability 15(1) : (2023) // Article ID 215es_ES
dc.identifier.issn2071-1050
dc.identifier.urihttp://hdl.handle.net/10810/59213
dc.description.abstractThe development of new renewable energy technologies is generally perceived as a critical factor in the fight against climate change. However, significant difficulties arise when estimating the future performance and costs of nascent technologies such as wave energy. Robust methods to estimate the commercial costs that emerging technologies may reach in the future are needed to inform decision-making. The aim of this paper is to increase the clarity, consistency, and utility of future cost estimates for emerging wave energy technologies. It proposes a novel three-step method: (1) using a combination of existing bottom-up and top-down approaches to derive the current cost breakdown; (2) assigning uncertainty ranges, depending on the estimation reliability then used, to derive the first-of-a-kind cost of the commercial technology; and (3) applying component-based learning rates to produce the LCOE of a mature technology using the upper bound from (2) to account for optimism bias. This novel method counters the human propensity toward over-optimism. Compared with state-of-the-art direct estimation approaches, it provides a tool that can be used to explore uncertainties and focus attention on the accuracy of cost estimates and potential learning from the early stage of technology development. Moreover, this approach delivers useful information to identify remaining technology challenges, concentrate innovation efforts, and collect evidence through testing activities.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectemerging technologyes_ES
dc.subjectfuture cost projectiones_ES
dc.subjectlearning ratees_ES
dc.subjectuncertainty propagationes_ES
dc.subjectwave energyes_ES
dc.titleEstimating Future Costs of Emerging Wave Energy Technologieses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.date.updated2023-01-06T13:53:00Z
dc.rights.holder© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).es_ES
dc.relation.publisherversionhttps://www.mdpi.com/2071-1050/15/1/215es_ES
dc.identifier.doi10.3390/su15010215
dc.departamentoesIngeniería Energética
dc.departamentoeuEnergia Ingenieritza


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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's license is described as © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).