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Modeling Epistemic Uncertainty in Offshore Wind Farm Production Capacity to Reduce Risk.
Zitrou, Athena; Bedford, Tim; Walls, Lesley.
Afiliação
  • Zitrou A; Department of Management Science, University of Strathclyde, Glasgow, Scotland.
  • Bedford T; Department of Management Science, University of Strathclyde, Glasgow, Scotland.
  • Walls L; Department of Management Science, University of Strathclyde, Glasgow, Scotland.
Risk Anal ; 42(7): 1524-1540, 2022 07.
Article em En | MEDLINE | ID: mdl-34837889
ABSTRACT
Financial stakeholders in offshore wind farm projects require predictions of energy production capacity to better manage the risk associated with investment decisions prior to construction. Predictions for early operating life are particularly important due to the dual effects of cash flow discounting and the anticipated performance growth due to experiential learning. We develop a general marked point process model for the times to failure and restoration events of farm subassemblies to capture key uncertainties affecting performance. Sources of epistemic uncertainty are identified in design and manufacturing effectiveness. The model then captures the temporal effects of epistemic and aleatory uncertainties across subassemblies to predict the farm availability-informed relative capacity (maximum generating capacity given the technical state of the equipment). This performance measure enables technical performance uncertainties to be linked to the cost of energy generation. The general modeling approach is contextualized and illustrated for a prospective offshore wind farm. The production capacity uncertainties can be decomposed to assess the contribution of epistemic uncertainty allowing the value of gathering information to reduce risk to be examined.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Incerteza Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Risk Anal Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Incerteza Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Risk Anal Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Reino Unido