Sanz Rodrigo, JavierFrías Paredes, LauraGirard, RobinKariniotakis, GeorgeLaquaine, KevinStoffels, NicoleBremen, Lueder von2024-11-222024-11-222017-06-23Sanz Rodrigo, J., Frías Paredes, L., Girard, R., Kariniotakis, G., Laquaine, K., Stoffels, N., Von Bremen, L. (2017) The role of predictability in the investment phase of wind farms. In Kariniotakis G. (Ed.), Renewable energy forecasting: from models to applications (pp. 341-357). Woodhead Publishing. https://doi.org/10.1016/B978-0-08-100504-0.00014-7978-0-08-100504-010.1016/B978-0-08-100504-0.00014-7https://academica-e.unavarra.es/handle/2454/52562Acceso cerrado a este documento. No se encuentra disponible para la consulta pública. Depositado en Academica-e para cumplir con los requisitos de evaluación y acreditación académica del autor/a (sexenios, acreditaciones, etc.).Within the SAFEWIND project, wind power predictability is evaluated to suggest potential benefits during the planning phase of wind farm deployment. Predictability assessment can be useful, for instance, to anticipate operational costs due to market imbalance for energy traders, costs related to prediction of offshore weather windows for turbine installation or maintenance, or to benefit from portfolio effects when aggregating wind farms that operate in uncorrelated wind climates. While the weight of predictability for a wind farm developer is low in the decision-making process compared to the capacity factor, it remains a useful indicator of the quality of wind for grid integration purposes. A series of case studies are presented in various European regions to present tools for wind power predictability assessment at different scales.application/pdfeng© 2017 Elsevier Ltd.AssessmentDecision-makingInvestment phasePortfolio effectPredictabilitySpatial planningWind farminfo:eu-repo/semantics/bookPart2024-11-22info:eu-repo/semantics/closedAccess