A methodology for evaluating the spatial variability of wind energy resources: Application to assess the potential contribution of wind energy to baseload power
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DOI: 10.1016/j.renene.2014.03.006
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- Astariz, S. & Iglesias, G., 2016. "Output power smoothing and reduced downtime period by combined wind and wave energy farms," Energy, Elsevier, vol. 97(C), pages 69-81.
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- Correia, J.M. & Bastos, A. & Brito, M.C. & Trigo, R.M., 2017. "The influence of the main large-scale circulation patterns on wind power production in Portugal," Renewable Energy, Elsevier, vol. 102(PA), pages 214-223.
- Santos-Alamillos, F.J. & Thomaidis, N.S. & Usaola-García, J. & Ruiz-Arias, J.A. & Pozo-Vázquez, D., 2017. "Exploring the mean-variance portfolio optimization approach for planning wind repowering actions in Spain," Renewable Energy, Elsevier, vol. 106(C), pages 335-342.
- Daniel Ambach & Carsten Croonenbroeck, 2016. "Space-time short- to medium-term wind speed forecasting," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(1), pages 5-20, March.
- Chiacchio, Ferdinando & D’Urso, Diego & Famoso, Fabio & Brusca, Sebastian & Aizpurua, Jose Ignacio & Catterson, Victoria M., 2018. "On the use of dynamic reliability for an accurate modelling of renewable power plants," Energy, Elsevier, vol. 151(C), pages 605-621.
- Zhang, Chongyu & Lu, Xi & Ren, Guo & Chen, Shi & Hu, Chengyu & Kong, Zhaoyang & Zhang, Ning & Foley, Aoife M., 2021. "Optimal allocation of onshore wind power in China based on cluster analysis," Applied Energy, Elsevier, vol. 285(C).
- Artur Amsharuk & Grażyna Łaska, 2023. "The Approach to Finding Locations for Wind Farms Using GIS and MCDA: Case Study Based on Podlaskie Voivodeship, Poland," Energies, MDPI, vol. 16(20), pages 1-24, October.
- Gruber, Katharina & Klöckl, Claude & Regner, Peter & Baumgartner, Johann & Schmidt, Johannes, 2019. "Assessing the Global Wind Atlas and local measurements for bias correction of wind power generation simulated from MERRA-2 in Brazil," Energy, Elsevier, vol. 189(C).
- Santos-Alamillos, F.J. & Thomaidis, N.S. & Quesada-Ruiz, S. & Ruiz-Arias, J.A. & Pozo-Vázquez, D., 2016. "Do current wind farms in Spain take maximum advantage of spatiotemporal balancing of the wind resource?," Renewable Energy, Elsevier, vol. 96(PA), pages 574-582.
- Ingeborg Graabak & Magnus Korpås, 2016. "Variability Characteristics of European Wind and Solar Power Resources—A Review," Energies, MDPI, vol. 9(6), pages 1-31, June.
- Daniel Ambach & Carsten Croonenbroeck, 2016. "Space-time short- to medium-term wind speed forecasting," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(1), pages 5-20, March.
- Daniel Ambach & Robert Garthoff, 2016. "Vorhersagen der Windgeschwindigkeit und Windenergie in Deutschland [Predictions of wind speed and wind energy in Germany]," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 10(1), pages 15-36, February.
- Brijs, Tom & De Vos, Kristof & De Jonghe, Cedric & Belmans, Ronnie, 2015. "Statistical analysis of negative prices in European balancing markets," Renewable Energy, Elsevier, vol. 80(C), pages 53-60.
- Monforti, F. & Gaetani, M. & Vignati, E., 2016. "How synchronous is wind energy production among European countries?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1622-1638.
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Keywords
Wind energy variability; PCA; Andalusia; Firm capacity; Balancing;All these keywords.
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