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Do current wind farms in Spain take maximum advantage of spatiotemporal balancing of the wind resource?

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  • Santos-Alamillos, F.J.
  • Thomaidis, N.S.
  • Quesada-Ruiz, S.
  • Ruiz-Arias, J.A.
  • Pozo-Vázquez, D.

Abstract

Optimal siting of wind farms based on a pre-assessment of the spatiotemporal variability of wind resources is considered a suitable method for reducing fluctuations in the delivered output. In this study, we explore the potential for balancing wind energy generation in the Iberian Peninsula using Principal Component Analysis (PCA). This technique permits the discovery of possibly new promising locations for wind power harvesting and an evaluation of the existing wind farm network in terms of reliability in energy generation. Data input to the PCA consists of hourly wind capacity factor in a 5-km spatial resolution grid covering the entire peninsula. These data are derived from an equivalent wind farm power curve fed by modeled wind speed data from 80 m above ground level. PCA reveals three significant balancing patterns prevailing over the IP, where half of the currently operating wind farms in Spain are placed. Hence, among the many constituents of the existing wind farm network, these spots offer the best opportunity for stable power supply. The paper concludes by making proposals on an optimum wind capacity allocation based on the idea of equally distributing installed power between positive/negative dipoles emerging from balancing principal components.

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  • 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.
  • Handle: RePEc:eee:renene:v:96:y:2016:i:pa:p:574-582
    DOI: 10.1016/j.renene.2016.05.019
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    References listed on IDEAS

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    1. Santos-Alamillos, F.J. & Pozo-Vázquez, D. & Ruiz-Arias, J.A. & Lara-Fanego, V. & Tovar-Pescador, J., 2014. "A methodology for evaluating the spatial variability of wind energy resources: Application to assess the potential contribution of wind energy to baseload power," Renewable Energy, Elsevier, vol. 69(C), pages 147-156.
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    Citations

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    Cited by:

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    5. 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.
    6. Chidean, Mihaela I. & Caamaño, Antonio J. & Ramiro-Bargueño, Julio & Casanova-Mateo, Carlos & Salcedo-Sanz, Sancho, 2018. "Spatio-temporal analysis of wind resource in the Iberian Peninsula with data-coupled clustering," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2684-2694.
    7. Álvarez-García, Francisco J. & Fresno-Schmolk, Gonzalo & OrtizBevia, María J. & Cabos, William & RuizdeElvira, Antonio, 2020. "Reduction of aggregate wind power variability using Empirical Orthogonal Teleconnections: An application in the Iberian Peninsula," Renewable Energy, Elsevier, vol. 159(C), pages 151-161.

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