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

被引:15
|
作者
Santos-Alamillos, F. J. [1 ,2 ]
Thomaidis, N. S. [3 ]
Quesada-Ruiz, S. [1 ,4 ,5 ]
Ruiz-Arias, J. A. [1 ]
Pozo-Vazquez, D. [1 ]
机构
[1] Univ Jaen, Dept Phys, Campus Las Lagunillas S-N, E-23071 Jaen, Andalusia, Spain
[2] Univ Malaga, Dept Elect Engn, E-29071 Malaga, Spain
[3] Aristotle Univ Thessaloniki, Sch Econ, Thessaloniki, Greece
[4] Meteo France, CNRM GAME, Toulouse, France
[5] Lab Aerol, Toulouse, France
关键词
Wind power fluctuations; Spatiotemporal balancing; Firm capacity; Principal component analysis; Wind farms; Spain; BASELOAD POWER; ENERGY; VARIABILITY; ELECTRICITY; VARIANCE; STORAGE; PLANTS;
D O I
10.1016/j.renene.2016.05.019
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:574 / 582
页数:9
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