A numerical approach for planning offshore wind farms from regional to local scales over the Mediterranean

被引:51
作者
Balog, Irena [1 ]
Ruti, Paolo M. [2 ]
Tobin, Isabelle [3 ]
Armenio, Vincenzo [1 ]
Vautard, Robert [3 ]
机构
[1] Univ Trieste, Doctoral Sch Environm & Ind Fluid Mech, E1FM, Dipartimento Ingn & Architettura, I-34127 Trieste, Italy
[2] ENEA Italian Natl Agcy New Technol Energy & Susta, UTMEA CLIM Energy Environm Modeling Unit, Climate & Impact Modeling Lab, I-00123 Rome, Italy
[3] CEA Saclay, CEA CNRS UVSQ, IPSL, Lab Sci Climat & Environm,UMR 8212, F-91191 Gif Sur Yvette, France
关键词
Offshore wind energy; Mediterranean sea; Regional climate models; QuikSCAT satellite observations; Wind resources atlas; Wind variability;
D O I
10.1016/j.renene.2015.06.038
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Renewable energy resources, such as wind, are available worldwide. Locating areas with high and continual wind sources are crucial in pre-planning of wind farms. Vast offshore areas are characterized by higher and more reliable wind resources in comparison with continental areas. However, offshore wind energy production is in a quite preliminary phase. Elaborating the potential productivity of wind farms over such areas is challenging due to sparse in situ observations. The Mediterranean basin is not an exception. In this study we are proposing numerical simulations of near-surface wind fields from regional climate models (RCMs) in order to obtain and fill the gaps in observations over the Mediterranean basin. Four simulations produced with two regional climate models are examined here. Remote sensing observations (QuikSCAT satellite) are used to assess the skill of the simulated fields. A technique for estimating the potential energy from the wind fields over the region is introduced. The wind energy potential atlas and the map of a wind turbine's functional range are presented, locating the potentially interesting sub-regions for wind farms. The ability of models to reproduce the annual cycle and the probability density function of wind speed anomalies are detailed for specified sub-regions. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:395 / 405
页数:11
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