Wind energy potential for the electricity production - Knjazevac Municipality case study (Serbia)

被引:27
作者
Potic, Ivan [1 ]
Joksimovic, Tatjana [2 ]
Milincic, Uros [2 ]
Kicovic, Dusan [3 ]
Milincic, Miroljub [2 ]
机构
[1] Republ Geodet Author, Bulevar Vojvode Mis 39, Belgrade 11000, Serbia
[2] Univ Belgrade, Fac Geog, Studentski Trg 3-111, Belgrade 11000, Serbia
[3] Minist Educ Sci & Technol Dev, Zahumska 14, Belgrade 11000, Serbia
关键词
Wind park; Annual energy output (AEO); Wind power output (WPO); Geographic information systems (GIS); Multispectral analysis; MULTICRITERIA DECISION-MAKING; FARM SITE SELECTION; OPTIMAL LOCATION; SUITABLE LOCATIONS; INFORMATION-SYSTEM; POWER-PLANTS; BIOMASS; MODEL; RESOURCE; SUPPORT;
D O I
10.1016/j.esr.2020.100589
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Geospatial potential for harvesting wind energy is not an easy task to perform in conditions of deficiency of accurate data in remote and large areas (macro to medium locations). There are different methodologies available to identify the most suitable location for the installation of wind power generators. One of the most suitable approaches that employ the Multi-Criteria Analysis method for wind energy potential of the Municipality of Knjazevac (East Serbia) is combining the Analytic Hierarchy Process (AHP) and Geographic Information Systems. Collection and creation of geospatial data for the research encompassed meteorological data from all available sources, digital elevation model (DEM) to analyze the orography of the terrain, and Landsat 8 satellite data to analyze six land cover (LC) classes. The identification of three best locations for the wind power generators (wind farms) using Multi-Criteria Decision Making (MCDM) analysis solved the major location problem: how to select the best locations for investment in the renewable energy sector and minimize the impact on the environment. The result indicates that only one part of the municipality, at the hub height of 100 m, has enough wind potential to produce energy.
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页数:13
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