王思恒等:Selecting photovoltaic generation sites in Tibet using remote sensing and geographic analysis
被阅读 775 次
2016-08-06
Selecting photovoltaic generation sites in Tibet using remote sensing and geographic analysis
作者:Wang, SH (Wang, Siheng)[ 1,2 ] ; Zhang, LF (Zhang, Lifu)[ 1 ] ; Fu, DJ (Fu, Dongjie)[ 1 ] ; Lu, X (Lu, Xu)[ 3 ] ; Wu, TX (Wu, Taixia)[ 1 ] ; Tong, QX (Tong, Qingxi)[ 1 ]
 
SOLAR ENERGY
卷: 133  页: 85-93
DOI: 10.1016/j.solener.2016.03.069
出版年: AUG 2016
 
摘要
Harnessing solar energy through photovoltaic (PV) generation of electricity is a promising method, expected to reduce greenhouse gas emissions at a relatively low cost. A primary obstacle for the large-scale exploitation of solar energy in regions with poor electrical infrastructure is that the output of the PV systems is hard to match their connection with the electric grid, due to the lack of strategical planning. This study aims to map the most promising locations for potential PV investments in Tibet, China, where solar radiation is in abundance, presenting an opportunity to install PV stations across the country. Geographic information science (GIS) overlay was implemented, considering solar energy distribution, local terrain and native land cover. Several remotely sensed data were employed as input, including time series of solar radiation data, land cover data and digital elevation model data. In total, 4005 sites were selected, with the majority in the regions of Shigatse and Ngari. The results were discussed according to their distance to existing electricity substations, to evaluate the difficulty to be connected to the grid. The work highlights a method for the selection of suitable PV power generation sites, and provides a guidance for the construction of these stations, particularly in Tibet-like regions with poor electrical infrastructure, and harsh environmental conditions. (C) 2016 Elsevier Ltd. All rights reserved.
 
通讯作者地址: Zhang, LF (通讯作者)
Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.
地址:
[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
[ 2 ] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[ 3 ] Clark Univ, 950 Main St, Worcester, MA 01610 USA