Suitability evaluation system for the shallow geothermal energy implementation in region by Entropy Weight Method and TOPSIS method

被引:190
作者
Li, Zhao [1 ]
Luo, Zujiang [1 ]
Wang, Yan [2 ]
Fan, Guanyu [3 ]
Zhang, Jianmang [3 ]
机构
[1] Hohai Univ, Sch Earth Sci & Engn, Nanjing 210098, Jiangsu, Peoples R China
[2] Jilin Jianzhu Univ, Changchun 130118, Jilin, Peoples R China
[3] Environm Geol Explorat Inst Jiangsu Prov, Nanjing 211102, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Suitable evaluation; Shallow geothermal energy; Entropy weight method; TOPSIS Method; ANALYTIC HIERARCHY PROCESS; HEAT-PUMP; GIS; GROUNDWATER; PREDICTION; EFFICIENCY; MODEL; MAPS;
D O I
10.1016/j.renene.2021.11.112
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Shallow geothermal energy suitability map presents the potential for implementation in a region. The potential for implementation depends on hydrogeology, geotechnical, geology environment, and geothermal characteristics. Plenty of scholars evaluate shallow geothermal energy by the algorithm combined Analytic Hierarchy Process and Index Overlap. But Analytic Hierarchy Process and Index Overlap, as knowledge driven methods, rely on the experts' experience. This research presents a data driven algorithm based on Entropy Weight Method and TOPSIS Method. The weights are calculated by the Entropy Weight Method and assigned to the TOPSIS model. The closeness coefficient could be calculated by TOPSIS model. The suitability potential is analysed by comparing the closeness coefficient. The algorithm is accomplished by coding a program using Matlab. The algorithm is also applied to Nantong, China. Depending on the principle of ground source heat pump system, the suitability evaluation system of the open loop system and the closed loop system are established, respectively. Hydro geology, geotechnical, geothermal, and geology environmental investigations are carried out to obtain the measured data and parameters for suitability analysis. The suitability maps are drawn in according with closeness coefficient. The algorithm is able to overcome the subjectivity of experts' experience. Compared with knowledge driven methods, the proposed algorithm tends to compare the relative potential in a region, rather than assess whether the site is suitable for SGE implementation. Consequently, it is more suitable for selecting the best field-site. (c) 2021 Published by Elsevier Ltd.
引用
收藏
页码:564 / 576
页数:13
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