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

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.

Automated summary

This study proposes a data-driven algorithm for assessing the suitability of shallow geothermal energy based on the Entropy Weight Method and TOPSIS Method. The algorithm calculates weights using the Entropy Weight Method and assigns them to the TOPSIS model to determine the closeness coefficient. The algorithm overcomes the subjectivity of expert experience and is more suitable for selecting the best field-site. The algorithm was applied to Nantong, China and produced suitability maps based on the closeness coefficient.