LAUSR

Shallow geothermal energy (SGE) is a green, clean, and renewable energy source that is widely used for heating and cooling. However, hydrogeology conditions, thermophysical properties, geological environment conditions, and other factors influence the implementation of SGE projects. Making a suitability evaluation before implementing the SGE projects is necessary. The two most common methods of suitability evaluation are knowledge-driven and data-driven methods. The knowledge-driven method relies on expert experience. The data-driven method relies on criteria and lacks subjective analysis. To address this shortcoming, this study developed a comprehensive multicriteria decision analysis framework (CMCDAF) for SGE suitability evaluation. The framework comprehensively uses fuzzy analytic hierarchy process (FAHP), Shannon entropy, criteria importance through intercrieria correlation (CRITIC) and genetic algorithm to calulate weights. Then the technique for order preference by similarity to ideal solution (TOPSIS) and grey relation analysis(GRA) are used to rank the suitability of each node and select the most suitable area. To verify CMCDAF, the framework is used to evaluate the suitability of a ground-coupled heat pump (GCHP) system in the Yinchuan area. Results showed the evaluation framework is stable and effective. It has the advantages of avoiding the subjective and one-sided evaluation criteria weights, facilitating the selection of the most suitable areas. The evaluation framework also has the potential to be applied to other decision-making processes.