Method multi-criteria decision-making method for site selection analysis and evaluation of urban integrated energy stations based on geographic information system

As an important carrier of multi-energy coupling of regional integrated energy system, the integrated energy station integrates a variety of energy coupling devices, which can fulfill interconnection and complementarity of energy between regions and enhance the economic and environmental benefits of energy use. In the planning of integrated energy stations, it is necessary to consider the characteristics of regional resource endowments and load energy consumption. In this paper geographic information system (GIS) is introduced into the site selection planning of integrated energy stations, and a location decision model is built based on GIS & improved TOPSIS. In order to verify this for the feasibility of the model, Tianjin, China is selected as a representative case for empirical research. First, according to Chinese national standards and local planning requirements, GIS is adopted to initially screen the distribution and area of exclusion areas and viable areas for construction in the study area. Secondly, a comprehensive evaluation index system is established for nature, economy and society, in which the AHP method is used for calculate the weight of each index to obtain the final optimal alternative with the integration of the GIS geographic layer overlay function. Finally, the improved TOPSIS model is used to rank the alternatives and obtain the ranking results. Sensitivity analysis and comparative analysis is conducted on the ranking results, indicating a higher priority of selecting sites A1, A4, A5 and A11. Analysis result effectively verifies that the improved TOPSIS method can improve the accuracy of the site selection decision for integrated energy stations. This paper can provide support for the site selection and layout of integrated energy stations, effectively improve the decision-making level and work efficiency of decision-makers, and enrich the application space of GIS methods in the energy field.