Potential zones identification for district cooling system: A GIS-based multi-criteria assessment method incorporating cooling demand mapping

Abstract

The district cooling system (DCS) is seen as a promising cooling solution for its flexibility and high efficiency. Identifying suitable zones for DCS construction is one of the major challenges in implementing DCS, as the characteristics of the selected zones significantly impact the performance and benefits of DCS. This paper presents a geographic information system (GIS) based two-stage assessment method to rapidly determine potential zones for DCS from a large-scale. Firstly, employing a top-down method to spatially assess cooling demand. Secondly, three novel indicators (RCI, Rday, Rcap) for DCS cooling intensity, cooling duration, and capacity utilization rate evaluation are proposed, and a multi-criteria decision-making method is applied to identify potential zones for DCS implementation. Based on the proposed method, the cooling demand in China is mapped. Shanghai, Guangzhou, Chongqing, and Shenzhen are identified as the four cities with the highest cooling demand. Furthermore, the potential zones for DCS in Guangzhou are assessed. The results indicate that zones with the highest potential exhibit high robustness against weight uncertainty and are primarily concentrated in densely populated areas. The proposed indicators and method could provide support for macro-level planning of DCS to effectively improve the decision-making efficiency.