Abstract
District heating (DH) has a major potential to increase the efficiency, security, and sustainability of energy management at the community scale. However, there is a huge challenge for decision makers due to the lack of knowledge about thermal energy demand during a year. Thermal energy demand is strongly dependent on the outdoor temperature, building area, and activities. In this context, this paper presents an innovative monthly thermal energy mapping method to calculate and visualize heat demand accurately for various types of buildings. The method includes three consecutive phases: (i) calculating energy loss, (ii) completing a dataset that includes energy and building information, and (iii) generating the monthly heat demand maps for the community. Determining the amount of demand and the best location for energy generators from the perspective of energy efficiency in a DH system in an urban context is one of the important applications of heat maps. Exploring heat demand characteristics and visualizing them on maps is the foundation of smart DHs.
Highlights
Cities are responsible for more than 50% of total global energy demand [1], while a huge portion of this demand is utilized for thermal purposes to provide comfortable indoor temperatures as well as domestic hot water in buildings [2,3]
In ArcGIS, the district heat balance (DHB) tool was linked with energy building database (EBD)
The results show that the heat demand of Trinity College Dublin (TCD) in January was approximately 2.5 times greater than that in July
Summary
Cities are responsible for more than 50% of total global energy demand [1], while a huge portion of this demand is utilized for thermal purposes to provide comfortable indoor temperatures as well as domestic hot water in buildings [2,3]. The developed methodology helps to manage the heat demand in shorter time periods, and this achievement increases the efficiency as well as the security of a DHN. This method can improve knowledge in the field of DHN, moving the field toward smart DHN (SDHN). Determination of the best location for central heat generators in an urban context from the perspective of energy efficiency is one of the basic advantages of the heat maps Assessing the criteria, such as minimum heat loss and costs and maximum efficiency, as well as the optimum land cost to determine the best location for heat generators, could be investigated in future studies
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