Abstract
Decarbonisation and a transition towards sustainable energy systems in cities are key elements of the United Nations sustainability goal. Large-scale district heating networks sourced by excess heat or renewable energy allow to effectively transform building-related energy systems. This study proposes two different approaches for modelling load curves in large-scale district heating networks: 1) physics-based static energy balance model 2) data-driven regression model trained and adjusted on measured load curves. The load curves generated by application of these two approaches are compared with the actual load of an urban district heating network in Geneva, Switzerland. Both models allow to recreate the actual load curve of the district heating network, however with lower accuracy for higher time resolution in the case of the physics-based model. The physics-based static model can be used to simulate the demand and generate load curves of sufficient quality at monthly and daily resolution. For an hourly load curve, it is recommended to use the data-driven regression model if consumption data of the network is available.
Highlights
Decarbonisation represents a major challenge across all sectors including the built environment with its share of 40% of the total final energy demand [1]
This study proposes two different approaches for modelling load curves in large-scale district heating networks: 1) physics-based static energy balance model 2) data-driven regression model trained and adjusted on measured load curves
This is reflected in the Sustainability Development Goals (SDG) set by the United Nations which, among others, concern the transition to sustainable cities (SDG 11) while ensuring access to affordable and clean energy (SDG 7) as well as an overall reduction of greenhouse gas (GHG) emissions (SDG 13) [2]
Summary
Decarbonisation represents a major challenge across all sectors including the built environment with its share of 40% of the total final energy demand [1] This is reflected in the Sustainability Development Goals (SDG) set by the United Nations which, among others, concern the transition to sustainable cities (SDG 11) while ensuring access to affordable and clean energy (SDG 7) as well as an overall reduction of greenhouse gas (GHG) emissions (SDG 13) [2]. The installation of district heating systems requires labour intensive work as well as very high upfront investment cost When designing these networks, it is crucial to ensure a comprehensive energy planning which entails an estimation of the expected heat load during operation.
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call