This paper presents a newly developed methodology aimed at assessing at national level the techno-economic potential of district heating (DH) based on renewables and excess heat sources. The novelty of the model lies in the use of an optimization approach to match heat demand and heat sources at large scale level, while keeping a high degree of spatial detail. Areas suitable for DH adoption are identified by minimizing heat delivery costs, and therefore by choosing the most economical technology between district heating and the alternative individual solution. The optimization approach, usually applicable at limited analytical scope because of the computational burden, is here adapted to large scale analysis through the introduction of novel methodological elements with which the network topology is simulated nationwide. The methodology applies to preliminarily identified maps of available heat sources and eligible heat demand, with the quantification of the latter including retrofitting and low connection rate scenarios. It then consists in two steps: connecting elements in a graph through triangulation and routing algorithms and optimizing connections to minimize the overall heat delivery costs, either by adopting district heating or individual heating systems. The whole methodology is based on open-source data and tools for broad applicability. The paper presents the elaborated methodology together with the application of the entire model to Italy. The outcome is a map of the potential district heating systems identified with significant spatial detail nationwide. A four-fold

Assessing district heating potential at large scale: Presentation and application of a spatially-detailed model to optimally match heat sources and demands

Fattori F.;
2024-01-01

Abstract

This paper presents a newly developed methodology aimed at assessing at national level the techno-economic potential of district heating (DH) based on renewables and excess heat sources. The novelty of the model lies in the use of an optimization approach to match heat demand and heat sources at large scale level, while keeping a high degree of spatial detail. Areas suitable for DH adoption are identified by minimizing heat delivery costs, and therefore by choosing the most economical technology between district heating and the alternative individual solution. The optimization approach, usually applicable at limited analytical scope because of the computational burden, is here adapted to large scale analysis through the introduction of novel methodological elements with which the network topology is simulated nationwide. The methodology applies to preliminarily identified maps of available heat sources and eligible heat demand, with the quantification of the latter including retrofitting and low connection rate scenarios. It then consists in two steps: connecting elements in a graph through triangulation and routing algorithms and optimizing connections to minimize the overall heat delivery costs, either by adopting district heating or individual heating systems. The whole methodology is based on open-source data and tools for broad applicability. The paper presents the elaborated methodology together with the application of the entire model to Italy. The outcome is a map of the potential district heating systems identified with significant spatial detail nationwide. A four-fold
2024
District heating potential; Matching heat demand and sources; Optimization algorithm; Routing algorithm; GIS; Energy graph
Spirito, G.; Dénarié, A.; Fattori, F.; Muliere, G.; Motta, M.; Persson, U.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2178811
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