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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 expansion is envisaged, covering 12% of the national heat demand with renewables- and excess heat- based district heating. © 2024 The Authors. Published by Elsevier Ltd., Funding: AIRU - the Italian District Heating Association - and Utilitalia - the Italian association of multiutilities.

The economical sustainability of DH compared to individual heating systems depends on the cost of producing heat, transporting and distributing it. Assessing economically sustainable potential of district heating DH thus requires the ability to combine this costs, detecting the relative distance of sources and demands and the density of demand, comparing it to the alternative solution. In this work we present an open model, based on the Oemof modelling framework, which is able to take into account the possibility of connecting sources and demands on national scale level with a high spatial resolution. The model considers the investment and operating costs of production and distribution of heat in competition with the individual heating systems costs specific to each area. The end result is the most economically viable heat supply configuration, identifying the demand shares where the most cost-effective solutions are individual systems or DH and its composition in terms of energy sources. The model is part of the method used for the assessment of district heating potential in Italy. The latter is based on GIS maps of both energy demand, waste and renewable heat sources. Of the 114 TWh of potential demand for DH, 38 TWh are those that the optimisation suggests could be economically served by DH. The composition is mostly waste heat, 22 TWh, geothermal heat, 11 TWh and a minority of solar thermal, 2 TWh with 3 TWH of natural gas CHP back up.

This work aims at developing a methodology for the assessment of district heating (DH) potential through the mapping of energy demand and waste heat sources. The presented method is then applied to the Metropolitan City of Milano as a case study in order to investigate the current and, especially, the future sustainability of DH with the foreseen building refurbishment and consequent heat demand reduction. The first step is the identification of the areas the most interesting from a heat density and an economic point of view through a clustering algorithm, in which lies the main novelty of the work. The potential is then assessed by investigating their synergy with the available heat sources, which are mapped and analyzed in terms of recoverable thermal energy and costs. In future scenarios with foreseen heat demand reduction, low-temperature networks and excess heat sources are considered, such as metro stations and datacenters, together with the conventional sources, such as thermoelectric plants. The outcomes prove that lower heat demand corresponds to higher network costs with consequently reduced district heating potential but also prove that the properties of low-temperature district heating can potentially compensate for the drop in its cost-effectiveness. Another interesting finding is that the renovation of buildings in an area should be not performed evenly but with criteria; for instance, in synergy with DH diffusion. © 2021 by the authors. Licensee MDPI, Basel, Switzerland., Funding Agency:Italian district heating association, AIRUItalian association of multiutilities, UTILITALIA, in the framework of the project "Valutazione del potenziale di diffusione del teleriscaldamento efficiente su territorio nazionale"EIT Climate-KIC in the framework of the project "Deep Demonstration: Milan" (DDMI)Project "Analysis on new models for 4GDH in Italy: an innovative tool for the fast integration of RES sources?"

The evaluation of the district heating network investment costs requires the knowledge of its topology. However, when assessing district heating potential, the topology is not known a priori and a simulation is required. One method for modelling future heat networks involves the use of Minimum Spanning Tree, from the graph theory. In this work, the MST is used together with real networks lengths to elaborate an updated equation describing the effective width in correlation with the number of building ratio instead of plot ratio. The reason motivating the use of simulated networks lies in the goal of analysing sparse areas where there’s a general lack of data. In this study, the census cells vertexes and local roads layout are used as inputs for the application of the MST in order to simulate DH network layouts in areas where DH is not present. The method has been validated by running simulations in areas where DH is already present, allowing the comparison of the respective lengths. The validation shows a variable but systematic overestimation of the simulated lengths. The study of the error has brought to the definition of a correlation between accuracy of results and the share of buildings with centralized heating systems suitable for DH connection. The updated version of the effective width confirms the exponential tendency and gives higher results for Italian cities then for Scandinavian ones, showing an important impact of the city structure in the curve. The city of Milano is finally used as a case study to show the effects of using the updated effective width curve.