Litcius/Paper detail

District energy models: A comparative assessment of features and criteria for tools selection

Yingqing Xu, Jaqueline Litardo, Claudio Del Pero, Fabrizio Leonforte, Paola Caputo

2024Energy and Buildings14 citationsDOIOpen Access PDF

Abstract

In order to reach the goal of reducing emissions by at least 55% by 2030 and achieving decarbonization by 2050, the increasing emphasis on net-zero energy buildings/districts encourages the development of advanced modelling tools to better design and manage district energy systems. This paper presents a critical review of such tools, considering the different detail level of building data and analysing the reliability of obtainable results. Initially, it elaborates on the characteristics of data resources and formats, energy demand representations of individual buildings, and the interconnection between individual buildings and districts, which are subsequently used to analyse the accuracy level of case studies. Then, the most used evaluation criteria for comparing tools are revised. Five categories are defined: (i) input data and representation of buildings, (ii) district energy system components (i.e., generation, distribution, storage), (iii) outdoor environment, (iv) user behaviour and mobility, and (v) validation and licencing. 29 tools suitable for district energy systems modelling are critically analysed with a focus on accuracy and validation, as well as on their application and future perspectives. The results highlighted the importance of data reliability in modelling approaches and results. Difficulties in achieving accurate results included robust data acquisition, interconnection among individual buildings, outdoor environment, and modelling approaches. The results also emphasized that, although no tools can cover all the possible features at the current stage, this study can support the selection of the most suitable tool for specific applications at the district scale.

Topics & Concepts

Selection (genetic algorithm)Energy (signal processing)Computer scienceOperations researchEngineeringStatisticsArtificial intelligenceMathematicsIntegrated Energy Systems OptimizationHybrid Renewable Energy SystemsBuilding Energy and Comfort Optimization