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WIREs Energy Environ.
Impact Factor: 2.889

Uses of dynamic simulation to predict thermal‐energy performance of buildings and districts: a review

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The design of sustainable constructions also resilient to climate change has become a challenging issue given the increasing greenhouse emissions rate imputable to the built environment in urban areas. In this context, dynamic simulation models represent a suitable tool to support the design from very preliminary phases, since they allow an accurate prediction of the constructions requirements, their environmental performance, and indoor comfort conditions for their occupants. Therefore, starting from specific inputs, that is, weather conditions, construction technologies, materials, energy systems, operation settings, occupancy, and so forth, it is possible to estimate the realistic building energy performance. Moreover, the calibration procedures allow making the model even more representative of the field conditions of a construction. Given the massive progress carried out by the scientific community during the last decades, this paper presents a comprehensive review of the different building dynamic simulation approaches and available tools. While previous review studies focused on single separated aspects of dynamic simulations approaches, that is, calibration methods, software, simulation of single building energy systems, the aim of the present review is to propose a more holistic approach by investigating the recent scientific progress in simulating realistic dense urban environments. In this view, the review focus bridges the gap between the simulation at single‐building level and simulation at the increasingly important neighborhood scale by showing the multiple benefits deriving from using dynamic simulation tools at district level, for a more reliable investigation of building performance in their urban context, where more than 50% of the global population worldwide currently lives.

Motivation and contents of the work.
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Framework of the house building simulation system [234].
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The developed framework to consider the influence of wind sheltering on building dynamic simulation models [221].
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System boundaries and approach of the model [212].
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Spatial, temporal, and contextual fields of application of the behavior research and stakeholders [199].
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Simplified scheme of the simulation model in TRNSYS [194].
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Matrix indicating the capabilities of a selection of software tools and packages [98].
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Comparison of software in terms of their capability to fulfill the requirements of the proposed software framework. Check marks indicate fulfilment of the requirement. Check marks in parenthesis indicate that software include the specific feature without satisfying the requirement [10].
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Building energy simulation models [192].
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Flow chart of the structure of the review.
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Number of documents about a) building dynamic simulation and (b) district dynamic simulation grouped with respect to the affiliation institution of the first author as indexed in Scopus (2017‐04‐24).
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Number of documents about a) building dynamic simulation and (b) district dynamic simulation grouped with respect to the country of the first author as indexed in Scopus (2017‐04‐24).
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Number of documents about a) building dynamic simulation and (b) district dynamic simulation clustered according to the publication source as indexed in Scopus (2017‐04‐24).
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Subjects of the documents related to (a) building dynamic simulation and (b) district dynamic simulation as indexed by Scopus database (2017‐04‐24).
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Number of documents about (a) building dynamic simulation and (b) district dynamic simulation as indexed in the Scopus database in the last sixteen years (2017‐04‐24).
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