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From White to Black-Box Models: A Review of Simulation Tools for Building Energy Management and Their Application in Consulting Practices
Department of Mechanical Engineering, École de Technologie Supérieure, Montreal, QC H3C 1K3, Canada;.
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Applied Thermodynamics and Refrigeration.ORCID iD: 0000-0001-7354-6643
Department of Mechanical Engineering, École de Technologie Supérieure, Montreal, QC H3C 1K3, Canada;.
2024 (English)In: Energies, E-ISSN 1996-1073, Vol. 17, no 2, article id 376Article, review/survey (Refereed) Published
Abstract [en]

Buildings consume significant energy worldwide and account for a substantial proportion of greenhouse gas emissions. Therefore, building energy management has become critical with the increasing demand for sustainable buildings and energy-efficient systems. Simulation tools have become crucial in assessing the effectiveness of buildings and their energy systems, and they are widely used in building energy management. These simulation tools can be categorized into white-box and black-box models based on the level of detail and transparency of the model’s inputs and outputs. This review publication comprehensively analyzes the white-box, black-box, and web tool models for building energy simulation tools. We also examine the different simulation scales, ranging from single-family homes to districts and cities, and the various modelling approaches, such as steady-state, quasi-steady-state, and dynamic. This review aims to pinpoint the advantages and drawbacks of various simulation tools, offering guidance for upcoming research in the field of building energy management. We aim to help researchers, building designers, and engineers better understand the available simulation tools and make informed decisions when selecting and using them.

Place, publisher, year, edition, pages
MDPI AG , 2024. Vol. 17, no 2, article id 376
Keywords [en]
BES, black-box, building energy, deep learning, machine learning, simulation tool, white-box
National Category
Building Technologies Energy Engineering
Identifiers
URN: urn:nbn:se:kth:diva-343161DOI: 10.3390/en17020376ISI: 001149088200001Scopus ID: 2-s2.0-85183330410OAI: oai:DiVA.org:kth-343161DiVA, id: diva2:1836063
Note

QC 20240208

Available from: 2024-02-08 Created: 2024-02-08 Last updated: 2024-02-08Bibliographically approved

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Madani Larijani, Hatef

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