Building energy simulation and its application for building performance optimization : A review of methods, tools, and case studies

Yiqun Pan*, Mingya Zhu, Yan Lv, Yikun Yang, Yumin Liang, Ruxin Yin, Yiting Yang, Xiaoyu Jia, Xi Wang, Fei Zeng, Seng Huang, Danlin Hou, Lei Xu, Rongxin Yin, Xiaolei Yuan

*Corresponding author for this work

Research output: Contribution to journalReview Articlepeer-review

13 Citations (Scopus)
98 Downloads (Pure)


As one of the most important and advanced technology for carbon-mitigation in the building sector, building performance simulation (BPS) has played an increasingly important role with the powerful support of building energy modelling (BEM) technology for energy-efficient designs, operations, and retrofitting of buildings. Owing to its deep integration of multi-disciplinary approaches, the researchers, as well as tool developers and practitioners, are facing opportunities and challenges during the application of BEM at multiple scales and stages, e.g., building/system/community levels and planning/design/operation stages. By reviewing recent studies, this paper aims to provide a clear picture of how BEM performs in solving different research questions on varied scales of building phase and spatial resolution, with a focus on the objectives and frameworks, modelling methods and tools, applicability and transferability. To guide future applications of BEM for performance-driven building energy management, we classified the current research trends and future research opportunities into five topics that span through different stages and levels: (1) Simulation for performance-driven design for new building and retrofit design, (2) Model-based operational performance optimization, (3) Integrated simulation using data measurements for digital twin, (4) Building simulation supporting urban energy planning, and (5) Modelling of building-to-grid interaction for demand response. Additionally, future research recommendations are discussed, covering potential applications of BEM through integration with occupancy and behaviour modelling, integration with machine learning, quantification of model uncertainties, and linking to building monitoring systems.

Original languageEnglish
Article number100135
JournalAdvances in Applied Energy
Publication statusPublished - Jun 2023
MoE publication typeA2 Review article, Literature review, Systematic review


  • Building performance simulation
  • Building-to-grid
  • Digital twin
  • Operational optimization
  • Performance-driven design


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