建筑能源模拟及其在建筑性能优化中的应用:方法、工具和案例研究综述

IF 13 Q1 ENERGY & FUELS
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
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引用次数: 20

摘要

作为建筑领域最重要和最先进的碳减排技术之一,建筑性能模拟(BPS)在建筑能源建模(BEM)技术的有力支持下,在建筑节能设计、运营和改造方面发挥着越来越重要的作用。由于其多学科方法的深度融合,在建筑/系统/社区层面和规划/设计/运营阶段等多个尺度和阶段的应用中,研究人员、工具开发人员和实践者都面临着机遇和挑战。通过对近期研究的回顾,本文旨在提供一个清晰的图像,BEM如何在不同的建筑阶段和空间分辨率尺度上解决不同的研究问题,重点是目标和框架,建模方法和工具,适用性和可移植性。为了指导BEM在绩效驱动型建筑能源管理中的未来应用,我们将当前的研究趋势和未来的研究机会分为五个主题,跨越不同的阶段和层次:(1)针对新建筑和改造设计的性能驱动设计仿真;(2)基于模型的运行性能优化;(3)基于数字孪生数据测量的集成仿真;(4)支持城市能源规划的建筑仿真;(5)针对需求响应的建筑与电网交互建模。此外,还讨论了未来的研究建议,包括BEM的潜在应用,包括与占用和行为建模的集成,与机器学习的集成,模型不确定性的量化,以及与建筑监测系统的连接。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Building energy simulation and its application for building performance optimization: A review of methods, tools, and case studies

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.

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来源期刊
Advances in Applied Energy
Advances in Applied Energy Energy-General Energy
CiteScore
23.90
自引率
0.00%
发文量
36
审稿时长
21 days
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