Uncertainty and sensitivity analysis of cooling and heating loads for building energy planning

• Published in: Journal of Building Engineering Vol. 45; p. 103440
• Main Authors: Zhu, Li, Zhang, Jiqiang, Gao, Yuzhe, Tian, Wei, Yan, Zhexing, Ye, Xueshun, Sun, Yong, Wu, Cuigu
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.01.2022
• Subjects: Building energy planning; Cooling and heating loads; Meta modeling sensitivity analysis; Monte Carlo method; Uncertainty analysis; Meta modeling sensitivity analysis; Monte Carlo method; Cooling and heating loads; Uncertainty analysis; Building energy planning
• ISSN: 2352-7102; 2352-7102
• DOI: 10.1016/j.jobe.2021.103440

It has become crucial to investigate the uncertainty and sensitivity of building loads (peak cooling load, peak heating load, annual cooling demand and annual heating demand) for meeting the risk assessment of building energy planning. Therefore, a new Monte Carlo (MC) method based on building performance simulation (BPS) is proposed to solve the problem of building loads forecasting at planning phase. Furthermore, the sensitivity of building loads is examined using two global sensitivity analysis (GSA) methods, including meta modeling method based on tree Gaussian process (TGP) and regression method based on standard regression coefficient (SRC). Finally, a case study of office building is conducted. The results show that the MC method constructed by the combination of R language platform and EnergyPlus software can generate models rapidly and simulate accurately building loads. Note that it is necessary to assess the stability of results as a function of sample size from uncertainty analysis in applying the MC method into building loads assessment. The TGP-based GSA method is applicable to identify and analyze key variables affecting building loads. It is recommended that at least two inherently different GSA methods should be applied to provide robust sensitivity results. Moreover, this study also provides insight on building energy planning and energy conservation design according to the results of uncertainty and sensitivity analysis for case study. •A new MC method based on BPS has been developed for forecasting building cooling and heating loads at planning phase.•The TGP-based GSA method is applicable to identify and analyze key variables affecting building loads.•A case study of an office building in Tianjin, China was conducted using the proposed methods.•The main influencing factors of office building loads are identified and analyzed by using TGP-based method and SRC method.