Development of Data-driven Models for Thermal Dynamic Analysis of Buildings

  • Author / Creator
    Wang, Zequn
  • Data-driven modelling has been widely applied in building operation optimization, energy management, ongoing commissioning, and so on. This thesis presents a comprehensive study of data-driven modelling for analysis of building thermal dynamics. First, three types of data-driven models, namely, transfer-function based models (TF models), resistor-capacitor based models (RC models), and artificial-intelligence based models (AI models) are critically reviewed, including their formulations, interpretability of physical meanings, and prediction accuracy. Fundamental concepts and common techniques for model training and selection are also presented. By applying the data-driven approach to a low-energy house using on-site monitored data, features of different data-driven models are further demonstrated. It is found that, in general, RC models are the most suitable for physical interpretation.Then, a simple yet effective methodology is proposed to obtain reliable RC models for building thermal dynamic analysis. In this methodology, complex preliminary model structures are first created based on physical principles and then simplified by progressively removing non-identifiable parameters. Two important techniques are adopted in the simplification process: 1) a genetic algorithm is employed during model training to ensure the satisfactory fitting ability of large model structures; 2) asymptotic confidence intervals are calculated for parameter estimates and used to define parameter non-identifiability. The methodology is illustrated using a case study of the low energy house. This case study shows that the obtained RC model can predict room temperatures with satisfactory accuracy, and the estimated parameters are physically interpretable. Finally, the estimated RC model parameters are related to building configurations, and the model is used to evaluate the design of the low energy house, with a focus on the adequacy and effectiveness of its thermal energy storage (TES) system. The influences of different parameter values on energy consumption and temperature fluctuations are compared. The findings show that the current TES system (i.e., the concrete wall and slabs) is designed with sufficient thickness and surface area. Decreasing its thickness or surface area will result in considerably more fluctuations of indoor air temperatures. Regarding energy consumption for space heating, varying the design would not result in significant improvement. The RC model is also used in evaluating other aspects of the thermal performance of the house, such as the overall thermal transmission of the envelop, the equivalent solar aperture, and the relative significance of different energy flow paths.

  • Subjects / Keywords
  • Graduation date
    Spring 2019
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
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