Design-Build-Operate Energy Information Modeling for Occupant-Oriented Predictive Building Control
Green buildings aim to save land, energy, water, and material, as well as to create a healthy and comfortable environment for their occupants throughout the life-cycle. One of the primary goals for the design of green buildings is reducing operating energy costs. Mainly due to the energy performance requirements of various green building rating systems, building energy modeling (BEM) is being increasingly used in the building industry, which definitely improves building energy efficiency through code and standard compliances. However, as a scientific and standardized method, using BEM can provide far more benefits than just code and standard compliances. BEM can be used for many other purposes at different stages of the building life-cycle. This dissertation has developed and demonstrated the concept of Design-build-operate Energy Information Modeling (DBO-EIM) infrastructure, which can be used at different stages of the building life-cycle to improve energy and thermal comfort performance. The whole process is tested using a medium-size office building in Pittsburgh, PA. At the design stage, for the purpose of design decision making a parametric BEM process is demonstrated in the test-bed building. The case study results show that the proposed design case building has better energy performance than the baseline, design alternatives, and various benchmark buildings. At the commissioning and early operation stages, an EnergyPlus model calibration method is introduced using empirical data that are collected from the test-bed building. The final calibrated model has a mean biased error of 1.27% and a coefficient of variation of the root mean squared error of 6.01%. This calibration method provides a scientific and systematic framework to conduct high accuracy EnergyPlus model calibration. At the operation stage, on the basis of the calibrated EnergyPlus model, an occupant-oriented mixed-mode EnergyPlus predictive control (OME+PC) system is developed. Given the Pittsburgh weather context and current operation assumptions, the simulation results suggest a potential 29.37% reduction in annual HVAC energy consumption. In addition, OME+PC enables building occupants to control their thermal environment through an internet-based dashboard. Several important research findings are also concluded from the studies in the DBO-EIM development process that may benefit future work in the building science realm, including the development of an occupant behavior modeling method, the integration of the real-time building operation data collection system, an passive cooling control simulation study, and an occupant subjective thermal comfort field study. In order to show the applicability of the Design-build-operation Energy Information Modeling infrastructure, the process is demonstrated again in a generic Department of Energy prototype medium office EnergyPlus model. Step-by-step instructions and computation time are documented to facilitate future studies. In summary, this dissertation has demonstrated that an original design stage EnergyPlus model can be updated and utilized through the entire DBO-EIM process. Compared to typical building operation, implementing this process can achieve better energy performance and maintain occupant thermal comfort.