Monitoring-based optimization-assisted calibration of the thermal performance model of an office building

Abstract

This paper reports on a case study of monitoring-based optimization-assisted calibration of a thermal simulation model for an office building. Such a calibrated model could effectively support the operation of the building. For example, it could be deployed toward diagnostics, fault detection, preventive maintenance, and a model-based building systems control. To explore the potential of optimization-assisted calibration in a realistic setting, we selected an actual office. This facility is equipped with a monitoring infrastructure, which provides various streams of data about outdoor and building conditions. Our intention was to deploy data obtained via the monitoring system to both populate the initial simulation model and to maintain its fidelity through a systematic calibration process. The initial simulation model used, asides from static physical building information, dynamic monitored data including electrical plug loads, occupancy, and state of devices such as luminaires and windows. In the optimization-assisted calibration, a weighted cost function was defined, which addressed the bias error between measured and simulated indoor temperature and the goodness of fit of the model. A limited number of model input parameters were varied in the optimization process toward minimizing the cost function. The resulting calibrated model showed noticeable accuracy improvement and the optimization-assisted method displayed a promising potential as a systematic calibration method in model-based predictive systems control.