A mixed-mode building energy model for performance evaluation and diagnosis of existing buildings

Building level energy models are important to provide accurate energy consumption prediction for building performance diagnosis at building level as well as energy efficiency assessment of retrofitting alternatives for building performance upgrading. However, it is a great challenge to establish building energy models of existing buildings for long-term energy performance prediction only using short-term monitoring operation data. In this study, a mixed-mode building energy model is proposed to describe building system for thermal performance prediction at the building level. The model includes two parts. One part is the simplified energy models (3R2C) of building envelopes. The parameters of these simplified models are determined by comparing the frequency characteristics of those simplified models and their theoretical frequency characteristics based on the easily available detailed physical properties of exterior walls and roof. The other part is the simplified 2R2C model for building internal mass, whose detailed physical properties are very difficult to obtain. The parameters of the building internal mass model are optimised using short-term monitored operation data. A genetic algorithm estimator is developed to optimise these parameters. The parameter optimisation of the simplified building internal mass model (2R2C) and the mixed-mode building energy model are validated in a high rising commercial office building under various weather conditions. An application of this model for performance evaluation of alternative control strategies is illustrated briefly.