Dynamic simulation-based surrogate model for the dimensioning of building energy systems

Abstract

In recent decades, building design and operation have been an important field of study, due to the significant share of buildings in global primary energy consumption and the time that most people spend indoors. As such, multiple studies focus on aspects of building energy consumption and occupant comfort optimization. The scientific community has discerned the importance of operation optimization through retrofitting actions for on-site building energy systems, achieved by the use of simulation techniques, surrogate modeling, as well as the guidance of existing building performance and indoor occupancy standards. However, more knowledge should be attained on the matter of whether this methodology can be extended towards the early stages of thermal system and/or building design. To this end, the present study provides a building thermal system design optimization methodology. A data set of minimum thermal system power, for a typical range of building characteristics, is generated, according to the criterion of occupant discomfort in degree hours. Respectively, a surrogate model, providing a configurable correlation of the above set of thermal system dimensioning solutions is developed, using regression model fitting techniques. Computational results indicate that such a model could provide both desirable calculative simplification and accuracy on par with existing respective thermal load calculation standards and simplified system dimensioning methods.