ESTIMATION OF THERMAL PARAMETERS OF BUILDINGS THROUGH INVERSE MODELING AND CLUSTERING FOR A PORTFOLIO OF BUILDINGS
Lianjun An, Raya Horesh, Young T . Chae, Young M. Lee
Estimating heat transfer parameters of building enve- lope for existing buildings is challenging due to limited data from sensors and meters. In this study, we have de- veloped a method for estimating heat transfer parameters of building envelope through clustering technique with in- verse modeling for portfolio of buildings. Firstly, we de- rived a static heat transfer model from a system of dy- namic equations by integrating the equations for differ- ent time periods. The model links monthly energy us- age with cooling and heating loads, and latent heat loads. Secondly, temporal data from a building was used to es- timate the overall heat transfer parameters. Thirdly, a clustering scheme was developed to segment all buildings in the portfolio into different clusters based on similar- ity criteria. The overall heat transfer parameters are then separated into different heat transfer coefficients for wall, roof and windowusing data from multiple buildings in the same cluster. We describe an application of this method to K-12 school buildings in the New York City.
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