Estimating building thermal properties by integrating heat transfer inversion model with clustering and regression techniques for a portfolio of existing buildings

A system for determining heat transfer parameters of a portfolio of existing buildings, comprising:

• a processor;
• a dynamic model characterizing heat and moisture transfer through building envelope;
• a static heat transfer model transformed from the dynamic equations, the static heat transfer model generated by integrating the dynamic equations over a time period covering a season;
• an inverse parameter estimation module operable to execute on the processor and further operable to perform inverse parameter estimation based on at least the static heat transfer model, energy usage data associated with the existing buildings over the time period, dimension information associated with the existing buildings, data associated with one or more characteristics of the existing buildings, temperature information during the time period, and humidity information during the time period, the inverse parameter estimation module operable to determine the heat transfer parameters associated with the overall building envelope based on the inverse parameter estimation;
• a clustering module operable to cluster the existing buildings into two or more clusters of buildings based on the dimension information associated with the existing buildings and the data associated with one or more characteristics of the existing buildings;
• a regression model associated with each of the clusters of buildings, the regression model describing the heat transfer parameters associated with the overall building envelop in terms of individual components of the building envelop;
• and
• a module operable to estimate individual heat transfer parameters associated with the individual components of the building envelope based on the regression model and the heat transfer parameters associated with the overall building envelope.

A computer readable storage medium storing a program of instructions executable by a machine to perform a method of determining heat transfer parameters of a portfolio of existing buildings, comprising:

• generating dynamic equations describing heat and moisture transfer through building envelope;
• generating a static heat transfer model by transforming the dynamic equations, the static heat transfer model generated by integrating the dynamic equations over a time period covering a season;
• quantifying all terms for the generated static heat transfer model based on energy usage data associated with the existing buildings over the time period, dimension information associated with the existing buildings, data associated with one or more characteristics of the existing buildings, temperature information during the time period, and humidity information during the time period;
• estimating coefficients of the terms by fitting calculated energy usage with the observed energy usage over multiple time periods, the estimated coefficients representing aggregated quantities of multiple physical properties of the building envelope;
• clustering the existing buildings into two or more clusters of buildings based on a physical similarity associated with one or more characteristics of the existing buildings;
• developing a regression model for each of the clusters of buildings, the regression model describing how the aggregated quantities mathematically depend on the multiple physical properties of the building envelope;
• and
• estimating individual heat transfer parameters associated with individual components of the building envelope based on the regression model and the estimated coefficients representing aggregated quantities of multiple physical properties of the building envelope.