K-12 SCHOOL BUILDINGS IN NEW YORK CITY
Young M Lee, Fei Liu, Estepan Meliksetian, Jane Snowdon, Michael Bobker
An integrated statistical method for computing energy performance metrics of buildings and visualizing the energy performance through spatial analysis is described. This technique combines the hierarchical multivariate regression models and the Variable Base Degree Day (VBDD) model to compute the overall energy performance indicator, and the energy performance indices of base load, heating load and cooling load for each building in a portfolio. Then the various energy performance metrics in the portfolio are selectively visualized on the associated Geographical Information System (GIS) based heat map. The method provides useful information for accurately assessing energy performance, benchmarking and identifying energy performance improvement opportunities in a large portfolio of buildings. The method has been successfully applied and deployed for K-12 school buildings in New York City.
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