APPARATUS AND METHOD FOR FINE-GRAINED WEATHER NORMALIZATION OF ENERGY CONSUMPTION BASELINE DATA

摘要

An apparatus for estimating a building's energy consumption, including thermal response processor and a regression engine. The thermal response processor generates energy use data sets, each having energy consumption values along with corresponding time and outside temperature values. The consumption values within each of the data sets are shifted by one of a plurality of lag values relative to the time and temperature values, where each of the plurality of lag values is different from other lag values. The thermal response processor performs a regression analysis on each of the energy use data sets to yield corresponding regression model parameters and a corresponding residual. The thermal response processor determines a least valued residual from all residuals yielded by the regression engine, the least valued residual indicating an energy lag for the building, and regression model parameters that correspond to the least valued residual are employed to estimate the energy consumption.

主权项

1. An apparatus for estimating energy consumption of a building as a function of outside temperature, the apparatus comprising:
a thermal response processor, configured to generate a plurality of energy use data sets for the building, each of said plurality of energy use data sets comprising energy consumption values along with corresponding time and outside temperature values, wherein said energy consumption values within said each of said plurality of energy use data sets are shifted by one of a plurality of lag values relative to said corresponding time and outside temperature values, and wherein each of said plurality of lag values is different from other ones of said plurality of lag values; and a regression engine, coupled to said thermal response processor, configured to receive said plurality of energy use data sets, and configured to perform a regression analysis on said each of said plurality of energy use data sets to yield corresponding regression model parameters and a corresponding residual; wherein said thermal response processor determines a least valued residual from all residuals yielded by said regression engine, said least valued residual indicating an energy lag for the building, and regression model parameters that correspond to said least valued residual are employed to estimate the energy consumption.