System for weather induced facility energy consumption characterization

Abstract

A method for characterizing buildings, including generating energy use data sets for each of the buildings, each of the energy use data sets comprising energy consumption values along with corresponding time and outside temperature values, where the energy consumption values within each of the sets are shifted by one of a plurality of lag values relative to the corresponding time and outside temperature values, and where each of the plurality of lag values is different from other ones of the plurality of lag values; performing a regression analysis on the each of the plurality of energy use data sets to yield corresponding regression model parameters and a corresponding residual; determining a least valued residual from all residuals yielded by the regression engine, the least valued residual indicating a corresponding energy lag for the each of the buildings; and categorizing the buildings into types according to similar energy lags.

What is claimed is: 
     
         1 . A building characterization apparatus, comprising:
 a building lag optimizer, configured to receive identifiers for buildings, and configured to generate energy use data sets for each of said buildings, each of said 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 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 configured to perform a regression analysis on said each of said energy use data sets to yield corresponding regression model parameters and a corresponding residual, and configured to determine a least valued residual from all residuals yielded, said least valued residual indicating a corresponding energy lag for said each of said buildings, and regression model parameters that correspond to said least valued residual; and   a facility processor, coupled to said building lag optimizer, configured, for said each of said buildings, to receive said corresponding energy lag, and configured to categorize said plurality of buildings in types according to similar energy lags.   
     
     
         2 . The apparatus as recited in  claim 1 , wherein said plurality of lag values indicates shifts of said energy consumption values to different time and outside temperature values. 
     
     
         3 . The apparatus as recited in  claim 1 , wherein said corresponding time values are less than or equal to said similar energy lags. 
     
     
         4 . The apparatus as recited in  claim 1 , wherein said corresponding time values comprise hourly values and said plurality of lag values spans a 24-hour period. 
     
     
         5 . The apparatus as recited in  claim 1 , wherein said similar energy lags comprise energy lags having the same value. 
     
     
         6 . The apparatus as recited in  claim 1 , wherein said similar energy lags comprise energy lags within a range of values. 
     
     
         7 . The apparatus as recited in  claim 1 , wherein said each of said energy use data sets comprises a first portion of a corresponding each of a plurality of baseline energy use data sets, and wherein required energy consumption values resulting from shifts are taken from a second portion of said corresponding each of a plurality of baseline energy use data sets. 
     
     
         8 . An apparatus for characterizing buildings, the apparatus comprising:
 a building lag optimizer, configured to determine an energy lag for a building, said building lag optimizer comprising:
 a thermal response processor, configured to generate a plurality of energy use data sets for said 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 the energy lag for said building; and 
   a facility processor, coupled to said building lag optimizer, configured to direct said building lag optimizer to determine corresponding energy lags for all of the buildings, and configured to receive said corresponding energy lags, and configured to categorize the buildings in types according to similar corresponding energy lags.   
     
     
         9 . The apparatus as recited in  claim 8 , wherein said plurality of lag values indicates shifts of said energy consumption values to different time and outside temperature values. 
     
     
         10 . The apparatus as recited in  claim 8 , wherein said corresponding time values are less than or equal to said similar energy lags. 
     
     
         11 . The apparatus as recited in  claim 8 , wherein said corresponding time values comprise hourly values and said plurality of lag values spans a 24-hour period. 
     
     
         12 . The apparatus as recited in  claim 8 , wherein said similar corresponding energy lags comprise energy lags having the same value. 
     
     
         13 . The apparatus as recited in  claim 8 , wherein said similar corresponding energy lags comprise energy lags within a range of values. 
     
     
         14 . The apparatus as recited in  claim 8 , wherein said each of said plurality of energy use data sets comprises a first portion of a corresponding each of a plurality of baseline energy use data sets, and wherein required energy consumption values resulting from shifts are taken from a second portion of said corresponding each of a plurality of baseline energy use data sets. 
     
     
         15 . A method for characterizing buildings, the method comprising:
 generating a plurality of energy use data sets for each of the buildings, each of the plurality of energy use data sets comprising energy consumption values along with corresponding time and outside temperature values, wherein the energy consumption values within the each of the plurality of energy use data sets are shifted by one of a plurality of lag values relative to the corresponding time and outside temperature values, and wherein each of the plurality of lag values is different from other ones of the plurality of lag values;   performing a regression analysis on the each of the plurality of energy use data sets to yield corresponding regression model parameters and a corresponding residual;   determining a least valued residual from all residuals yielded by the regression engine, the least valued residual indicating a corresponding energy lag for the each of the buildings; and   categorizing the buildings into types according to similar energy lags.   
     
     
         16 . The method as recited in  claim 15 , wherein the plurality of lag values indicates shifts of the energy consumption values to different time and outside temperature values. 
     
     
         17 . The method as recited in  claim 15 , wherein the corresponding time values are less than or equal to the similar energy lags. 
     
     
         18 . The method as recited in  claim 15 , wherein the corresponding time values comprise hourly values and the plurality of lag values spans a 24-hour period. 
     
     
         19 . The method as recited in  claim 15 , wherein the similar energy lags comprise energy lags having the same value. 
     
     
         20 . The method as recited in  claim 15 , wherein the similar energy lags comprise energy lags within a range of values. 
     
     
         21 . The method as recited in  claim 15 , wherein the each of the plurality of energy use data sets comprises a first portion of a corresponding each of a plurality of baseline energy use data sets, and wherein required energy consumption values resulting from shifts are taken from a second portion of the corresponding each of a plurality of baseline energy use data sets.