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Systems and methods for detecting changes in energy usage in a building

  • US 9,286,582 B2
  • Filed: 10/03/2011
  • Issued: 03/15/2016
  • Est. Priority Date: 06/22/2009
  • Status: Active Grant
First Claim
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1. A method for generating a baseline energy usage model for a building management system comprising:

  • receiving, at a processing circuit, an initial set of variables for potential use in a baseline energy usage model for predicting energy use in a building;

    performing, by the processing circuit, statistical hypothesis testing on each of the initial set of variables to determine which of the initial set of variables are statistically significant to the energy use in the building, the statistical hypothesis testing comprising;

    generating a first set of coefficients for the baseline energy usage model based on the initial set of variables;

    removing one of the variables from the initial set of variables to create a subset of the initial set of variables;

    generating a second set of coefficients for the baseline energy usage model based on the subset of the initial set of variables; and

    calculating a test statistic for the removed variable using a difference between the first set of coefficients and the second set of coefficients and comparing the calculated test statistic to a critical value;

    automatically selecting, by the processing circuit, one or more of the initial set of variables for use in the baseline energy usage model based on a result of the statistical hypothesis testing, wherein a variable is selected for use in the baseline energy usage model when the test statistic calculated for the variable exceeds the critical value;

    causing the one or more automatically selected variables to be displayed on a user interface device;

    receiving, at the user interface, a selection of one or more variables which differ from the one or more automatically selected variables; and

    using the selection of the one or more variables which differ from the one or more automatically selected variables to generate a new baseline energy usage model.

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