SYSTEM AND METHOD OF MODELING AND MONITORING AN ENERGY LOAD
First Claim
1. A computer-implemented method of modeling and monitoring an energy load, the method comprising:
- defining a dependent variable with a load monitoring server, the dependent variable representing an operation of the energy load;
defining at least one independent variable with the load monitoring server, the at least one independent variable representing at least one influencing driver of the operation of the energy load;
defining at least one partition variable with the load monitoring server, the at least one partition variable representing an operating condition of the energy load as a set of two or more discrete values;
receiving a reference dataset at the load monitoring server, the reference dataset including coincident values of the dependent variable, at least one independent variable, and at least one partition variable;
analyzing the reference dataset with the load monitoring server to arrange the reference dataset into interdependent data based upon the discrete values of the at least one partition variable;
creating a model for each discrete value of the at least one partition variable in the analyzed reference dataset with the load monitoring server in which the dependent variable is modeled as a function of the at least one independent variable, the model representing operation of the energy load;
receiving an input dataset at the load monitoring server, the input dataset including additional coincident values of the at least one independent variable and the at least one partition variable;
processing the additional coincident values of the at least one independent variable and the at least one partition variable with the created models; and
generating an output dataset with the load monitoring server from the created models, the output dataset including predicted dependent variable values from the at least one independent variable and the at least one partition variable from the input dataset.
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Accused Products
Abstract
A system, method, and computer program product for predicting operation for physical systems with distinct operating modes uses observable qualities of the system to predict other qualities of the system. Independent variables including temperature or production volume are observed to determine the degree to which a dependent modeled variable, including energy load, is influenced. Partition variables representing operating conditions of the dependent variables are defined as discrete values. Reference datasets with coincident values of the dependent variable, independent variable, and partition variables are received, and models are created for each discrete value of the partition variables in the reference dataset. Each model is populated with the values of the dependent variable and the independent variable. The dependent variable is modeled as a function of the independent variable. Model accuracy is evaluated by processing new input data to generate output data that includes values of the coincident dependent variable, the independent variable, and the partition variable from the input dataset.
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Citations
20 Claims
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1. A computer-implemented method of modeling and monitoring an energy load, the method comprising:
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defining a dependent variable with a load monitoring server, the dependent variable representing an operation of the energy load; defining at least one independent variable with the load monitoring server, the at least one independent variable representing at least one influencing driver of the operation of the energy load; defining at least one partition variable with the load monitoring server, the at least one partition variable representing an operating condition of the energy load as a set of two or more discrete values; receiving a reference dataset at the load monitoring server, the reference dataset including coincident values of the dependent variable, at least one independent variable, and at least one partition variable; analyzing the reference dataset with the load monitoring server to arrange the reference dataset into interdependent data based upon the discrete values of the at least one partition variable; creating a model for each discrete value of the at least one partition variable in the analyzed reference dataset with the load monitoring server in which the dependent variable is modeled as a function of the at least one independent variable, the model representing operation of the energy load; receiving an input dataset at the load monitoring server, the input dataset including additional coincident values of the at least one independent variable and the at least one partition variable; processing the additional coincident values of the at least one independent variable and the at least one partition variable with the created models; and generating an output dataset with the load monitoring server from the created models, the output dataset including predicted dependent variable values from the at least one independent variable and the at least one partition variable from the input dataset. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 20)
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16. A system for modeling and monitoring an energy load, the system comprising:
a load monitoring server configured to; define a dependent variable, the dependent variable representing an operation of the energy load; define at least one independent variable, the at least one independent variable representing at least one influencing driver of the operation of the energy load; define at least one partition variable, the at least one partition variable representing an operating condition of the energy load as a set of two or more discrete values; receive a reference dataset, the reference dataset including coincident values of the dependent variable, at least one independent variable, and at least one partition variable; analyze the reference dataset to arrange the reference dataset into interdependent data based upon the discrete values of the at least one partition variable; create a model for each discrete value of the at least one partition variable in the analyzed reference dataset in which the dependent variable is modeled as a function of the at least one independent variable, the model representing operation of the energy load; receive an input dataset, the input dataset including additional coincident values of the at least one independent variable and the at least one partition variable; process the additional coincident values of the at least one independent variable and the at least one partition variable with the created models; and generate an output dataset from the created models, the output dataset including predicted dependent variable values from the at least one independent variable and the at least one partition variable from the input dataset. - View Dependent Claims (17, 18)
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19. A computer-readable storage media for modeling and monitoring an energy load, the computer-readable storage media comprising one or more computer-readable instructions configured to cause one or more computer processors to execute the operations comprising:
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defining a dependent variable with a load monitoring server, the dependent variable representing an operation of the energy load; defining at least one independent variable with the load monitoring server, the at least one independent variable representing at least one influencing driver of the operation of the energy load; defining at least one partition variable with the load monitoring server, the at least one partition variable representing an operating condition of the energy load as a set of two or more discrete values; receiving a reference dataset at the load monitoring server, the reference dataset including coincident values of the dependent variable, at least one independent variable, and at least one partition variable; analyzing the reference dataset with the load monitoring server to arrange the reference dataset into interdependent data based upon the discrete values of the at least one partition variable; creating a model for each discrete value of the at least one partition variable in the analyzed reference dataset with the load monitoring server in which the dependent variable is modeled as a function of the at least one independent variable, the model representing operation of the energy load; receiving an input dataset at the load monitoring server, the input dataset including additional coincident values of the independent variable and the partition variable; processing the additional coincident values of the at least one independent variable and the at least one partition variable with the created models; and generating an output dataset with the load monitoring server from the created models, the output dataset including predicted dependent variable values from the at least one independent variable and the at least one partition variable from the input dataset.
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Specification