IP Library Granted Patent US 9,639,643
Granted Patent B2
US 9,639,643 · App. 14/297,748 · Granted May 2, 2017

Method and system for generating electric load models

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Quick Facts
Patent No.
US 9,639,643
App. No.
14/297,748
Granted
May 2, 2017
Kind
B2
Abstract

A method for generating electric load models that includes receiving a plurality of measurements representative of input provided by a power source to electric loads is provided. The method includes generating a plurality of combination of model loads and assigning a contribution factor to each model load in each combination. The method further includes computing a match index for each combination for each measurement. The match index is computed by comparing a predicted output of each combination with an actual output generated by the electric loads for each input represented by each measurement. Furthermore, the method includes computing a first likelihood index for each combination based on the match index for each combination for the plurality of measurements. The method also includes computing a second likelihood index for each contribution factor in each combination based on the match index for each combination.

Claims (22)

1. A method for generating electric load models, the method comprising:

receiving a plurality of measurements representative of input provided by at least one power source to a plurality of electric loads at different time instances;

generating a plurality of combination of model loads and assigning a contribution factor to each model load in each combination;

computing a match index for each combination of model loads for each measurement by comparing a predicted output of each combination with an actual output generated by the plurality of electric loads for each input represented by each measurement, wherein the predicted output for each combination is generated by providing input equivalent to each measurement;

computing a first likelihood index for each combination based on the match index for each model load for the plurality of measurements; and

computing a second likelihood index for each contribution factor in each combination based on the match index for each combination for the plurality of measurements.

2. The method of claim 1 , wherein a first set of combinations is selected based on a set of user defined criteria pertaining to the first likelihood index and the second likelihood index.

3. The method of claim 1 , further comprising generating a graphical illustration of the first likelihood index and the second likelihood index for each combination.

4. The method of claim 1 , further comprising iteratively changing the contribution factor assigned to each model load in each combination till a difference between the predicted output for the combination and the actual output is minimum.

5. A system for generation of electric load models, comprising:

at least one input system configured to receive a plurality of measurements that are representative of input provided by a power source to a plurality of electrical loads at different time instances, wherein the measurements are collected from a power bus that couples the power source with the plurality of electrical loads;

a processing system configured to:

generate a plurality of combination of model loads and assigning a contribution factor to each model load in each combination;

compute a match index for each combination for each measurement by comparing a predicted output of each combination with an actual output generated by the plurality of electric loads for each input represented by each measurement, wherein the predicted output for each combination is generated by providing input equivalent to each measurement;

compute a first likelihood index for each combination based on the match index for each combination for the plurality of measurements; and

compute a second likelihood index for each contribution factor in each combination based on the match index for each combination for the plurality of measurements.

6. The system of claim 5 , wherein the processing system is further configured to iteratively change the contribution factor assigned to each model load in each combination till a difference between the predicted output for the combination and the actual output is minimum.

7. The system of claim 5 , further comprising a data repository configured to store a plurality of model load types.

8. The system of claim 7 , wherein the data repository is coupled with the input system and is configured to store information pertaining to inputs provided by the power source to the electric load at different time instances.

9. The system of claim 5 , wherein the processing system is further configured to select the first set of combinations based on the first likelihood index and the second likelihood index.

10. The system of claim 5 , further comprising a user interface configured to display a graphical illustration of the first likelihood index and the second likelihood index for each combination.

11. The system of claim 5 , further comprising a plurality of intelligent electronic devices (IEDs) coupled to the input system, wherein the plurality of IEDs are connected to the power bus and are configured to generate the plurality of measurements.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 17, 2023
From: GENERAL ELECTRIC COMPANY
To: GE DIGITAL HOLDINGS LLC
Reel/Frame 065612/0085 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 6, 2014
From: PAN, YAN; BOSE, SUMIT; REN, WEI
To: GENERAL ELECTRIC COMPANY
Reel/Frame 033045/0865 →