The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 21, 2021

Filed:

Nov. 17, 2017
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Umamaheswari Devi, Bangalore, IN;

Amith Singhee, Bangalore, IN;

Mathieu Sinn, Dublin, IE;

Vincent Lonij, Dublin, IE;

Amar P. Azad, Bangalore, IN;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G05B 17/02 (2006.01); G06F 9/50 (2006.01); H04L 29/08 (2006.01); H02J 3/38 (2006.01); G01W 1/10 (2006.01); G06N 20/00 (2019.01); G06Q 50/06 (2012.01); G06F 30/20 (2020.01); G06F 17/18 (2006.01); G06F 119/06 (2020.01);
U.S. Cl.
CPC ...
G05B 17/02 (2013.01); G01W 1/10 (2013.01); G06F 9/5072 (2013.01); G06F 30/20 (2020.01); G06N 20/00 (2019.01); G06Q 50/06 (2013.01); H02J 3/382 (2013.01); H04L 67/1002 (2013.01); G06F 17/18 (2013.01); G06F 2119/06 (2020.01); H02J 2203/20 (2020.01); H04L 67/12 (2013.01); H04L 67/18 (2013.01);
Abstract

The present invention provides a method, system, and computer program product of modeling and calculating aggregate power of a set of renewable energy source stations using power output from representative renewable energy source stations. In an embodiment, the present invention includes receiving location, power output time series, and weather time series data of renewable energy source stations in a geographic region and aggregate power output time series data for the geographic region, for each cluster of stations, normalizing the aggregate power value to a representative renewable energy source station, learning a regression model, and de-normalizing a normalized aggregate output power model with respect to a maximum possible power value, and applying a combined model to the received data and power output of representative renewable energy source stations for a particular day, resulting in a total aggregate power value of the renewable energy source stations for the particular day.


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