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. 31, 2024

Filed:

Apr. 27, 2021
Applicant:

Accenture Global Solutions Limited, Dublin, IE;

Inventors:

Jinu Jayan, Bangalore, IN;

Pallavi S. Gawade, Thane-West, IN;

Bhushan Gurmukhdas Jagyasi, Thane West, IN;

Sandeep Narendra Vaity, Mumbai, IN;

Pollachi Seetharam Sreedhar, Pollachi, IN;

Rengaraj Ramasubbu, Chennai, IN;

Saurabh Pashine, Indore, IN;

Tamal Bhattacharyya, Bangalore, IN;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
H02J 3/00 (2006.01); G06N 20/00 (2019.01); G06Q 30/0201 (2023.01); G06Q 50/06 (2012.01);
U.S. Cl.
CPC ...
H02J 3/003 (2020.01); G06N 20/00 (2019.01); G06Q 30/0206 (2013.01); G06Q 50/06 (2013.01); H02J 2300/20 (2020.01);
Abstract

Aspects of the present disclosure provide systems, methods, and computer-readable storage media that leverage artificial intelligence and machine learning (ML) to forecast energy demand and to generate an energy plan for one or more facilities of an organization. For example, a system may forecast an occupancy of the facilities for use with historical demand data in forecasting the energy demand. The forecasting may be performed by one or more trained ML models. Additional ML models may be trained to select energy resources that satisfy the forecasted energy demand and that prioritize constraint(s). The system may generate an energy plan that indicates information related to the selected energy resources, such as cost, energy type, environmental impact, etc., for use in increasing an amount of renewable energy resources used at the facilities. In some implementations, the system may recommend actions to reduce a negative environmental impact associated with the selected energy resources.


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