Systems and methods for regression-based determination of expected energy consumption and efficient energy consumption

US10346933B2 · kind B2 · utility

Assignee

• C3 IoT, Inc. · US

Inventors

• Mehdi Maasoumy · Redwood City, US
• Zico Kolter · Pittsburgh, US
• Henrik Ohlsson · Palo Alto, US

Key dates

• Filing date: Feb 12, 2015
• Grant date: Jul 9, 2019
• Expiry date: Mar 16, 2036

Classification

• Technology area (CPC Y): Emerging Cross-Sectional Technologies
• CPC primary: Y02D10/00
• WIPO field: IT methods for management
• WIPO sector: Electrical engineering

Abstract

Various embodiments of the present disclosure can include systems, methods, and non-transitory computer readable media configured to identify a set of features associated with at least one of a collection of residences or an energy billing period. Measured energy consumption information and a plurality of feature values can be acquired for each residence in the collection of residences. Each feature value in the plurality of feature values can correspond to a respective feature in the set of features. A regression model can be trained based on the measured energy consumption information and the plurality of features values for each residence in the collection of residences. At least one expected consumption value and at least one efficient consumption value can be determined based on the regression model.