General Electric Company

Mark Joseph Meyerhofer

James Joseph Schmid

Jerry Steven Massey

Jaime Alberto Sierra

Bobby Antione Wilson

Anthony Steven McCulley

Sthitaprajna Acharya

Chad Eric Knodle

Ninad Vijaykumar Kulkarni

A computing device for use with a demand response system is provided. The computing device includes a communication interface for receiving customer data of a plurality of customers, wherein the customer data includes a participation history and historical consumption values for each customer for participating in at least one demand response event. A processor is coupled to the communication interface and is programmed to select at least one customer from the plurality of customers by considering the participation history and the historical consumption values for each of the customers. The processor is also programmed to estimate a future reduction in energy consumption for the customer based on the customer data and to determine whether the estimated future reduction in energy consumption is substantially accurate.

Systems and methods to predict a reduction of energy consumption

A computing device for use with a demand response system is provided. The computing device includes an interface for receiving customer data that includes at least a location for each customer and/or a preference selection made by each customer associated with at least one demand response program. A processor coupled to the interface and programmed to select a plurality of participants from the customer data to receive a plurality of signals representative of at least one demand response event. The processor selects the participants based at least in part on the customer location and/or the preference selection associated with each customer.

Systems and methods to implement demand response events

A computing device for use with a demand response system is provided. The computing device includes a communication interface for receiving customer data of a plurality of customers, wherein the customer data includes at least a location, a policy limitation, a participation history, and an enrollment status for each customer. A processor is coupled to the communication interface and programmed to select at least one participant from the plurality of customers, based on the customer data, to participate in at least one demand response event. The processor is further programmed to verify that the selected participant, based on the customer data, satisfies at least one precondition to receive at least one signal representative of the demand response event.

Disclosed and described herein are embodiments of systems, methods and computer program for scheduling demand events over a time period based on differences between the estimated power availability and the estimated power consumption at various points during the time period. In one aspect, methods are described. One embodiment of a method comprises establishing a defined time period, estimating power availability over the time period, estimating power consumption over the time period, and scheduling, using a computing device, demand events over the time period based on differences between the estimated power availability and the estimated power consumption at various points during the time period.

Method, system and computer program product for scheduling demand events

Certain embodiments of the invention may include systems, methods, and apparatus for estimating demand response load change. According to an example embodiment of the invention, a method is provided for estimating energy usage change associated with a demand event. The method may include determining energy potential change during a demand event for one or more devices associated with a location; estimating energy usage patterns for the location over predefined time periods before and after the demand event; determining pre-demand event and post-demand event energy rebounds based at least in part on the estimated energy usage patterns; determining an energy change profile associated with the location based at least in part on the determined energy potential change, and the pre-demand event and post-demand event energy rebounds.

Growing community of inventors

Acworth, GA, United States of America

Mark Joseph Meyerhofer