Richard J Curtis

20120310708, Dec 6, 2012

May 4, 2012

13/464314

Richard Tyler Curtis - Washington DC, US
Kyle Yost - Washington DC, US

OPOWER, INC. - Arlington VA

G06Q 30/02

705 733

Illustrative embodiments of the present invention are directed to methods and computer systems for reporting a consumer's usage of a resource. A computer system retrieves consumer characteristic data and resource usage data for the first consumer and a set of second consumers including characteristic data related to each consumer. The computer system selects at least one consumer that is similar to the first consumer from the set of second consumers based upon a plurality of common criteria between the first consumer's characteristic data and a second consumer's characteristic data. The computer processes may be performing iteratively until the total number of similar consumers is equal to or greater than the predetermined number of consumers. Once a desired number of similar consumers is found, the computer system generates a report that displays the first consumer's resource usage data and the at least one similar consumers' resource usage data.

20140074300, Mar 13, 2014

Mar 13, 2013

13/799550

Richard Tyler Curtis - Washington DC, US

G05D 23/01

700276

The disclosure provides a computer-implemented method and system of reducing commodity usage by providing tailored consumer information to the consumer. The method utilizes neural network and machine learning techniques to calculate and cluster statistical data to classify the premises for desired observable condition, including the presence of a programmed thermostat. A score is determined that corresponds to at least one of: (i) a present state of an observable condition, (ii) a non-present state of the observable condition, and (iii) a degree of a condition of the observable condition, to provide tailored consumer information associated to the consumer's usage of the commodity.

20160005015, Jan 7, 2016

Dec 19, 2014

14/577929

- Arlington VA, US
Richard Tyler Curtis - Washington DC, US

G06Q 20/14
G06Q 50/06

Techniques for unusual usage alerts without smart meter data are provided. The computing device can determine a set of climate control disaggregation coefficients and obtain weather data corresponding to at least a portion of a billing period. In turn, the computing device can determine first forecasted usage data for the at least a portion of the billing period based on the set of climate control disaggregation coefficients and the weather data, and determine second forecasted usage data for a length of the billing period based at least in part on the first forecasted usage data. In some aspects, the computing device can project unusual energy usage for the billing period based on the second forecasted usage data determined to be greater than usage data for a prior time period. The computing device can generate an alert notification including an indication of the unusual energy usage projection.

20140107850, Apr 17, 2014

Mar 15, 2013

13/839082

- Arlington VA, US
Richard Tyler Curtis - Washington DC, US

OPOWER, INC. - Arlington VA

G06Q 50/06

700291

Methods and computer systems are disclosed for identifying the power-demand of a climate-control system at a premises to reduce usage of energy at the premises. A computer system receives energy usage data and run-time data of the climate-control system. The operational data includes an on-time and/or off-time associated with the climate-control system. The computer system determines a power-draw of the climate-control system using the energy usage data and the run-time data and outputs the power-draw to be used to reduce the energy usage at the premises.