Michael T Ozog

US Patent:

8364609, Jan 29, 2013

Filed:

Jan 14, 2010

Appl. No.:

12/687827

Inventors:

Michael T. Ozog - Fort Collins CO, US

Assignee:

Integral Analytics, Inc. - Cincinnati OH

International Classification:

G06F 17/00

US Classification:

705412, 705 725

Abstract:

An energy distribution may include a server and one or more databases. The system may communicate with an energy provider to receive energy provider data, at least one information collector to receive information collector data such as individualized energy usage data, customer preferences, and customer or location characteristics, and the one or more databases for receiving data for optimization. The system may calculate a cost of service or avoided cost using at least one of the individualized energy usage data and a system generation cost at a nearest bus. The system may also forecast individualized demand by end-use, individualized demand by location, energy prices, or energy costs. The system may optimize energy distribution, energy use, cost of service, or avoided cost using the forecasted individualized demand by end-use, the forecasted individualized demand by location, the forecasted energy prices, and the forecasted energy costs.

US Patent:

20110035073, Feb 10, 2011

Filed:

Oct 29, 2010

Appl. No.:

12/915870

Inventors:

Michael T. Ozog - Fort Collins CO, US

Assignee:

Integral Analytics, Inc. - Cincinnati OH

International Classification:

G06F 1/28

US Classification:

700291

Abstract:

An energy distribution may include a server and one or more databases. The system may communicate with an energy provider to receive energy provider data, at least one information collector to receive information collector data such as individualized energy usage data, customer preferences, and customer or location characteristics, and the one or more databases for receiving data for optimization. The system may calculate a cost of service or avoided cost using at least one of the individualized energy usage data and a system generation cost at a nearest bus. The system may also forecast individualized demand by end-use, individualized demand by location, energy prices, or energy costs. The system may optimize energy distribution, energy use, cost of service, or avoided cost using the forecasted individualized demand by end-use, the forecasted individualized demand by location, the forecasted energy prices, and the forecasted energy costs.

US Patent:

20110231028, Sep 22, 2011

Filed:

Apr 5, 2011

Appl. No.:

13/080541

Inventors:

Michael T. Ozog - Fort Collins CO, US

International Classification:

G06F 1/26

US Classification:

700291

Abstract:

Systems and methods for energy optimization may receive receiving energy provider data, near-real time individualized energy usage data for each of a plurality of end-uses or near-real time individualized whole premise energy usage data, customer preferences, and near-real time and forecasted weather information. The systems and methods may forecast, for a selected time period, individualized energy usage for each of the plurality of end-uses or individualized whole premise energy usage data for a customer location using: (1) the energy provider data, (2) the near-real time individualized energy usage data, (3) the customer preferences, and (4) the near-real time and forecasted weather information. The systems and methods may optimize, for the selected time period, energy usage at the customer location using (1) the individualized energy usage, (2) the energy provider data, and (3) the customer preferences.

US Patent:

20140148963, May 29, 2014

Filed:

Jan 31, 2014

Appl. No.:

14/169577

Inventors:

- Cincinnati OH, US
MICHAEL T. OZOG - Fort Collins CO, US

Assignee:

Integral Analytics, Inc. - Cincinnati OH

International Classification:

G06Q 50/06

US Classification:

700291

Abstract:

Systems and methods for energy optimization may receive receiving energy provider data, near-real time individualized energy usage data for each of a plurality of end-uses or near-real time individualized whole premise energy usage data, customer preferences, and near-real time and forecasted weather information. The systems and methods may forecast, for a selected time period, individualized energy usage for each of the plurality of end-uses or individualized whole premise energy usage data for a customer location using: (1) the energy provider data, (2) the near-real time individualized energy usage data, (3) the customer preferences, and (4) the near-real time and forecasted weather information. The systems and methods may optimize, for the selected time period, energy usage at the customer location using (1) the individualized energy usage, (2) the energy provider data, and (3) the customer preferences.