ENERGY-SAVING MEASUREMENT, ADJUSTMENT AND MONETIZATION SYSTEM AND METHOD

• US 20110251933A1
• Filed: 04/07/2011
• Published: 10/13/2011
• Est. Priority Date: 04/08/2010
• Status: Active Grant

• Current Assignee: Energy Resource Management Corp.
• Original Assignee: Energy Resource Management Corp.
• Inventors: Campbell, William C., Reichmuth, Howard, Egnor, Terry
• Granted Patent: US 8,355,827 B2
• Time in Patent Office: Days
• US Class Current: 705/30
• CPC Class Codes: G05B 19/02 electric
• CPC Class Codes: G06Q 40/12 Accounting
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: Y02P 90/84 Greenhouse gas [GHG] management systems
• CPC Class Codes: Y02P 90/845 Inventory and reporting systems for greenhouse gases [GHG]

Abstract

System and method include precisely modeling of a facility'"'"'s energy usage over time based on historic data, and precisely predicting or measuring its actual, reduced energy usage over time after a redesign, retrofit, or renovation, or other positive change to the facility. The energy cost savings, whether over a time point of view (POV) of predicted, real-time, or historic, are creditable to the intervening remediation or renovation of the facility'"'"'s energy footprint. In accordance with one embodiment, multiple-variable inputs are modeled using arithmetic regression and steepest-descent convergence arithmetic solutions based in large part on building-science (construction) data versus outside average temperature (t) that simplifies the modeling and measurements. Additionality is thus addressed along with a system and method that is more accurate, more repeatable, more reliable, and thus more credible and more readily monetized.

Claims

1. An energy conservation commoditization system, comprising:

a metering portion configured with each of a thermal meter apparatus suitable to measure an external environmental temperature and an energy meter apparatus suitable to measure an energy load of a facility; and

a modeling mechanism coupled with the metering portion and configured with stored device-readable instructions, wherein the instructions are configured when executed by data processing circuitry to cause the modeling mechanism to process each of a first set of facility energy load data associated with a first time period and a first set of external environmental temperature data also associated with the first time period, and to produce a first analog facility model, wherein the first set of facility energy load data represents a total facility energy load for the first time period, and wherein the first analog facility model comprises plural identified end-use energy load portions.

2. The energy conservation commoditization system of claim 1, further comprising:

an analog facility model database comprising a non-transitory data storage medium coupled with the modeling mechanism, wherein the analog facility, model database is configured to receive from the modeling mechanism and to retrievably store the first analog facility model.

3. The energy conservation commoditization system of claim 1, wherein the facility comprises any of one or more buildings, one or more factories, one or more campuses, or any combination thereof.

4. The energy conservation commoditization mechanism of claim 1, wherein the processing each of a first set of facility energy load data and a first set of external environmental temperature data comprises executing an iterative steepest-descent convergence algorithm.

5. The energy conservation commoditization mechanism of claim 1, wherein the modeling mechanism is further configured to recalculate the plural identified end-use energy load portions according to a second set of external environmental temperature data associated with a second time period that is different than the first time period.

6. The energy conservation commoditization mechanism of claim 1, further comprising:

a controller portion operatively coupled with either or both of a heating subsystem and a cooling subsystem of a facility, the controller portion including instructions configured when executed to affect control of either or both of the heating and cooling subsystem.

7. The energy conservation commoditization system of claim 5, further comprising:

a calculator configured to compare a sum of the recalculated plural identified end-use energy load portions to a second set of facility energy load data associated with the second time period.

8. The energy conservation commoditization system of claim 1, wherein the metering portion further comprises plural energy meter apparatuses each suitable to measure a portion of the total energy load of the facility.

9. The energy conservation commoditization system of claim 7, further comprising:

a data aggregator coupled with any one of or any combination of the metering portion, the modeling mechanism, and the calculator, wherein the data aggregator includes device-readable instructions configured when executed by data processing circuitry to cause the data aggregator to aggregate the first set of facility energy load data from the plural buildings.

10. The energy conservation commoditization system of claim 7, further comprising:

a data recording mechanism operatively coupled with the calculator and configured to record at either or both of a non-transitory, machine-readable data storage medium and a human-readable medium, a quantitative difference between the sum of the recalculated plural identified end-use energy load portions and a total energy load of the second set of time-based facility energy load data associated with the second time period.

11. The energy conservation commoditization system of claim 7, wherein two or more selected from the group consisting of the metering portion, the modeling mechanism, an analog facility model database, the calculator, a data aggregator and a data reporting mechanism are configured as a unitary device.

12. The energy conservation commoditization system of claim 7, further comprising:

a utility grid coupled with the metering portion to receive energy redirected from the facility, wherein the redirected energy is quantitatively measured by the calculator.

13. A method for quantifying energy redirected from an energy-consuming facility to a metered utility grid, comprising:

collecting each of a first set of external environmental temperature data and a first set of total energy load data of a facility throughout a first time period;

collecting, by a metering device, each of a second set of external environmental temperature data and a second set of total energy load data of the facility throughout a second time period, wherein the second time period is approximately equivalent in duration to and later in time than the first time period;

executing device-readable instructions stored at a non-transitory data storage medium and configured when executed by data processing circuitry to cause the circuitry to process the first set of total energy load data of the facility according to the first set of external environmental temperature data and to produce a first analog facility model comprising plural model end-use energy load portions;

executing similarly stored device-readable instructions configured when executed to cause the circuitry to process the first analog facility model according to the second set of external environmental temperature data and to produce plural revised model end-use energy load portions;

calculating a sum of the plural revised end-use energy load portions; and

calculating a quantified difference between the second set of total energy load data and the sum of the plural revised end-use energy load portions.

14. The method of claim 13, wherein the facility comprises plural buildings.

15. The method of claim 13, wherein the processing of the first set of total energy load data of the facility according to the first set of external environmental temperature data comprises executing an iterative steepest-descent convergence algorithm.

16. The method of claim 13, further comprising:

recording the quantified difference at either or both of a non-transitory, machine-readable data storage medium and a human-readable medium.

17. The method of claim 13, further comprising:

executing, in response to the quantified difference between the second set of total energy load data and the sum of the plural identified end-use energy load portions of the first analog facility model, device-readable instructions stored at a non-transitory data storage medium and configured when executed by the data processing circuitry to cause the circuitry to process the second set of total energy load data of the facility according to the second set of external environmental temperature data and to produce a second analog facility model comprising plural model end-use energy load portions.

18. The method of claim 14, further comprising:

aggregating a total energy load of the plural buildings to produce either or both of the first set of total facility energy load data and the second set of total facility energy load data.

19. The method of claim 13, further comprising:

determining a credit due against a contracted cost for energy, wherein an amount of the credit corresponds to the quantified difference between the second set of total energy load data and the sum of the plural revised end-use energy load portions; and

recording the credit at either or both of a non-transitory, machine-readable data storage medium and a human-readable medium.

20. An article of manufacture, comprising:

coded instructions stored at a non-transitory device-readable medium, wherein the instructions are configured when executed by data processing circuitry to cause the circuitry to;

process each of a first set of facility energy load data associated with a first time period and a first set of external environmental temperature data associated with the first time period, wherein the first set of facility energy load data represent a total facility energy load for the first time period; and

produce from the processed facility energy load data and external environmental temperature data a first analog facility model comprising plural identified end-use energy load portions.

21. The article of manufacture of claim 20, wherein the coded instructions are further configured when executed to:

reprocess the first analog facility model according to a second set of external environmental temperature data corresponding to a second time period that is different from the first time period, and to produce plural revised identified model end-use energy load portions;

calculate a sum of the plural revised end-use energy load portions;

calculate a quantified difference between a second set of facility energy load data corresponding to the second time period and the sum of the plural revised end-use energy load portions; and

record the quantified difference at either or both of a non-transitory, machine-readable data storage medium and a human-readable medium.

22. The article of manufacture of claim 20, wherein the instructions are further configured when executed to cause the circuitry to aggregate a total energy load of plural buildings to produce the first set of facility energy load data.

23. The article of manufacture of claim 21, wherein the instructions are further configured when executed to cause the circuitry to determine a credit due against a contracted cost for energy, and to record the credit at either or both of a non-transitory, machine-readable data storage medium and a human-readable medium, wherein an amount of the credit corresponds to the quantified difference between a second set of measured energy load data corresponding to the second time period and the sum of the plural revised end-use energy load portions.

24. The article of manufacture of claim 20, wherein the circuitry and the non-transitory device-readable medium are combined within a real-time metering instrument configured to measure a facility energy load.

25. The article of manufacture of claim 20, wherein the processing of the first set of facility energy load data according to the first set of external environmental temperature data comprises executing an iterative steepest-descent convergence algorithm.