SYSTEM AND METHOD FOR ENERGY MANAGEMENT

• US 20150277467A1
• Filed: 06/10/2015
• Published: 10/01/2015
• Est. Priority Date: 10/23/2009
• Status: Abandoned Application

• Current Assignee: Viridity Energy Solutions, Inc.
• Original Assignee: Viridity Energy Incorporated
• Inventors: Steven, Alain Pierre, Zibelman, Audrey A.
• Application Number:
  US14/735,629
• Publication Number:
  US 20150277467A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G05B 13/041 in which a variable is automatically adjusted to optimise the performance
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 17/02 electric
• CPC Class Codes: G05F 1/66 Regulating electric power
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 2300/10 The dispersed energy generation being of fossil origin, e.g. diesel generators
• CPC Class Codes: H02J 2300/24 of photovoltaic origin
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: H02J 3/008 involving trading of energy or energy transmission rights
• CPC Class Codes: H02J 3/381 Dispersed generators
• CPC Class Codes: H02J 3/466 Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
• CPC Class Codes: H02S 10/00 PV power plants; Combinations of PV energy systems with other systems for the generation of electric power
• CPC Class Codes: Y02E 10/56 Power conversion systems, e.g. maximum power point trackers
• CPC Class Codes: Y02E 40/70 Smart grids as climate change mitigation technology in the energy generation sector
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y02P 90/84 Greenhouse gas [GHG] management systems
• CPC Class Codes: Y04S 10/12 Monitoring or controlling equipment for energy generation units, e.g. distributed energy generation [DER] or load-side generation
• CPC Class Codes: Y04S 10/50 Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
• CPC Class Codes: Y04S 40/20 Information technology specific aspects, e.g. CAD, simulation, modelling, system security
• CPC Class Codes: Y04S 50/10 : Energy trading, including energy flowing from end-user application to grid

Abstract

Embodiments of the present invention assist customers in managing the four types of energy assets, that is, generation, storage, usage, and controllable load assets. Embodiments of the present invention for the first time develop and predict a customer baseline (“CBL”) usage of electricity, using a predictive model based on simulation of energy assets, based on business as usual (“BAU”) of the customer'"'"'s facility. The customer is provided with options for operating schedules based on algorithms, which allow the customer to maximize the economic return on its generation assets, its storage assets, and its load control assets. Embodiments of the invention enable the grid to verify that the customer has taken action to control load in response to price. This embodiment of the invention calculates the amount of energy that the customer would have consumed, absent any reduction of use made in response to price. Specifically, the embodiment models the usage of all the customer'"'"'s electricity consuming devices, based on the customer'"'"'s usual conditions. This model of the expected consumption can then be compared to actual actions taken by the customer, and the resulting consumption levels, to verify that the customer has reduced consumption and is entitled to payment for the energy that was not consumed.

Claims

1. A method for optimizing the use of electric energy by a facility comprising a plurality of energy assets, the method comprising:

(a) modeling, using a computer, the usage of electric energy by the facility, by creating a simulation model of the facility and calculating a customer baseline (“

CBL”

);

(b) storing the model in the computer;

(c) determining, using the computer, a plan for controlling the operation of at least one of the facility'"'"'s energy assets to reduce the electricity provider'"'"'s overall charge to the facility for electric energy, or to provide a revenue source to the facility, the determining being done on the basis of the model, and variations in the price of electric energy during a day;

(d) generating, using the computer, control signals based on the plan from data derived from the computer; and

(e) controlling, using the generated control signals, at least one of the facility'"'"'s energy assets so that operation of the facility conforms to the plan.

2. The method of claim 1, wherein the energy assets comprise at least one of:

generation, storage, usage, and controllable load assets.

3. The method of claim 1, wherein the step of determining a plan for controlling the operation of at least one of the facility'"'"'s energy assets is also based on weather prediction data provided to the computer and price prediction data provided to the computer.

4. The method of claim 1, in which said at least one of the facility'"'"'s energy assets is a controllable air conditioning unit.

5. The method of claim 1, in which the facility further comprises an energy storage device and a solar generator connected to the energy storage device, the method further comprising:

(a) controlling the use of the solar generation by a control signal automatically generated from electric data derived from the computer, to charge the energy storage device with solar generation during a time when the price of energy is below a first predetermined level, and

(b) controlling the energy storage device by a control signal automatically generated from electronic data derived from the computer, to discharge the energy storage device to the utility power grid when the price of energy charged to the facility by the energy provider is above a second predetermined level.

6. The method of claim 1, in which the facility further comprises an energy storage device connected to a utility power grid, the method further comprising

(a) controlling the energy storage device by control signals automatically generated from electronic data derived from the computer to charge the energy storage device when the price of energy is below a first predetermined level, and

(b) controlling the energy storage device by control signals automatically generated from electronic data derived from the computer to discharge the energy storage device to the utility power grid when the price of energy charged is above a second predetermined level.

7. A computer system for optimizing use of electric energy by a facility comprising a plurality of energy assets, the system programmed to execute a method comprising:

(a) modeling, using a computer, the usage of electric energy by the facility, by creating a simulation model of the facility and calculating a customer baseline (“

CBL”

);

(b) storing the model in the computer;

(c) determining, using the computer, a plan for controlling the operation of at least one of the facility'"'"'s energy assets to reduce the electricity provider'"'"'s overall charge to the facility for electric energy, or to provide a revenue source to the facility, the determining being done at least on the basis of the model, and variations in the price of electric energy during a day;

(d) generating, using the computer, control signals based on the plan from data derived from the computer; and

(e) controlling, using the generated control signals, at least one of the facility'"'"'s energy assets so that operation of the facility conforms to the plan.

8. The computer system of claim 7, wherein the energy assets comprise at least one of:

generation, storage, usage, and controllable load assets.

9. The computer system of claim 7, wherein the step of determining a plan for controlling the operation of at least one of the facility'"'"'s energy assets is also based on weather prediction data provided to the computer and price prediction data provided to the computer.

10. The computer system of claim 7, in which said at least one of the facility'"'"'s energy assets is a controllable air conditioning unit.

11. The computer system of claim 7, in which the facility further comprises an energy storage device and a solar generator connected to the energy storage device, the method further comprising:

(a) controlling the use of the solar generation by a control signal automatically generated from electric data derived from the computer, to charge the energy storage device with solar generation during a time when the price of energy is below a first predetermined level, and

(b) controlling the energy storage device by a control signal automatically generated from electronic data derived from the computer, to discharge the energy storage device to the utility power grid when the price of energy charged to the facility by the energy provider is above a second predetermined level.

12. The computer system of claim 7, in which the facility further comprises an energy storage device connected to a utility power grid, the method further comprising

(a) controlling the energy storage device by control signals automatically generated from electronic data derived from the computer to charge the energy storage device when the price of energy is below a first predetermined level, and

(b) controlling the energy storage device by control signals automatically generated from electronic data derived from the computer to discharge the energy storage device to the utility power grid when the price of energy charged is above a second predetermined level.

13. A non-transitory machine readable memory medium, containing computer instructions which when executed cause a computer to execute the method comprising:

(a) modeling, using a computer, the usage of electric energy by the facility, by creating a simulation model of the facility and calculating a customer baseline (“

CBL”

);

(b) storing the model in the computer;

(c) determining, using the computer, a plan for controlling the operation of at least one of the facility'"'"'s energy assets to reduce the electricity provider'"'"'s overall charge to the facility for electric energy, or to provide a revenue source to the facility, the determining being done at least on the basis of the model, and variations in the price of electric energy during a day;

(d) generating, using the computer, control signals based on the plan from data derived from the computer; and

(e) controlling, using the generated control signals, at least one of the facility'"'"'s energy assets so that operation of the facility conforms to the plan.

14. The memory medium in claim 13, wherein the energy assets comprise at least one of:

generation, storage, usage, and controllable load assets.

15. The memory medium in claim 13, wherein the step of determining a plan for controlling the operation of at least one of the facility'"'"'s energy assets is also based on weather prediction data provided to the computer and price prediction data provided to the computer.

16. The memory medium in claim 13, in which said at least one of the facility'"'"'s energy assets is a controllable air conditioning unit.

17. The memory medium in claim 13, in which the facility further comprises an energy storage device and a solar generator connected to the energy storage device, the method further comprising:

(a) controlling the use of the solar generation by a control signal automatically generated from electric data derived from the computer, to charge the energy storage device with solar generation during a time when the price of energy is below a first predetermined level, and

(b) controlling the energy storage device by a control signal automatically generated from electronic data derived from the computer, to discharge the energy storage device to the utility power grid when the price of energy charged to the facility by the energy provider is above a second predetermined level.

18. The memory medium in claim 13, in which the facility further comprises an energy storage device connected to a utility power grid, the method further comprising

(a) controlling the energy storage device by control signals automatically generated from electronic data derived from the computer to charge the energy storage device when the price of energy is below a first predetermined level, and

(b) controlling the energy storage device by control signals automatically generated from electronic data derived from the computer to discharge the energy storage device to the utility power grid when the price of energy charged is above a second predetermined level.

19. A computer system for optimizing the use of electric energy by a facility comprising energy assets, the system comprising:

(a) a model builder module;

(b) a components library module;

(c) a generation forecast module;

(d) a load forecast module;

(e) an optimization module;

(f) a power analytics module; and

(g) a carbon calculation module.

wherein all of the modules are in electronic communication with each other.

20. The system in claim 19, further comprising:

(a) a monitor and control module, and

(b) a process interface module.

21. The system in claim 20, adapted to electronically communicate with:

(a) a weather forecast module;

(b) a price forecast module;

(c) a market/utility interface, adapted to communicate with a settlement module, and

(d) a gate adapted to communicate with at least one of an EMS, BMS, and SCADA.

22. The system in claim 20, wherein the model builder module is configured to create a simulation model of usage of electric energy by the facility and to calculate a customer baseline (“

CBL”

).