Facilitating revenue generation from wholesale electricity markets based on a self-tuning energy asset model

• US 9,098,876 B2
• Filed: 05/06/2013
• Issued: 08/04/2015
• Est. Priority Date: 05/06/2013
• Status: Active Grant

• Current Assignee: Viridity Energy Solutions, Inc.
• Original Assignee: Viridity Energy Incorporated
• Inventors: Steven, Alain P., Hameyie, Eunice B., Wen, Jin, Wu, Teresa, Sunder, Ajay
• Primary Examiner(s): Masinick, Michael D
• Application Number:
  US13/888,323
• Publication Number:
  US 20140330695A1
• Time in Patent Office: 820 Days
• Field of Search: 700/291, 700/295, 703/18
• US Class Current: 1/1
• CPC Class Codes: G05B 13/02 electric
• CPC Class Codes: G05B 13/0265 the criterion being a learning criterion
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 2219/2642 Domotique, domestic, home control, automation, smart house
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• CPC Class Codes: G06Q 30/0283 Price estimation or determination
• CPC Class Codes: G06Q 30/0611 Request for offers or quotes
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 3/00 Circuit arrangements for ac mains or ac distribution networks
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: Y02B 10/30 Wind power
• 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 40/20 Information technology specific aspects, e.g. CAD, simulation, modelling, system security

Abstract

The apparatus, systems and methods herein facilitate generation of energy-related revenue for an energy customer of an electricity supplier. The apparatuses and methods herein can be used to generate suggested operating schedules for the energy assets that including a controllable energy asset, using an objective function. The objective function is determined based on a dynamic simulation model of the energy profile of the energy assets. The dynamic simulation model is adaptive to physical changes in the energy assets based on a parametric estimation using at least one model parameter. The model parameter is at least one of an operation characteristic of the controllable energy asset, a thermodynamic property of the energy assets, and a projected environmental condition. Energy-related revenue available to the energy customer is based at least in part on a wholesale electricity market or on a regulation market.

Claims

1. An apparatus for determining a suggested operating schedule for at least one energy asset operated by an energy customer, the apparatus comprising:

at least one communication interface;

at least one memory to store processing unit-executable instructions and an objective function for the at least one energy asset, wherein the at least one energy asset comprises at least one controllable energy asset, wherein the objective function facilitates a determination of the suggested operating schedule for the at least one energy asset based at least in part on data representative of model parameters, and wherein the model parameters are;

(a) an operation characteristic of the at least one controllable energy asset, (b) a thermodynamic property of the at least one energy asset, (c) a projected environmental condition during time period T; and

at least one processing unit communicatively coupled to the at least one memory, wherein, upon execution of the processing unit-executable instructions, the at least one processing unit;

A) prior to time period T, determines the suggested operating schedule based on an optimization of the objective function over time period T,

wherein the objective function is determined based on a dynamic simulation model of the energy profile of the at least one energy asset, a customer baseline (CBL) energy profile for the at least one energy asset, and a forecast wholesale electricity price, over time period T, associated with a wholesale electricity market,

wherein the dynamic simulation model is adaptive to physical changes in the at least one energy asset based on a parametric estimation using at least one of the model parameters, and

wherein the dynamic simulation model is trained using the data; and

B) controls the at least one communication interface to transmit to the energy customer the suggested operating schedule determined in A), and/or controls the at least one memory so as to store the determined suggested operating schedule,

wherein the operation of the at least one energy asset according to the suggested operating schedule, over a time period T, facilitates generation of energy-related revenue based at least in part on the wholesale electricity market.

2. The apparatus of claim 1, wherein the CBL energy profile is computed based on applying the dynamic simulation model to the data representative of the operation characteristic of the at least one controllable energy asset, the thermodynamic property of the building asset, and an environmental condition, all during a time period T_A prior to time period T.

3. The apparatus of claim 1, wherein the data representative of the projected environmental condition is data representative of at least one of an ambient temperature of the environment in which the building asset is located;

a humidity of the environment in which the building asset is located;

an amount of solar irradiance of the environment in which the building asset is located, an amount of cloud cover of the environment in which the building asset is located, an outside air temperature, an outside air humidity, an outside air enthalpy, an outside air wet bulb temperature, a dewpoint temperature, and a heat index.

4. The apparatus of claim 1, wherein the at least one energy asset comprises at least one building asset.

5. The apparatus of claim 4, wherein the data representative of the thermodynamic property of the building asset is data representative of at least one of an occupancy schedule of the building asset, a relative humidity of the building asset, a temperature of the building asset, and a lighting level of the building asset.

6. The apparatus of claim 1, wherein the operation characteristic of the at least one controllable energy asset is a load use schedule.

7. The apparatus of claim 6, wherein the load use schedule imposes a maximum allowable load drawn by the at least one controllable energy asset over a time interval that is less than time period T.

8. The apparatus of claim 7, wherein the load use schedule impose a different value of maximum allowable load at different time intervals during time period T.

9. The apparatus of claim 1, wherein the operation characteristic of the at least one controllable energy asset is an energy consumption profile as a function of time of the at least one controllable energy asset.

10. The apparatus of claim 1, wherein the operation characteristic of the at least one controllable energy asset is a set point.

11. The apparatus of claim 1, wherein the thermodynamic property of the at least one energy asset is a zone temperature.

12. The apparatus of claim 1, wherein, upon execution of the processor-executable instructions, the at least one processing unit determines the suggested operating schedule for the at least one energy asset using the objective function in A) by minimizing a net energy-related cost over the time period T,

wherein the net-energy related cost is based at least in part on:

an electricity consumption by the at least one controllable energy asset; and

the CBL energy profile; and

wherein the energy-related revenue available to the energy customer is based at least in part on the minimized net energy-related cost.

13. The apparatus of claim 12, wherein the net energy-related cost is specified as a difference between an electricity supply cost and a demand response revenue over the time period T.

14. The apparatus of claim 1, wherein the at least one processing unit determines the suggested operating schedule for the at least one energy asset as at least one bias signal, as an interruptible load function, or as at least one use modulation signal.

15. The apparatus of claim 14, wherein the at least one processing unit determines the suggested operating schedule for the at least one energy asset in (A) as at least one bias signal, and controls the at least one communication interface in (B) to transmit to the energy customer the at least one bias signal at different times during time period T.

16. The apparatus of claim 14, wherein the at least one processing unit controls the at least one communication interface to transmit to the energy customer the suggested operating schedule as at least one use modulation signal, and wherein the operation of the at least one energy asset according to the at least one use modulation signal causes a modulation with time of the load use of the controllable energy asset.

17. The apparatus of claim 1, wherein the dynamic simulation model of the energy profile of the at least one energy asset is a semi-linear regression over at least one of the model parameters.

18. The apparatus of claim 17, wherein the dynamic simulation model of the energy profile of the at least one energy asset is a semi-linear regression over at least one of a zone temperature of the at least one energy asset, a load schedule of the at least one energy asset, the projected environmental condition, and a control setpoint of the at least one controllable energy asset.

19. The apparatus of claim 18, wherein the zone temperature of the at least one energy asset is a semi-linear regression over at least one of the projected environmental condition, the load schedule of the at least one energy asset, and the control setpoint of the at least one controllable energy asset.

20. The apparatus of claim 1, wherein:

the at least one energy asset is at least one building asset; and

the at least one controllable energy asset comprises at least one heating, ventilation and air conditioning (HV AC) system to control a variable internal temperature of the at least one building asset.