Automated demand response energy management system

• US 8,838,281 B2
• Filed: 02/27/2013
• Issued: 09/16/2014
• Est. Priority Date: 12/15/2011
• Status: Active Grant

• Current Assignee: REstore NV (Centrica PLC)
• Original Assignee: REstore NV (Centrica PLC)
• Inventors: Rombouts, Jan-Willem, Gheerardyn, Jos
• Primary Examiner(s): Padmanabhan, Kavita
• Assistant Examiner(s): Everett, Christopher E
• Application Number:
  US13/779,560
• Publication Number:
  US 20130178993A1
• Time in Patent Office: 566 Days
• Field of Search: None
• US Class Current: 700/291
• CPC Class Codes: G05B 13/02 electric
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• 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 2310/12 The local stationary network supplying a household or a building
• CPC Class Codes: H02J 3/14 by switching loads on to, or off from, network, e.g. progressively balanced loading
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y02B 90/20 Smart grids as enabling technology in buildings sector smart grids supporting the management or operation of end-user stationary applications in general, or like technologies with no associated climate change mitigation effect Y04S20/00
• 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 80/10 Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
• 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 20/00 Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 40/20 Information technology specific aspects, e.g. CAD, simulation, modelling, system security
• CPC Class Codes: Y04S 50/16 Energy services, e.g. dispersed generation or demand or load or energy savings aggregation

Abstract

The power flexibility of energy loads are maximized using a value function for each load and outputting optimal control parameters per load. These loads are aggregated into a virtual load by maximizing a global value function that includes the value function for each individual load. The solution yields a dispatch function providing: a percentage of energy to be assigned to each individual load, a possible time-varying power level within a time interval for each load, and control parameters and values. An economic term of the global value function represents the value of the power flexibility to different energy players. A user interface includes for each time interval upper and lower bounds representing respectively the maximum power that may be reduced to the virtual load and the maximum power that may be consumed by the virtual load. An energy trader modifies an energy level in a time interval relative to the reference curve for the virtual load. Automatically, energy compensation for the other intervals and recalculation of upper and lower boundaries occurs and is displayed. The energy schedule for the virtual load is distributed to the actual loads using the dispatch function.

Claims

1. A method of rescheduling energy for a virtual energy load, said method comprising:

computing an energy schedule for said virtual load, said energy schedule indicating an energy level to be consumed by said virtual load for each of a plurality of time intervals within a time period, said virtual load representing a plurality of actual energy loads;

distributing an individual control schedule to each of said actual loads such that said actual loads in total consume energy according to said energy schedule;

receiving power logging data from at least one of said actual loads during a current one of said time intervals, said power logging data indicating an amount of energy consumed by said at least one of said actual loads in said current time interval;

estimating a total energy consumption of said virtual load in said current time interval;

comparing said total energy consumption with said energy level from said energy schedule for said current time interval;

recomputing said individual control schedules using an updated value for said energy level for said current time interval;

distributing said recomputed individual control schedules among said actual loads, whereby each actual load receives its recomputed individual control schedule and whereby said actual loads in total consume energy according to said energy schedule;

recalibrating a load model for each of said actual loads using logged state variables for each of said actual loads received during said current time interval, wherein said recomputing includes using an inverse model for each of said recalibrated load models in order to output said recomputed individual control schedules; and

controlling said actual loads during said time period using said recomputed individual control schedules.

2. A method as recited in claim 1 wherein each actual load operates under a set of constraints, said method further comprising:

controlling each of said actual loads using its individual control schedule while following said set of constraints for said each actual load.

3. A method as recited in claim 1 further comprising:

performing said steps of receiving, recomputing and distributing said recomputed individual control schedules during said current time interval.

4. A method as recited in claim 1 wherein said recomputing includes inputting a power for each load into an inverse model for each load in order to output said recomputed individual control schedules;

and

controlling each actual load during said time period using said recomputed individual control schedules.

5. A method as recited in claim 1 further comprising:

updating a load model for one of said actual loads, wherein said recomputing includes inputting a power for said one of said actual loads into an inverse model of said updated load model in order to output said recomputed individual control schedule for said one of said actual loads; and

controlling said one of said actual loads during said time period using said recomputed individual control schedule.

6. A method as recited in claim 1 further comprising:

determining if a deviation exists between said total energy consumption and said energy level from said energy schedule for said current time interval.

7. A method as recited in claim 1 further comprising:

submitting said energy schedule to a system operator as a reference curve.

8. A method as recited in claim 1 wherein said recomputed individual control schedules assure that said virtual load will consume only said energy level for said current time interval during said current time interval.

9. A method as recited in claim 1 wherein each of said actual energy loads are in geographically distributed locations and have different owners.

10. A method as recited in claim 1 wherein said virtual load is not an actual energy load that consumes energy.

11. A method as recited in claim 1 wherein said updated value is a difference between said energy level for said current time interval and said total energy consumption.

12. A method as recited in claim 1 wherein said actual loads in total consuming energy according to said energy schedule includes consuming energy within about 10 kW-hours of said energy level in said energy schedule for said current time interval.

13. A method as recited in claim 1 wherein said energy schedule is dictated by an energy player external to and outside control of an owner of said actual energy loads.