Aggregate load management at a system level

• US 9,014,864 B2
• Filed: 02/22/2012
• Issued: 04/21/2015
• Est. Priority Date: 02/22/2012
• Status: Active Grant

• Current Assignee: Haier US Appliance Solutions, Inc. DBA GE Appliances (Haier Group Company)
• Original Assignee: General Electric Company
• Inventors: Najewicz, David Joseph, Smith, Charles Ray, Drake, Jeff Donald, Burke, William Jerome
• Primary Examiner(s): DUNN, DARRIN D
• Application Number:
  US13/402,403
• Publication Number:
  US 20130218360A1
• Time in Patent Office: 1,154 Days
• Field of Search: 700/48, 700/49, 700/50, 700/275, 700/286, 700/291, 700/295, 700/297
• US Class Current: 700/286
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 2219/2642 Domotique, domestic, home control, automation, smart house
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass
• CPC Class Codes: H02J 13/00017 using optical fiber
• CPC Class Codes: H02J 13/00028 involving the use of Internet protocols
• CPC Class Codes: H02J 13/00034 the elements or equipment being or involving an electric power substation
• CPC Class Codes: H02J 3/144 Demand-response operation of the power transmission or distribution network
• CPC Class Codes: Y02B 70/30 Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y02E 60/00 Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
• CPC Class Codes: Y04S 20/20 End-user application control systems
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 40/124 using wired telecommunication networks or data transmission busses
• CPC Class Codes: Y04S 50/16 Energy services, e.g. dispersed generation or demand or load or energy savings aggregation

Abstract

A method for aggregate load management includes determining whether a load capacity limit within a utility power network will be exceeded, selecting an aggregated demand reduction target to remain within capacity bounds if the load capacity limit is to be exceeded, selecting a demand reduction strategy, and sending a control signal that includes a randomized PWM level, based on the strategy, to a controller in a load component of the utility system based on the reduction target. A method for component load management includes receiving a control signal from a utility system based on a utility demand reduction strategy, converting the signal into randomized PWM control of the load component in accordance therewith, receiving an updated control signal based on utility system monitoring of an aggregate load of a component of the utility system, and converting the updated signal into randomized PWM control of the load component in accordance therewith.

Claims

1. A method for aggregate load management, comprising:

determining whether a load capacity limit within a utility power network will be exceeded;

selecting an aggregated demand reduction target to remain within capacity bounds if the load capacity limit is to be exceeded;

selecting a demand reduction strategy;

sending a first control signal that includes a first pulse width modulation level to a first controller in at least a first load component of the utility system based on the aggregated demand reduction target; and

sending a second control signal that includes a second pulse width modulation level different than the first pulse width modulation level to a second controller in at least a second load component of the utility system based on the aggregated demand reduction target,

wherein respective magnitudes of the first and second pulse width modulation levels are based on the strategy selected, load levels at the first and second load components, types of loads at the first and second load components, availability of loads suitable for reduction at the first and second load components, and a local need for load reduction at the first and second load components, and

wherein the first and second controllers include respective randomization algorithms to randomize on and off times of duty cycles for respective loads in the first and second load components over a control period.

2. The method of claim 1, further comprising:

monitoring an aggregate load of the first and second load components of the utility system to determine if the target is achieved; and

sending an updated control signal to at least one of the first and second load components of the utility system if the target is not achieved, until the target is achieved.

3. The method of claim 1, wherein the aggregated demand reduction target comprises at least one of a local demand reduction target and a global demand reduction target.

4. The method of claim 1, wherein the load capacity limit within the utility power network comprises at least one of a local load capacity limit and a global load capacity limit.

5. The method of claim 1, wherein at least one of the first load component and the second load component of the utility system comprises a household or a building equipped with one or more energy controllers with one or more types of loads.

6. The method of claim 1, wherein determining whether the load capacity limit within the utility power network will be exceeded comprises analyzing at least one of generation capacity, transmission and distribution equipment capacity, geographic and power network topology information, component load information provided by a plurality of controllers, rate structure information, weather predictions and past history for the utility system.

7. The method of claim 1, wherein the demand reduction strategy is based on a uniform reduction amongst one or more loads in at least one of the first and second load components of the utility system.

8. The method of claim 1, wherein the demand reduction strategy is based on a magnitude of current component loads, wherein one or more comparatively larger loads are targeted for comparatively larger reductions, as compared to one or more smaller loads.

9. The method of claim 1, wherein the demand reduction strategy is based on geographic or network topology.

10. The method of claim 1, wherein the demand reduction strategy is based on a type of rate agreement with each component.

11. The method of claim 1, wherein the demand reduction strategy is based on a type of load to be reduced as selected by a consumer, wherein the consumer selects, in at least one of the first controller and the second controller, a preference of one or more loads to be controlled from a highest priority to a lowest priority.

12. The method of claim 1, further comprising:

obtaining a level and a nature of at least one load in the utility system via an advanced metering infrastructure system.

13. The method of claim 1, further comprising:

obtaining a level and a nature of at least one load in the utility system via a communication path using at least one of a wireless carrier, a power line carrier, and the Internet.

14. The method of claim 1, further comprising:

performing a controlled system load restoration at an end of a demand reduction period.

15. A system for aggregate load management, comprising:

at least one distinct software module, each distinct software module being embodied on a tangible computer-readable recordable medium;

a memory; and

at least one processor coupled to the memory and operative for;

determining whether a load capacity limit within a utility power network will be exceeded;

selecting an aggregated demand reduction target to remain within capacity bounds if the load capacity limit is to be exceeded;

selecting a demand reduction strategy;

sending a first control signal that includes a first pulse width modulation level to a first controller in at least a first load component of the utility system based on the aggregated demand reduction target; and

sending a second control signal that includes a second pulse width modulation level different than the first pulse width modulation level to a second controller in at least a second load component of the utility system based on the aggregated demand reduction target,

wherein respective magnitudes of the first and second pulse width modulation levels are based on the strategy selected, load levels at the first and second load components, types of loads at the first and second load components, availability of loads suitable for reduction at the first and second load components, and a local need for load reduction at the first and second load components, and

wherein the first and second controllers include respective randomization algorithms to randomize on and off times of duty cycles for respective loads in the first and second load components over a control period.

16. The system of claim 15, wherein the at least one processor coupled to the memory is further operative for:

monitoring an aggregate load of the first and second load components of the utility system to determine if the target is achieved; and

sending an updated control signal to at least one of the first and second load components of the utility system if the target is not achieved, until the target is achieved.

17. The system of claim 15, wherein the at least one processor coupled to the memory operative for determining whether the load capacity limit within the utility power network will be exceeded is further operative for analyzing at least one of generation capacity, transmission and distribution equipment capacity, geographic and power network topology information, component load information provided by a plurality of controllers, rate structure information, weather predictions and past history for the utility system.

18. The system of claim 15, wherein the demand reduction strategy is based on type of load to be reduced as selected by a consumer, wherein the consumer selects, in at least one of the first controller and the second controller, a preference of one or more loads to be controlled from a highest priority to a lowest priority.

19. The system of claim 15, wherein the at least one processor coupled to the memory is further operative for:

performing a controlled system load restoration at an end of a demand reduction period.

20. A method for load management at a component level, comprising:

receiving, via a first controller in a first load component, a first control signal from a utility system based on a utility demand reduction strategy;

converting the first control signal into a randomized pulse width modulation control of the first load component in accordance with the first control signal and a randomization algorithm included in the first controller to randomize on and off times of duty cycles for respective loads in the first load component over a control period;

receiving, via the first controller in the first load component, an updated control signal from the utility system based on utility system monitoring of an aggregate load of at least one component of the utility system; and

converting the updated control signal into a pulse width modulation control of the first load component in accordance with the updated control signal and the randomization algorithm to randomize on and off times of duty cycles for respective loads in the first load component over another control period;

wherein the first control signal includes a first pulse width modulation level, the first pulse width modulation level being different than a second pulse width modulation level of a second control signal received at a second controller for a second load component in the utility system,

wherein respective magnitudes of the first and second pulse width modulation levels are based on the utility demand reduction strategy, load levels at the first and second load components, types of loads at the first and second load components, availability of loads suitable for reduction at the first and second load components, and a local need for load reduction at the first and second load components.