Coordination of thermostatically controlled loads with unknown parameters

• US 10,210,568 B2
• Filed: 09/25/2015
• Issued: 02/19/2019
• Est. Priority Date: 09/26/2014
• Status: Active Grant

• Current Assignee: Battelle Memorial Institute, Ohio State Innovation Foundation (Ohio State University)
• Original Assignee: Battelle Memorial Institute, Ohio State Innovation Foundation (Ohio State University)
• Inventors: Lian, Jianming, Kalsi, Karanjit, Li, Sen, Zhang, Wei
• Primary Examiner(s): Wallis, Michael Rutland
• Application Number:
  US14/866,457
• Publication Number:
  US 20160092986A1
• Time in Patent Office: 1,243 Days
• Field of Search: 700121, 700286, 700291
• CPC Class Codes: G05B 13/041 in which a variable is automatically adjusted to optimise the performance
• CPC Class Codes: G06N 7/01 Probabilistic graphical models, e.g. probabilistic networks
• CPC Class Codes: G06Q 30/08 Auctions
• 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 13/00017 using optical fiber
• CPC Class Codes: H02J 13/00034 the elements or equipment being or involving an electric power substation
• CPC Class Codes: H02J 2310/64 The condition being economic, e.g. tariff based load management
• CPC Class Codes: H02J 3/00 Circuit arrangements for ac mains or ac distribution networks
• CPC Class Codes: H02J 3/008 involving trading of energy or energy transmission rights
• 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: 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 50/10 Energy trading, including energy flowing from end-user application to grid

Abstract

Apparatus and methods are disclosed for coordination of a population of Thermostatically Controlled Loads (TCLs) with unknown parameters to achieve group objectives including bidding and market clearing strategies designed to motivate self-interested users to realize efficient energy allocation subject to a peak power constraint. In one examples of the disclosed technology, a method of operating a load includes estimating a set of values for unmeasured parameters of the load'"'"'s thermal environment based on output measurements of the thermal environment, determining an energy response based on the estimated set of values for the unmeasured parameters, and transmitting a bid for power for a finite time period based on the determined energy response to the coordinator. A clearing price is received from the coordinator responsive to the transmitted bid and power is sent to the load responsive to the received clearing price.

Claims

1. A method of operating a load coupled to a thermal environment with power received from a power grid by submitting bids to a coordinator, the method comprising:

estimating a set of values for one or more unmeasured parameters of the thermal environment based at least in part on a plurality of output measurements of the thermal environment;

determining an energy response function that relates price data to quantity data for power to be consumed by the load based on the estimated set of values for the unmeasured parameters; and

transmitting a bid for power for a finite time period based on the determined energy response function to the coordinator, the bid indicating one price and one corresponding quantity of power.

2. The method of claim 1, further comprising receiving a clearing price from the coordinator responsive to the transmitted bid, the clearing price being based at least in part on the transmitted bid and on bids received from a plurality of additional loads;

and

responsive to the received clearing price, determining to send power received from the power grid to the load.

3. The method of claim 1, wherein the estimating comprises determining a distribution for a system state vector based in part on the output measurements, the output measurements including a time-ordered sequence of air temperatures, the system state vector being based in part on values determined for one or more model parameters.

4. The method of claim 1, wherein the estimating comprises updating a set of values for one or more model parameters to substantially maximize a likelihood function.

5. The method of claim 1, wherein the energy response function is determined based at least in part on the following:

a measured air temperature, a control deadband value, and the set of unmeasured parameters.

6. The method of claim 1, wherein the set of values for the one or more unmeasured parameters is determined using an equivalent thermal parameter model to estimate an inner mass temperature of the thermal environment.

7. The method of claim 1, further comprising estimating a state trajectory, wherein the determining the energy response function is based at least in part on the state trajectory.

8. The method of claim 1, wherein the estimating the parameters comprises:

performing an initial estimation of values for the one or more unmeasured parameters; and

determining a conditional distribution of a state of the thermal environment using a recursive B ayes filter.

9. The method of claim 8, wherein the recursive Bayes filter is a Kalman filter.

10. The method of claim 1, wherein the estimating the set of values for the unmeasured parameters comprises:

performing an initial estimation of values for a set of model parameters;

determining a conditional distribution of a set of state values for the thermal environment;

determining new values for the set of model parameters selected to maximize a likelihood function based on the conditional distribution;

repeating the determining the conditional distribution and the determining new values for the set of model parameters until a set of convergence criteria is met; and

after the convergence criteria has been met, providing an estimation of state trajectory and an updated set of parameters for determining the energy response function.

11. The method of claim 1, wherein the estimating is performed using means for estimating the set of values.

12. One or more computer-readable storage media storing computer-executable instructions that cause a computer to perform the method of claim 1.

13. A controller for operating a thermostatically-controlled load, the controller comprising:

one or more sensors configured to generate temperature data used to determine the energy response function;

a network adapter configured to transmit the bid to the coordinator;

one or more processors, the thermostatically-controlled load being configured to be activated and/or deactivated responsive to one or more signals received from the processors; and

one or more computer-readable storage media storing computer-executable instructions that cause the controller to perform the method of claim 1.

14. The method of claim 1, wherein the coordinator is configured to send clearing prices for a retail power market to a plurality of controllers configured to operate thermostatically-controlled loads, the coordinator comprising one or more processors configured to, for each of the loads:

receive the transmitted bid;

determine a clearing price for the transmitted bid; and

transmit the clearing price to the load.

15. A method of allocating power, comprising:

receiving one respective bid for power for each of a plurality of loads coupled to a power grid, the bid for each load being generated by a controller coupled to the load based on an energy response function that relates price data to quantity data for power to be consumed by the load, the controller being configured to determine the energy response function by estimating a respective set of values for one or more unmeasured parameters of a thermal environment of each of the loads;

determining a clearing price for the plurality of received bids;

transmitting the clearing price to each of the loads; and

sending power via the power grid to a selected one or more of the loads, the loads being selected based on the received bids and the clearing price.

16. A power grid, comprising:

an electric power distribution system configured to transmit electric power from one or more power sources to a plurality of thermostatically controlled loads; and

a market coordinator configured to perform the method of claim 15.

17. The method of claim 15, wherein the unmeasured parameters comprise an inner mass temperature of the thermal environment.

18. The method of claim 15, further comprising, for each of the plurality of loads:

when the received bid for the load is greater than or equal to the clearing price, activating the load via the controller coupled to the load; and

when the received bid for the load is less than the clearing price, de-activating the load via the controller coupled to the load.

19. A market-based control system configured to coordinate a group of thermostatically controlled loads to achieve system-level objectives with pricing incentives, the system comprising:

a market coordinator configured to generate clearing price data based on a plurality of bids specifying a quantity and a price for consuming power;

a plurality of thermostatically controlled loads (TCLs), each of the TCLs being configured to transmit bid data to the market coordinator specifying a bid quantity and a bid price for power received via a power grid for a predetermined time period, the transmitted bid data determined based on an energy response function that relates price data to quantity data for power to be consumed by the load, the energy response function being determined based at least in part on estimating unmeasured parameters for a thermal environment to which each of the respective TCLs is coupled to supply heating or cooling to, each of the TCLs being further configured to consume or not consume power from the power grid based at least in part on the clearing price data and the TCL'"'"'s respective bid data for the predetermined time period; and

a computer network configured to transmit the bid data and the clearing price data between the market coordinator and each of the TCLs.

20. The system of claim 19, further comprising the power grid, the power grid being configured to distribute power to the TCLs based at least in part on a market cleared by the market coordinator.

21. The system of claim 19, further comprising a power generation market administrator configured to send wholesale energy price data to the market coordinator, the wholesale energy price data being used at least in part to determine the clearing price data.

22. The system of claim 19, further comprising means for determining the bid quantity and the bid price based at least in part on estimated unmeasured parameters for each TCL'"'"'s respective thermal environment.