Coordination of thermostatically controlled loads

• US 10,607,303 B2
• Filed: 09/25/2015
• Issued: 03/31/2020
• 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
• Inventors: Lian, Jianming, Kalsi, Karanjit, Li, Sen, Zhang, Wei
• Primary Examiner(s): Flynn, Kevin H
• Assistant Examiner(s): Walsh, Emmett K.
• Application Number:
  US14/866,404
• Publication Number:
  US 20160092978A1
• Time in Patent Office: 1,649 Days
• Field of Search: 705412, 705 735
• 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 for a market-based control framework to coordinate a group of autonomous thermostatically controlled loads (TCL) to achieve system-level objectives with pricing incentives is disclosed. In one example of the disclosed technology, a method of providing power to a load via a power grid by submitting bids to a coordinator includes determining an energy response relating price data for one or more energy prices to quantity data for power to be consumed by the load, sending a bid for power for a finite time period based on the energy response to the coordinator, and receiving a clearing price based on: the bid, on bids received from a plurality of additional loads, and a feeder power constraint. In some examples, the energy response is based at least in part on an equivalent thermal parameter model and a control policy indicating one or more power states for the load.

Claims

1. A method of providing power to a load via a power grid by submitting bids to a coordinator, the method comprising:

with a controller;

determining an energy function characterized by a parameter vector, the energy function relating price data for one or more energy prices to quantity data for power to be consumed by the load, the load being coupled to receive power from the power grid; and

sending the parameter vector as a bid for power for a finite time period to the coordinator, wherein the bid further includes a structure of the energy function;

responsive to the sending of the parameter vector, receiving a clearing price from the coordinator; and

responsive to the receiving of the clearing price, sending a signal to cause actuation of the load during the finite time period,

wherein the energy function is an approximation of a true energy function, the approximated energy function determined as a step function that intersects the true energy function at a point half way between a first price point representing a maximum of the true energy function and a second price point at which the true energy function is equal to zero.

2. The method of claim 1, wherein the clearing price is based at least in part on the bid, on bids received by the coordinator from a plurality of additional loads, and on a feeder power constraint.

3. The method of claim 1, wherein the energy function is based at least in part on one or more of the following:

a consumption state of the load, an air temperature, or an inner mass temperature.

4. The method of claim 1, wherein the energy function is based at least in part on a user response parameter, the user response parameter relating energy price and a selected user comfort level.

5. The method of claim 1, wherein the energy function is based at least in part on an equivalent thermal parameter model and a control policy indicating one or more power states for the load.

6. The method of claim 1, wherein the energy function is based at least in part on an equivalent thermal parameter model.

7. The method of claim 1, wherein the finite time period is less than one hour.

8. The method of claim 1, wherein the controller further comprises:

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

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

one or more processors; and

one or more actuators configured to activate and/or deactivate the load responsive to one or more signals received from the processors.

9. The method of claim 1, wherein the load is one of a plurality of homogeneous loads receiving power from the power grid.

10. One or more computer-readable storage media storing computer-executable instructions that when executed by a computer, cause the computer to perform a method, the computer-executable instructions comprising:

instructions that cause the computer to determine an energy function, wherein the energy function relates price data for one or more energy prices to quantity data for power to be consumed by a load coupled to receive power from a power grid, and wherein the energy function is an approximation of a true energy function, the approximation determined as a step function that intersects the true energy function at a point half way between a first price point representing a maximum of the true energy function and a second price point at which the true energy function is equal to zero;

instructions that cause the computer to parameterize the energy function as a vector;

instructions that cause the computer to transmit the vector parameterizing the energy function as a bid for power for a finite time period to a coordinator;

instructions that cause the computer to receive clearing price data from the coordinator responsive to the transmitting of the vector parameterizing the energy function; and

instructions that cause the computer to send a signal that causes actuation of the load, the signal being based on the clearing price data.

11. The one or more computer-readable storage media of claim 10, further comprising:

instructions that cause the computer to receive a clearing price from the coordinator responsive to transmitting the bid, the clearing price being based at least in part on the bid and on bids received from a plurality of additional loads.

12. The one or more computer-readable storage media of claim 10, wherein the energy function based at least in part on one or more of the following:

a consumption state of the load, an air temperature, or an inner mass temperature.

13. The one or more computer-readable storage media of claim 10, wherein the energy function is based at least in part on a user response parameter, the user response parameter relating energy price and a selected user comfort level.

14. The one or more computer-readable storage media of claim 10, wherein the energy function is based at least in part on an equivalent thermal parameter model and a control policy indicating one or more power states for the load.

15. 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;

a plurality of homogeneous thermostatically controlled loads (TCLs), each of the TCLs being configured to determine an energy function characterized by a parameter vector and transmit the parameter vector to the market coordinator as a bid for power received via a power grid for a predetermined time period, the energy function for each TCL relating price data for one or more energy prices to quantity data for power to be consumed by the TCL, and 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 for the predetermined time period; and

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

wherein the energy functions for the plurality of TCLs have the same structure, and wherein differences between the energy functions for the plurality of TCLs are captured by the parameter vectors.

16. The system of claim 15, 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.

17. The system of claim 15, 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.

18. The system of claim 15, wherein the market coordinator is further configured to produce a demand curve by ordering the bids in a decreasing sequence from the highest bid to the lowest bid.

19. The system of claim 15, wherein the bid for at least one of the TCLs does not include the structure of the energy function.