Method and Apparatus for Managing Demand Response Resources in a Power Distribution Network

• US 20140316598A1
• Filed: 03/06/2014
• Published: 10/23/2014
• Est. Priority Date: 03/13/2013
• Status: Active Grant

• Current Assignee: Hitachi Energy Limited (Hitachi, Ltd.)
• Original Assignee: ABB Research Ltd. (ABB Limited)
• Inventors: Mohagheghi, Salman, Yang, Fang
• Granted Patent: US 9,577,435 B2
• Time in Patent Office: Days
• US Class Current: 700/295
• CPC Class Codes: H02J 2203/20 Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
• CPC Class Codes: H02J 2310/60 Limiting power consumption in the network or in one section of the network, e.g. load shedding or peak shaving
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: H02J 3/007 Arrangements for selectively connecting the load or loads to one or several among a plurality of power lines or power sources for providing uninterruptable power supply H02J9/00
• CPC Class Codes: H02J 3/144 Demand-response operation of the power transmission or distribution network
• CPC Class Codes: H02J 4/00 Circuit arrangements for mains or distribution networks not specified as ac or dc
• 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 20/222 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

Abstract

In one aspect of the teachings herein, demand responsive loads are selected for involvement in a given DR event using an advantageous approach to selection that is based on using a mathematical network model to evaluate power loss in a power distribution network as a function of different combinations of demand responsive load selections and corresponding load reduction values. The mathematical network model comprises a mathematical representation of the power distribution network as a multi-phase unbalanced distribution network, including mathematical representations of the physical components in the power distribution network and the connecting relationships of those components. As overall power loss in the system is a function of different combinations of demand responsive load selections, the mathematical network model is used to evaluate system power loss under different demand response load selections, in a manner that automatically accommodates mesh networks and other complex network topologies, distributed generation sources, etc.

Claims

1. A method in a computer system of selecting demand responsive loads in a power distribution network for inclusion in a demand response event having a defined load reduction target, said method comprising:

determining that the demand response event has been triggered for the power distribution network;

identifying demand responsive loads in the power distribution network that are candidates for inclusion in the demand response event;

selecting a set of the demand responsive loads to include in the demand response event and determining corresponding load reduction values for the selected set of demand responsive loads based on using a mathematical network model to evaluate power loss in the power distribution network as a function of different combinations of demand responsive load selections and corresponding load reduction values, to determine which combination of demand responsive load selections and corresponding load reduction values maximizes a reduction in power loss in the power distribution network while simultaneously satisfying the defined load reduction target and a number of solution constraints that include one or more network operating constraints, including at least one of power flow limits, node voltage limits and distribution line capacity limits; and

saving or otherwise outputting a demand response solution that indicates the selected set of demand responsive loads and the corresponding load reduction values determined for the selected set of demand responsive loads.

2. The method of claim 1, further comprising comparing the demand response solution to an alternative demand response solution involving a randomly selected set of the demand responsive loads, and selecting either the demand response solution or the alternative demand response solution in dependence on which one sheds the least amount of loading from the power distribution network.

3. The method of claim 1, wherein the mathematical network model of the power distribution network comprises a mathematical representation of the power distribution network as a multi-phase unbalanced distribution network, including mathematical representations of the physical components in the power distribution network and the connecting relationships of those physical components.

4. The method of claim 1, wherein using a mathematical network model to evaluate power loss in the power distribution network as a function of different combinations of demand responsive load selections and corresponding load reduction values comprises evaluating power flow equations by applying the power and current balance laws at each bus or node represented in the mathematical network model, according to a known set of load values corresponding to the demand responsive loads, as adjusted for any particular combination of load reduction values being considered.

5. The method of claim 1, further comprising sending signaling to customer premises equipment corresponding to the selected set of demand responsive loads, indicating the corresponding load reduction values determined for the selected set of demand responsive loads, to effectuate the demand response solution.

6. The method of claim 1, wherein using a mathematical network model to evaluate power loss in the power distribution network as a function of different combinations of demand responsive load selections and corresponding load reduction values comprises finding the combination of load reduction values that minimizes, subject to the solution constraints, a power loss function for the power distribution network subject that is expressed as a function of the load reduction values and of a set of system states, and wherein the solution constraints include any load reduction limits and load reduction timing restrictions associated with the demand responsive loads, and further include the network operating constraints, as applied to the set of system states.

7. The method of claim 6, further comprising optimizing the power loss function over a number of time intervals within a defined time window, including computing an updated demand response solution at each of the time intervals.

8. The method of claim 6, further comprising further expressing the power loss function as a summation of branch power losses over a plurality of branches represented in the mathematical network model, and computing the loss in each branch as a function of the modeled branch resistance and the square of the branch current magnitude calculated according to each evaluated combination of load reduction values.

9. The method of claim 6, further comprising further expressing the power loss function as a function of customer incentive payments that would arise from the application of each evaluated combination of load reduction values.

10. A computer system configured to select demand responsive loads in a power distribution network for inclusion in a demand response event having a defined load reduction target, said computer system comprising:

one or more memory or storage elements;

input/output interface circuitry; and

a processing circuit operatively associated with the input/output interface circuitry and the one or more memory or storage elements, said processing circuit configured to;

determine that the demand response event has been triggered for the power distribution network;

identify demand responsive loads in the power distribution network that are candidates for inclusion in the demand response event;

select a set of the demand responsive loads to include in the demand response event and determine corresponding load reduction values for the selected set of demand responsive loads based on using a mathematical network model to evaluate power loss in the power distribution network as a function of different combinations of demand responsive load selections and corresponding load reduction values, to determine which combination of demand responsive load selections and corresponding load reduction values maximizes a reduction in power loss in the power distribution network while simultaneously satisfying the defined load reduction target and a number of solution constraints that include one or more network operating constraints, including at least one of power flow limits, node voltage limits and distribution line capacity limits; and

save or otherwise output a demand response solution that indicates the selected set of demand responsive loads and the corresponding load reduction values determined for the selected set of demand responsive loads.

11. The computer system of claim 10, wherein the processing circuit is configured to compare the demand response solution to an alternative demand response solution involving a randomly selected set of the demand responsive loads, and select either the demand response solution or the alternative demand response solution in dependence on which one sheds the least amount of loading from the power distribution network.

12. The computer system of claim 10, wherein the mathematical network model of the power distribution network comprises a mathematical representation of the power distribution network as a multi-phase unbalanced distribution network, including mathematical representations of the physical components in the power distribution network and the connecting relationships of those physical components.

13. The computer system of claim 10, wherein the processing circuit is configured to use the mathematical network model to evaluate the power loss in the power distribution network as a function of different combinations of demand responsive load selections and corresponding load reduction values, based on evaluating power flow equations, including applying the power and current balance laws at each bus or node represented in the mathematical network model, according to a known set of load values corresponding to the demand responsive loads, as adjusted for any particular combination of load reduction values being considered.

14. The computer system of claim 10, wherein the processing circuit is configured to send signaling to customer premises equipment corresponding to the selected set of demand responsive loads, indicating the corresponding load reduction values determined for the selected set of demand responsive loads, to effectuate the demand response solution.

15. The computer system of claim 10, wherein the processing circuit is configured to use the mathematical network model to evaluate the power loss in the power distribution network as a function of different combinations of demand responsive load selections and corresponding load reduction values, based on finding the combination of load reduction values that minimizes, subject to the solution constraints, a power loss function for the power distribution network that is expressed as a function of the load reduction values and of a set of system states, and wherein the solution constraints include any load reduction limits and load reduction timing restrictions associated with the demand responsive loads, and further include the network operating constraints, as applied to the set of system states.

16. The computer system of claim 15, wherein the processing circuit is configured to optimize the power loss function over a number of time intervals within a defined time window, including computing an updated demand response solution at each of the time intervals.

17. The computer system of claim 15, wherein the processing circuit is configured to express the power loss function as a summation of branch power losses over a plurality of branches represented in the mathematical network model, and to compute the power loss in each branch as a function of the modeled branch resistance and the square of the branch current magnitude calculated according to the different combinations of load reduction values.

18. The computer system of claim 15, wherein the processing circuit is configured to further express the power loss function as a function of customer incentive payments that would arise from the application of the different combinations of load reduction values.