REGIONAL CHARGING CONTROL SERVICE

• US 20160052413A1
• Filed: 08/25/2014
• Published: 02/25/2016
• Est. Priority Date: 08/25/2014
• Status: Active Grant

• Current Assignee: Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation)
• Original Assignee: Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation)
• Inventors: Yokoyama, Akihisa, Kumita, Kunihiko, Shimizu, Takayuki, Ohno, Tomoya
• Granted Patent: US 9,789,779 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: B60L 2240/70 Interactions with external data bases, e.g. traffic centres
• CPC Class Codes: B60L 2250/14 by input of vehicle departure time
• CPC Class Codes: B60L 2260/52 drive range estimation, e.g. of estimation of available travel distance
• CPC Class Codes: B60L 2260/58 Departure time prediction
• CPC Class Codes: B60L 53/30 Constructional details of charging stations
• CPC Class Codes: B60L 53/305 Communication interfaces
• CPC Class Codes: B60L 53/63 in response to network capacity
• CPC Class Codes: B60L 53/64 Optimising energy costs, e.g. responding to electricity rates
• CPC Class Codes: B60L 53/65 involving identification of vehicles or their battery types
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: H02J 13/00024 by means of mobile telephony
• CPC Class Codes: H02J 13/00026 involving a local wireless network, e.g. Wi-Fi, ZigBee or Bluetooth
• 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 3/14 by switching loads on to, or off from, network, e.g. progressively balanced loading
• CPC Class Codes: H02J 3/322 the battery being on-board an electric or hybrid vehicle, e.g. vehicle to grid arrangements [V2G], power aggregation, use of the battery for network load balancing, coordinated or cooperative battery charging
• CPC Class Codes: H04W 4/027 using movement velocity, acceleration information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• 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: Y02T 10/70 : Energy storage systems for electromobility, e.g. batteries
• CPC Class Codes: Y02T 10/7072 : Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
• CPC Class Codes: Y02T 10/72 : Electric energy management in electromobility
• CPC Class Codes: Y02T 90/12 : Electric charging stations
• CPC Class Codes: Y02T 90/14 : Plug-in electric vehicles
• CPC Class Codes: Y02T 90/16 : Information or communication technologies improving the operation of electric vehicles
• CPC Class Codes: Y02T 90/167 : Systems integrating technologies related to power network operation and communication or information technologies for supporting the interoperability of electric or hybrid vehicles, i.e. smartgrids as interface for battery charging of electric vehicles [EV] or hybrid vehicles [HEV]
• CPC Class Codes: Y04S 10/126 : the energy generation units being or involving electric vehicles [EV] or hybrid vehicles [HEV], i.e. power aggregation of EV or HEV, vehicle to grid arrangements [V2G]
• CPC Class Codes: Y04S 20/222 : Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 30/14 : Details associated with the interoperability, e.g. vehicle recognition, authentication, identification or billing
• CPC Class Codes: Y04S 50/10 : Energy trading, including energy flowing from end-user application to grid

Abstract

The disclosure includes a system and method for providing charging services to mobile client devices. The system includes a processor and a memory storing instructions that, when executed, cause the system to: receive demand response event data associated with a geographic region; determine a last-mile distribution network that includes a first endpoint in the geographic region, the first endpoint associated with a mobile client device; estimate one or more last-mile power usage factors describing power usage of a set of endpoints in the last-mile distribution network, the set of endpoints including the first endpoint associated with the mobile client device; and determine a charge schedule for the mobile client device based on the demand response event data and the one or more last-mile power usage factors.

Claims

1. A method comprising:

receiving demand response event data associated with a geographic region;

determining a last-mile distribution network that includes a first endpoint in the geographic region, the first endpoint associated with a mobile client device;

estimating one or more last-mile power usage factors describing power usage of a set of endpoints in the last-mile distribution network, the set of endpoints including the first endpoint associated with the mobile client device; and

determining, by a processor-based computing device programmed to perform the determining, a charge schedule for the mobile client device based on the demand response event data and the one or more last-mile power usage factors.

2. The method of claim 1, further comprising:

receiving data describing a utility charging preference of a utility service;

receiving data describing a user charging preference of a user associated with the mobile client device; and

determining the charge schedule for the mobile client device further based on the utility charging preference and the user charging preference.

3. The method of claim 1, further comprising:

performing a negotiation process between the set of endpoints within the last-mile distribution network to keep a total load in the last-mile distribution network below a threshold; and

determining the charge schedule further based on a negotiation result from the negotiation process.

4. The method of claim 3, wherein performing the negotiation process between the set of endpoints within the last-mile distribution network comprises:

receiving a prioritized signal from the first endpoint associated with the mobile client device, the prioritized signal indicating to charge the mobile client device during a time period;

determining a second endpoint in the last-mile distribution network that agrees to reduce power usage during the time period responsive to the prioritized signal;

estimating an amount of power saved by the second endpoint during the time period; and

generating the negotiation result that includes the amount of power saved by the second endpoint.

5. The method of claim 4, wherein the charge schedule uses the amount of power saved by the second endpoint to charge the mobile client device.

6. The method of claim 4, further comprising:

increasing a first reward value associated with the second endpoint based on the amount of power saved by the second endpoint; and

reducing a second reward value associated with the first endpoint based on the amount of power.

7. The method of claim 1, wherein the demand response event data includes time-of-use pricing data, peak time rebate data, and direct load control data.

8. A system comprising:

one or more processors;

one or more non-transitory tangible computer readable mediums communicatively coupled to the one or more processors and storing executable instructions executable by the one or more processors to perform operations comprising;

receiving demand response event data associated with a geographic region;

determining a last-mile distribution network that includes a first endpoint in the geographic region, the first endpoint associated with a mobile client device;

estimating one or more last-mile power usage factors describing power usage of a set of endpoints in the last-mile distribution network, the set of endpoints including the first endpoint associated with the mobile client device; and

determining a charge schedule for the mobile client device based on the demand response event data and the one or more last-mile power usage factors.

9. The system of claim 8, wherein the instructions executable by the one or more processors perform operations further comprising:

receiving data describing a utility charging preference of a utility service;

receiving data describing a user charging preference of a user associated with the mobile client device; and

determining the charge schedule for the mobile client device further based on the utility charging preference and the user charging preference.

10. The system of claim 8, wherein the instructions executable by the one or more processors perform operations further comprising:

performing a negotiation process between the set of endpoints within the last-mile distribution network to keep a total load in the last-mile distribution network below a threshold; and

determining the charge schedule further based on a negotiation result from the negotiation process.

11. The system of claim 10, wherein the instructions executable by the one or more processors perform the negotiation process between the set of endpoints within the last-mile distribution network by:

receiving a prioritized signal from the first endpoint associated with the mobile client device, the prioritized signal indicating to charge the mobile client device during a time period;

determining a second endpoint in the last-mile distribution network that agrees to reduce power usage during the time period responsive to the prioritized signal;

estimating an amount of power saved by the second endpoint during the time period; and

generating the negotiation result that includes the amount of power saved by the second endpoint.

12. The system of claim 11, wherein the charge schedule uses the amount of power saved by the second endpoint to charge the mobile client device.

13. The system of claim 11, wherein the instructions executable by the one or more processors perform operations further comprising:

increasing a first reward value associated with the second endpoint based on the amount of power saved by the second endpoint; and

reducing a second reward value associated with the first endpoint based on the amount of power.

14. The system of claim 8, wherein the demand response event data includes time-of-use pricing data, peak time rebate data, and direct load control data.

15. A computer program product comprising a non-transitory computer-usable medium including a computer-readable program, wherein the computer-readable program when executed on a computer causes the computer to:

receive demand response event data associated with a geographic region;

determine a last-mile distribution network that includes a first endpoint in the geographic region, the first endpoint associated with a mobile client device;

estimate one or more last-mile power usage factors describing power usage of a set of endpoints in the last-mile distribution network, the set of endpoints including the first endpoint associated with the mobile client device; and

determine a charge schedule for the mobile client device based on the demand response event data and the one or more last-mile power usage factors.

16. The computer program product of claim 15, wherein the computer-readable program when executed on the computer further causes the computer to:

receive data describing a utility charging preference of a utility service;

receive data describing a user charging preference of a user associated with the mobile client device; and

determine the charge schedule for the mobile client device further based on the utility charging preference and the user charging preference.

17. The computer program product of claim 15, wherein the computer-readable program when executed on the computer further causes the computer to:

perform a negotiation process between the set of endpoints within the last-mile distribution network to keep a total load in the last-mile distribution network below a threshold; and

determine the charge schedule further based on a negotiation result from the negotiation process.

18. The computer program product of claim 17, wherein performing the negotiation process between the set of endpoints within the last-mile distribution network comprises:

receiving a prioritized signal from the first endpoint associated with the mobile client device, the prioritized signal indicating to charge the mobile client device during a time period;

determining a second endpoint in the last-mile distribution network that agrees to reduce power usage during the time period responsive to the prioritized signal;

estimating an amount of power saved by the second endpoint during the time period; and

generating the negotiation result that includes the amount of power saved by the second endpoint.

19. The computer program product of claim 18, wherein the charge schedule uses the amount of power saved by the second endpoint to charge the mobile client device.

20. The computer program product of claim 18, wherein the computer-readable program when executed on the computer further causes the computer to:

increase a first reward value associated with the second endpoint based on the amount of power saved by the second endpoint; and

reduce a second reward value associated with the first endpoint based on the amount of power.