Electric vehicle distributed intelligence

Patent metadata

Field	Value
Publication number	US-9766671-B2
Application number	US-201313766518-A
Country	US
Kind code	B2
Filing date	Feb 13, 2013
Priority date	Feb 13, 2012
Publication date	Sep 19, 2017
Grant date	Sep 19, 2017

Abstract

A system and method for distributed intelligence of power tracking and power allocation may include: receiving data by at least one computer from a plurality of identified charging stations and vehicles of customers at distributed locations throughout a power grid; analyzing, with at least one processor of the at least one computer, the data with respect to available power for those locations and customer historical usage and profiles; and sending commands, with the at least one processor, to reallocate power to assets of the power grid to handle fluctuations or forecasted fluctuations in power demand based on the analysis. Customer preferences may also be considered in predicting power demand issues and need for demand response. Economic rules may be executed to incentivize the customers to comply with demand response requirements where demand is greater than power supply.

First claim

The invention claimed is:

1. A method for distributed intelligence of power tracking and power allocation, the method executable by at least one computer including at least one processor and memory, the method comprising:
receiving, by the at least one computer, first parameters related to system and charging infrastructure within power transmission and distribution assets of a power grid, and second parameters associated with a plurality of electric vehicles, wherein the second parameters associated with an electric vehicle (EV) of the plurality of electric vehicles comprise a scheduled time and a scheduled location for charging the EV, according to a travel plan of the EV, at one or more charging stations geographically distributed as charging points throughout the power grid, the power grid comprising generators, substations and feeder circuits, the substations configured to supply power from the generators to the charging stations via the feeder circuits;
analyzing, using the at least one processor, the first parameters to determine available power for charging stations connected to the feeder circuits and geographically positioned at the scheduled locations;
analyzing, using the at least one processor, the first parameters and the second parameters of the electric vehicles, the analyzing comprising:
forecasting power demand at the scheduled times and at the scheduled locations based on an aggregation of the second parameters of the plurality of electric vehicles; and
determining whether the power demand at the scheduled times and scheduled locations for charging the electric vehicles can be met by the available power at the charging stations; and

in response to determining that the power demand for charging the electric vehicles cannot be met by the available power, the processor executing instructions to:
execute a demand response in the power grid to compensate for a lack of available power for charging the electric vehicles, wherein the demand response comprises allocation and delivery of power at the scheduled locations at the scheduled times; and
execute economic rules to incentivize charging the electric vehicles in compliance with the demand response.

2. The method of claim 1 , where the parameters related to the system and charging infrastructure include availability of on-site power storage at a scheduled location and level of charge of the on-site power storage to support EV charging.

3. The method of claim 1 , further comprising executing business rules based on the electric vehicle being a new or an existing customer; and a payment mechanism being used to charge the electric vehicle.

4. The method of claim 1 , where parameters related to the economic rules include: a rate in effect at time of charging at a charging station; demand response rates in effect at a peak pricing; and localized rates.

5. The method of claim 1 , where parameters related to the economic rules include penalties for opting out of a scheduled time or a scheduled location for charging; and applicable rates or tariffs for a transaction during the demand response.

6. The method of claim 1 , further comprising: tracking the EVs to determine the second parameters associated with the respective EVs.

7. The method of claim 1 , further comprising: identifying a first EV of the plurality of Evs being charged at the scheduled time and at the scheduled location based on an identifier associated with the first EV.

8. A system for distributed intelligence of power tracking and power allocation, the system comprising:
a communication interface configured to receive:
first parameters related to power transmission and distribution assets of a power grid comprising generators, substations and feeder circuits, and
second parameters related to an electric vehicle (EV), the second parameters comprise a time-interval and a geographic location of a charging station of the power grid to charge the EV based on a travel route of the EV that reaches the geographic location of the charging station during the time interval;

a processor configured to:
analyze the first parameters to determine available power at the charging station during the time interval of the EV reaching the geographic location of the charging station, the charging station connected to a substation configured to supply the available power from a generator to the charging station via a feeder circuit;
analyze the first and second parameters to:
forecast power demand at the charging station at the geographic location during the time-interval; and
compare the forecasted power demand with the available power at the charging station; and

in response to the forecasted power demand not being met by the determined available power:
execute a demand response in the power grid to compensate for a lack of available power for EV charging, where the demand response comprises allocation and delivery of power to the charging station at the location during the time-interval; and
execute economic rules to incentivize compliance with the location and time-interval.

9. The system of claim 8 , where the processor is further configured to reallocate power to and from a plurality of assets of the power grid to handle fluctuations or forecasted fluctuations in power demand based on receipt of changes to the second parameters that affect the power demand at the charging station.

10. The system of claim 8 , where the first parameters related to the system and charging infrastructure comprise: an operational restriction of a charging station; a reservation of a charging station by a customer; a presence of an abnormal event; and a level of infrastructure capability as related to a charging station.

11. The system of claim 8 , where the processor is further configured to execute business rules, where parameters related to the business rules include: the EV being a new or an existing customer; and a payment mechanism associated with the electric vehicle.

12. The system of claim 8 , where the first parameters related to the system and charging infrastructure, which includes availability of on-site power generation for the EV charging.

13. The system of claim 8 , where the parameters related to the economic rules include: a rate in effect at time of charging at the charging stations, demand response rates in effect at a peak pricing, and localized rates.

14. The system of claim 8 , where parameters related to the economic rules include penalties for opting out of a demand response event that would decrease or stop power available for charging at the location during the time-interval, and applicable rates or tariffs for a transaction at the location during the time-interval.

15. A non-transitory computer-readable medium having a plurality of instructions executable by a processor to manage distributed intelligence in tracking and allocating power of a power grid, the computer-readable medium comprising:
instructions to direct the processor to receive a first set of parameters and a second set of parameters, the first set of parameters related to the power grid, the power grid comprising a generator, a substation, a feeder circuit, and a charging infrastructure comprising a plurality of charging stations included within power transmission and distribution assets of the power grid, and the second set of parameters related to multiple electric vehicles (EV), each second set of parameters of an EV comprising a charging station location along a travel route of said EV and a time-interval scheduled for said EV to be charged at said charging station location;
instructions to direct the processor to analyze t

Assignees

• Accenture Global Services Ltd

Inventors

• Dorn John Z
• Malcolm Wade P

Classifications

• H02J3/322

  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 title

• H02J2103/30

  Simulating, planning, modelling, reliability check or computer assisted design [CAD] of electric power networks · CPC title

• H02J3/003

  Load forecast, e.g. methods or systems for forecasting future load demand · CPC title

• G06Q30/0202

  Market predictions or forecasting for commercial activities · CPC title

• B60L53/63 Primary

  in response to network capacity · CPC title