U.S. patent application number 14/986083 was filed with the patent office on 2016-08-04 for electric vehicle power management systems.
This patent application is currently assigned to GridPoint, Inc.. The applicant listed for this patent is GridPoint, Inc.. Invention is credited to Zachary Axelrod, Seth W. Bridges, Joby Lafky, Seth B. Pollack.
Application Number | 20160221453 14/986083 |
Document ID | / |
Family ID | 42982790 |
Filed Date | 2016-08-04 |
United States Patent
Application |
20160221453 |
Kind Code |
A1 |
Bridges; Seth W. ; et
al. |
August 4, 2016 |
ELECTRIC VEHICLE POWER MANAGEMENT SYSTEMS
Abstract
A system that enables power flow management for electrical
devices, such as electric vehicles. Power flow managers can
coordinate charging activities. Power flow decisions may be based
on site-level information. Power flow management strategies may be
optimized. Power spikes may be avoided by using safe failure modes.
Generation stacks may be used for reducing cost. AGC commands are
used to control power resources. Power regulation are apportioned
to power resources, and power regulation ranges may be determined.
Power flow strategies are implemented in response to changes in
intermittent power flow. Locations of devices may be determined
using network fingerprints. Power flow measurements are determined,
and AC power flows are inferred from DC power flows. Network
traffic consumption are minimized. Communication protocols are
translated. Enhanced vehicle communications are provided that
communicate to vehicle subsystems, that arbitrate smart charge
points, and that use existing hardware, non-specific hardware, or
control extensibility systems.
Inventors: |
Bridges; Seth W.; (Seattle,
WA) ; Pollack; Seth B.; (Seattle, WA) ; Lafky;
Joby; (Seattle, WA) ; Axelrod; Zachary;
(Washington, DC) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
GridPoint, Inc. |
Arlington |
VA |
US |
|
|
Assignee: |
GridPoint, Inc.
Arlington
VA
|
Family ID: |
42982790 |
Appl. No.: |
14/986083 |
Filed: |
December 31, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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14338427 |
Jul 23, 2014 |
9283862 |
|
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14986083 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
B60L 11/184 20130101;
Y04S 10/126 20130101; B60L 2240/70 20130101; B60L 53/65 20190201;
Y02T 90/12 20130101; H02J 2300/10 20200101; Y02T 10/7072 20130101;
Y02T 10/70 20130101; H02J 7/00 20130101; Y02E 60/00 20130101; B60L
55/00 20190201; Y04S 30/14 20130101; B60L 53/18 20190201; B60L
53/665 20190201; Y04S 30/12 20130101; H02J 3/381 20130101; Y02T
90/167 20130101; Y02T 10/72 20130101; B60L 53/63 20190201; B60L
53/68 20190201; Y02T 90/16 20130101; B60L 53/64 20190201; Y02T
90/14 20130101; B60L 53/305 20190201 |
International
Class: |
B60L 11/18 20060101
B60L011/18 |
Claims
1. A method for managing power flow using safe failure modes in an
electric vehicle charging network, comprising: communicating a
first charging behavior from a central flow controller to a
plurality of electric vehicles; controlling power flow between each
of a plurality of charging stations and their corresponding
electric vehicles according to the first charging behavior;
detecting a communications failure mode between the central flow
controller and one or more of the plurality of electric vehicles;
controlling, in response to detecting the communications failure
mode, power flow between each of a plurality of charging stations
and their corresponding electric vehicles according to the second
charging behavior during the period of time of the communications
failure, wherein the second charging behavior is predictable and
non-disruptive to a power circuit supplying power to the plurality
of charging stations.
2. The method of claim 1, wherein the second charging behavior
comprises: maintaining the first charging behavior for a predefined
period of time; and transitioning to a predefined autonomous
charging strategy after the predefined period of time.
3. The method of claim 1, wherein the second charging behavior
comprises: limiting the power flow to each of the plurality of
electric vehicles to a value calculated to allow the plurality of
electric vehicles to charge at combined maximum power draw of the
electrical circuit supplying power to the plurality of charging
stations.
4. The method of claim 1, wherein the second charging behavior
comprises: executing charging behavior state transitions for each
of the plurality of electric vehicles, the charging state behavior
state transitions occurring at random offset times after the
detection of the failure mode.
5. The method of claim 1, wherein the second charging behavior
comprises: executing charging behavior state transitions for each
of the plurality of electric vehicles, the charging behavior state
transitions occurring at random offset times after the detection of
the failure mode, wherein electric vehicles of the plurality of
electric vehicles that are not being charged at the time of the
detected failure mode wait a random amount of time before
initiating charging, and wherein electric vehicles of the plurality
of electric vehicles that are being charged at the time of the
detected failure mode wait a random amount of time before
terminating charging.
6. The method of claim 1, wherein the second charging behavior
comprises: controlling power flow of each of the plurality of
electric vehicles detecting the failure mode according to a
predefined power curve stored in each of the plurality of electric
vehicles and in the central flow controller; determining, by the
flow controller, appropriate charging behaviors for each of the
plurality of electric vehicles that are not experiencing a failure
mode based on the predefined power curve stored in each of the
plurality of electric vehicles that are experiencing a power
failure mode; and communicating the appropriate charging behaviors
from the central flow controller to the plurality of electric
vehicles that are not experiencing a power failure mode.
7. The method of claim 1, wherein the second charging behavior
comprises: predicting the connection and disconnection of other of
the plurality of electric vehicles to and from the plurality of
charging stations, and controlling power flow based on those
predictions.
8. A computer program product for managing power flow using safe
failure modes in an electric vehicle charging network, comprising:
a computer usable medium having computer readable program code
embodied in the computer usable medium for causing an application
program to execute on a computer system, the computer readable
program code means comprising: computer readable program code for
communicating a first charging behavior from a central flow
controller to a plurality of electric vehicles; computer readable
program code for controlling power flow between each of a plurality
of charging stations and their corresponding electric vehicles
according to the first charging behavior; computer readable program
code for detecting a communications failure mode between the
central flow controller and the plurality of electric vehicles;
computer readable program code for controlling, in response to
detecting the communications failure mode, power flow between each
of a plurality of charging stations and their corresponding
electric vehicles according to the second charging behavior during
the period of time of the communications failure, wherein the
second charging behavior is predictable and non-disruptive to a
power circuit supplying power to the plurality of charging
stations.
9. The computer program product of claim 8, wherein the computer
readable program code for controlling power flow according to the
second charging behavior comprises: computer readable program code
for maintaining the first charging behavior for a predefined period
of time; and computer readable program code for transitioning to a
predefined autonomous charging strategy after the predefined period
of time.
10. The computer program product of claim 8, wherein the computer
readable program code for controlling power flow according to the
second charging behavior comprises: computer readable program code
for limiting the power flow to each of the plurality of electric
vehicles to a value calculated to allow the plurality of electric
vehicles to charge at combined maximum power draw of the electrical
circuit supplying power to the plurality of charging stations.
11. The computer program product of claim 8, wherein the computer
readable program code for controlling power flow according to the
second charging behavior comprises: computer readable program code
for executing charging behavior state transitions for each of the
plurality of electric vehicles, the charging behavior state
transitions occurring at random offset times after the detection of
the failure mode.
12. The computer program product of claim 8, wherein the computer
readable program code for controlling power flow according to the
second charging behavior comprises: computer readable program code
for executing charging behavior state transitions for each of the
plurality of electric vehicles, the charging behavior state
transitions occurring at random offset times after the detection of
the failure mode, wherein electric vehicles of the plurality of
electric vehicles that are not being charged at the time of the
detected failure mode wait a random amount of time before
initiating charging, and wherein electric vehicles of the plurality
of electric vehicles that are being charged at the time of the
detected failure mode wait a random amount of time before
terminating charging.
13. The computer program product of claim 8, further comprising:
computer readable program code for controlling power flow of each
of the plurality of electric vehicles detecting the failure mode
according to a predefined curve stored in each of the plurality of
electric vehicles and in the central flow controller; computer
readable program code for determining appropriate charging
behaviors for each of the plurality of electric vehicles that are
not experiencing a failure mode based on the predefined power curve
stored in each of the plurality of electric vehicles that are
experiencing a power failure mode; and computer readable program
code for communicating the appropriate charging behaviors from the
central flow controller to the plurality of electric vehicles that
are not experiencing a power failure mode.
14. The computer program product of claim 8, wherein the computer
readable program code for controlling power flow according to the
second charging behavior comprises: computer readable program code
for predicting the connection and disconnection of other of the
plurality of electric vehicles to and from the plurality of
charging stations, and controlling power flow based on those
predictions.
15. A system for managing power flow using safe failure modes in an
electric vehicle charging network, comprising: a central power flow
controller communicatively coupled to a plurality of electric
vehicles, the central power flow controller communicating a first
charging behavior to the plurality of electric vehicles, each of
the plurality of electric vehicles including: a memory for storing
a plurality of charging behaviors from the central flow controller;
a processor for controlling power flow between its associated
electric vehicle and an associated charging station according to
the first charging behavior of the plurality of charging behaviors
received from the central flow controller; and a communication
interface for detecting a communications failure mode between the
central flow controller and the electric vehicle, wherein in
response to detecting the communications failure mode, the
processor controls power flow between the charging station and the
electric vehicle according to the second charging behavior during
the period of time of the communications failure, wherein the
second charging behavior is predictable and non-disruptive to a
power circuit supplying power to the plurality of charging
stations.
16. The system of claim 15, wherein the second charging behavior
comprises: maintaining the first charging behavior for a predefined
period of time; and transitioning to a predefined autonomous
charging strategy after the predefined period of time.
17. The system of claim 15 wherein the second charging behavior
comprises: limiting the power flow to each of the plurality of
electric vehicles to a value calculated to allow the plurality of
electric vehicles to charge at combined maximum power draw of the
electrical circuit supplying power tot eh plurality of charging
stations.
18. The system of claim 15, wherein the second charging behavior
comprises: executing charging behavior state transitions for each
of the plurality of electric vehicles, the charging behavior state
transitions occurring at random offset times after the detection of
the failure mode.
19. The system of claim 15, wherein the second charging behavior
comprises: executing charging behavior state transitions for each
of the plurality of electric vehicles, the charging behavior state
transitions occurring at random offset times after the detection of
the failure mode, wherein electric vehicles of the plurality of
electric vehicles that are not being charged at the time of the
detected failure mode wait a random amount of time before
initiating charging, and wherein electric vehicles of the plurality
of electric vehicles that are being charged at the time of the
detected failure mode wait a random amount of time before
terminating charging.
20. The system of claim 15, wherein the second charging behavior
includes controlling power flow of each of the plurality of
electric vehicles detecting the failure mode according to a
predefined power curve stored in each of the plurality of electric
vehicles and in the flow controller, and the flow controller
determines appropriate charging behaviors for each of the plurality
of electric vehicles that are not experiencing a failure mode based
on the predefined power curve stored in each of the plurality of
electric vehicles that are experiencing a power failure mode, and
communicates the appropriate charging behaviors to the plurality of
electric vehicles that are not experiencing a power failure
mode.
21. The system of claim 8, wherein the second charging behavior
includes predicting the connection and disconnection of other of
the plurality of electric vehicles to and from the plurality of
charging stations, and controlling power flow based on those
predictions.
Description
[0001] This patent application is a continuation of, and
incorporates herein by reference, U.S. patent application Ser. No.
14/338,427 filed Jul. 23, 2014, which is a continuation of U.S.
patent application Ser. No. 13/671,717 filed Nov. 8, 2012, which is
a continuation of each of the following applications: U.S. patent
application Ser. No. 12/751,853 filed Mar. 31, 2010, U.S. patent
application Ser. No. 12/751,837 filed Mar. 31, 2010, U.S. patent
application Ser. No. 12/751,821 filed Mar. 31, 2010, U.S. patent
application Ser. No. 12/751,845 filed Mar. 31, 2010, U.S. patent
application Ser. No. 12/751,862 filed Mar. 31, 2010, and U.S.
patent application Ser. No. 12/751,852 filed Mar. 31, 2010, which
each claim priority to U.S. Provisional Patent Application No.
61/165,344 filed on Mar. 31, 2009. This application also
incorporates herein by reference the following: U.S. patent
application Ser. No. 12/252,657 filed Oct. 16, 2008; U.S. patent
application Ser. No. 12/252,209 filed Oct. 15, 2008; U.S. patent
application Ser. No. 12/252,803 filed Oct. 16, 2008; and U.S.
patent application Ser. No. 12/252,950 filed Oct. 16, 2008. Each of
these applications is incorporated herein in its entirety.
[0002] This application includes material which is subject to
copyright protection. The copyright owner has no objection to the
facsimile reproduction by anyone of the patent disclosure, as it
appears in the Patent and Trademark Office files or records, but
otherwise reserves all copyright rights whatsoever.
FIELD OF THE INVENTION
[0003] The present invention relates in general to the field of
electric vehicles, and in particular to novel systems and methods
for power flow management for electric vehicles.
BACKGROUND OF THE INVENTION
[0004] Low-level electrical and communication interfaces to enable
charging and discharging of electric vehicles with respect to the
grid is described in U.S. Pat. No. 5,642,270 to Green et al.,
entitled, "Battery powered electric vehicle and electrical supply
system," incorporated herein by reference. The Green reference
describes a bi-directional charging and communication system for
grid-connected electric vehicles.
[0005] Communication parameters can be used to infer a remote
machine's operating system fingerprint. For example, in an IP over
Ethernet based system there are several layers of message framing
all with unique or semi unique characteristics. The MAC address of
the gateway, the number of network peers and their addresses can
all be determined by watching existing network traffic, or by
soliciting such information of the network peers themselves.
Techniques like port scanning are in wide use for determining
network topology. Several techniques exist for determining the host
operating systems of network peers using IP stack
fingerprinting.
[0006] Modern automobiles, including electric vehicles, have many
electronic control units for various subsystems. While some
subsystems are independent, communications among others are
essential. To fill this need, controller-area network (CAN or
CAN-bus) was devised as a multi-master broadcast serial bus
standard for connecting electronic control units. Using a message
based protocol designed specifically for automotive applications,
CAN-bus is a vehicle bus standard designed to allow
microcontrollers and devices to communicate with each other within
a vehicle without a host computer. The CAN-bus is used in vehicles
to connect the engine control unit, transmission, airbags, antilock
braking, cruise control, audio systems, windows, doors, mirror
adjustment, climate control, and seat control. CAN is one of five
protocols used in the (On-Board Diagnostics) OBD-II vehicle
diagnostics standard.
[0007] Modern vehicles contain a variety of subsystems that may
benefit from communications with various off-vehicle entities. As
the smart energy marketplace evolves, multiple application-level
protocols may further develop for the control of power flow for
electric vehicles and within the home. For example, energy
management protocols are being developed for both ZigBee and
Homeplug. A vehicle manufacturer may need to support multiple
physical communications mediums. For example, ZigBee is used in
some installations while PLC is used in others. Considering the
very long service life of items such as utility meters and
automobiles, the use of multiple incompatible protocols may pose an
barrier to deployment. For example, if a homeowner buys a car that
utilizes one protocol and receives a utility meter that uses
another protocol, it is unlikely that either device will quickly
replace other device.
[0008] The electric power grid has become increasingly unreliable
and antiquated, as evidenced by frequent large-scale power outages.
Grid instability wastes energy, both directly and indirectly, e.g.
by encouraging power consumers to install inefficient forms of
backup generation. While clean forms of energy generation, such as
wind and solar, can help to address the above problems, they suffer
from intermittency. Hence, grid operators are reluctant to rely
heavily on these sources, making it difficult to move away from
carbon-intensive forms of electricity.
[0009] With respect to the electric power grid, electric power
delivered during periods of peak demand costs substantially more
than off-peak power. The electric power grid contains limited
inherent facility for storing electrical energy. Electricity must
be generated constantly to meet uncertain demand, which often
results in over-generation (and hence wasted energy) and sometimes
results in under-generation (and hence power failures). Distributed
electric resources, en masse can, in principle, provide a
significant resource for addressing the above problems. However,
current power services infrastructure lacks provisioning and
flexibility that are required for aggregating a large number of
small-scale resources, such as electric vehicle batteries, to meet
large-scale needs of power services.
[0010] The communications protocol by which an utility controls a
power plant in regulation mode is known as Automatic Generation
Control, or AGC. AGC signals have been sent to large scale
conventional power plants, generally with a capacity of 1 Megawatt
or more.
[0011] Modern Electric vehicles could benefit in a variety of ways
from a centrally controlled smart charging program, wherein a
central server coordinates the charging activities of a number of
vehicles. Significant opportunities for improvement exist in
managing power flow at local level. More economical, reliable
electrical power needs to be provided at times of peak demand.
Power services, such as regulation and spinning reserves, can be
provided to electricity markets to provide a significant economic
opportunity. Technologies can be enabled to provide broader use of
intermittent power sources, such as wind and solar.
[0012] What is needed are power flow management systems and methods
that manage power flow at the site-level, that implement various
power flow strategies for the optimizing how to dispatch the
resources under management, that avoid power spikes, and that
minimize the total daily cost of providing energy generation. Novel
grid stabilization systems and methods are needed that aggregate
the power generation behavior of resources via Automatic Generation
Control (AGC), that provide system frequency regulation via AGC,
and that smooth and level power generation.
[0013] While various other techniques for fingerprinting devices on
a network are known in the art, novel methods are needed to
determine the network location of mobile devices connected to a
power grid in order to provide enhanced techniques for smart
charging. Significant opportunities for improvement exist with
respect to locating electric vehicles on a network that
communications with power grids and various mobile devices. What is
needed are systems and methods that determine the location of a
device with respect to a known location on the electrical grid.
With respect to the statistical nature of the fingerprint, there is
also a need for novel statistical modeling that weighs the
relevance of various pieces of communication based information
collected to construct a network fingerprint. In particular, novel
systems and methods are needed that efficiently determine the
network location of mobile devices on networks for power management
systems.
[0014] Significant opportunities for improvement exist with respect
to metering and translating measurements for power grids and
electric vehicles. What is needed are systems and methods that
provide for the efficient transfer of higher levels of information
dealing with mobile populations of electric vehicles, the
complexities of accurately metering such large populations.
[0015] Improvement also exist with respect to communications
between power grids and electric vehicles. What is needed are
systems and methods that provide for the complexity of translating
information among various protocols. In addition to cost of
translating messages, there is a cost associated with transmitting
messages across networks. As such, there is also a need for novel
communication techniques that provide for bandwidth
minimization.
[0016] It would be beneficial to enhance modern electric vehicles
to have a centrally controlled charging program. What is needed are
systems and methods that provide for the complexity of charging
intelligence of smart vehicles. There is also a need for novel
communication techniques effectively use existing communication
hardware, that allow for upgrading existing equipment, and that do
not require specific hardware. In addition, novel systems and
methods are needed that effectively provide communication services
to vehicle subsystems.
SUMMARY
[0017] In an embodiment, a method for managing power flow at a
local site includes site-level charging of electrical devices by a
power flow manager. The power flow manager runs a smart charging
program, and coordinates charging activities of the electrical
devices. The electrical devices may be located at the local site.
The method includes receiving site-level information, which is
received by the power flow manager. In addition, power flow
decisions are made, by the power flow manager, based on the
site-level information. Further, power flow to the electrical
devices is managed by the power flow manager, wherein the power
flow manager responds to requests.
[0018] In another embodiment, a method for managing power flow by
optimizing multiple power flow management strategies includes
coordinating charging activities of electrical devices. The charge
activities are coordinated by a power flow manager. Power flow
services are also controlled by the power flow manager. A power
flow management strategy is chosen by a meta-optimizer, which also
chooses the electrical devices to utilize for implementing the
power flow management strategy. The power flow management
strategies are implemented by the power flow manager.
[0019] In one embodiment, a method for managing power flow using
safe failure modes includes coordinating charging activities of
electrical devices by a power flow manager. The method includes
detecting a system failure event by a power flow manager, and
implementing a safe failure mode. The safe failure mode implemented
by the power flow manager provides that the charging activities be
coordinated in a predictable and non-disruptive manner.
[0020] In another embodiment, a method for managing power flow uses
generation stacks of power production to reduce cost of providing
power to electrical devices. This method also includes coordinating
charging activities of electrical devices by a power flow manager.
In addition, the power flow manager controls a power production
stack, which orders available power. A dispatchable load is listed
in the power production stack. The dispatchable load is removed
based on a cost reduction strategy.
[0021] In an embodiment, a method for managing power flow includes
controlling power resources via Automatic Generation Control (AGC)
commands. The AGC commands are transmitted by a power flow manager
to the power resources. The AGC commands request power regulation.
The method includes apportioning the power regulation to the power
resources based on an apportionment scheme. In addition, the method
may include transmitting an AGC command to a power resource,
wherein the AGC command requests an apportioned amount of the power
regulation from the power resource.
[0022] The apportionment scheme may relate to various factors,
including: power range of each power resource; power range of some
power resources; minimization of communications to the power
resources; fairness to the power resources; maximization future
abilities to provide power services by the power resources; and/or,
preferences or requirements of the power resources.
[0023] In another embodiment, the method for managing power flow
also includes controlling a plurality of power resources via
Automatic Generation Control (AGC) commands. The AGC commands are
transmitted by a power flow manager to power resources, and the AGC
commands request power regulation. Further, the method determines a
power regulation range for a power resource, and transmits an AGC
command to the power resource. The AGC command is based on the
power regulation range for the power resource.
[0024] In yet another embodiment, a method for managing power flow
may include detecting a change in an intermittent power flow.
Accordingly, a power flow manager detects the change in the
intermittent power flow. The power flow manager also coordinates
power resources to respond to the change in the intermittent power
flow by implementing a power flow strategy. The power flow strategy
may be a smoothing strategy or a leveling strategy.
[0025] In an embodiment, a method for determining the location of
devices on power flow management system using network fingerprints
includes receiving network information. Such network information is
associated with electric devices, such as electric vehicles. The
method includes generating a network fingerprint based on the
network information, and storing the network fingerprint in a
database. Further, the method includes detecting a change in device
information for an electric devices. The changed device information
of the electric devices is compared with the network fingerprint.
The location of the electric device is determined based on the
network fingerprint.
[0026] In one embodiment the invention is a method. A plurality of
power flow measurements are received from each of a plurality of
devices. Each device is associated with a power flow and is capable
of measuring the respective device's power flow within a
measurement error. The plurality of power flow measurements are
aggregated, using a computing device, producing an aggregated power
flow measurement. The error bounds of the aggregated power flow
measurement are then determined, using the computing device, using
at least one error model.
[0027] In another embodiment the invention is a system. The system
comprises: a plurality of devices, each device being associated
with a power flow, each of the devices being capable of measuring
the respective device's power flow within a measurement error; an
aggregate power measurement module comprising one or more
processors programmed to execute software code retrieved from a
computer readable storage medium storing software for a method. The
method comprises the steps of receiving, over a network, a
plurality of power flow measurements from each of the plurality of
devices; aggregating the power flow measurements, producing an
aggregated power flow measurement; and determining the error bounds
of the aggregated power flow measurement using at least one error
model.
[0028] In another embodiment, the invention is a method. A device
having at least one DC power flow sensor is augmented with at least
one AC power flow sensor and AC and DC power flows through the
device are measured using the sensors over a range of operating
points. An inference model of AC power flow in the device as a
function of DC power flow is then built, wherein the error of the
model is bounded. The AC power flow sensor can then be removed from
the device. The DC power flow through the device is then measured
and the AC power flow for the device is inferred, using the
computing device, using the inference model.
[0029] In another embodiment the invention is a system. The system
comprises a plurality of endpoint devices, each endpoint device
having at least one sensor for measuring power flow through the
respective device, wherein one or more of the at least one of
sensors are DC sensors. The system further comprises an inference
module comprising one or more processors programmed to execute
software code retrieved from a computer readable storage medium
storing software for a method comprising the steps: receiving
measurements, over a network, from each of the sensors; and
inferring an AC power flow of the plurality of endpoint devices
using the measurements, wherein AC power flow for devices having DC
sensors is inferred using an inference model developed by measuring
the relationship of AC power flow to DC sensor measurements in
devices similar to the respective device.
[0030] In one embodiment, a system for minimizing network traffic
consumption in a power flow management system includes devices
operable to generate, consume, or store electric energy, and a
power flow management system, which manages power flow transferred
between the plurality of devices and a power grid. This
minimization system also includes a network to communicate device
information and power flow information between the power flow
management system and the devices. The device information is
received by the power flow management system. The power flow
information is transmitted by the power flow management system, and
includes an energy rate command received by a devices. The power
flow management system reduces consumption of the traffic
traversing the network via a network traffic consumption reduction
technique.
[0031] In one embodiment of a system for communications protocol
translation in a power flow management system, the system includes
networks that connect electric devices and electric power supplies.
One network utilizes a communications protocol that is different
from the communications protocol utilized by another network. A
communications protocol translation device communicates with the
networks, and formulates messages from one communications protocol
to the other communications protocol. The reformulated messages
pass from one network to another network.
[0032] In an embodiment, a system for communicating in a power flow
management system utilizing existing hardware includes a smart
charging module that is configured to be implemented on an server
subsystem in a vehicle. The server subsystem is connected to a
shared vehicle-wide communications medium for communication with
another subsystem in the vehicle. The module is further configured
to provide a set of services using capabilities provided by the
server subsystem and the other subsystem. These services includes
sending messages, using the shared vehicle-wide communications
medium to one subsystem in the vehicle to implement a smart
charging program.
[0033] In another embodiment, a communications module for providing
communication services to vehicle subsystems includes a central
processing unit in a vehicle and a CAN-bus transceiver operatively
connected to the central processing unit connected to an external
bus in the vehicle. The external bus is operatively connected to a
vehicle subsystem. The module includes a software stack operatively
connected to the central processing unit configured to wrap
communications packets in a CAN header for communications packets
entering a vehicle from an external network. The software stack is
further configured to remove CAN headers for communications packets
leaving the vehicle. The module includes software, executed by the
central processing unit, configured to translate messages
comprising the communications packets from a remote network format
to CAN format. The module also includes software, executed by the
central processing unit, configured to support a bonding or
provisioning process required by an external communications
protocol.
[0034] In yet another embodiment, an interface enabling the
installation of a charge controller for a control extensibility
system includes a physical interface to a vehicle's CAN-bus
comprising an electrical contact plug. The interface also includes
an expansion module providing a standardization of software
messages sent over the CAN-bus to control charging. In addition,
the interface includes a physical location for the charge
controller to reside, where the CAN interface plug is located.
[0035] In an embodiment, an interface enabling an electric vehicle
to communicate with an electric power supply device without
specific hardware includes transmitting information from an
electrical load associated with the electric vehicle to an electric
power supply by modulating the power transfer between the
electrical load and an electric power supply.
[0036] In another embodiment, a system for arbitrating a smart
chargepoint includes a first smart charging module that is
configured to be implemented on equipment located inside a vehicle.
The first smart charging module is configured to communicate with a
server implementing a smart charging program. The smart charging
program coordinating the charging activities of a plurality of
vehicles distributed over an area. The first smart charging module
is moderates electrical load in the vehicle by reducing the power
consumption of the vehicle. In addition, the first smart charging
module communicates with a second smart charging module in external
equipment responsible for providing electricity to the vehicle,
enabling the first smart charging module and the second smart
charging module to implement a charge coordination protocol to
determine which of the two modules is responsible for communicating
with the server implementing the smart charging program.
BRIEF DESCRIPTION OF THE DRAWINGS
[0037] The foregoing and other objects, features, and advantages of
the invention will be apparent from the following more particular
description of embodiments as illustrated in the accompanying
drawings, in which reference characters refer to the same parts
throughout the various views. The drawings are not necessarily to
scale, emphasis instead being placed upon illustrating principles
of the invention.
[0038] FIG. 1 is a diagram of an example of a power aggregation
system.
[0039] FIGS. 2A-2B are diagrams of an example of connections
between an electric vehicle, the power grid, and the Internet.
[0040] FIG. 3 is a block diagram of an example of connections
between an electric resource and a flow control server of the power
aggregation system.
[0041] FIG. 4 is a diagram of an example of a layout of the power
aggregation system.
[0042] FIG. 5 is a diagram of an example of control areas in the
power aggregation system.
[0043] FIG. 6 is a diagram of multiple flow control centers in the
power aggregation system and a directory server for determining a
flow control center.
[0044] FIG. 7 is a block diagram of an example of flow control
server.
[0045] FIG. 8A is a block diagram of an example of remote
intelligent power flow module.
[0046] FIG. 8B is a block diagram of an example of transceiver and
charging component combination.
[0047] 8C is an illustration of an example of simple user interface
for facilitating user controlled charging.
[0048] FIG. 9 is a diagram of an example of resource communication
protocol.
[0049] FIG. 10 is a diagram of an example of a site power flow
manager.
[0050] FIG. 11 is a flow chart of an example of a site power flow
manager.
[0051] FIG. 12 is a flow chart of an example of optimization across
multiple power flow management strategies.
[0052] FIG. 13 is a flow chart of an example of avoiding power
spikes during energy management failures using safe failure
modes.
[0053] FIG. 14 is a flow chart of an example of
generation-stack-aware dispatch of resources.
[0054] FIG. 15 is a flow chart of an example for AGC
virtualization.
[0055] FIG. 16 is a flow chart of an example for AGC for resources
beyond generation.
[0056] FIG. 17 is a flow chart of an example of smoothing and
leveling intermittent generation.
[0057] FIG. 18 is a flow chart of an example of fingerprinting a
local network for a power management system, in accordance with the
currently disclosed invention.
[0058] FIG. 19 is a flow chart of an example of determining the
location of an electric vehicle using a network fingerprint.
[0059] FIG. 20 is a block diagram illustrating a method for
inferring an aggregate power flow for a power management
system.
[0060] FIG. 21 is a block diagram illustrating a method for
inferring AC power flow in a device from DC measurements.
[0061] FIG. 22 is a flow chart of an example of a bandwidth
minimization technique.
[0062] FIG. 23 is a flow chart of an example of a protocol
translation system.
[0063] FIG. 24 is a block diagram of an example of a communications
protocol translation device.
[0064] FIG. 25 is a diagram of an example of communications using
existing hardware.
[0065] FIG. 26 is a diagram of an example of communication services
to vehicle subsystems.
[0066] FIG. 27 is a diagram of an example of an extensibility
system.
[0067] FIG. 28 is a diagram of an example of communications without
specific hardware.
[0068] FIG. 29 is a diagram of an example of arbitrating a smart
charge point.
DETAILED DESCRIPTION OF THE EMBODIMENTS
[0069] Reference will now be made in detail to the embodiments of
the present invention, examples of which are illustrated in the
accompanying drawings.
Overview
[0070] Described herein is a power aggregation system for
distributed electric resources, and associated methods. In one
implementation, a system communicates over the Internet and/or some
other public or private networks with numerous individual electric
resources connected to a power grid (hereinafter, "grid"). By
communicating, the system can dynamically aggregate these electric
resources to provide power services to grid operators (e.g.
utilities, Independent System Operators (ISO), etc.).
[0071] "Power services" as used herein, refers to energy delivery
as well as other ancillary services including demand response,
regulation, spinning reserves, non-spinning reserves, energy
imbalance, reactive power, and similar products.
[0072] "Aggregation" as used herein refers to the ability to
control power flows into and out of a set of spatially distributed
electric resources with the purpose of providing a power service of
larger magnitude.
[0073] "Charge Control Management" as used herein refers to
enabling or performing the starting, stopping, or level-setting of
a flow of power between a power grid and an electric resource.
[0074] "Power grid operator" as used herein, refers to the entity
that is responsible for maintaining the operation and stability of
the power grid within or across an electric control area. The power
grid operator may constitute some combination of manual/human
action/intervention and automated processes controlling generation
signals in response to system sensors. A "control area operator" is
one example of a power grid operator.
[0075] "Control area" as used herein, refers to a contained portion
of the electrical grid with defined input and output ports. The net
flow of power into this area must equal (within some error
tolerance) the sum of the power consumption within the area and
power outflow from the area.
[0076] "Power grid" as used herein means a power distribution
system/network that connects producers of power with consumers of
power. The network may include generators, transformers,
interconnects, switching stations, and safety equipment as part of
either/both the transmission system (i.e., bulk power) or the
distribution system (i.e. retail power). The power aggregation
system is vertically scalable for use within a neighborhood, a
city, a sector, a control area, or (for example) one of the eight
large-scale Interconnects in the North American Electric
Reliability Council (NERC). Moreover, the system is horizontally
scalable for use in providing power services to multiple grid areas
simultaneously.
[0077] "Grid conditions" as used herein, refers to the need for
more or less power flowing in or out of a section of the electric
power grid, in response to one of a number of conditions, for
example supply changes, demand changes, contingencies and failures,
ramping events, etc. These grid conditions typically manifest
themselves as power quality events such as under- or over-voltage
events or under- or over-frequency events.
[0078] "Power quality events" as used herein typically refers to
manifestations of power grid instability including voltage
deviations and frequency deviations; additionally, power quality
events as used herein also includes other disturbances in the
quality of the power delivered by the power grid such as sub-cycle
voltage spikes and harmonics.
[0079] "Electric resource" as used herein typically refers to
electrical entities that can be commanded to do some or all of
these three things: take power (act as load), provide power (act as
power generation or source), and store energy. Examples may include
battery/charger/inverter systems for electric or hybrid-electric
vehicles, repositories of used-but-serviceable electric vehicle
batteries, fixed energy storage, fuel cell generators, emergency
generators, controllable loads, etc.
[0080] "Electric vehicle" is used broadly herein to refer to pure
electric and hybrid electric vehicles, such as plug-in hybrid
electric vehicles (PHEVs), especially vehicles that have
significant storage battery capacity and that connect to the power
grid for recharging the battery. More specifically, electric
vehicle means a vehicle that gets some or all of its energy for
motion and other purposes from the power grid. Moreover, an
electric vehicle has an energy storage system, which may consist of
batteries, capacitors, etc., or some combination thereof. An
electric vehicle may or may not have the capability to provide
power back to the electric grid.
[0081] Electric vehicle "energy storage systems" (batteries, super
capacitors, and/or other energy storage devices) are used herein as
a representative example of electric resources intermittently or
permanently connected to the grid that can have dynamic input and
output of power. Such batteries can function as a power source or a
power load. A collection of aggregated electric vehicle batteries
can become a statistically stable resource across numerous
batteries, despite recognizable tidal connection trends (e.g., an
increase in the total number of vehicles connected to the grid at
night; a downswing in the collective number of connected batteries
as the morning commute begins, etc.) Across vast numbers of
electric vehicle batteries, connection trends are predictable and
such batteries become a stable and reliable resource to call upon,
should the grid or a part of the grid (such as a person's home in a
blackout) experience a need for increased or decreased power. Data
collection and storage also enable the power aggregation system to
predict connection behavior on a per-user basis.
An Example of the Presently Disclosed System
[0082] FIG. 1 shows a power aggregation system 100. A flow control
center 102 is communicatively coupled with a network, such as a
public/private mix that includes the Internet 104, and includes one
or more servers 106 providing a centralized power aggregation
service. "Internet" 104 will be used herein as representative of
many different types of communicative networks and network mixtures
(e.g., one or more wide area networks--public or private--and/or
one or more local area networks). Via a network, such as the
Internet 104, the flow control center 102 maintains communication
108 with operators of power grid(s), and communication 110 with
remote resources, i.e., communication with peripheral electric
resources 112 ("end" or "terminal" nodes/devices of a power
network) that are connected to the power grid 114. In one
implementation, power line communicators (PLCs), such as those that
include or consist of Ethernet-over-power line bridges 120 are
implemented at connection locations so that the "last mile" (in
this case, last feet--e.g., in a residence 124) of Internet
communication with remote resources is implemented over the same
wire that connects each electric resource 112 to the power grid
114. Thus, each physical location of each electric resource 112 may
be associated with a corresponding Ethernet-over-power line bridge
120 (hereinafter, "bridge") at or near the same location as the
electric resource 112. Each bridge 120 is typically connected to an
Internet access point of a location owner, as will be described in
greater detail below. The communication medium from flow control
center 102 to the connection location, such as residence 124, can
take many forms, such as cable modem, DSL, satellite, fiber, WiMax,
etc. In a variation, electric resources 112 may connect with the
Internet by a different medium than the same power wire that
connects them to the power grid 114. For example, a given electric
resource 112 may have its own wireless capability to connect
directly with the Internet 104 or an Internet access point and
thereby with the flow control center 102.
[0083] Electric resources 112 of the power aggregation system 100
may include the batteries of electric vehicles connected to the
power grid 114 at residences 124, parking lots 126 etc.; batteries
in a repository 128, fuel cell generators, private dams,
conventional power plants, and other resources that produce
electricity and/or store electricity physically or
electrically.
[0084] In one implementation, each participating electric resource
112 or group of local resources has a corresponding remote
intelligent power flow (IPF) module 134 (hereinafter, "remote IPF
module" 134). The centralized flow control center 102 administers
the power aggregation system 100 by communicating with the remote
IPF modules 134 distributed peripherally among the electric
resources 112. The remote IPF modules 134 perform several different
functions, including, but not limited to, providing the flow
control center 102 with the statuses of remote resources;
controlling the amount, direction, and timing of power being
transferred into or out of a remote electric resource 112;
providing metering of power being transferred into or out of a
remote electric resource 112; providing safety measures during
power transfer and changes of conditions in the power grid 114;
logging activities; and providing self-contained control of power
transfer and safety measures when communication with the flow
control center 102 is interrupted. The remote IPF modules 134 will
be described in greater detail below.
[0085] In another implementation, instead of having an IPF module
134, each electric resource 112 may have a corresponding
transceiver (not shown) to communicate with a local charging
component (not shown). The transceiver and charging component, in
combination, may communicate with flow control center 102 to
perform some or all of the above mentioned functions of IPF module
134. A transceiver and charging component are shown in FIG. 2B and
are described in greater detail herein.
[0086] FIG. 2A shows another view of electrical and communicative
connections to an electric resource 112. In this example, an
electric vehicle 200 includes a battery bank 202 and a remote IPF
module 134. The electric vehicle 200 may connect to a conventional
wall receptacle (wall outlet) 204 of a residence 124, the wall
receptacle 204 representing the peripheral edge of the power grid
114 connected via a residential powerline 206.
[0087] In one implementation, the power cord 208 between the
electric vehicle 200 and the wall outlet 204 can be composed of
only conventional wire and insulation for conducting alternating
current (AC) power to and from the electric vehicle 200. In FIG.
2A, a location-specific connection locality module 210 performs the
function of network access point--in this case, the Internet access
point. A bridge 120 intervenes between the receptacle 204 and the
network access point so that the power cord 208 can also carry
network communications between the electric vehicle 200 and the
receptacle 204. With such a bridge 120 and connection locality
module 210 in place in a connection location, no other special
wiring or physical medium is needed to communicate with the remote
IPF module 134 of the electric vehicle 200 other than a
conventional power cord 208 for providing residential line current
at any conventional voltage. Upstream of the connection locality
module 210, power and communication with the electric vehicle 200
are resolved into the powerline 206 and an Internet cable 104.
[0088] Alternatively, the power cord 208 may include safety
features not found in conventional power and extension cords. For
example, an electrical plug 212 of the power cord 208 may include
electrical and/or mechanical safeguard components to prevent the
remote IPF module 134 from electrifying or exposing the male
conductors of the power cord 208 when the conductors are exposed to
a human user.
[0089] In some embodiments, a radio frequency (RF) bridge (not
shown) may assist the remote IPF module 134 in communicating with a
foreign system, such as a utility smart meter (not shown) and/or a
connection locality module 210. For example, the remote IPF module
134 may be equipped to communicate over power cord 208 or to engage
in some form of RF communication, such as Zigbee or Bluetooth.TM.,
and the foreign system may be able to engage in a different form of
RF communication. In such an implementation, the RF bridge may be
equipped to communicate with both the foreign system and remote IPF
module 134 and to translate communications from one to a form the
other may understand, and to relay those messages. In various
embodiments, the RF bridge may be integrated into the remote IPF
module 134 or foreign system, or may be external to both. The
communicative associations between the RF bridge and remote IPF
module 134 and between the RF bridge and foreign system may be via
wired or wireless communication.
[0090] FIG. 2B shows a further view of electrical and communicative
connections to an electric resource 112. In this example, the
electric vehicle 200 may include a transceiver 212 rather than a
remote IPF module 134. The transceiver 212 may be communicatively
coupled to a charging component 214 through a connection 216, and
the charging component itself may be coupled to a conventional wall
receptacle (wall outlet) 204 of a residence 124 and to electric
vehicle 200 through a power cord 208. The other components shown in
FIG. 2B may have the couplings and functions discussed with regard
to FIG. 2A.
[0091] In various embodiments, transceiver 212 and charging
component 214 may, in combination, perform the same functions as
the remote IPF module 134. Transceiver 212 may interface with
computer systems of electric vehicle 200 and communicate with
charging component 214, providing charging component 214 with
information about electric vehicle 200, such as its vehicle
identifier, a location identifier, and a state of charge. In
response, transceiver 212 may receive requests and commands which
transceiver 212 may relay to vehicle 200's computer systems.
[0092] Charging component 214, being coupled to both electric
vehicle 200 and wall outlet 204, may effectuate charge control of
the electric vehicle 200. If the electric vehicle 200 is not
capable of charge control management, charging component 214 may
directly manage the charging of electric vehicle 200 by stopping
and starting a flow of power between the electric vehicle 200 and a
power grid 114 in response to commands received from a flow control
server 106. If, on the other hand, the electric vehicle 200 is
capable of charge control management, charging component 214 may
effectuate charge control by sending commands to the electric
vehicle 200 through the transceiver 212.
[0093] In some embodiments, the transceiver 212 may be physically
coupled to the electric vehicle 200 through a data port, such as an
OBD-II connector. In other embodiments, other couplings may be
used. The connection 216 between transceiver 212 and charging
component 214 may be a wireless signal, such as a radio frequency
(RF), such as a Zigbee, or Bluetooth.TM. signal. And charging
component 214 may include a receiver socket to couple with power
cord 208 and a plug to couple with wall outlet 204. In one
embodiment, charging component 214 may be coupled to connection
locality module 210 in either a wired or wireless fashion. For
example, charging component 214 might have a data interface for
communicating wirelessly with both the transceiver 212 and locality
module 210. In such an embodiment, the bridge 120 may not be
required.
[0094] Further details about the transceiver 212 and charging
component 214 are illustrated by FIG. 8B and described in greater
detail herein.
[0095] FIG. 3 shows another implementation of the connection
locality module 210 of FIG. 2, in greater detail. In FIG. 3, an
electric resource 112 has an associated remote IPF module 134,
including a bridge 120. The power cord 208 connects the electric
resource 112 to the power grid 114 and also to the connection
locality module 210 in order to communicate with the flow control
server 106.
[0096] The connection locality module 210 includes another instance
of a bridge 120, connected to a network access point 302, which may
include such components as a router, switch, and/or modem, to
establish a hardwired or wireless connection with, in this case,
the Internet 104. In one implementation, the power cord 208 between
the two bridges 120 and 120' is replaced by a wireless Internet
link, such as a wireless transceiver in the remote IPF module 134
and a wireless router in the connection locality module 210.
[0097] In other embodiments, a transceiver 212 and charging
component 214 may be used instead of a remote IPF module 134. In
such an embodiment, the charging component 214 may include or be
coupled to a bridge 120, and the connection locality module 210 may
also include a bridge 120', as shown. In yet other embodiments, not
shown, charging component 214 and connection locality module 210
may communicate in a wired or wireless fashion, as mentioned
previously, without bridges 120 and 120'. The wired or wireless
communication may utilize any sort of connection technology known
in the art, such as Ethernet or RF communication, such as Zigbee,
or Bluetooth.TM..
System Layouts
[0098] FIG. 4 shows a layout 400 of the power aggregation system
100. The flow control center 102 can be connected to many different
entities, e.g., via the Internet 104, for communicating and
receiving information. The layout 400 includes electric resources
112, such as plug-in electric vehicles 200, physically connected to
the grid within a single control area 402. The electric resources
112 become an energy resource for grid operators 404 to
utilize.
[0099] The layout 400 also includes end users 406 classified into
electric resource owners 408 and electrical connection location
owners 410, who may or may not be one and the same. In fact, the
stakeholders in a power aggregation system 100 include the system
operator at the flow control center 102, the grid operator 404, the
resource owner 408, and the owner of the location 410 at which the
electric resource 112 is connected to the power grid 114.
[0100] Electrical connection location owners 410 can include:
[0101] Rental car lots--rental car companies often have a large
portion of their fleet parked in the lot. They can purchase fleets
of electric vehicles 200 and, participating in a power aggregation
system 100, generate revenue from idle fleet vehicles.
[0102] Public parking lots--parking lot owners can participate in
the power aggregation system 100 to generate revenue from parked
electric vehicles 200. Vehicle owners can be offered free parking,
or additional incentives, in exchange for providing power
services.
[0103] Workplace parking--employers can participate in a power
aggregation system 100 to generate revenue from parked employee
electric vehicles 200. Employees can be offered incentives in
exchange for providing power services.
[0104] Residences--a home garage can merely be equipped with a
connection locality module 210 to enable the homeowner to
participate in the power aggregation system 100 and generate
revenue from a parked car. Also, the vehicle battery 202 and
associated power electronics within the vehicle can provide local
power backup power during times of peak load or power outages.
[0105] Residential neighborhoods--neighborhoods can participate in
a power aggregation system 100 and be equipped with power-delivery
devices (deployed, for example, by homeowner cooperative groups)
that generate revenue from parked electric vehicles 200.
[0106] The grid operations 116 of FIG. 4 collectively include
interactions with energy markets 412, the interactions of grid
operators 404, and the interactions of automated grid controllers
118 that perform automatic physical control of the power grid
114.
[0107] The flow control center 102 may also be coupled with
information sources 414 for input of weather reports, events, price
feeds, etc. Other data sources 414 include the system stakeholders,
public databases, and historical system data, which may be used to
optimize system performance and to satisfy constraints on the power
aggregation system 100.
[0108] Thus, a power aggregation system 100 may consist of
components that:
[0109] communicate with the electric resources 112 to gather data
and actuate charging/discharging of the electric resources 112;
[0110] gather real-time energy prices;
[0111] gather real-time resource statistics;
[0112] predict behavior of electric resources 112 (connectedness,
location, state (such as battery State-Of-Charge) at a given time
of interest, such as a time of connect/disconnect);
[0113] predict behavior of the power grid 114/load;
[0114] encrypt communications for privacy and data security;
[0115] actuate charging of electric vehicles 200 to optimize some
figure(s) of merit;
[0116] offer guidelines or guarantees about load availability for
various points in the future, etc.
[0117] These components can be running on a single computing
resource (computer, etc.), or on a distributed set of resources
(either physically co-located or not).
[0118] Power aggregation systems 100 in such a layout 400 can
provide many benefits: for example, lower-cost ancillary services
(i.e., power services), fine-grained (both temporal and spatial)
control over resource scheduling, guaranteed reliability and
service levels, increased service levels via intelligent resource
scheduling, and/or firming of intermittent generation sources such
as wind and solar power generation.
[0119] The power aggregation system 100 enables a grid operator 404
to control the aggregated electric resources 112 connected to the
power grid 114. An electric resource 112 can act as a power source,
load, or storage, and the resource 112 may exhibit combinations of
these properties. Control of a set of electric resources 112 is the
ability to actuate power consumption, generation, or energy storage
from an aggregate of these electric resources 112.
[0120] FIG. 5 shows the role of multiple control areas 402 in the
power aggregation system 100. Each electric resource 112 can be
connected to the power aggregation system 100 within a specific
electrical control area. A single instance of the flow control
center 102 can administer electric resources 112 from multiple
distinct control areas 501 (e.g., control areas 502, 504, and 506).
In one implementation, this functionality is achieved by logically
partitioning resources within the power aggregation system 100. For
example, when the control areas 402 include an arbitrary number of
control areas, control area "A" 502, control area "B" 504, . . . ,
control area "n" 506, then grid operations 116 can include
corresponding control area operators 508, 510, . . . , and 512.
Further division into a control hierarchy that includes control
division groupings above and below the illustrated control areas
402 allows the power aggregation system 100 to scale to power grids
114 of different magnitudes and/or to varying numbers of electric
resources 112 connected with a power grid 114.
[0121] FIG. 6 shows a layout 600 of a power aggregation system 100
that uses multiple centralized flow control centers 102 and 102'
and a directory server 602 for determining a flow control center.
Each flow control center 102 and 102' has its own respective end
users 406 and 406'. Control areas 402 to be administered by each
specific instance of a flow control center 102 can be assigned
dynamically. For example, a first flow control center 102 may
administer control area A 502 and control area B 504, while a
second flow control center 102' administers control area n 506.
Likewise, corresponding control area operators (508, 510, and 512)
are served by the same flow control center 102 that serves their
respective different control areas.
[0122] In various embodiments, an electric resource may determine
which flow control center 102/102' administers its control area
502/504/506 by communicating with a directory server 602. The
address of the directory server 602 may be known to electric
resource 112 or its associated IPF module 134 or charging component
214. Upon plugging in, the electric resource 112 may communicate
with the directory server 602, providing the directory server 112
with a resource identifier and/or a location identifier. Based on
this information, the directory server 602 may respond, identifying
which flow control center 102/102' to use.
[0123] In another embodiment, directory server 602 may be
integrated with a flow control server 106 of a flow control center
102/102'. In such an embodiment, the electric resource 112 may
contact the server 106. In response, the server 106 may either
interact with the electric resource 112 itself or forward the
connection to another flow control center 102/102' responsible for
the location identifier provided by the electric resource 112.
[0124] In some embodiments, whether integrated with a flow control
server 106 or not, directory server 602 may include a publicly
accessible database for mapping locations to flow control centers
102/102'.
Flow Control Server
[0125] FIG. 7 shows a server 106 of the flow control center 102.
The illustrated implementation in FIG. 7 is only one example
configuration, for descriptive purposes. Many other arrangements of
the illustrated components or even different components
constituting a server 106 of the flow control center 102 are
possible within the scope of the subject matter. Such a server 106
and flow control center 102 can be executed in hardware, software,
or combinations of hardware, software, firmware, etc.
[0126] The flow control server 106 includes a connection manager
702 to communicate with electric resources 112, a prediction engine
704 that may include a learning engine 706 and a statistics engine
708, a constraint optimizer 710, and a grid interaction manager 712
to receive grid control signals 714. Grid control signals 714 are
sometimes referred to as generation control signals, such as
automated generation control (AGC) signals. The flow control server
106 may further include a database/information warehouse 716, a web
server 718 to present a user interface to electric resource owners
408, grid operators 404, and electrical connection location owners
410; a contract manager 720 to negotiate contract terms with energy
markets 412, and an information acquisition engine 414 to track
weather, relevant news events, etc., and download information from
public and private databases 722 for predicting behavior of large
groups of the electric resources 112, monitoring energy prices,
negotiating contracts, etc.
Remote IPF Module
[0127] FIG. 8A shows the remote IPF module 134 of FIGS. 1 and 2 in
greater detail. The illustrated remote IPF module 134 is only one
example configuration, for descriptive purposes. Many other
arrangements of the illustrated components or even different
components constituting a remote IPF module 134 are possible within
the scope of the subject matter. Such a remote IPF module 134 has
some hardware components and some components that can be executed
in hardware, software, or combinations of hardware, software,
firmware, etc. In other embodiments, executable instructions
configured to perform some or all of the operations of remote IPF
module 134 may be added to hardware of an electric resource 112
such as an electric vehicle that, when combined with the executable
instructions, provides equivalent functionality to remote IPF
module 134. References to remote IPF module 134 as used herein
include such executable instructions.
[0128] The illustrated example of a remote IPF module 134 is
represented by an implementation suited for an electric vehicle
200. Thus, some vehicle systems 800 are included as part of the
remote IPF module 134 for the sake of description. However, in
other implementations, the remote IPF module 134 may exclude some
or all of the vehicles systems 800 from being counted as components
of the remote IPF module 134.
[0129] The depicted vehicle systems 800 include a vehicle computer
and data interface 802, an energy storage system, such as a battery
bank 202, and an inverter/charger 804. Besides vehicle systems 800,
the remote IPF module 134 also includes a communicative power flow
controller 806. The communicative power flow controller 806 in turn
includes some components that interface with AC power from the grid
114, such as a powerline communicator, for example an
Ethernet-over-powerline bridge 120, and a current or
current/voltage (power) sensor 808, such as a current sensing
transformer.
[0130] The communicative power flow controller 806 also includes
Ethernet and information processing components, such as a processor
810 or microcontroller and an associated Ethernet media access
control (MAC) address 812; volatile random access memory 814,
nonvolatile memory 816 or data storage, an interface such as an
RS-232 interface 818 or a CANbus interface 820; an Ethernet
physical layer interface 822, which enables wiring and signaling
according to Ethernet standards for the physical layer through
means of network access at the MAC/Data Link Layer and a common
addressing format. The Ethernet physical layer interface 822
provides electrical, mechanical, and procedural interface to the
transmission medium--i.e., in one implementation, using the
Ethernet-over-powerline bridge 120. In a variation, wireless or
other communication channels with the Internet 104 are used in
place of the Ethernet-over-powerline bridge 120.
[0131] The communicative power flow controller 806 also includes a
bidirectional power flow meter 824 that tracks power transfer to
and from each electric resource 112, in this case the battery bank
202 of an electric vehicle 200.
[0132] The communicative power flow controller 806 operates either
within, or connected to an electric vehicle 200 or other electric
resource 112 to enable the aggregation of electric resources 112
introduced above (e.g., via a wired or wireless communication
interface). These above-listed components may vary among different
implementations of the communicative power flow controller 806, but
implementations typically include:
[0133] an intra-vehicle communications mechanism that enables
communication with other vehicle components;
[0134] a mechanism to communicate with the flow control center
102;
[0135] a processing element;
[0136] a data storage element;
[0137] a power meter; and
[0138] optionally, a user interface.
[0139] Implementations of the communicative power flow controller
806 can enable functionality including:
[0140] executing pre-programmed or learned behaviors when the
electric resource 112 is offline (not connected to Internet 104, or
service is unavailable);
[0141] storing locally-cached behavior profiles for "roaming"
connectivity (what to do when charging on a foreign system, i.e.,
when charging in the same utility territory on a foreign meter or
in a separate utility territory, or in disconnected operation,
i.e., when there is no network connectivity);
[0142] allowing the user to override current system behavior;
and
[0143] metering power-flow information and caching meter data
during offline operation for later transaction.
[0144] Thus, the communicative power flow controller 806 includes a
central processor 810, interfaces 818 and 820 for communication
within the electric vehicle 200, a powerline communicator, such as
an Ethernet-over-powerline bridge 120 for communication external to
the electric vehicle 200, and a power flow meter 824 for measuring
energy flow to and from the electric vehicle 200 via a connected AC
powerline 208.
Power Flow Meter
[0145] Power is the rate of energy consumption per interval of
time. Power indicates the quantity of energy transferred during a
certain period of time, thus the units of power are quantities of
energy per unit of time. The power flow meter 824 measures power
for a given electric resource 112 across a bidirectional
flow--e.g., power from grid 114 to electric vehicle 200 or from
electric vehicle 200 to the grid 114. In one implementation, the
remote IPF module 134 can locally cache readings from the power
flow meter 824 to ensure accurate transactions with the central
flow control server 106, even if the connection to the server is
down temporarily, or if the server itself is unavailable.
Transceiver and Charging Component
[0146] FIG. 8B shows the transceiver 212 and charging component 214
of FIG. 2B in greater detail. The illustrated transceiver 212 and
charging component 214 is only one example configuration, for
descriptive purposes. Many other arrangements of the illustrated
components or even different components constituting the
transceiver 212 and charging component 214 are possible within the
scope of the subject matter. Such a transceiver 212 and charging
component 214 have some hardware components and some components
that can be executed in hardware, software, or combinations of
hardware, software, firmware, etc.
[0147] The illustrated example of the transceiver 212 and charging
component 214 is represented by an implementation suited for an
electric vehicle 200. Thus, some vehicle systems 800 are
illustrated to provide context to the transceiver 212 and charging
component 214 components.
[0148] The depicted vehicle systems 800 include a vehicle computer
and data interface 802, an energy storage system, such as a battery
bank 202, and an inverter/charger 804. In some embodiments, vehicle
systems 800 may include a data port, such as an OBD-II port, that
is capable of physically coupling with the transceiver 212. The
transceiver 212 may then communicate with the vehicle computer and
data interface 802 through the data port, receiving information
from electric resource 112 comprised by vehicle systems 800 and, in
some embodiments, providing commands to the vehicle computer and
data interface 802. In one implementation, the vehicle computer and
data interface 802 may be capable of charge control management. In
such an embodiment, the vehicle computer and data interface 802 may
perform some or all of the charging component 214 operations
discussed below. In other embodiments, executable instructions
configured to perform some or all of the operations of the vehicle
computer and data interface 802 may be added to hardware of an
electric resource 112 such as an electric vehicle that, when
combined with the executable instructions, provides equivalent
functionality to the vehicle computer and data interface 802.
References to the vehicle computer and data interface 802 as used
herein include such executable instructions.
[0149] In various embodiments, the transceiver 212 may have a
physical form that is capable of coupling to a data port of vehicle
systems 800. Such a transceiver 212 may also include a plurality of
interfaces, such as an RS-232 interface 818 and/or a CANBus
interface 820. In various embodiments, the RS-232 interface 818 or
CANBus interface 820 may enable the transceiver 212 to communicate
with the vehicle computer and data interface 802 through the data
port. Also, the transceiver may be or comprise an additional
interface (not shown) capable of engaging in wireless communication
with a data interface 820 of the charging component 214. The
wireless communication may be of any form known in the art, such as
radio frequency (RF) communication (e.g., Zigbee, and/or
Bluetooth.TM. communication). In other embodiments, the transceiver
may comprise a separate conductor or may be configured to utilize a
powerline 208 to communicate with charging component 214. In yet
other embodiments, not shown, transceiver 212 may simply be a radio
frequency identification (RFID) tag capable of storing minimal
information about the electric resource 112, such as a resource
identifier, and of being read by a corresponding RFID reader of
charging component 214. In such other embodiments, the RFID tag
might not couple with a data port or communicate with the vehicle
computer and data interface 802.
[0150] As shown, the charging component 214 may be an intelligent
plug device that is physically connected to a charging medium, such
as a powerline 208 (the charging medium coupling the charging
component 214 to the electric resource 112) and an outlet of a
power grid (such as the wall outlet 204 shown in FIG. 2B). In other
embodiments charging component 214 may be a charging station or
some other external control. In some embodiments, the charging
component 214 may be portable.
[0151] In various embodiments, the charging component 214 may
include components that interface with AC power from the grid 114,
such as a powerline communicator, for example an
Ethernet-over-powerline bridge 120, and a current or
current/voltage (power) sensor 808, such as a current sensing
transformer.
[0152] In other embodiments, the charging component 214 may include
a further Ethernet plug or wireless interface in place of bridge
120. In such an embodiment, data-over-powerline communication is
not necessary, eliminating the need for a bridge 120. The Ethernet
plug or wireless interface may communicate with a local access
point, and through that access point to flow control server
106.
[0153] The charging component 214 may also include Ethernet and
information processing components, such as a processor 810 or
microcontroller and an associated Ethernet media access control
(MAC) address 812; volatile random access memory 814, nonvolatile
memory 816 or data storage, a data interface 826 for communicating
with the transceiver 212, and an Ethernet physical layer interface
822, which enables wiring and signaling according to Ethernet
standards for the physical layer through means of network access at
the MAC/Data Link Layer and a common addressing format. The
Ethernet physical layer interface 822 provides electrical,
mechanical, and procedural interface to the transmission
medium--i.e., in one implementation, using the
Ethernet-over-powerline bridge 120. In a variation, wireless or
other communication channels with the Internet 104 are used in
place of the Ethernet-over-powerline bridge 120.
[0154] The charging component 214 may also include a bidirectional
power flow meter 824 that tracks power transfer to and from each
electric resource 112, in this case the battery bank 202 of an
electric vehicle 200.
[0155] Further, in some embodiments, the charging component 214 may
comprise an RFID reader to read the electric resource information
from transceiver 212 when transceiver 212 is an RFID tag.
[0156] Also, in various embodiments, the charging component 214 may
include a credit card reader to enable a user to identify the
electric resource 112 by providing credit card information. In such
an embodiment, a transceiver 212 may not be necessary.
[0157] Additionally, in one embodiment, the charging component 214
may include a user interface, such as one of the user interfaces
described in greater detail below.
[0158] Implementations of the charging component 214 can enable
functionality including:
[0159] executing pre-programmed or learned behaviors when the
electric resource 112 is offline (not connected to Internet 104, or
service is unavailable);
[0160] storing locally-cached behavior profiles for "roaming"
connectivity (what to do when charging on a foreign system or in
disconnected operation, i.e., when there is no network
connectivity);
[0161] allowing the user to override current system behavior;
and
[0162] metering power-flow information and caching meter data
during offline operation for later transaction.
User Interfaces (UI)
[0163] Charging Station UI. An electrical charging station, whether
free or for pay, can be installed with a user interface that
presents useful information to the user. Specifically, by
collecting information about the grid 114, the electric resource
state, and the preferences of the user, the station can present
information such as the current electricity price, the estimated
recharge cost, the estimated time until recharge, the estimated
payment for uploading power to the grid 114 (either total or per
hour), etc. The information acquisition engine 414 communicates
with the electric resource 112 and with public and/or private data
networks 722 to acquire the data used in calculating this
information.
[0164] The types of information gathered from the electric resource
112 could include an electric resource identifier (resource ID) and
state information like the state of charge of the electric resource
112. The resource ID could be used to obtain knowledge of the
electric resource type and capabilities, preferences, etc. through
lookup with the flow control server 106.
[0165] In various embodiments, the charging station system
including the UI might also gather grid-based information, such as
current and future energy costs at the charging station.
[0166] User Charge Control UI Mechanisms. In various embodiments,
by default, electric resources 112 may receive charge control
management via power aggregation system 100. In some embodiments,
an override control may be provided to override charge control
management and charge as soon as possible. The override control may
be provided, in various embodiments, as a user interface mechanism
of the remote IPF module 134, the charging component 214, of the
electric resource (for example, if electric resource is a vehicle
200, the user interface control may be integrated with dash
controls of the vehicle 200) or even via a web page offered by flow
control server 106. The control could be presented, for example, as
a button, a touch screen option, a web page, or some other UI
mechanism. In one embodiment, the UI may be the UI illustrated by
FIG. 8C and discussed in greater detail below. In some embodiments,
the override would be a one-time override, only applying to a
single plug-in session. Upon disconnecting and reconnecting, the
user may again need to interact with the UI mechanism to override
the charge control management.
[0167] In some embodiments, the user may pay more to charge with
the override on than under charge control management, thus
providing an incentive for the user to accept charge control
management. Such a cost differential may be displayed or rendered
to the user in conjunction with or on the UI mechanism. This
differential could take into account time-varying pricing, such as
Time of Use (TOU), Critical Peak Pricing (CPP), and Real-Time
Pricing (RTP) schemes, as discussed above, as well as any other
incentives, discounts, or payments that might be forgone by not
accepting charge control management.
[0168] UI Mechanism for Management Preferences. In various
embodiments, a user interface mechanism of the remote IPF module
134, the charging component 214, of the electric resource (for
example, if electric resource is a vehicle 200, the user interface
control may be integrated with dash controls of the vehicle 200) or
even via a web page offered by flow control server 106 may enable a
user to enter and/or edit management preferences to affect charge
control management of the user's electric resource 112. In some
embodiments, the UI mechanism may allow the user to enter/edit
general preferences, such as whether charge control management is
enabled, whether vehicle-to-grid power flow is enabled or whether
the electric resource 112 should only be charged with clean/green
power. Also, in various embodiments, the UI mechanism may enable a
user to prioritize relative desires for minimizing costs,
maximizing payments (i.e., fewer charge periods for higher
amounts), achieving a full state-of-charge for the electric
resource 112, charging as rapidly as possible, and/or charging in
as environmentally-friendly a way as possible. Additionally, the UI
mechanism may enable a user to provide a default schedule for when
the electric resource will be used (for example, if resource 112 is
a vehicle 200, the schedule would be for when the vehicle 200
should be ready to drive). Further, the UI mechanism may enable the
user to add or select special rules, such as a rule not to charge
if a price threshold is exceeded or a rule to only use charge
control management if it will earn the user at least a specified
threshold of output. Charge control management may then be
effectuated based on any part or all of these user entered
preferences.
[0169] Simple User Interface. FIG. 8C illustrates a simple user
interface (UI) which enables a user to control charging based on
selecting among a limited number of high level preferences. For
example, UI 2300 includes the categories "green", "fast", and
"cheap" (with what is considered "green", "fast", and "cheap"
varying from embodiment to embodiment). The categories shown in UI
2300 are selected only for the sake of illustration and may instead
includes these and/or any other categories applicable to electric
resource 112 charging known in the art. As shown, the UI 2300 may
be very basic, using well known form controls such as radio
buttons. In other embodiments, other graphic controls known in the
art may be used. The general categories may be mapped to specific
charging behaviors, such as those discussed above, by a flow
control server 106.
Electric Resource Communication Protocol
[0170] FIG. 9 illustrates a resource communication protocol. As
shown, a remote IPF module 134 or charging component 214 may be in
communication with a flow control server 106 over the Internet 104
or another networking fabric or combination of networking fabrics.
In various embodiments, a protocol specifying an order of messages
and/or a format for messages may be used to govern the
communications between the remote IPF module 134 or charging
component 214 and flow control server 106.
[0171] In some embodiments, the protocol may include two channels,
one for messages initiated by the remote IPF module 134 or charging
component 214 and for replies to those messages from the flow
control server 106, and another channel for messages initiated by
the flow control server 106 and for replies to those messages from
the remote IPF module 134 or charging component 214. The channels
may be asynchronous with respect to each other (that is, initiation
of messages on one channel may be entirely independent of
initiation of messages on the other channel). However, each channel
may itself be synchronous (that is, once a message is sent on a
channel, another message may not be sent until a reply to the first
message is received).
[0172] As shown, the remote IPF module 134 or charging component
214 may initiate communication 902 with the flow control server
106. In some embodiments, communication 902 may be initiated when,
for example, an electric resource 112 first plugs in/connects to
the power grid 114. In other embodiments, communication 902 may be
initiated at another time or times. The initial message 902
governed by the protocol may require, for example, one or more of
an electric resource identifier, such as a MAC address, a protocol
version used, and/or a resource identifier type.
[0173] Upon receipt of the initial message by the flow control
server 106, a connection may be established between the remote IPF
module 134 or charging component 214 and flow control server 106.
Upon establishing a connection, the remote IPF module 134 or
charging component 214 may register with flow control server 106
through a subsequent communication 903. Communication 903 may
include a location identifier scheme, a latitude, a longitude, a
max power value that the remote IPF module 134 or charging
component 214 can draw, a max power value that the remote IPF
module 134 or charging component 214 can provide, a current power
value, and/or a current state of charge.
[0174] After the initial message 902, the protocol may require or
allow messages 904 from the flow control server 106 to the remote
IPF module 134 or charging component 214 or messages 906 from
remote IPF module 134 or charging component 214 to the flow control
server 106. The messages 904 may include, for example, one or more
of commands, messages, and/or updates. Such messages 904 may be
provided at any time after the initial message 902. In one
embodiment, messages 904 may include a command setting, a power
level and/or a ping to determine whether the remote IPF module 134
or charging component 214 is still connected.
[0175] The messages 906 may include, for example, status updates to
the information provided in the registration message 903. Such
messages 906 may be provided at any time after the initial message
902. In one embodiment, the messages 906 may be provided on a
pre-determined time interval basis. In various embodiments,
messages 906 may even be sent when the remote IPF module 134 or
charging component 214 is connected, but not registered. Such
messages 906 may include data that is stored by flow control server
106 for later processing. Also, in some embodiments, messages 904
may be provided in response to a message 902 or 906.
Site Power Flow Manager
[0176] Modern electric vehicles benefit in a variety of ways from a
centrally controlled smart charging program where a central server
coordinates the charging activities of a number of vehicles. While
many such smart charging programs may be operated by electric
utilities to control electric vehicles over a wide area, many of
the benefits of a smart charging program can be realized at a local
level by the operator of a facility operating in isolation from the
any other entity. In a place where multiple plug-in vehicles may
park and connect to the grid, it is valuable to have site-level
charging management.
[0177] As shown in FIG. 10, the charging process of electric
vehicles 1000 is managed by a site power flow manager 1010 at the
site-level 1020. Site-level charging management is an important
feature at charging locations where multiple plug-in electric
vehicles 1000 may park and connect to the grid 1030. Such
locations/sites 1020 may include public or private parking lots, or
the base of operations for a fleet.
[0178] There are a number of benefits for managing the power flow
at the site-level. Having control over the flow of power is useful
when, for example, the grid connection 1030 at the site 1020 is not
capable of supporting every electric vehicle 1000, and/or other
devices on site, that is simultaneously drawing power. In some
instances, the wiring to specific charge points 1040 at the site,
or to banks of charge points at the site 1020, may not be capable
of supporting every vehicle 1000 drawing power at the same time.
Many sites are subject to demand charges based on peak power draw
during a time period (e.g. month), so avoiding power spikes can
also save money. Furthermore, power usage can be tuned to the
specific electric rate structure of the site.
[0179] A site power flow manager 1010 could address these issues,
inter alia. Providing a power flow management system at the
site-level allows important information to be taken as input,
including but not limited to: electrical meter data for the site
1020 as a whole, and/or electrical meter data for specific charge
points 1040 or banks of charge points. In addition, the system can
consider information from devices, such as plug-in vehicles 1000,
at the site that are connected to the electric grid 1030. Such
information might be transmitted in a variety of ways, including by
a powerline carrier or a wireless means. This information may
include a unique identifier, resource type, current state of
charge, and max power in/out levels. Further, the system can
receive information about the electric rate structure of the site,
and information about the electrical topology and power limitations
of various circuits within the site. A connection to a power flow
manager 1010 operates at a higher level of the grid topology, i.e.
at the substation level or the control area level, so that the site
power flow manager 1010 can receive information and also respond to
requests, such as a demand response event, a reserves call,
renewable resource following, or system regulation. In one
embodiment, the site power flow manager 1010 and the higher level
site controller can have priority rules, e.g. not overloading local
circuits takes priority over remote requests.
[0180] A site power flow manager 1010 can analyze the current, and
the predicted future, state of the world. In doing so, the site
power flow manager 1010 can make various determinations, including
whether or not to allow certain devices/vehicles 1000 to draw
power. In addition, site power flow manager 1010 can request that
the devices/vehicles 1000 provide power, and further control the
power levels of the devices/vehicles 1000. These decisions could be
made within constraints, such as not overloading a circuit or going
over a certain total power draw. Such constraints may be performed,
as in one embodiment, with prioritization, such as optimizing to
get power to certain devices versus others. For example, the site
power flow manager 1010 may charge vehicles 1000 that are at the
lowest state of charge, that have been plugged in the longest, or
that have priority for recharge. In an embodiment, the site power
flow manager 1010 may allow for optimizing with regard to the
overall site electric cost minimization or total cost minimization,
or to recharge in the greenest, most efficient meaner.
[0181] Decisions made by the site power flow manager 1010 can be
carried out in several ways, including controlling relays to open
or close certain circuits. In addition, the site power flow manager
1010 can communicate with smart charging points 1040 or smart banks
of charging points 1040 to control certain circuits or devices 1000
on those circuits. The site power flow manager 1010 may also
communicate with the devices 1000 to give them a request or command
for their power flow behavior, such as telling a vehicle 1000 to
charge at half power or to recharge in an efficient manner. Such
communications may traverse via a smart charging point 1040 or bank
thereof. The site power flow manager 1010 may be located at the
site 1020 being managed, but can also located remote to the site
1020.
[0182] FIG. 11 illustrates the site-level charging of electrical
devices by a power flow manager 1110. The power flow manager
receives site-level information 1120, and makes power flow
decisions based on the site-level information 1130. In addition,
power flow to the electrical devices is managed by the power flow
manager 1140, such that the power flow manager responds to requests
including demand response event, reserves call, renewable resource
following, or system regulation.
Meta-Optimization Across Multiple Power Flow Management
Strategies
[0183] Managing one or an aggregation of power resources (such as
load, generation, storage, plug-in vehicles), power flow manager
can use the combined capabilities of the assets under its control
to implement a variety of beneficial services. These services may
include regulation, spinning reserve, and/or peak avoidance.
Regulation involves increasing or decreasing the load present on
the grid in real time in order to maintain balance between power
production and power consumption in the entire grid. Spinning
reserve provides the ability to quickly make up a large amount of
missing power after the failure of a generation or transmission
asset within the grid. Peak avoidance results in reducing peak
power consumption for the day, which is typically the most
expensive power for the utility to provide.
[0184] There are many other similar services, such as to provide
capacity or to provide renewable generation following. As the power
flow manager may use any number of different strategies to decide
how to dispatch the resources under management, it will be
understood by those skilled in the art that other strategies, and
combinations thereof, may be implemented in various embodiments. In
one embodiment, the power flow manager may be a site power flow
manager 1010, as shown in FIG. 10.
[0185] Such services provide a substantial cost savings to an
electric utility. In many circumstances, it is also possible for a
utility or other operator to sell these services through an energy
market. While each of these services have very distinct
characteristics from the perspective of the electric utility, the
services are each implemented in fundamentally the same way on the
power resource endpoint. That is, by selectively flowing power in
to or out of the power resource in response to commands from the
central power flow manager.
[0186] Because the same pool of resources can be used to implement
each of the possible services, a conflict arises. As an example, If
an entire population of electric vehicles is committed entirely to
regulation services, that population not be able to fully
participate in a peak avoidance program. Because the relative costs
and benefits of the various services change over time, it is
undesirable to simply pick the most valuable service and commit all
the assets to it all of the time.
[0187] Given a set of such strategies, a meta-optimizer decides
which strategy to use at appropriate times. The meta-optimizer may
be located within the power flow manager. The meta-optimizer
determines which resources are to be used in implementing a
strategy. The determination may be based on a variety of factors,
such as maximizing value generated and/or minimizing environmental
impact. In an embodiment, the meta-optimizer chooses the strategy
that is likely to generate the most value for a given time period,
e.g. the next hour. The implementation may have a value function
associated with each strategy, and then take the maximum value
across all strategies.
[0188] The decision may vary by grid topological location. For
example, if a given feeder is overloaded, the best decision for
resources on that feeder may be to reduce the load, even if
elsewhere on the grid a different strategy or action may be
best.
[0189] The decision may also take into account multiple component
requirements. For example, in managing plug-in vehicle recharging,
it may be desirable to get vehicles recharged in a timely fashion,
while also maximizing value created through other services
provided.
[0190] In one embodiment, the decision may be based on predictions
about the future. For example, it may be worth a certain amount at
hour N to take some action, such as charging plug-in vehicles to
provide down regulation. However, if that means the resources might
be unavailable at hour N+1, when the resource may be worth more
than at hour N, then the meta-optimizer might delay the action so
that the resource is available to provide more value.
[0191] FIG. 12 shows an embodiment of a method for managing power
flow by optimizing multiple power flow management strategies
including coordinating charging activities 1210 and controlling
power flow service 1220. A meta-optimizer can choose a power flow
management strategy and an electrical device 1230 such that the
power flow manager may implement the power flow management
strategies 1240.
Avoiding Power Spikes During Energy Management Failures
[0192] Historically, utilities had to depend on the independent and
random nature of electrical loads on the grid. While an individual
electrical load is unpredictable and can be switched on or off at
any time, each load is only a small part of total power
consumption. The large number of individual loads on the electrical
system provides a form of smoothing. Electrical consumption
increases and decreases over time, but the overall change
fluctuates along a somewhat predictable curve and power companies
are able to adjust power production to match consumption.
[0193] In distributed energy management systems where
communications are not 100% reliable, it is important that no loss
of communications between the elements of the system or unexpected
system controller failure cause unexpected system behavior. One
particular behavior to be avoided is an unexpected, coordinated
action across distributed resources that results from a failure
mode. For example, when a controller suffers a failure, it could be
detrimental to the electrical grid if all distributed resources
started drawing power from the grid simultaneously.
[0194] The introduction of a smart charging or energy management
system causes otherwise isolated loads to potentially operate in
concert. This creates the possibility of adverse coordinated action
in the event of system failure. In particular, if each electrical
load is designed to revert to a maximum energy consumption level in
the case of communications loss, then a failure of the management
system may result in an instantaneous and coordinated spike in
electricity demand. When the population of controlled devices is
sufficiently large, the spike in demand can exceed the utility's
capacity for rapid adjustment and result in a blackout.
[0195] An example of a failure mode includes failed communications
between individual resources and the master controller or
controllers. Communications can also fail between a controller and
some or all of the resources. In addition, a controller or a set of
controllers can fail in a non-network related way that renders such
controllers incapable of communicating with the resources. A
failure mode may also be a design defect shared by a large
population of resources causing the population to simultaneously
lose communications capabilities when an unexpected event
occurred.
[0196] In the case of any failure mode, the system behavior should
be predictable and non-disruptive. To prevent disruptive impacts on
the grid as a whole, endpoints normally controlled by a central
energy management server may employ a variety of safe failure
modes. A system for maintaining predictable behavior may include a
distributed resource with various capabilities, including the
ability to receive/enact a sequence of commands to be executed at
one or various points in time.
[0197] An example of a safe failure mode includes maintaining
stable (non-changing) behavior for a defined period of time around
a failure event. For example, after communications is lost, an
isolated EVSE can continue charging at the rate last specified by
the charge management controller. After some period of time, the
EVSE may slowly transition to a different autonomous strategy.
[0198] Another safe failure mode includes executing a pre-arranged
behavior in the event of a failure condition. As an example, if a
group of EVSE's was connected to a electrical circuit that was only
capable of providing 70% of the combined maximum power draw of the
group, each EVSE could be pre-programmed to operate at 70% of
capacity in the event of communications failure.
[0199] Yet another safe failure mode includes executing state
transitions in pre-arranged behaviors at the determined time offset
by a random interval of time. As an example, EVSE's that are off
when communications fail could wait a random amount of time between
0 and 30 minutes before powering on. This random startup causes the
increase in power consumption to be spread over time, allowing the
utility the opportunity to respond.
[0200] A safe failure mode may also include using predictions about
resource behaviors, such as the comings and goings from the system,
to further enhance the estimate of the state of the world. As an
example, if an EVSE is normally commanded to consume power along a
curve (to harmonize with grid conditions), the EVSE could be
programmed to follow type-based typical curve in the absence of
communications. Since the central smart charging system would know
the curve the detached EVSE was following, its behavior could still
be input in to the charge management algorithms.
[0201] FIG. 13 illustrates an embodiment for managing power flow
using safe failure modes including coordinating charging activities
of electrical devices 1310 and detecting a system failure event
1320. The power flow manager implements a safe failure mode 1330
that provides predictable and non-disruptive system behavior.
Generation-Stack-Aware Dispatch of Resources
[0202] One potential goal of a distributed energy management system
is to dispatch resources to minimize cost. A basic cost reduction
strategy is to reduce electricity consumption when electricity
prices are high. This basic strategy reduces the cost of
electricity consumed by the endpoints under active management.
[0203] A more advanced strategy could manipulate the electricity
consumed by controlled endpoints in a way that impacts the market
price of power. Such a system can reduce the cost of providing
power to all devices within a utility's service area, not just
those under active management.
[0204] In many regions, power production is managed by separate
entities from the utilities responsible for distribution. Utilities
purchase electricity from Power producers, and re-sell it to their
customers.
[0205] Often, the transactions between power producers and
distribution utilities take place in formalized market. Such a
market typically operates as a single price auction. In such a
market, each power producer states the price at which they are
willing to provide power, and power production is allocated to the
cheapest producers first, moving up the stack to more expensive
produces until sufficient power has been obtained. The last
(highest) price selected set the price that all power producers are
paid.
[0206] Each type of generation asset in an energy generation
system, such as the electrical grid, has a marginal cost.
Generation assets are dispatched in the order of increasing
marginal cost. The most expensive generator dispatched at any time
sets the cost basis for energy generation.
[0207] Different types of power plants have sharply different
marginal costs of operation. For example, Hydroelectric is often
much cheaper than gas turbines. As a result, there may be a sharp
increase in the cost of electricity as available hydro is
exhausted, and the gas turbines begin coming online.
[0208] At times, a distributed energy manager can remove enough
load from the system to eliminate the need for higher cost
generation, thereby decreasing the total cost to provide
service.
[0209] The distributed energy manager can minimize the total daily
cost to provide energy generation by forecasting total system and
dispatchable load. The distributed energy manager schedules
dispatchable load to draw power from the grid at times that will
minimize cost based on the available generation stack. Altering the
total price of power paid has a larger financial impact than the
amount paid specifically for automotive power. Also, moving the
market may be easier at one time of day than another. As a result,
dispatchable load will not always be scheduled to the lowest-cost
time of day, but rather when it will have the most beneficial
overall effect to the utility.
[0210] Further, the generation stack can change from region to
region, and load profiles and consumption can change daily.
Therefore, the present method will produce different dispatch
patterns in different regions.
[0211] FIG. 14 shows an embodiment of managing power flow using
generation stacks of power production to reduce cost of providing
power to electrical devices. Charge activities are coordinated by a
power flow manager 1410. A power production stack is controlled the
power flow manager 1420 such that the power production stack orders
available power. Based on a cost reduction strategy, a dispatchable
load is removed 1430. The dispatchable load is listed in the power
production stack.
Business Model of Selling Aggregated Power Resource Management
Services to Power Generators or Others
[0212] Power resource management services include aggregating the
following: plug-in vehicles, thermostats, residential or
commercial/industrial load, or fixed energy storage. Such services
provide regulation, reserves, load shifting, renewable resource
following, or peak avoidance. A power flow manager is able to
provide a variety of services that can improve the stability of the
electric grid. For example, electricity consumption of distributed
resources can be increased and decreased as necessary to absorb the
differences between electricity production and consumption on the
grid.
[0213] Customers for aggregated power resource management services
include electric utilities, ISOs, and TSOs. Such entities are
primarily responsible for the stability of the grid. But aggregated
power resource management services may be sold to various types of
power generators.
[0214] Some classes of electricity generation suffer from a high
degree of intermittency, meaning that their power production is
irregular. By bundling this irregular power production with the
smoothing/stabilizing abilities of aggregated power resource
management assets, it is possible to produce a higher grade of
wholesale power, which may be more easily sold in energy
markets.
[0215] In one example, a wind farm is the buyer of aggregated power
resource management services. Wind farms are susceptible to
fluctuations in the supply and demand of energy. For example,
prices for energy may drop drastically when the amount of wind is
great, or unexpectedly high. In addition, wind farms may be
temporarily disconnected from a grid when there is not enough
transmission or other capacity to absorb the power.
[0216] Economical issues resulting from such instability in the
supply or demand of energy can be effectively addressed by
providing owners of intermittent renewable generation with
aggregated power resource management services. Power generators may
increase their net load from the aggregated power resources when
there is a large and/or unexpectedly high amount of wind, and
decrease net load with there is a small and/or unexpectedly low
amount of wind. [00231] In an embodiment, power generators can use
aggregated power resource management to smooth sudden ramping
events in power output, or to firm the power output to a desired
level. The sum of power generation plus net load from the
aggregated power resources can be made constant, or less
susceptible to changes in the supply or demand of energy.
[0217] As a result, power generators such as power plants may
retain the value of the energy they create. Such an integration
allow the operator of the generation asset to take direct action to
address the intermittency issues associated with their type of
generation. In some markets, this may be far more desirable than
waiting for other parties to provide such services through the
marketplace.
Age Virtualizer
[0218] An attribute of the electrical grid is that power production
must always be closely matched to power consumption. As such,
electric utilities predict power consumption in advance using a
variety of techniques in order to schedule power production to
match consumption. Because these predictions are never entirely
accurate, the electric utility is left with a shortfall or surplus
of produced electricity.
[0219] To address this mismatch between predicted and actual power
consumption, utilities arrange for some power generation plant to
operate in a regulation mode. This is sometimes called system
regulation, or frequency regulation. In regulation mode, the power
output of a power plant can be increased or decreased in near real
time. In the event of a power surplus, the utility orders the power
plant in regulation mode to decrease power production. In the event
of a power shortage, the utility orders the power plant to increase
power production. Not all power plants are capable of operating in
this mode, and the power plants that are often incur increased
costs while in this mode. Issues such as fuel efficiently and
mechanical stress must be accounted for when figuring the cost of
regulation mode.
[0220] A power flow manager can provide system frequency regulation
via Automatic Generation Control (AGC) commands. As such, the
system may appear to behave as an ISO/TSO or a grid operator, such
as a power plant, even though it is not actually a power plant. The
power flow manager coordinates the behavior of power resources,
such as the following: load, generation, or storage. The power
resources can include plug-in vehicles, fixed energy storage, loads
such as HVAC, or other devices. The AGC commands can be translated
by the power flow manager into commands to specific devices, or
sets of devices within its pool, in order to achieve aggregate
behavior across the set of resources that matches the AGC
request.
[0221] In an embodiment, the AGC command can be transmitted to all
power resources. The magnitude of the command can be divided up
among the power resources in proportion to the power range of each
resource, accordingly to one embodiment. For example, a command for
1 MW of down regulation can be divided up such that a device with a
2 kW potential power swing between max power in and max power out
would be asked to provide half as much contribution as a device
with a 4 kW potential power swing. More complex schemes can
optimize dispatch based on a variety of factors, including:
minimizing communication to resources; fairness; maximizing ability
to provide services in the future, e.g. not filling up a plug-in
vehicle that can only be charged; or, resource owner preferences or
requirements.
[0222] AGC allows for regulation in two directions. Up regulation
is a request for additional power, while down regulation is the
request for a reduction in power. A power flow manager can
implement bi-directional regulation (both up and down) using only
power resources that are capable of unidirectional power flow. This
is accomplished by setting a population of power resources to
consume power at a rate less than their maximum (e.g. 50%), and
then adjusting power consumption up and down in accordance with AGC
commands. During periods of power shortage (resulting in up
regulation requests), the power resources could curtail energy use
and/or increase energy output. During periods of power surplus
(resulting in down regulation requests), the power resources could
increase energy use and/or decrease energy output relative to their
initial rate.
[0223] FIG. 15 shows an embodiment of power flow management using
AGC commands to control power resources 1510. Power regulation is
apportioned to the power resources 1520. An AGC command, which
requests an apportioned amount of the power regulation, is
transmitted to a power resource 1530.
AGC for Resources Beyond Generation
[0224] Automatic Generation Control (AGC) can be utilized to
control power plants so that they may provide system frequency
regulation. In an embodiment, a power plant might be scheduled to
provide 30 MW of power during a certain hour, while also being
available to provide 10 MW of down regulation and 20 MW of up
regulation during that hour. As such, the plant output might vary
anywhere from 20 MW to 50 MW. In an embodiment, AGC typically
transmits a power level set point within this range, e.g. 37 MW, or
may send relative power request, i.e. increase power or decrease
power relative to the current level.
[0225] Given a load or energy-storage based power resource, or an
aggregation of such power resources, system frequency regulation
can also be provided by adjusting the net balance of supply and
demand for energy. Energy storage in discharge mode can output
power much like a generation plant. Load, or energy storage in
charge mode, can consume power like negative generation. When a
number of vehicles/resources are grid-connected and charging, an up
regulation request can be serviced by temporarily reducing the rate
of vehicle charge. Additionally, generation based power resources
can be part of an aggregate of other load or energy-storage based
power resources.
[0226] In one embodiment, AGC systems and protocols can be extended
to handle power level set points that can be negative. As such, the
power flow manager receiving the request can treat negative values
as requests for energy consumption, and positive values as requests
for energy production. When the AGC system does not support
negative numbers, the entire power range can be shifted to start at
zero, such that the shift amount becomes a separate load amount
within the system. For example, a power range of -5 MW to 10 MW can
be shifted to be 0 MW to 15 MW with the offset amount becoming a
separate load amount of 5 MW.
[0227] FIG. 16 illustrates an embodiment of power flow management
using AGC commands to control power resources 1610 where a power
regulation range for a power resource is determined 1620. An AGC
command based on the power regulation range is transmitted to the
power resource 1630.
Intermittent Generation Smoothing and Leveling
[0228] Intermittent generation resources, such as wind or solar,
can suffer from sudden ramping up or down in output, as well as
somewhat unpredictable output levels over time. For example, the
wind speed or direction can shift rapidly or a cloud can
temporarily obscure the sun over a solar generation asset. Since
power production must always be closely matched to power
consumption, it is very difficult to integrate unreliable
generation resources in to the grid, particularly as the percentage
of power being provided by such resources increases in the
generation mix.
[0229] In some situations, utilities are forced to provision
conventionally fueled standby power generation assets to provide
backup to the intermittent generation resources. For example,
natural gas turbines are often used in this way. Other rapidly
adjustable generation such as hydro may also be used to provide
this firming of intermittent generation. This substantially
increases the real cost of renewable energy sources. To address
these issues, a single power source or an aggregated collection of
power resources can be controlled. Such resources may include load,
generation, or storage.
[0230] In the case of unexpected drop-off in electricity
production, managed power resources can reduce their electricity
consumption. Power resources capable of reverse energy flow may
also contribute electricity back to the grid. In the case of an
unexpected spike in electricity production, managed power resources
can consume the surplus electricity by increasing their rate of
energy consumption, or by other means. A collection of power
resources could be managed using at least two distinct strategies:
smoothing and leveling.
[0231] In a smoothing method, the rate of change of power output
can be limited. When a sudden increase or decrease in power
production occurs, the managed power resources can be used to
spread this sudden change over more time. As an example, a sudden
drop-off in wind production from 10 MW to 0 MW could be spread out
over 20 minutes (using stored power, deferred charging, and other
shifts in net power draw), affording the utility additional time to
locate replacement power sources or otherwise address the
shortfall.
[0232] In a leveling method, the overall contribution of the
generation resources to the grid can be balanced by the power
resources to provide a desired level of net generation. In an
embodiment, such methods are used when output from a wind farm
falls below a desired level. A collection of aggregated resources,
such as plug-in vehicles, are dispatched to absorb the power drop.
Some of the plug-in vehicles are requested to stop charging, or to
charge at a lower rate. With a sufficiently large and capable
collection of distributed power resources, leveling could increase
the reliability of renewables to the same level as conventional
power sources.
[0233] In an embodiment, leveling may be more valuable than
smoothing to an utility or other operator. However, leveling may
require a large amount of reserve capacity relative to the amount
of renewable energy being managed. Smoothing can provide
substantial benefit while requiring a smaller population of
distributed energy resources.
[0234] FIG. 17 illustrates an embodiment of power flow management
that detects a change in an intermittent power flow 1710 and
implements a power flow strategy in response to the change in the
intermittent power flow 1720. The power flow strategy may be a
smoothing strategy or a leveling strategy.
Mobile Resource Locator
[0235] Referring back to FIG. 1, the exemplary power aggregation
system 100 also includes various techniques for determining the
electrical network location of a mobile electric resource 112, such
as a plug-in electric vehicle 200 as illustrated in FIG. 2A.
Electric vehicles 200 can connect to the grid 114 in numerous
locations and accurate control and transaction of energy exchange
can be enabled by specific knowledge of the charging location. Some
of the exemplary techniques for determining electric vehicle
charging locations include:
[0236] querying a unique identifier for the location (via wired,
wireless, etc.), which can be:
[0237] the unique ID of the network hardware at the charging
site;
[0238] the unique ID of the locally installed smart meter, by
communicating with the meter;
[0239] a unique ID installed specifically for this purpose at a
site; and
[0240] using GPS or other signal sources (cell, WiMAX, etc.) to
establish a "soft" (estimated geographic) location, which is then
refined based on user preferences and historical data (e.g.,
vehicles tend to be plugged-in at the owner's residence 124, not a
neighbor's residence).
Location Determination Using a Network Fingerprint
[0241] The presently disclosed systems and methods can solve the
problem of determining the location of a device with respect to a
known location on the electrical grid or a known physical location
(e.g. my home, my office) associated with a location on the
electrical grid. Traditional approaches of using the Global
Positioning System (GPS) or cellular tower based Location Based
Services (LBS) are not sufficient. Limitations in GPS and cellular
resolution make the precise determination of a location difficult,
especially in cases where two locations are overlapping or in close
proximity. When two locations are too close to distinguish and
resolve their locations using GPS and/or cellular information, or
in cases where GPS and cellular information is not available
because of the lack of a transceiver or the lack of signal, the
device described herein uses a collection of other communication
based information to construct a network fingerprint of a known
location that is subsequently used to determine whether a device is
at a previously known or unknown location.
[0242] In one embodiment, the disclosed methods determine whether
an electric car, or other electrical equipment such as a charging
station that may be semi or completely mobile, has moved from one
known location to another or otherwise left a known location. This
is crucial when determining billing related matters; for example,
when deciding whether to bill my home or my office for the electric
power used or produced. It is also important to have knowledge
about which devices are located on a network when establishing the
overall load characteristics of a given area of the grid. In one
example, such knowledge is useful in determining whether charging a
device affects, or will affect, the overall load of my home
neighborhood or my office neighborhood.
[0243] To address the issue of location resolution, a device may
contain one or more communications adapters, such as Ethernet,
Wi-Fi, ZigBee, Cellular, LBS, or GPS. The device may use some or
all of these communications mediums in a combination of active or
passive modes to extract information that is unique to a given
location. Various techniques fingerprinting devices on a network
may be combined to construct an overall fingerprint of the
surrounding network as a whole.
[0244] Once a network location fingerprint is collected and stored
it may be associated with a known location (e.g. home, or office,
or parking lot space #12), or it may be assigned an otherwise
random location identifier. The fingerprint may be stored in a
database for later use when trying to determine a device's
location.
[0245] The disclosed system can also take into account the dynamic
nature of such information. A portion of the fingerprint may be
expected to change over time. For example, the list of network
peers may change as new peers are added or removed from the
network. The MAC address of devices may change as they are replaced
with new hardware. Host operating system information collected in
IP stack fingerprinting may change as operating systems are
upgraded. As such, the fingerprint of a location may change over
time and the database can record the last fingerprint. The database
may also record the entire history of fingerprints of a location in
cases where the variation over time is itself useful in identifying
the location. For example, a given home location may have three
network peers in the evenings while various people are home from
work with their networked laptops and phones, but may have only one
peer during the workweek while they are at work. Depending on the
time that the network location fingerprint is compared, this sort
of dynamic information can be used to resolve the location
name.
[0246] Pattern matching can be used to match one location
fingerprint against another. Based on the statistical nature of the
fingerprint, the disclosed system is capable of making a location
determination in the presence of partial or changing fingerprints
by applying any number of statistical methods, such as regression
analysis, logistic regression, Bayesian, pattern matching, or ad
hoc weighting of various parts of the fingerprint. For example, the
likelihood that a given location will replace the communications
gateway that a car would connect to (and thus a change in the MAC
address present in IP traffic from the gateway) is probably low in
comparison to the probability of adding or removing of peers to the
same network.
[0247] In an embodiment, the disclosed method uses a process by
which a device connected to a network can query network peers and
collect and store a set of identification information, such as MAC
address, IP address, and trace routes. The method may utilize other
various pieces of information to construct a fingerprint of the
device's current location such as ping latencies to gateways, other
network peers, cell tower information, or GPS information. As such,
the method constructs a location fingerprint that is the
aggregation of various sources of information, and may further use
a statistical model weighting the relevance of the various pieces
of information. The information can be stored on a server or the
device.
[0248] When a device subsequently performs the fingerprint process,
the device can subsequently detect whether the device has changed
locations by detecting differences in some or all of this set of
information. Upon detecting that the device has returned to a known
location, or that the device is at a new location, the device or a
server can take certain actions. Such actions may include:
notifying a user, notifying another server, initiating a
configuration process, or operating in different modes.
[0249] According to an embodiment, a user plugs in a device to
their home network, and the device scans for and records the MAC
addresses of the user's router, home PC and printer. The device
transmits this information to a server, such that a fingerprint is
associated with the location. The user may move the device to a new
location, e.g. the user's office. The device detects a different
fingerprint from the MAC of a new router, and several dozen work
computers. Another information relating to the new location is
stored in the server so that the fingerprint is associated with the
location. When the user returns the device to the home network, the
device recognizes it is at home. The device can recognize a
location even if some, but not all, of the fingerprint has changed.
For example, a printer may no longer be present.
[0250] FIG. 18 shows an embodiment of fingerprinting a local
network for a power management system. Network information from
devices, such as electric vehicles, is collected 1810 in order to
generate a network fingerprint 1820, which is stored 1830 in a
database. As shown in FIG. 19, according to an embodiment, a change
in the location of a device is detected 1910 and compared with a
network fingerprint 1920 in order to determine 1930 the location of
an electric vehicle.
Accurate System Metering Via Statistical Averaging
[0251] Metering information for an aggregate power system from the
endpoints requires a meter at each endpoint. A potential cost
reduction for such system is to reduce the accuracy of each
individual meter. Building a model for the meter error for each
type of meter in a system provides an upper bound on system
accuracy. Any bias, or offset from zero, can be removed from the
system level calculation by utilizing such a model. Additionally,
the standard deviation of the meter error can be characterized.
[0252] In an embodiment, the meter population can be characterized
as 1,000 meters in the system being uniformly distributed over the
range of +/-2% with a standard deviation of 1.15. The total system
error is defined by the sum of the meter error terms. This error
can be estimated by computing the standard error on the sample mean
of the sampling distribution using the formula stderr=stdv/sqrt(N)
which provides a standard error=1.15/sqrt(1000)=0.0364 in this
embodiment. To maintain a certainty of 99% on this estimate, the
error percentage estimate may be multiplied by 3 because, under a
normal distribution, 3 standard deviations covers roughly 99% of
the samples. This results in 0.1091% for the currently presented
embodiment.
[0253] The implication of this observation is that even if our
meter error is uniformly distributed within +/-20% with only 1,000
meters, the disclosed system can still achieve a measurement
accuracy of +/-1.1%.
Aggregate System Power Flow Inference
[0254] A power flow management system is responsible for producing
an estimate of the aggregate power flow to or a from a set of
devices that are participating in system. By collecting individual
power flow measurements from endpoints participating in the power
flow management system and aggregating those measurements, the
system produces an estimate for the aggregate power flow of the
devices.
[0255] For the purposes of this disclosure, ESVE or should be
understood to be Electric Vehicle Service Equipment, which is
herein defined as a device that is a permanently installed piece of
electric vehicle charging infrastructure that serves as an electric
vehicle outlet. This type of equipment may include an energy
meter.
[0256] For the purposes of this disclosure, aggregate power flow
should be understood to be the sum of the power flows in a set of
individual, distributed devices that are under the management of a
power flow management system.
[0257] For the purposes of this disclosure, error bounds should be
understood to be a limit on the magnitude of the error in the
estimation of an aggregate power flow my a power flow management
system. The error bounds on an aggregate power flow are specified
with a level of confidence.
[0258] The devices that measure power flow at the endpoints of the
systems (e.g. vehicles, homes, HVAC, EVSE) have non-ideal levels of
measurement accuracy. That is, the power flow reported by the
devices is the sum of the actual power flow and some amount
measurement error (the error could be positive or negative).
[0259] By characterizing and modeling the measurement error of a
class of devices, it is possible to produce error bounds for the
power flow measurement of a population of devices by considering
the device error model and the number of devices included in the
computation. [00281] FIG. 20 illustrates a method for inferring an
aggregate power flow for devices attached to a power management
system. A plurality of power flow measurements are received 2010
from a plurality of devices, each device being associated with a
power flow, each of the devices being capable of measuring the
respective device's power flow within a measurement error. The
plurality of power flow measurements are aggregated 2020, producing
an aggregated power flow measurement.
[0260] In one embodiment, the power flow aggregate for a set of
devices can be computed as the sum of the individual measurements
that are a part of the aggregate measure.
[0261] In one embodiment, the error bounds on an aggregate power
flow measurement of a set of endpoints connected to a power flow
management system can be additionally be computed. Making an
assumption that the power flows at each individual device are
independent and identically distributed (i.i.d.), the standard
error of the aggregate power flow measurement can be computed by
using the statistical definitions for i.i.d. random variables. That
is, divide the error bounds of each individual device by the square
root of the number of devices in the set to compute the standard
error. The error on the aggregate power flow measurement is then
bounded by multiplying the standard error by the number of standard
deviations desired. For example, if a 95% confidence is desired,
then the computed standard error value is scaled by 1.96 (the
matching quartile for the normal distribution).
[0262] Power flow estimates can be produced for the entire system
being managed by the power flow management system as well as for
sub-parts (portions) of the complete system. Because the error
bounds can be produced by an error model parameterized by the
number of devices included in the computation, computing the error
bounds for subsets of the device population requires adjusting the
input (number of included devices) to the error model.
[0263] By modeling the measurement error in the measurement device
at the endpoint, the power flow management system can compute the
error bounds for the aggregate estimate of the power flow
measurement at any point in the power flow management system.
[0264] This approach can support any meter error model and can even
combine an arbitrary number of measurement error models. If the
device type that performs the metering is known on a per-endpoint
basis, it is possible to compute the number of instances of each
device type contributing to the aggregate estimate. These
individual devices counts are then used to feed the per-device-type
model of error bounds.
[0265] In one embodiment, an error model for a set of devices of an
identical type can be constructed. In one example of such an error
model for a set of metering device, each individual device of a
particular type is guaranteed to have all measurements within +/-N
% of the true value.
[0266] In one embodiment, the error bounds of a subpart of the
endpoints in a power flow management system can be computed. If it
is needed to compute the error bounds for a subset of the endpoints
under the management of the power flow management system, the
standard error is computed by dividing the error bounds of an
individual device by the square root of the number of devices in
the subset. The error on the aggregate power flow measurement is
then bounded by multiplying the standard error by the number of
standard deviations we would like to capture in our estimate.
[0267] In various other embodiments, different error models are
combined. One method for combining multiple error models (i.e.
multiple types of power flow measurement devices) in the same power
flow management system is to compute the weighted average of the
error bounds for each set of devices described by a single error
model where the weight is the percentage of total power measured by
that set of devices.
Inferring AC Power Flow from DC Measurements
[0268] In a power flow management system, each endpoint device is
responsible for reporting its own power consumption and production.
In many cases, the endpoint device has sensors for measuring the
Alternating Current (AC) power flow through the device (i.e. how
much power the device is taking/delivering from/to the grid).
However, some devices may not have the ability to produce accurate
sensor data for the AC power flow of the device.
[0269] In cases where the device has other sensors that produce
some information about the state and behavior of the system, it is
possible to build an inference model for the AC power flow given
the information for the other sensors. For example, in a battery
charger, there may not be AC metering sensors, but their may be
sensors that measure the battery's DC voltage and the DC current
being used to charge it. If this additional information is
available, then the battery charging device can be characterized
such that accurate AC metering information can be inferred from the
DC sensor readings.
[0270] FIG. 21 illustrates a method for inferring AC power flow in
a device from DC measurements. A device having at least one DC
power flow sensor is augmented 2110 with at least one AC power flow
sensor. AC and DC power flow is then measured 2120 over a range of
operating points. The power flows are then used to build 2130,
using at least one computing device, an inference model of AC power
flow in the device as a function of DC power flow, wherein the
error of the model is bounded. The AC power flow sensor can then be
removed 2140 from the device. DC power flows through the device can
then be measured 2150 and used to infer 2160 the AC power flow for
the device using the inference model and measurements from the at
least one DC power flow sensor.
[0271] By augmenting a single device with AC metering sensors, it
is possible to build an accurate inference model by gathering AC
and DC sensor information for the devices, developing a model that
produces the inferred AC metering outputs given the DC
measurements, and bounding the error of the model and inference
outputs. With this model in place, it is possible to apply this
model to the DC readings of other similar devices to infer the AC
power flow information of these devices without augmenting them
with AC metering sensors.
[0272] If a set of devices is available, augmenting each of them
with AC metering sensors enables the construction of a set of
inference models for AC power flow from DC sensor information.
Using this set of information, it is possible to construct a single
model and its error bounds when applied to any of the devices in
the set.
[0273] Consider a battery charging system that contains a battery
charger and a rechargeable battery. When the battery charger is
plugged into the grid, it is capable of charging the battery by
passing DC current into the battery. This system is able to sense
the DC (direct current) battery voltage and current directly.
However, this system does not require or have AC power flow
sensors.
[0274] To build an inference model for the AC power flow in this
battery charging system, the system can be temporarily augmented
with AC power flow sensors. By taking readings from the DC voltage,
DC current, and AC power flow sensors for a broad range of
operating points of this system, enough data can be collected to
build a model of the AC power flow as a function of the DC current
and voltage.
[0275] One such model may be a linear regression that scales some
constant, M, by the DC power (DC voltage times DC current) plus
some fixed offset, B. Given the full set of readings for AC power,
it is possible to calculate the values of M and B to produce an
approximation of the AC power from the DC power.
Bandwidth Minimization Techniques
[0276] A distributed energy management system must be in constant
communication with the distributed energy resources to maintain a
high level of certainty that the system is behaving as reported.
Sending messages between the energy management system and the
distributed energy resources is expensive because each message has
a cost associated with it. Minimizing the number of bytes sent
between the system and the resources will minimize the
communications cost of the system. Accordingly, the consumption of
network bandwidth is reduced.
[0277] Bandwidth, as used herein, can refer to network bandwidth.
Bandwidth is the number of bytes per second of data traffic that
flows into or out of a device or control system. Devices managed by
the power flow management system can be any load, generation, or
storage asset. Storage assets can comprise batteries and
bi-directional power electronics such as inverters and chargers.
Load assets may include water heaters, plug-in electric or plug-in
hybrid electric vehicles, water heaters, generation facilities, or
other controllable load, storage, or generation asset.
[0278] The disclosed system and methods can provide for the
minimization of network traffic consumption in a system that
manages the power flows to and from devices connected to a power
grid. This power flow management system communicates with the
devices, and can be centralized or decentralized. Through this
communication, information about power flows is communicated to
devices and information about device behavior and status is
communicated to the system.
[0279] The system communicates with the devices to instruct devices
as to when and at what rate energy should be taken from and
delivered to the grid. These commands enable the devices to consume
or produce energy when doing so is deemed optimal by the power flow
management system.
[0280] The instructions that are delivered to the devices by the
power flow management system can take many forms. One form of
instruction is a direct command to flow power immediately at the
requested level. Another form of instruction is a schedule of power
flow that should be followed by the device and can take many forms.
A schedule can indicate a single point in time at which a power
flow level should be activated. A schedule can indicate a sequence
of power flow levels that should be activated at various times in
the future. The schedule can be repeating on a dynamic or fixed
pattern, e.g. repeat a set of actions each day, each week, etc.
[0281] The devices also communicate information to the power flow
management system about the current state of the world at the
device. Information that can be transmitted for the benefit of
controlling power flows includes information about how much power
is currently flowing through the device and in what direction,
capacity information pertaining to the resource (e.g. storage state
of charge, fuel level of a generator), faults and error messages,
presence of a resource (e.g.: electric vehicles come and go; is the
electric vehicle currently available), scheduling constraints (e.g.
how long is the resource available), energy consumption in a period
(e.g. kWh consumed/produced in the last time period), etc.
[0282] Sending messages between the power flow management system
and the devices requires the sending of data bytes across a
network, which consumes network bandwidth. Because many
communications costs can be directly measured by the number of
bytes transferred to and from a device, minimizing the transfer of
bytes between the device and the power flow management system
minimizes the communications costs and consumption of network
bandwidth.
[0283] A power flow management system can perform in a more
efficient manner when it has complete information about the state
of all of the devices under its control at all times. To realize
this level of information awareness requires all assets to
communication all information pertaining to the power flow
management system in a timely fashion. Such a level of information
communication comes with an associated cost.
[0284] There are a number of techniques that can be used to reduce
the network traffic consumption in a power flow management system
to reduce the cost of communicating with the distributed assets.
Such techniques include the following: data compression, data
overhead reduction, action/schedule pre-distribution, minimum
change dispatch, communication of all status changes, configuration
limits on relevant behavior, and non-time-critical information
bundling. These bandwidth minimization techniques, and embodiments
thereof, are further described below.
[0285] Data Compression.
[0286] One of the techniques for minimizing bytes between the
system and the distributed resources is data compression within a
message. Compressing the data that is sent between the power flow
management system and the distributed devices can reduce the total
network traffic consumption.
[0287] A power flow management system that communicates with
devices can send compressed messages to save on network traffic.
One manner in which this works is to have both the power flow
management server and the device use a compression algorithm or
library (such as zlib or gzip) to compress data before transmission
and to decompress data after transmission.
[0288] Reducing Data Overhead.
[0289] In one technique, more bytes are included into a single
message in order to reduce per-message overhead. Because each
network message has some associated overhead, it is beneficial to
put more data into a single message to reduce the network
consumption on overhead traffic.
[0290] A device that is part of a power flow management system may
collect data from its sensors and internal processes. For the bits
of data that are not time critical to the system, the device can
cache the data until the ratio of data to overhead is less than 5%.
In the case of TCP/IP, this means waiting until the device had
gathered 1280 bytes of data before sending. [00312] Action and
Schedule Pre-distribution. For complicated or long sequences of
actions, these actions can be pre-distributed to the devices (or
distributed one time over the network). When any of the
pre-distributed actions need to be communicated, an identifier for
the more complicated sequence is all that needs to be communicated.
For dispatching actions or sets of actions, pre-compute large sets
of actions can be directed using an action identifier. As such, the
action sets are coded and only the code is transmitted. While this
method consumes memory on the client and server, bandwidth
consumption is reduced.
[0291] To achieve an application-level data compression, a power
flow management system can define a set of compact messages that
represent a pre-defined set of functionality. For example, consider
a device that runs just 4 distinct schedules during its normal
behavior. Rather than send the schedule that the device should run
each time the behavior should begin, the power flow management
system can send the device each schedule just once. Subsequent
times that each of those four schedules need to run, the power flow
management system can indicate which of the four schedules to run
(by name or ID), and a substantial amount of bandwidth can be
saved.
[0292] Minimum Change Dispatch.
[0293] Another technique for minimizing bytes between the system
and the distributed resources includes dispatching resources in a
way that minimizes the total state change on a per-resource basis
within the system. In one example, as few resources as possible
communicate in order to effect the desired change within the
system. Each time that the power flow management system needs to
change the state of the distributed devices (e.g. now there is a
need for 15 MW of power flow in some part of the grid, where the
earlier needs was for only 13 MW), it can choose to achieve the
targeted power flow by looking for the minimum number of changes in
the system (e.g. a device that was off needs to be on or vice
versa) that satisfies the constraint. In one embodiment, techniques
use a single bit to toggle from one state to another, such as from
off to on and from on to off.
[0294] There are many different algorithms that a power flow
management system can use to determine which of the connected
devices should be at what power flow level at any point in time.
Should the power flow management system need to revise the net
aggregate behavior of the power flow management system, it will
likely need to communicate with some subset of the connected
resources to signal a change in behavior.
[0295] One measure of the quality of a particular set of device
change orders is how many of the resources need to be contacted to
enact the change. One algorithm for achieving the minimum change
set to achieve the system-wide power flow goal is to find resource
for which a power flow change in the required direction is
possible, and to then sort the devices by the amount of power flow
they control. Starting with the device that controls the most
power, work down the list of available devices until enough power
has been recruited to achieve the goal of the power flow
system.
[0296] Devices should Communicate all Status Changes.
[0297] This technique does not use application level pings. In the
case of any change in device status (e.g. power level change, fuel
level change by some interesting quantity, resource
arrived/departed where resource may be a vehicles), communicating
all such status changes eliminates the need for the power flow
management system to use application level pings (i.e. messages
from the power flow management system, which has the purpose of
asking the device "Are you there?").
[0298] In one embodiment, the implemented technique provides that
resources communicate their departure from the system. This enables
the removal of all application level pings from the system. This
also requires that the resources have the ability to maintain power
for enough time after being disconnected that they can communicate.
When there is a local communications controller, the controller can
indicate the disappearance of a resource to the system.
[0299] Configurable Limits on Interesting Behavior.
[0300] Another bandwidth minimization technique involves increasing
the tolerance limits for state changes that require notification of
the main system. Relevant information should be communicated to the
power flow management system in real time. The devices should
support the ability to increase and decrease the limits of
interesting behavior to make the network traffic consumption be
tailor-able against responsiveness (e.g. knowing each time the
power flow changes by 3% is more informative than if it changes by
10% but requires network bandwidth to communicate).
[0301] Non-Time-Critical Information should be Bundled.
[0302] Techniques may minimize message overhead by saving data that
is not time-sensitive for same-message transmission with data that
is time sensitive, thereby saving the messaging overhead and
enabling data compression on a larger message. For information that
is not time critical to the operation of the power flow information
system (diagnostic data, logged data, summary statistics, etc), the
devices should gather this information in memory and only transmit
it to the power flow management system when a sufficient amount of
information is collected such that the portion of the message
dedicated to overhead is small.
[0303] Various combination of the bandwidth minimization techniques
may be implemented in an embodiment. For example, devices may
communicate all interesting changes to the power flow management
system and the limits defining interesting behavior for the device
may be configurable. A power flow system that is fully informed and
frequently updated about the behavior of the endpoints that are
connected to it defines one endpoint on a continuum of control and
flexibility. On the other end of the spectrum is a power flow
management system that has little or no visibility into the
behavior and status of the devices connected to it.
[0304] To enable the most flexible power flow management system
while minimizing the use of network traffic, the system can
establish criteria for devices that triggers an update action of
status to the power flow management system. This way, only when
something changes in the status of the device does communication
need to be made. Such a scheme does not waste network traffic
having devices inform the power flow management system that things
are unchanged from the last communication.
[0305] For example, consider a battery charging device that is
connected to a battery and participates in the network of the power
flow management system. Once the device has connected to the power
flow management system and reported its power flow (e.g. 800 W),
there is no need for the device to report new information to the
power flow management system unless there is a change in status.
For example, if a device is reporting the amount of power flowing
into a battery that is being charged and the battery fills up and
does not require further charging. [00324] FIG. 22 illustrates an
embodiment of a bandwidth minimization technique. A power flow
management system, which manages electric devices and electric
power supplies 2210, communicates device information 2220 and power
flow information 2230. Bandwidth reduction techniques described
above are applied to reduce network traffic 2240.
Smart Energy Protocol Translation Device
[0306] A protocol translation device may be provided that fully
participates in two or more networks using physical signaling
mechanisms that are capable of communication with each network.
Messages are reformulated messages such that the messages can pass
from one network to another. Since two relevant protocols may not
be compatible, such a device passes high-level information as
opposed to binary packets. This method is distinct from the method
used by Internet routers that simply forward messages from one
network to another without modification.
[0307] A Power Line Communicator (PLC), such as a power line
carrier, is a signaling mechanism by which a high-frequency signal
is added to the AC power line in a home or business. The
high-frequency signal carries information in a variety of protocols
to other devices that are able to decode these high frequency
signals.
[0308] The protocol translation device may include the following: a
microprocessor and power supply; physical transceivers for each
supported communications protocol stack; a software stack capable
of decoding messages from each of the communications protocols;
and, a software/hardware layer that can translate, if necessary,
and re-encode messages from one communications protocol to another
communications protocol. Because modern home networking
technologies can be wireless or PLC based, the protocol translation
device need not be located near any device that it provides
translation services for. The protocol translation device can be
attached to any outlet in the home, such as wall outlet 204
illustrated in FIG. 2A. The protocol translation device can stand
alone or co-reside with a device on the network.
[0309] In an embodiment, a device acts as an information bridge
between two networks. An electric vehicle service equipment (EVSE),
or a charge point, may communicate with an electric vehicle via the
SAEJ2836 application protocol over a HomePlug AV physical
communication mechanism and with a home area network (HAN) using
smart energy application protocol over a ZigBee wireless physical
communication mechanism. Such an EVSE or charge point can implement
the message translation between the two networks. For messages that
have equivalent meanings in both networks, the EVSE can reformulate
the message that comes in from the ZigBee/Smart Energy network to
the format of the J2836/PLC network and transmit the message from
the HAN to the vehicle.
[0310] In another embodiment, the device is a member of two
different networks and the device passes messages back and forth
between the two networks. The networks have some incompatibility,
such as a physical layer or application layer. Smart energy is an
application layer protocol that is implemented for multiple
physical interfaces including ZigBee and HomePlug PLC. The device
can be located such that it is able to participate in both networks
simultaneously. The device may contain the physical equipment to be
able to send/receive messages on either network, such as ZigBee for
wireless and HomePlug PLC for wired. As a message is observed on
either network, the device translates the message to the other
network's physical layer. When both networks implement smart
energy, there is no need to translate the application layer as
well.
[0311] In one embodiment, an electric vehicle service equipment
(EVSE) can act as such a translation device. When a vehicle has the
ability to communicate via one protocol, and an EVSE is located
where access to the central charge management server is provided by
a different protocol, the EVSE could act as a translator between
the two protocols. Such an EVSE includes complete implementations
of both the hardware and software necessary to support both
protocols to fully decode each protocol to obtain the application
level messages.
[0312] An EVSE can be connected to a vehicle using the SAE2836
protocol over PLC and can be connected to a home network using a
wireless ZigBee protocol, according to one embodiment. The EVSE can
include complete implementations of each hardware and protocol
stack. As such, the EVSE can forward messages between the two
stacks.
[0313] In an embodiment, the translation device could be physically
distinct. For example, in an installation with a PLC based vehicle
and a wireless internet access point, the translation device can be
a self-contained box plugged into a power outlet.
[0314] FIG. 23 illustrates an embodiment of a protocol translation
for a power flow management system that utilizes networks to
communicate between electric devices and electric power supplies
2310. A communications protocol translation device reformulates
messages from one protocol to another protocol 2320 in order to
transmit such messages from a network using one communications
protocol to a network using a different protocol. FIG. 24 shows a
communications protocol translation device 2410 implemented between
two networks 2420 that are connected to electric power supplies and
electric devices 2430.
Communications Utilizing Existing Hardware
[0315] Certain automotive subsystems, such as battery charge
controllers, require real-time communications links to off-vehicle
networks. The communications hardware to provide this off vehicle
link includes Cellular, Wi-Fi, ZigBee, and Homeplug. Such equipment
is expensive and can be difficult to configure.
[0316] Subsystems in a vehicle are connected together over a shared
bus, known as the CAN-bus. This bus provides high-speed low-latency
communication to attached devices, but does not provide the
mechanisms necessary for communicating with off-vehicle entities.
Rather than implement communications hardware directly, a client
subsystem issues commands over the CAN-bus to request off-vehicle
communications services from another "server" subsystem.
[0317] Existing subsystem in the vehicle that already possess
communications hardware can perform this server role without
requiring any additional hardware. Because the CAN-bus does not
support routing or packet forwarding, it is necessary to define an
encapsulation mechanism to permit the off-board communications
protocol to be embedded within CAN messages.
[0318] In some circumstances, vehicle designs may include existing
communications hardware for purposes other than charge management.
These other uses may include emergency response and remote vehicle
diagnostics. Rather than adding additional communications hardware,
an electric vehicle can make use of these existing communications
modules. Such module re-use is accomplished by enhancing the
software on the existing communications modules in order to expand
functionality.
[0319] Similar to modules installed via an extensibility mechanism,
preexisting modules upgraded through software can engage in smart
charging through two distinct mechanisms.
[0320] In one embodiment, the software upgraded communications
module provides a communications path to external networks which
allows vehicle modules to participate in a smart charging program
in a manner similar to that of a vehicle that is initially equipped
with a communications module.
[0321] In another embodiment, the software upgraded communications
module includes all smart charging logic. In this embodiment, the
software upgraded communications module is solely responsible for
participating in the smart charging program, and then implements
that program by sending primitive messages to other subsystems in
the vehicle.
[0322] FIG. 25 illustrates an embodiment of communications using
existing hardware with a smart charging module configured to be
implemented for a vehicle subsystem 2510. The vehicle subsystem is
connected to a shared vehicle-wide communications medium 2520. The
smart charging module is configured to provide messages to a
vehicle subsystem 2530.
Communication Services to Vehicle Subsystems
[0323] Modern electric vehicles benefit in a variety of ways from a
centrally controlled smart charging program. However, the modules
in the vehicle that are capable of executing a charge management
program, e.g. the Battery Management Systems Charge Controller, do
not generally have the ability to communicate with external
networks which are outside the vehicle. To work effectively, a
smart charging program requires the central control of an outside
entity via an external network, such as a server. This server is
responsible for coordinating the charging activities of a large
number of vehicles distributed over a wide area, such as a
city.
[0324] Establishing a communications channel between appropriate
vehicle subsystems and external networks facilitates smart charging
and reduce the cost of ownership of the vehicle. While most vehicle
subsystems lack off-vehicle communication, virtually all subsystems
are connected to a shared vehicle-wide communications medium or
bus. In many vehicles, this bus uses the CAN-bus standard, as
defined by the International Standards Organization (ISO) standard
#11898. Over time, some new vehicle designs will transition to
other vehicle-wide communications mediums, such as Flexray or other
similar technologies. However, the basic principle of a shared
communications medium to allow vehicle subsystems to communicate
will remain intact, and the concepts in the present disclosure will
be similarly applicable to these future communications mediums.
[0325] Rather than adding off-vehicle communications capabilities
to existing vehicle subsystems, a separate module provides
communication services to all subsystems on a vehicle, making these
services available via the vehicle's CAN-bus. Confining the
modification to a single module reduces the cost of switching
communications standards such that support can be accomplished by
installing different communications modules in different cars.
[0326] Such a communications module includes the hardware necessary
to communicate off-vehicle, and also connects to the vehicle's
CAN-bus. Software within the communications module translates or
encapsulates packets to allow information to flow between the
various vehicle subsystems and the entities outside the
vehicle.
[0327] In one embodiment, the communications module can forward
messages from the external network, unmodified, to other vehicle
subsystems. As an example, if the external network uses the TCP/IP
protocol, the communications module forwards TCP packets over the
CAN-bus to other vehicle subsystems. Because vehicle communication
busses such as CAN-bus do not natively support wide-area protocols
such as TCP/IP, an encapsulation protocol is required.
[0328] Encapsulation works by defining a specific CAN message for
TCP transport. Such a CAN message includes a packet header and a
packet body. The packet header can specify the packet type to
differentiate it from other types of CAN traffic. The packet header
can also specify the packet length, and may contain other CAN
packet attributes, such as addressing. The packet body includes the
bytes of the original external network packet, such as a TCP
packet.
[0329] Such a packet can be transmitted over the CAN-bus from the
communications module to the vehicle subsystem wishing to
communicate. When the vehicle subsystem wishing to communicate
receives such a packet, the subsystem uses the type and size
information present in the CAN packet to extract the original TCP
packet. When communicating in the reverse direction, i.e. from the
vehicle subsystem to the external network, the process is reversed.
The vehicle subsystem places a TCP packet within a properly
formatted CAN packet and transmits it over the CAN-bus to the
communications module. The communications module extracts the TCP
packet and transmits it over the external network.
[0330] In an embodiment, the communications module entirely decodes
messages received from the external network, and re-encodes the
messages as CAN-bus messages. As such, the communications module
extracts the actual intended purpose of the remote message, and
transmits a new message across the vehicle's CAN-bus.
[0331] As an example, the communications module may receive a
packet across the external bus with the command specifying the
current price of electricity. The communications module transmits a
CAN-bus message to the appropriate subsystems indicating the
current price of electricity. Since the communications module is
fully and completely decoding and encoding each message in each
direction, it is not necessary for the external network messages
and the vehicle-internal CAN-bus messages to be similar in any
way.
[0332] A communications module can include the following
components: a central processing unit (CPU) with sufficient power
to run the appropriate software; a CAN transceiver, or transceiver
for an alternate in-vehicle communications network; an external
communications transceiver for one or more external communications
networks; a software stack capable of wrapping high level
communications packets in a CAN header, for packets entering the
vehicle, and removing a can header, for packets leaving the
vehicle; software capable translating messages from a remote
network format to the local CAN format; and, software capable of
the bonding/provisioning process required by the specific external
communications protocol.
[0333] FIG. 26 illustrates an embodiment of communication services
to vehicle subsystems. A CAN transceiver is connected to a CPU in a
vehicle and to an external bus, which is connected to a vehicle
subsystem 2610. A software stack is connected to the CPU for
augmenting CAN headers for packets 2620. Software is configured to
translate messages from a remote network format to a CAN format
2630. Software is also configured for a provisioning process of
external communications protocol 2640.
Vehicle Power Systems Control Extensibility System
[0334] Electric and plug-in hybrid electric vehicles benefit
greatly from on-board charge-management controllers. Such
controllers can harmonize a vehicle's electricity consumption with
the needs of the power grid. However, price-sensitivity
time-to-market concerns, or a lack of standardization, can preclude
the factory installation of these charge management
controllers.
[0335] It is desirable that vehicles without factory-equipped
charge controllers have the capacity to be upgraded with an
after-market controller. A vehicle can be upgradable by providing a
physical and software interface to allow the installation of a
charge controller. This interface may include: a physical interface
to the vehicle's CAN-bus, via an electrical contact plug; a
standardization of software messages that are to be sent over the
CAN-bus to control charging; and, a physical location for the
charge controller to reside, where the CAN interface plug must be
located.
[0336] Vehicles may be sold without the ability to communicate with
off-vehicle networks or systems, and therefore without the ability
to coordinate their charging behavior with a central authority or
server. A vehicle manufacturer that recognizes the benefit of
charge management may opt to not include charge management, due to
reasons such as price sensitivity, time-to-market concerns, or a
lack of standardization. In these situations, it is beneficial for
vehicles to be easily upgradable through the installation of a
communications module or charge management module. Such
upgradability can be managed by clearly defining the physical,
electrical and software interfaces between a communications module
and the vehicle.
[0337] The mechanical interface may include a physical location for
the module to be installed in the vehicle. This physical location
provides access to the electrical/signaling interface, provides a
particular level of environmental protection, and accommodate a
particular size and shape of add-on modules.
[0338] The electrical/signaling interface may include a
standardized connector to the vehicle's standardized internal
communications bus, such as CAN-bus, and a standardized connector
to an electrical supply. In some vehicles, the vehicle's
communications bus can be a non-electrical standard, such as a
Fiber-optic based system. While such a system may not be compatible
with electrically signaled CAN based systems, the general principle
of the extension interface can still apply.
[0339] The software interface defines the protocol messages by
which the expansion module interfaces with existing modules in the
vehicle.
[0340] In one embodiment, the other relevant modules in the vehicle
are designed to communicate with the expansion module as defined
elsewhere in the application. The expansion module provides a
communications path to external networks which allows vehicle
modules to participate in a smart charging program in a manner
similar to that of a vehicle that is initially equipped with a
communications module.
[0341] In an embodiment, existing modules in the vehicle have no
explicit support for smart charging, and all smart charging logic
is contained in the expansion module. As such, the expansion module
is solely responsible for participating in the smart charging
program. The expansion module implements the program by sending
primitive messages to other subsystems in the vehicle.
[0342] FIG. 27 illustrates an embodiment of an extensibility system
including a contact plug for a CAN-bus in a vehicle 2710. An
expansion module provides standardization of transmitted messages
to control charging 2720. In addition, a charge controller for
control extensibility is located at the contact plug 2730.
Communications without Specific Hardware
[0343] In many applications, it is beneficial for an electrical
load, such as an electric vehicle, to communicate with an electric
power supply, such as a charging station or an electric vehicle
service equipment. Such communication can convey information such
as device identification, state of battery charge, or power
consumption preferences. This communication can also be utilized to
implement the arbitration protocol described herein. The
communication is desirable even in situations where the two devices
in question do not possess hardware designed to facilitate
communication.
[0344] For devices to communicate without specific communications
hardware, information can be conveyed by modulating the power
transfer between the electrical load (e.g. an electric vehicle) and
the electric power supply (electric vehicle service equipment). To
facilitate the transmission of information from the electrical load
to the electric power supply, an electric load device can
intermittently draw power and/or refrain from drawing power.
Communications time may be subdivided into seconds. For example,
each second wherein the load device drew power is interrupted as
the binary 1 digit, and each second wherein the load device did not
draw power is interrupted as the binary 0 digit. In a similar
manner, the power supply device can communicate with the load
device to facilitate the transmission of information from the
electric power supply to the electric load device. The electric
power supply can provide power for an interval, represented as the
binary 1 digit, or refraining from providing power, represent as
the binary 0 digit.
[0345] A variety of standard communication protocol techniques may
be used to address issues such as data reliability and clock drift.
Depending on the accuracy of both sensing equipment in the
receiving device and switching equipment in the transmitting
device, the time interval can be varied. For example, the time
interval may be varied to an interval much lower than one second.
Lower intervals would allow a greater amount of information to be
transmitted in the same amount of time.
[0346] Because the non-powered intervals deprive the load device of
electrical power, the load device requires a supplemental power
source to remain functional during such intervals. This
supplemental power source can be a storage battery, a capacitor, or
an alternative primary electrical source. This system does not
interfere with the primary function of the power circuit, which is
power transfer, because all communication may be completed early in
the power connection and power can flow uninterrupted for the
remainder of the connection time.
[0347] To address the limitation of communications mediums that
prohibit both the electric vehicle and the electric power source
from transmitting information simultaneously, a variety of sharing
protocols can be used. In one embodiment, the electric power supply
and the electric vehicle take turns transmitting information,
reversing roles after a fixed number of bits. In an embodiment, the
transmitted messages are structured as packets with a transmitted
size. After the transmission of a packet, the direction of
transmission is reversed.
[0348] FIG. 28 illustrates an embodiment of communications without
specific hardware including modulating power transfer between an
electrical load associated with an electric vehicle and a power
supply 2810, transmitting information from the electrical load to
the power supply 2820, and enabling the electrical vehicle to
communicate with the power supply 2830.
Arbitrating Smart Chargepoint with Smart Vehicle
[0349] Modern Electric vehicles could benefit in a variety of ways
from a centrally controlled smart charging program where a central
server coordinates the charging activities of a large number of
vehicles distributed over a wide area, such as a city. This
coordination is accomplished by the server communicating directly
with a smart charging module located at each vehicle. The smart
charging module can be located inside the vehicle, either as an
original component of the vehicle or an aftermarket accessory.
Equipment located inside the vehicle can moderate electrical load
by directly reducing the power consumption of the vehicle.
[0350] In one embodiment, the smart charging module will be located
in external equipment responsible for providing electricity to the
vehicle. Such external equipment may be electric vehicle service
equipment (EVSE). EVSE or charging stations can reduce power
consumption by curtailing the power available to the vehicle.
[0351] In the case where both the electric vehicle and the EVSE
contain smart charging modules, a potential problem arises. Because
charge management systems can be integrated into both vehicles and
vehicle charging infrastructure, each of these systems may
initially assume that they are the only charging intelligence
present in a charging session. When a smart car attaches to a smart
chargepoint, certain problems arise. Because the two devices are
not communicating with each other, the devices each act as if they
have full control of the charge session. If the central smart
charging server is not informed that the two devices represent a
single vehicle, it will manage the two devices independently. The
two devices may attempt to charge at different times, resulting in
no power flow. Furthermore, both devices may receive stop charging
messages from a utility at the same time, resulting in
double-counting of load reduction.
[0352] To address these concerns, electric vehicles and charging
equipment, or EVSE, can both implement a charge coordination
protocol. This protocol allows the EVSE and the vehicle to
determine which of the two entities is responsible for
communicating with the charge management server and implementing a
smart charging program. The other entity would enter a passive
mode, following the direction of the primary entity.
[0353] With such a protocol, an electric vehicle can transmit a
charge coordination capabilities message to the chargepoint when
the vehicle is connected. The capabilities message specifies charge
coordination modes that the vehicle supports. The charge equipment
can send a charge coordination mode message specifying the
coordination mode. This mode may be selected from the list provided
by the vehicle. When the two messages have been transmitted, the
charge equipment and vehicle commence coordinated charging.
[0354] Two coordinated charging modes are initially defined as
charge-equipment switching charging and vehicle-switching charging.
In the charge-equipment switched charging mode, the electric
vehicle stops smart charging and behaves as a dumb load. The EVSE,
or the charge equipment, sends electricity as it determines while
the vehicle does not communicate with any external entity for
purposes of charge management. As such, the EVSE controls the rate
of electricity flow to the vehicle and is responsible for all
communication with smart charging server.
[0355] In the vehicle-switched charging mode, the EVSE or charging
equipment does not engage in smart charging and provide electricity
on-demand to the Vehicle at all times. The electric vehicle
controls its rate of electricity consumption and is responsible for
all communication with the smart charging server. The electric
vehicle performs the physical regulation of charge level. However,
the regulation of charging is based on commands issued by the
charging equipment.
[0356] If the vehicle possessed an alternative communications
channel, such as cellular, the vehicle stops accepting charge
commands from that channel. Charging equipment may monitor the
vehicle to determine whether the vehicle had complied with charge
directives. The vehicle can fall back to direct control if it is
determined that the vehicle was non-compliant.
[0357] Additional charging modes may be defined over time.
Communication between the electric vehicle and the EVSE could be
accomplished via Power Line Communications (PLC) over the charging
cable, or via other means, including wireless communications.
[0358] FIG. 29 illustrates an embodiment of arbitrating a smart
chargepoint with a smart charging module configured to be
implemented on vehicle equipment 2910. The module is configured to
communicate with the smart charging program 2920, and to moderate
an electric load by reducing power consumption of the vehicle 2930.
In addition, the module is configured to communicate with a second
smart charging module in external charging equipment 2940, and the
modules implement a charge coordination protocol 2950.
CONCLUSION
[0359] Although systems and methods have been described in language
specific to structural features and/or methodological acts, it is
to be understood that the subject matter defined in the appended
claims is not necessarily limited to the specific features or acts
described. Rather, the specific features and acts are disclosed as
examples of implementations of the claimed methods, devices,
systems, etc. It will be understood by those skilled in the art
that various changes in form and details may be made therein
without departing from the spirit and scope of the invention.
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