US20090040029A1 - Transceiver and charging component for a power aggregation system - Google Patents

Abstract

Systems and methods are described for a power aggregation system. In one implementation, a system includes a transceiver device physically coupled to an electric resource, the transceiver device being configured to provide information about the electric resource to a charging component. Additionally, such a system may include a charging component, the charging component being coupled to the electric resource via a charging medium and communicatively coupled to the transceiver device. The charging component may also be configured to receive the electric resource information from the transceiver and, in response, effectuate charge control management of the electric resource.

Description

RELATED APPLICATIONS
• This application claims priority to U.S. Provisional Patent Application No. 60/980,663 to Seth Bridges, et al., entitled, “Plug-In-Vehicle Management System,” filed Oct. 17, 2007 and incorporated herein by reference.
• This application is also a continuation-in-part of U.S. Non-provisional patent application Ser. No. 11/837,407 to David L. Kaplan, et al., entitled, “Power Aggregation System for Distributed Electric Resources,” filed on Aug. 10, 2007 and incorporated herein by reference application Ser. No. 11/837,407 claims priority to U.S. Provisional Patent Application No. 60/822,047 to David L. Kaplan, entitled, “Vehicle-to-Grid Power Flow Management System,” filed Aug. 10, 2006 and incorporated herein by reference; U.S. Provisional Patent Application No. 60/869,439 to Seth W. Bridges, David L. Kaplan, and Seth B. Pollack, entitled, “A Distributed Energy Storage Management System,” filed Dec. 11, 2006 and incorporated herein by reference; and U.S. Provisional Patent Application No. 60/915,347 to Seth Bridges, Seth Pollack, and David Kaplan, entitled, “Plug-In-Vehicle Management System,” filed May 1, 2007 and incorporated herein by reference.
• This application is also related to U.S. patent application Ser. No. 11/836,743, entitled, “Electric Resource Module in a Power Aggregation System for Distributed Electric Resources” by Bridges et al., filed concurrently on Aug. 9, 2007, and incorporated herein by reference; to U.S. patent application Ser. No. 11/836,745, entitled, “Electric Resource Power Meter in a Power Aggregation System for Distributed Electric Resources” by Bridges et al., filed concurrently on Aug. 9, 2007, and incorporated herein by reference; to U.S. patent application Ser. No. 11/836,747, entitled, “Connection Locator in a Power Aggregation System for Distributed Electric Resources” by Bridges et al., filed concurrently on Aug. 9, 2007, and incorporated herein by reference; to U.S. patent application Ser. No. 11/836,749, entitled, “Scheduling and Control in a Power Aggregation System for Distributed Electric Resources” by Pollack et al., filed concurrently on Aug. 9, 2007, and incorporated herein by reference; to U.S. patent application Ser. No. 11/836,752, entitled, “Smart Islanding and Power Backup in a Power Aggregation System for Distributed Electric Resources” by Bridges et al., filed concurrently on Aug. 9, 2007, and incorporated herein by reference; to U.S. patent application Ser. No. 11/836,756, entitled, “User Interface and User Control in a Power Aggregation System for Distributed Electric Resources” by Pollack et al., filed concurrently on Aug. 9, 2007, and incorporated herein by reference; and to U.S. patent application Ser. No. 11/836,760, entitled, “Business Methods in a Power Aggregation System for Distributed Electric Resources” by Pollack et al., filed concurrently on Aug. 9, 2007, and incorporated herein by reference.
FIELD OF THE INVENTION
• Embodiments of the present invention relate generally to the field of power aggregation and distribution. More specifically, embodiments of the present invention relate to a service for aggregating power distributed to and from electric resources.
BACKGROUND
• Today's electric power and transportation systems suffer from a number of drawbacks. Pollution, especially greenhouse gas emissions, is prevalent because approximately half of all electric power generated in the United States is produced by burning coal. Virtually all vehicles in the United States are powered by burning petroleum products, such as gasoline or petro-diesel. It is now widely recognized that human consumption of these fossil fuels is the major cause of elevated levels of atmospheric greenhouse gases, especially carbon dioxide (CO₂), which in turn disrupts the global climate, often with destructive side effects. Besides producing greenhouse gases, burning fossil fuels also add substantial amounts of toxic pollutants to the atmosphere and environment. The transportation system, with its high dependence on fossil fuels, is especially carbon-intensive. That is, physical units of work performed in the transportation system typically discharge a significantly larger amount of CO₂into the atmosphere than the same units of work performed electrically.
• With respect to the electric power grid, expensive peak power—electric power delivered during periods of peak demand—can cost substantially more than off-peak power. The electric power grid itself has become increasingly unreliable and antiquated, as evidenced by frequent large-scale power outages. Grid instability wastes energy, both directly and indirectly (for example, 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 standard, typically carbon-intensive forms of electricity.
• 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 (e.g., electric vehicle batteries) to meet medium- and large-scale needs of power services.
• Thus, significant opportunities for improvement exist in the electrical and transportation sectors, and in the way these sectors interact. Fuel-powered vehicles could be replaced with vehicles whose power comes entirely or substantially from electricity. Polluting forms of electric power generation could be replaced with clean ones. Real-time balancing of generation and load can be realized with reduced cost and environmental impact. More economical, reliable electrical power can be provided at times of peak demand. Power services, such as regulation and spinning reserves, can be provided to electricity markets to stabilize the grid and provide a significant economic opportunity. Technologies can be enabled to provide broader use of intermittent power sources, such as wind and solar.
• Robust, grid-connected electrical storage could store electrical energy during periods of over-production for redelivery to the grid during periods of under-supply. Electric vehicle batteries in vast numbers could participate in this grid-connected storage. However, a single vehicle battery is insignificant when compared with the needs of the power grid.
• 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, but does not address the information processing requirements of dealing with large, mobile populations of electric vehicles, the complexities of billing (or compensating) vehicle owners, nor the complexities of assembling mobile pools of electric vehicles into aggregate power resources based on grid location, the aggregate power resources being robust enough to support firm power service contracts with grid operators.
BRIEF DESCRIPTION OF THE DRAWINGS
• FIG. 1 is a diagram of an exemplary power aggregation system.
• FIGS. 2A-2B are diagrams of exemplary connections between an electric vehicle, the power grid, and the Internet.
• FIG. 3 is a block diagram of exemplary connections between an electric resource and a flow control server of the power aggregation system.
• FIG. 4 is a diagram of an exemplary layout of the power aggregation system.
• FIG. 5 is a diagram of exemplary control areas in the power aggregation system.
• 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.
• FIG. 7 is a block diagram of an exemplary flow control server.
• FIG. 8A is a block diagram of an exemplary remote intelligent power flow module.
• FIG. 8B is a block diagram of an exemplary transceiver and charging component combination.
• FIG. 9 is a diagram of an exemplary resource communication protocol.
• FIG. 10 is diagram of exemplary safety measures in a vehicle-to-home implementation of the power aggregation system.
• FIG. 11 is a diagram of exemplary safety measures when multiple electric resources flow power to a home in the power aggregation system.
• FIG. 12 is a block diagram of an exemplary smart disconnect of the power aggregation system.
• FIG. 13 is a flow diagram of an exemplary method of power aggregation.
• FIG. 14 is a flow diagram of an exemplary method of communicatively controlling an electric resource for power aggregation.
• FIG. 15 is a flow diagram of an exemplary method of communication between a transceiver and charge component and charge control management by the charge component
• FIG. 16 is a flow diagram of an exemplary method of estimating a state of charge.
• FIG. 17 is a flow diagram of an exemplary method of controlling charging of load-only electric resources.
• FIG. 18 is a flow diagram of an exemplary method for a resource communication protocol.
• FIG. 19 is a flow diagram of an exemplary method of offline behavior for an electric resource.
• FIG. 20 is a flow diagram of an exemplary method of calculating an efficiency metric for an electric resource.
• FIG. 21 is a flow diagram of an exemplary method of smart islanding, including a safety mechanism.
• FIG. 22 is a flow diagram of an exemplary method of extending a user interface for power aggregation.
• FIG. 23 is an illustration of an exemplary simple user interface for facilitating user controlled charging.
DETAILED DESCRIPTIONOverview
• Described herein is a power aggregation system for distributed electric resources, and associated methods. In one implementation, the exemplary 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 exemplary system can dynamically aggregate these electric resources to provide power services to grid operators (e.g. utilities, Independent System Operators (ISO), etc).
• “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.
• “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.
• “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.
• “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.
• “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.
• “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 exemplary 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 exemplary system is horizontally scalable for use in providing power services to multiple grid areas simultaneously.
• “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.
• “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.
• “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.
• “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.
• Electric vehicle “energy storage systems” (batteries, supercapacitors, 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.
• Exemplary System
• FIG. 1 shows an exemplarypower aggregation system100. Aflow control center102 is communicatively coupled with a network, such as a public/private mix that includes theInternet104, and includes one ormore servers106 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 theInternet104, theflow control center102 maintainscommunication108 with operators of power grid(s), andcommunication110 with remote resources, i.e., communication with peripheral electric resources112 (“end” or “terminal” nodes/devices of a power network) that are connected to thepower grid114. In one implementation, powerline communicators (PLCs), such as those that include or consist of Ethernet-over-powerline bridges120 are implemented at connection locations so that the “last mile” (in this case, last feet—e.g., in a residence124) of Internet communication with remote resources is implemented over the same wire that connects eachelectric resource112 to thepower grid114. Thus, each physical location of eachelectric resource112 may be associated with a corresponding Ethernet-over-powerline bridge120 (hereinafter, “bridge”) at or near the same location as theelectric resource112. Eachbridge120 is typically connected to an Internet access point of a location owner, as will be described in greater detail below. The communication medium fromflow control center102 to the connection location, such asresidence124, can take many forms, such as cable modem, DSL, satellite, fiber, WiMax, etc. In a variation,electric resources112 may connect with the Internet by a different medium than the same power wire that connects them to thepower grid114. For example, a givenelectric resource112 may have its own wireless capability to connect directly with theInternet104 or an Internet access point and thereby with theflow control center102.
• Electric resources112 of the exemplarypower aggregation system100 may include the batteries of electric vehicles connected to thepower grid114 atresidences124,parking lots126 etc.; batteries in arepository128, fuel cell generators, private dams, conventional power plants, and other resources that produce electricity and/or store electricity physically or electrically.
• In one implementation, each participatingelectric resource112 or group of local resources has a corresponding remote intelligent power flow (IPF) module134 (hereinafter, “remote IPF module”134). The centralizedflow control center102 administers thepower aggregation system100 by communicating with theremote IPF modules134 distributed peripherally among theelectric resources112. Theremote IPF modules134 perform several different functions, including, but not limited to, providing theflow control center102 with the statuses of remote resources; controlling the amount, direction, and timing of power being transferred into or out of a remoteelectric resource112; providing metering of power being transferred into or out of a remoteelectric resource112; providing safety measures during power transfer and changes of conditions in thepower grid114; logging activities; and providing self-contained control of power transfer and safety measures when communication with theflow control center102 is interrupted. Theremote IPF modules134 will be described in greater detail below.
• In another implementation, instead of having anIPF module134, eachelectric resource112 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 withflow control center102 to perform some or all of the above mentioned functions ofIPF module134. An exemplary transceiver and charging component are shown inFIG. 2B and are described in greater detail herein.
• FIG. 2A shows another view of exemplary electrical and communicative connections to anelectric resource112. In this example, anelectric vehicle200 includes abattery bank202 and an exemplaryremote IPF module134. Theelectric vehicle200 may connect to a conventional wall receptacle (wall outlet)204 of aresidence124, thewall receptacle204 representing the peripheral edge of thepower grid114 connected via aresidential powerline206.
• In one implementation, thepower cord208 between theelectric vehicle200 and thewall outlet204 can be composed of only conventional wire and insulation for conducting alternating current (AC) power to and from theelectric vehicle200. InFIG. 2A, a location-specificconnection locality module210 performs the function of network access point—in this case, the Internet access point. Abridge120 intervenes between thereceptacle204 and the network access point so that thepower cord208 can also carry network communications between theelectric vehicle200 and thereceptacle204. With such abridge120 andconnection locality module210 in place in a connection location, no other special wiring or physical medium is needed to communicate with theremote IPF module134 of theelectric vehicle200 other than aconventional power cord208 for providing residential line current at any conventional voltage. Upstream of theconnection locality module210, power and communication with theelectric vehicle200 are resolved into thepowerline206 and anInternet cable104.
• Alternatively, thepower cord208 may include safety features not found in conventional power and extension cords. For example, anelectrical plug212 of thepower cord208 may include electrical and/or mechanical safeguard components to prevent theremote IPF module134 from electrifying or exposing the male conductors of thepower cord208 when the conductors are exposed to a human user.
• In some embodiments, a radio frequency (RF) bridge (not shown) may assist theremote IPF module134 in communicating with a foreign system, such as a utility smart meter (not shown) and/or aconnection locality module210. For example, theremote IPF module134 may be equipped to communicate overpower cord208 or to engage in some form of RF communication, such as Zigbee or Bluetooth™, 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 andremote IPF module134 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 theremote IPF module134 or foreign system, or may be external to both. The communicative associations between the RF bridge andremote IPF module134 and between the RF bridge and foreign system may be via wired or wireless communication.
• FIG. 2B shows a further view of exemplary electrical and communicative connections to anelectric resource112. In this example, theelectric vehicle200 may include atransceiver212 rather than aremote IPF module134. Thetransceiver212 may be communicatively coupled to acharging component214 through aconnection216, and the charging component itself may be coupled to a conventional wall receptacle (wall outlet)204 of aresidence124 and toelectric vehicle200 through apower cord208. The other components shown inFIG. 2B may have the couplings and functions discussed with regard toFIG. 2A.
• In various embodiments,transceiver212 and chargingcomponent214 may, in combination, perform the same functions as theremote IPF module134.Transceiver212 may interface with computer systems ofelectric vehicle200 and communicate with chargingcomponent214, providingcharging component214 with information aboutelectric vehicle200, such as its vehicle identifier, a location identifier, and a state of charge. In response,transceiver212 may receive requests and commands which transceiver212 may relay tovehicle200's computer systems.
• Charging component214, being coupled to bothelectric vehicle200 andwall outlet204, may effectuate charge control of theelectric vehicle200. If theelectric vehicle200 is not capable of charge control management, chargingcomponent214 may directly manage the charging ofelectric vehicle200 by stopping and starting a flow of power between theelectric vehicle200 and apower grid114 in response to commands received from aflow control server106. If, on the other hand, theelectric vehicle200 is capable of charge control management, chargingcomponent214 may effectuate charge control by sending commands to theelectric vehicle200 through thetransceiver212.
• In some embodiments, thetransceiver212 may be physically coupled to theelectric vehicle200 through a data port, such as an OBD-II connector. In other embodiments, other couplings may be used. Theconnection216 betweentransceiver212 and chargingcomponent214 may be a wireless signal, such as a radio frequency (RF), such as a Zigbee, or Bluetooth™ signal. And chargingcomponent214 may include a receiver socket to couple withpower cord208 and a plug to couple withwall outlet204. In one embodiment, chargingcomponent214 may be coupled toconnection locality module210 in either a wired or wireless fashion. For example, chargingcomponent214 might have a data interface for communicating wirelessly with both thetransceiver212 andlocality module210. In such an embodiment, thebridge120 may not be required.
• Further details about thetransceiver212 and chargingcomponent214 are illustrated byFIG. 8B and described in greater detail herein.
• FIG. 3 shows another implementation of theconnection locality module210 ofFIG. 2, in greater detail. InFIG. 3, anelectric resource112 has an associatedremote IPF module134, including abridge120. Thepower cord208 connects theelectric resource112 to thepower grid114 and also to theconnection locality module210 in order to communicate with theflow control server106.
• Theconnection locality module210 includes another instance of abridge120, connected to anetwork access point302, which may include such components as a router, switch, and/or modem, to establish a hardwired or wireless connection with, in this case, theInternet104. In one implementation, thepower cord208 between the twobridges120 and120′ is replaced by a wireless Internet link, such as a wireless transceiver in theremote IPF module134 and a wireless router in theconnection locality module210.
• In other embodiments, atransceiver212 and chargingcomponent214 may be used instead of aremote IPF module134. In such an embodiment, thecharging component214 may include or be coupled to abridge120, and theconnection locality module210 may also include abridge120′, as shown. In yet other embodiments, not shown, chargingcomponent214 andconnection locality module210 may communicate in a wired or wireless fashion, as mentioned previously, withoutbridges120 and120′. 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™.
• Exemplary System Layouts
• FIG. 4 shows anexemplary layout400 of thepower aggregation system100. Theflow control center102 can be connected to many different entities, e.g., via theInternet104, for communicating and receiving information. Theexemplary layout400 includeselectric resources112, such as plug-inelectric vehicles200, physically connected to the grid within asingle control area402. Theelectric resources112 become an energy resource forgrid operators404 to utilize.
• Theexemplary layout400 also includes end users406 classified intoelectric resource owners408 and electricalconnection location owners410, who may or may not be one and the same. In fact, the stakeholders in an exemplarypower aggregation system100 include the system operator at theflow control center102, thegrid operator404, theresource owner408, and the owner of thelocation410 at which theelectric resource112 is connected to thepower grid114.
• Electricalconnection location owners410 can include:
• • Rental car lots—rental car companies often have a large portion of their fleet parked in the lot. They can purchase fleets ofelectric vehicles200 and, participating in apower aggregation system100, generate revenue from idle fleet vehicles.
  • Public parking lots—parking lot owners can participate in thepower aggregation system100 to generate revenue from parkedelectric vehicles200. Vehicle owners can be offered free parking, or additional incentives, in exchange for providing power services.
  • Workplace parking—employers can participate in apower aggregation system100 to generate revenue from parked employeeelectric vehicles200. Employees can be offered incentives in exchange for providing power services.
  • Residences—a home garage can merely be equipped with aconnection locality module210 to enable the homeowner to participate in thepower aggregation system100 and generate revenue from a parked car. Also, thevehicle battery202 and associated power electronics within the vehicle can provide local power backup power during times of peak load or power outages.
  • Residential neighborhoods—neighborhoods can participate in apower aggregation system100 and be equipped with power-delivery devices (deployed, for example, by homeowner cooperative groups) that generate revenue from parkedelectric vehicles200.
  • Thegrid operations116 ofFIG. 4 collectively include interactions withenergy markets412, the interactions ofgrid operators404, and the interactions ofautomated grid controllers118 that perform automatic physical control of thepower grid114.
• Theflow control center102 may also be coupled withinformation sources414 for input of weather reports, events, price feeds, etc.Other data sources414 include the system stakeholders, public databases, and historical system data, which may be used to optimize system performance and to satisfy constraints on the exemplarypower aggregation system100. Thus, an exemplarypower aggregation system100 may consist of components that:
• • communicate with theelectric resources112 to gather data and actuate charging/discharging of theelectric resources112;
  • gather real-time energy prices;
  • gather real-time resource statistics;
  • predict behavior of electric resources112 (connectedness, location, state (such as battery State-Of-Charge) at a given time of interest, such as a time of connect/disconnect);
  • predict behavior of thepower grid114/load;
  • encrypt communications for privacy and data security;
  • actuate charging ofelectric vehicles200 to optimize some figure(s) of merit;
  • offer guidelines or guarantees about load availability for various points in the future, etc.
• 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).
• Exemplarypower aggregation systems100 in such alayout400 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.
• The exemplarypower aggregation system100 enables agrid operator404 to control the aggregatedelectric resources112 connected to thepower grid114. Anelectric resource112 can act as a power source, load, or storage, and theresource112 may exhibit combinations of these properties. Control of a set ofelectric resources112 is the ability to actuate power consumption, generation, or energy storage from an aggregate of theseelectric resources112.
• FIG. 5 shows the role ofmultiple control areas402 in the exemplarypower aggregation system100. Eachelectric resource112 can be connected to thepower aggregation system100 within a specific electrical control area. A single instance of theflow control center102 can administerelectric resources112 from multiple distinct control areas501 (e.g.,control areas502,504, and506). In one implementation, this functionality is achieved by logically partitioning resources within thepower aggregation system100. For example, when thecontrol areas402 include an arbitrary number of control areas, control area “A”502, control area “B”504, . . . , control area “n”506, thengrid operations116 can include correspondingcontrol area operators508,510, . . . , and512. Further division into a control hierarchy that includes control division groupings above and below the illustratedcontrol areas402 allows thepower aggregation system100 to scale topower grids114 of different magnitudes and/or to varying numbers ofelectric resources112 connected with apower grid114.
• FIG. 6 shows anexemplary layout600 of an exemplarypower aggregation system100 that uses multiple centralized flow control centers102 and102′ and adirectory server602 for determining a flow control center. Eachflow control center102 and102′ has its own respective end users406 and406′.Control areas402 to be administered by each specific instance of aflow control center102 can be assigned dynamically. For example, a firstflow control center102 may administercontrol area A502 andcontrol area B504, while a secondflow control center102′ administerscontrol area n506. Likewise, corresponding control area operators (508,510, and512) are served by the sameflow control center102 that serves their respective different control areas.
• In various embodiments, an electric resource may determine which flowcontrol center102/102′ administers itscontrol area502/504/506 by communicating with adirectory server602. The address of thedirectory server602 may be known toelectric resource112 or its associatedIPF module134 or chargingcomponent214. Upon plugging in, theelectric resource112 may communicate with thedirectory server602, providing thedirectory server112 with a resource identifier and/or a location identifier. Based on this information, thedirectory server602 may respond, identifying whichflow control center102/102′ to use.
• In another embodiment,directory server602 may be integrated with aflow control server106 of aflow control center102/102′. In such an embodiment, theelectric resource112 may contact theserver106. In response, theserver106 may either interact with theelectric resource112 itself or forward the connection to anotherflow control center102/102′ responsible for the location identifier provided by theelectric resource112.
• In some embodiments, whether integrated with aflow control server106 or not,directory server602 may include a publicly accessible database for mapping locations to flow control centers102/102′.
• Exemplary Flow Control Server
• FIG. 7 shows anexemplary server106 of theflow control center102. The illustrated implementation inFIG. 7 is only one example configuration, for descriptive purposes. Many other arrangements of the illustrated components or even different components constituting anexemplary server106 of theflow control center102 are possible within the scope of the subject matter. Such anexemplary server106 and flowcontrol center102 can be executed in hardware, software, or combinations of hardware, software, firmware, etc.
• The exemplaryflow control server106 includes aconnection manager702 to communicate withelectric resources112, aprediction engine704 that may include alearning engine706 and astatistics engine708, aconstraint optimizer710, and agrid interaction manager712 to receive grid control signals714. Grid control signals714 are sometimes referred to as generation control signals, such as automated generation control (AGC) signals. Theflow control server106 may further include a database/information warehouse716, a web server718 to present a user interface toelectric resource owners408,grid operators404, and electricalconnection location owners410; acontract manager720 to negotiate contract terms withenergy markets412, and aninformation acquisition engine414 to track weather, relevant news events, etc., and download information from public andprivate databases722 for predicting behavior of large groups of theelectric resources112, monitoring energy prices, negotiating contracts, etc.
• Operation of an Exemplary Flow Control Server
• Theconnection manager702 maintains a communications channel with eachelectric resource112 that is connected to thepower aggregation system100. That is, theconnection manager702 allows eachelectric resource112 to log on and communicate, e.g., using Internet Protocol (IP) if the network is theInternet104. In other words, theelectric resources112 call home. That is, in one implementation they may initiate the connection with theserver106. This facet enables theexemplary IPF modules134 to work around problems with firewalls, IP addressing, reliability, etc.
• For example, when anelectric resource112, such as anelectric vehicle200 plugs in athome124, theIPF module134 can connect to the home's router via the powerline connection. The router will assign thevehicle200 an address (DHCP), and thevehicle200 can connect to the server106 (no holes in the firewall needed from this direction).
• If the connection is terminated for any reason (including the server instance dies), then theIPF module134 knows to call home again and connect to the next available server resource.
• Also, when a connection is terminated, the connection manager may notify other components offlow control server106 to adjust an available resources level tracked by theflow control server106. Further, if the connection remains terminated for a pre-determined length of time, theconnection manager702 or another component forflow control server106 may notify an owner/user of theelectric resource112 via, for example, an email, phone call, or text message to alert him/her of the disconnect.
• Thegrid interaction manager712 receives and interprets signals from the interface of theautomated grid controller118 of agrid operator404. In one implementation, thegrid interaction manager712 also generates signals to send toautomated grid controllers118. The scope of the signals to be sent depends on agreements or contracts betweengrid operators404 and the exemplarypower aggregation system100. In one scenario thegrid interaction manager712 sends information about the availability of aggregateelectric resources112 to receive power from thegrid114 or supply power to thegrid114. In another variation, a contract may allow thegrid interaction manager712 to send control signals to theautomated grid controller118—to control thegrid114, subject to the built-in constraints of theautomated grid controller118 and subject to the scope of control allowed by the contract.
• The database716 can store all of the data relevant to thepower aggregation system100 including electric resource logs, e.g., forelectric vehicles200, electrical connection information, per-vehicle energy metering data, historical usage patterns for future prediction, resource owner preferences, account information, etc.
• The web server718 provides a user interface to the system stakeholders, as described above. Such a user interface serves primarily as a mechanism for conveying information to the users, but in some cases, the user interface serves to acquire data, such as preferences, from the users. In one implementation, the web server718 can also initiate contact with participatingelectric resource owners408 to advertise offers for exchanging electrical power.
• The bidding/contract manager720 interacts with thegrid operators404 and their associatedenergy markets412 to determine system availability, pricing, service levels, etc.
• Theinformation acquisition engine414 communicates with public andprivate databases722, as mentioned above, to gather data that is relevant to the operation of thepower aggregation system100.
• Theprediction engine704 may use data from the data warehouse716 to make predictions about electric resource behavior, such as whenelectric resources112 will connect and disconnect, location-specific electric resource availability, electrical system load, real-time energy prices, etc. The predictions enable thepower aggregation system100 to utilize more fully theelectric resources112 connected to thepower grid114. Thelearning engine706 may track, record, and process actual electric resource behavior, e.g., by learning behavior of a sample or cross-section of a large population ofelectric resources112. Thestatistics engine708 may apply various probabilistic techniques to the resource behavior to note trends and make predictions.
• In one implementation, theprediction engine704 performs predictions via collaborative filtering. Theprediction engine704 can also perform per-user predictions of one or more parameters, including, for example, connect-time, connect duration, state-of-charge at connect time, and connection location. In order to perform per-user prediction, theprediction engine704 may draw upon information, such as historical data, connect time (day of week, week of month, month of year, holidays, etc.), state-of-charge at connect, connection location, etc. In one implementation, a time series prediction can be computed via a recurrent neural network, a dynamic Bayesian network, or other directed graphical model.
• In one scenario, for one user disconnected from thegrid114, theprediction engine704 can predict the time and/or duration of the next connection, the state-of-charge at connection time, the location of the connection (and may assign it a probability/likelihood). Once theresource112 has connected, the time-of-connection, state-of-charge at-connection, and connection location become further inputs to refinements of the predictions of the connection duration. These predictions help to guide predictions of total system availability as well as to determine a more accurate cost function for resource allocation.
• Building a parameterized prediction model for each unique user is not always scalable in time or space. Therefore, in one implementation, rather than use one model for each user in thesystem100, theprediction engine704 builds a reduced set of models where each model in the reduced set is used to predict the behavior of many users. To decide how to group similar users for model creation and assignment, thesystem100 can identify features of each user, such as number of unique connections/disconnections per day, typical connection time(s), average connection duration, average state-of-charge at connection time, etc., and can create clusters of users in either a full feature space or in some reduced feature space that is computed via a dimensionality reduction algorithm such as Principal Components Analysis, Random Projection, etc. Once theprediction engine704 has assigned users to a cluster, the collective data from all of the users in that cluster is used to create a predictive model that will be used for the predictions of each user in the cluster. In one implementation, the cluster assignment procedure is varied to optimize thesystem100 for speed (less clusters), for accuracy (more clusters), or some combination of the two.
• Over time, individual users may change their behaviors and may be reassigned to new clusters that fit their behavior better.
• Theconstraint optimizer710 combines information from theprediction engine704, the data warehouse716, and thecontract manager720 to generate resource control signals that will satisfy the system constraints. For example, theconstraint optimizer710 can signal anelectric vehicle200 to charge itsbattery bank202 at a certain charging rate and later to discharge thebattery bank202 for uploading power to thepower grid114 at a certain upload rate: the power transfer rates and the timing schedules of the power transfers optimized to fit the tracked individual connect and disconnect behavior of the particularelectric vehicle200 and also optimized to fit a daily power supply and demand “breathing cycle” of thepower grid114.
• In one implementation, theconstraint optimizer710 plays a key role in converting generation control signals714 into vehicle control signals, mediated by theconnection manager702. Mapping generation control signals714 from agrid operator404 into control signals that are sent to each uniqueelectrical resource112 in thesystem100 is an example of a specific constraint optimization problem.
• Eachresource112 has associated constraints, either hard or soft. Examples of resource constraints may include: price sensitivity of the owner, vehicle state-of-charge (e.g., if thevehicle200 is fully charged, it cannot participate in loading the grid114), predicted amount of time until theresource112 disconnects from thesystem100, owner sensitivity to revenue versus state-of-charge, electrical limits of theresource114, manual charging overrides byresource owners408, etc. The constraints on aparticular resource112 can be used to assign a cost for activating each of the resource's particular actions. For example, a resource whosestorage system202 has little energy stored in it will have a low cost associated with the charging operation, but a very high cost for the generation operation. A fully chargedresource112 that is predicted to be available for ten hours will have a lower cost generation operation than a fully chargedresource112 that is predicted to be disconnected within the next 15 minutes, representing the negative consequence of delivering a less-than-full resource to its owner.
• The following is one example scenario of converting onegenerating signal714 that comprises a system operating level (e.g. −10 megawatts to +10 megawatts, where + represents load, − represents generation) to a vehicle control signal. It is worth noting that because thesystem100 can meter the actual power flows in eachresource112, the actual system operating level is known at all times.
• In this example, assume the initial system operating level is 0 megawatts, no resources are active (taking or delivering power from the grid), and the negotiated aggregation service contract level for the next hour is +/−5 megawatts.
• In this implementation, the exemplarypower aggregation system100 maintains three lists ofavailable resources112. The first list containsresources112 that can be activated for charging (load) in priority order. There is a second list of theresources112 ordered by priority for discharging (generation). Each of theresources112 in these lists (e.g., allresources112 can have a position in both lists) have an associated cost. The priority order of the lists is directly related to the cost (i.e., the lists are sorted from lowest cost to highest cost). Assigning cost values to eachresource112 is important because it enables the comparison of two operations that achieve similar results with respect to system operation. For example, adding one unit of charging (load, taking power from the grid) to the system is equivalent to removing one unit of generation. To perform any operation that increases or decreases the system output, there may be multiple action choices and in one implementation thesystem100 selects the lowest cost operation. The third list ofresources112 contains resources with hard constraints. For example, resources whose owner's408 have overridden thesystem100 to force charging will be placed on the third list of static resources.
• At time “1,” the grid-operator-requested operating level changes to +2 megawatts. The system activates charging the first ‘n’ resources from the list, where ‘n’ is the number of resources whose additive load is predicted to equal 2 megawatts. After the resources are activated, the results of the activations are monitored to determine the actual result of the action. If more than 2 megawatts of load is active, the system will disable charging in reverse priority order to maintain system operation within the error tolerance specified by the contract.
• From time “1” until time “2,” the requested operating level remains constant at 2 megawatts. However, the behavior of some of the electrical resources may not be static. For example, somevehicles200 that are part of the 2 megawatts system operation may become full (state-of-charge=100%) or may disconnect from thesystem100.Other vehicles200 may connect to thesystem100 and demand immediate charging. All of these actions will cause a change in the operating level of thepower aggregation system100. Therefore, thesystem100 continuously monitors the system operating level and activates or deactivatesresources112 to maintain the operating level within the error tolerance specified by the contract.
• At time “2,” the grid-operator-requested operating level decreases to −1 megawatts. The system consults the lists of available resources and chooses the lowest cost set of resources to achieve a system operating level of −1 megawatts. Specifically, the system moves sequentially through the priority lists, comparing the cost of enabling generation versus disabling charging, and activating the lowest cost resource at each time step. Once the operating level reaches −1 megawatts, thesystem100 continues to monitor the actual operating level, looking for deviations that would require the activation of anadditional resource112 to maintain the operating level within the error tolerance specified by the contract.
• In one implementation, an exemplary costing mechanism is fed information on the real-time grid generation mix to determine the marginal consequences of charging or generation (vehicle200 to grid114) on a “carbon footprint,” the impact on fossil fuel resources and the environment in general. Theexemplary system100 also enables optimizing for any cost metric, or a weighted combination of several. Thesystem100 can optimize figures of merit that may include, for example, a combination of maximizing economic value and minimizing environmental impact, etc.
• In one implementation, thesystem100 also uses cost as a temporal variable. For example, if thesystem100 schedules a discharged pack to charge during an upcoming time window, thesystem100 can predict its look-ahead cost profile as it charges, allowing thesystem100 to further optimize, adaptively. That is, in some circumstances thesystem100 knows that it will have a high-capacity generation resource by a certain future time.
• Multiple components of theflow control server106 constitute a scheduling system that has multiple functions and components:
• • data collection (gathers real-time data and stores historical data);
  • projections via theprediction engine704, which inputs real-time data, historical data, etc.; and outputs resource availability forecasts;
  • optimizations built on resource availability forecasts, constraints, such as command signals fromgrid operators404, user preferences, weather conditions, etc. The optimizations can take the form of resource control plans that optimize a desired metric.
• The scheduling function can enable a number of useful energy services, including:
• • ancillary services, such as rapid response services and fast regulation;
  • energy to compensate for sudden, foreseeable, or unexpected grid imbalances;
  • response to routine and unstable demands;
  • firming of renewable energy sources (e.g. complementing wind-generated power).
• Exemplary Remote IPF Module
• FIG. 8A shows theremote IPF module134 ofFIGS. 1 and 2 in greater detail. The illustratedremote IPF module134 is only one example configuration, for descriptive purposes. Many other arrangements of the illustrated components or even different components constituting an exemplaryremote IPF module134 are possible within the scope of the subject matter. Such an exemplaryremote IPF module134 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 ofremote IPF module134 may be added to hardware of anelectric resource112 such as an electric vehicle that, when combined with the executable instructions, provides equivalent functionality toremote IPF module134. References toremote IPF module134 as used herein include such executable instructions.
• The illustrated example of aremote IPF module134 is represented by an implementation suited for anelectric vehicle200. Thus, somevehicle systems800 are included as part of the exemplaryremote IPF module134 for the sake of description. However, in other implementations, theremote IPF module134 may exclude some or all of thevehicles systems800 from being counted as components of theremote IPF module134.
• The depictedvehicle systems800 include a vehicle computer anddata interface802, an energy storage system, such as abattery bank202, and an inverter/charger804. Besidesvehicle systems800, theremote IPF module134 also includes a communicativepower flow controller806. The communicativepower flow controller806 in turn includes some components that interface with AC power from thegrid114, such as a powerline communicator, for example an Ethernet-over-powerline bridge120, and a current or current/voltage (power)sensor808, such as a current sensing transformer.
• The communicativepower flow controller806 also includes Ethernet and information processing components, such as aprocessor810 or microcontroller and an associated Ethernet media access control (MAC)address812; volatilerandom access memory814,nonvolatile memory816 or data storage, an interface such as an RS-232interface818 or aCANbus interface820; an Ethernetphysical layer interface822, 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 Ethernetphysical layer interface822 provides electrical, mechanical, and procedural interface to the transmission medium—i.e., in one implementation, using the Ethernet-over-powerline bridge120. In a variation, wireless or other communication channels with theInternet104 are used in place of the Ethernet-over-powerline bridge120.
• The communicativepower flow controller806 also includes a bidirectionalpower flow meter824 that tracks power transfer to and from eachelectric resource112, in this case thebattery bank202 of anelectric vehicle200.
• The communicativepower flow controller806 operates either within, or connected to anelectric vehicle200 or otherelectric resource112 to enable the aggregation ofelectric resources112 introduced above (e.g., via a wired or wireless communication interface). These above-listed components may vary among different implementations of the communicativepower flow controller806, but implementations typically include:
• • an intra-vehicle communications mechanism that enables communication with other vehicle components;
  • a mechanism to communicate with theflow control center102;
  • a processing element;
  • a data storage element;
  • a power meter; and
  • optionally, a user interface.
• Implementations of the communicativepower flow controller806 can enable functionality including:
• • executing pre-programmed or learned behaviors when theelectric resource112 is offline (not connected toInternet104, or service is unavailable);
  • 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);
  • allowing the user to override current system behavior; and
  • metering power-flow information and caching meter data during offline operation for later transaction.
• Thus, the communicativepower flow controller806 includes acentral processor810,interfaces818 and820 for communication within theelectric vehicle200, a powerline communicator, such as an Ethernet-over-powerline bridge120 for communication external to theelectric vehicle200, and apower flow meter824 for measuring energy flow to and from theelectric vehicle200 via aconnected AC powerline208.
• Operation of the Exemplary Remote IPF Module
• Continuing withelectric vehicles200 as representative ofelectric resources112, during periods when such anelectric vehicle200 is parked and connected to thegrid114, theremote IPF module134 initiates a connection to theflow control server106, registers itself, and waits for signals from theflow control server106 that direct theremote IPF module134 to adjust the flow of power into or out of theelectric vehicle200. These signals are communicated to thevehicle computer802 via the data interface, which may be any suitable interface including the RS-232interface818 or theCANbus interface820. Thevehicle computer802, following the signals received from theflow control server106, controls the inverter/charger804 to charge the vehicle'sbattery bank202 or to discharge thebattery bank202 in upload to thegrid114.
• Periodically, theremote IPF module134 transmits information regarding energy flows to theflow control server106. If, when theelectric vehicle200 is connected to thegrid114, there is no communications path to the flow control server106 (i.e., the location is not equipped properly, or there is a network failure), theelectric vehicle200 can follow a preprogrammed or learned behavior of off-line operation, e.g., stored as a set of instructions in thenonvolatile memory816. For example, the instructions may enable a standard charging mode (i.e., charging without charge control management), charging when time-of-use rates are low (in which caseremote IPF module134 may store a listing of such times), and/or charging based on preferences set up by a user of the vehicle. Also, energy transactions can also be cached innonvolatile memory816 for later transmission to theflow control server106.
• During periods when theelectric vehicle200 is in operation as transportation, theremote IPF module134 listens passively, logging select vehicle operation data for later analysis and consumption. Theremote IPF module134 can transmit this data to theflow control server106 when a communications channel becomes available.
• Exemplary Power Flow Meter
• 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 exemplarypower flow meter824 measures power for a givenelectric resource112 across a bi-directional flow—e.g., power fromgrid114 toelectric vehicle200 or fromelectric vehicle200 to thegrid114. In one implementation, theremote IPF module134 can locally cache readings from thepower flow meter824 to ensure accurate transactions with the centralflow control server106, even if the connection to the server is down temporarily, or if the server itself is unavailable.
• Mobile Resource Locator
• The exemplarypower aggregation system100 also includes various techniques for determining the electrical network location of a mobileelectric resource112, such as a plug-inelectric vehicle200.Electric vehicles200 can connect to thegrid114 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:
• • querying a unique identifier for the location (via wired, wireless, etc.), which can be:
    • the unique ID of the network hardware at the charging site;
    • the unique ID of the locally installed smart meter, by communicating with the meter;
    • a unique ID installed specifically for this purpose at a site; and
  • 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'sresidence124, not a neighbor's residence).
Exemplary Transceiver and Charging Component
• FIG. 8B shows thetransceiver212 and chargingcomponent214 ofFIG. 2B in greater detail. The illustratedtransceiver212 and chargingcomponent214 is only one example configuration, for descriptive purposes. Many other arrangements of the illustrated components or even different components constituting thetransceiver212 and chargingcomponent214 are possible within the scope of the subject matter. Such atransceiver212 and chargingcomponent214 have some hardware components and some components that can be executed in hardware, software, or combinations of hardware, software, firmware, etc.
• The illustrated example of thetransceiver212 and chargingcomponent214 is represented by an implementation suited for anelectric vehicle200. Thus, somevehicle systems800 are illustrated to provide context to thetransceiver212 and chargingcomponent214 components.
• The depictedvehicle systems800 include a vehicle computer anddata interface802, an energy storage system, such as abattery bank202, and an inverter/charger804. In some embodiments,vehicle systems800 may include a data port, such as an OBD-II port, that is capable of physically coupling with thetransceiver212. Thetransceiver212 may then communicate with the vehicle computer anddata interface802 through the data port, receiving information fromelectric resource112 comprised byvehicle systems800 and, in some embodiments, providing commands to the vehicle computer anddata interface802. In one implementation, the vehicle computer anddata interface802 may be capable of charge control management. In such an embodiment, the vehicle computer anddata interface802 may perform some or all of thecharging component214 operations discussed below. In other embodiments, executable instructions configured to perform some or all of the operations of the vehicle computer anddata interface802 may be added to hardware of anelectric resource112 such as an electric vehicle that, when combined with the executable instructions, provides equivalent functionality to the vehicle computer anddata interface802. References to the vehicle computer anddata interface802 as used herein include such executable instructions.
• In various embodiments, thetransceiver212 may have a physical form that is capable of coupling to a data port ofvehicle systems800. Such atransceiver212 may also include a plurality of interfaces, such as an RS-232interface818 and/or aCANBus interface820. In various embodiments, the RS-232interface818 orCANBus interface820 may enable thetransceiver212 to communicate with the vehicle computer anddata interface802 through the data port. Also, the transceiver may be or comprise an additional interface (not shown) capable of engaging in wireless communication with adata interface820 of thecharging component214. The wireless communication may be of any form known in the art, such as radio frequency (RF) communication (e.g., Zigbee, and/or Bluetooth™ communication). In other embodiments, the transceiver may comprise a separate conductor or may be configured to utilize apowerline208 to communicate with chargingcomponent214. In yet other embodiments, not shown,transceiver212 may simply be a radio frequency identification (RFID) tag capable of storing minimal information about theelectric resource112, such as a resource identifier, and of being read by a corresponding RFID reader of chargingcomponent214. In such other embodiments, the RFID tag might not couple with a data port or communicate with the vehicle computer anddata interface802.
• As shown, thecharging component214 may be an intelligent plug device that is physically connected to a charging medium, such as a powerline208 (the charging medium coupling thecharging component214 to the electric resource112) and an outlet of a power grid (such as thewall outlet204 shown inFIG. 2B). In otherembodiments charging component214 may be a charging station or some other external control. In some embodiments, thecharging component214 may be portable.
• In various embodiments, thecharging component214 may include components that interface with AC power from thegrid114, such as a powerline communicator, for example an Ethernet-over-powerline bridge120, and a current or current/voltage (power)sensor808, such as a current sensing transformer.
• In other embodiments, thecharging component214 may include a further Ethernet plug or wireless interface in place ofbridge120. In such an embodiment, data-over-powerline communication is not necessary, eliminating the need for abridge120. The Ethernet plug or wireless interface may communicate with a local access point, and through that access point to flowcontrol server106.
• Thecharging component214 may also include Ethernet and information processing components, such as aprocessor810 or microcontroller and an associated Ethernet media access control (MAC)address812; volatilerandom access memory814,nonvolatile memory816 or data storage, a data interface826 for communicating with thetransceiver212, and an Ethernetphysical layer interface822, 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 Ethernetphysical layer interface822 provides electrical, mechanical, and procedural interface to the transmission medium—i.e., in one implementation, using the Ethernet-over-powerline bridge120. In a variation, wireless or other communication channels with theInternet104 are used in place of the Ethernet-over-powerline bridge120.
• Thecharging component214 may also include a bi-directionalpower flow meter824 that tracks power transfer to and from eachelectric resource112, in this case thebattery bank202 of anelectric vehicle200.
• Further, in some embodiments, thecharging component214 may comprise an RFID reader to read the electric resource information fromtransceiver212 whentransceiver212 is an RFID tag.
• Also, in various embodiments, thecharging component214 may include a credit card reader to enable a user to identify theelectric resource112 by providing credit card information. In such an embodiment, atransceiver212 may not be necessary.
• Additionally, in one embodiment, thecharging component214 may include a user interface, such as one of the user interfaces described in greater detail below.
• Implementations of thecharging component214 can enable functionality including:
• • executing pre-programmed or learned behaviors when theelectric resource112 is offline (not connected toInternet104, or service is unavailable);
  • 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);
  • allowing the user to override current system behavior; and
  • metering power-flow information and caching meter data during offline operation for later transaction.
• Operation of the Exemplary Transceiver and Charging Component
• In various embodiments, a transceiver such as thetransceiver212 shown inFIG. 8B may obtain information about an electric resource through, for example, the data port described above. In some embodiments, thetransceiver212 may obtain the information when theelectric resource212 is plugged in, started, and/or operated. Thetransceiver212 may then periodically obtain the information at various or pre-determined points of time thereafter. In some embodiments, the information may include at least one of an electric resource identifier, a state of charge of the electric resource, and/or a time since a last charge.
• Upon obtaining the information or at a later time, thetransceiver212 may provide the information to thecharging component214 through, for example, the communicative coupling described above. In some embodiments, where thetransceiver212 may provide information to any of a number of geographically dispersed chargingcomponents214,transceiver212 may provide the information to thecharging component214 to which theelectric resource112 is coupled or to thecharging component214 that has the strongest communication signal. In other embodiments, thetransceiver212 may be specifically coupled to asingle charging component214 and may only provide information to thatspecific component214. In any embodiments, thetransceiver212 and chargingcomponent214 may utilize a form of encryption, such as key-based encryption, to communicate.
• In some embodiments, where theelectric resource112 is capable of charge control management, the transceiver may receive one or more charge control commands from thecharging component214 and may provide the commands to the vehicle computer anddata interface802 to enable the electric resource to perform charge control management, such as starting or stopping a flow of power between theelectric resource112 and thegrid114.
• In various embodiments, thecharging component214 may receive information about anelectric resource112 to which thecharging component214 is coupled via a charging medium. In some embodiments, the information may be received by thetransceiver212, as discussed above. In other embodiment, the information may be obtained in any number of other ways. For example, the information may be obtained from a user directly entering the information through, for instance, a user interface, from a credit card reader if a user swipes a credit card through the reader, or from an RFID reader if theelectric resource112 has an RFID tag. If a credit card reader is used, the information obtained from the user may be sent to aflow control server106, or some other server, to obtain information about theelectric resource112 that is linked with the credit card information by, for example, a common owner/user.
• Upon receiving information about anelectric resource112, thecharging component214 may, for example, provide the information to aflow control server106 and receive, in response, one or more commands to cause thecharging component214 to effectuate charge control management. In some embodiments, in addition to providing the received information, chargingcomponent214 may provide other information, such as an identification of who owns the meter account, what tariff the account is on, ifresource112 togrid114 power flows are supported, a power rating of the charging connection, type description of the electric resource112 (such as a make/model), and/or a description of the energy storage system202 (e.g., battery size, power rating, etc.). In other embodiments, chargingcomponent214 may possess instructions enabling it to effectuate charge control management itself, without communicating with aflow control server106. In various embodiments, thecharging component214 may effectuate charge control management by starting or stopping a flow of power between theelectric resource112 andgrid114 or by providing the commands toelectric resource112 throughtransceiver212. Thecharging component214 may provide the commands if, for example, theelectric resource112 is capable of performing charge control management itself. In some embodiments, the information provided bytransceiver212 may include an indication of whether theelectric resource112 is capable of charge control management.
• In various embodiments, when state of charge information about anelectric resource112 is unavailable, thecharging component214 may estimate the state of charge. For example, thecharging component214 may determine that theelectric resource112 is at or near full charge when a current flow of power to theelectric resource112 begins to slow or taper off. In other embodiments, thecharging component214 may estimate the state of charge by tracking how long it has been since theelectric resource112 was last charged. In yet other embodiments, other estimating techniques may be used.
• If, when theelectric resource112 is connected to thegrid114, there is no communications path to the flow control server106 (i.e., the location is not equipped properly, or there is a network failure), thecharging component214 can follow a preprogrammed or learned behavior of off-line operation, e.g., stored as a set of instructions in thenonvolatile memory816. For example, the instructions may enable a standard charging mode (i.e., charging without charge control management), charging when time-of-use rates are low (in which case thecharging component214 may store a listing of such times), and/or charging based on preferences set up by a user of the vehicle. Also, energy transactions can also be cached innonvolatile memory816 for later transmission to theflow control server106.
• In some embodiments,power flow meter824 may perform as described above with regard toFIG. 2A, and chargingcomponent214 may determine a charging location in the same manner described above for theremote IPF module134.
Exemplary Transaction Methods
• The exemplarypower aggregation system100 supports the following functions and interactions:
• Setup. Thepower aggregation system100 creates contracts outside the system and/or bids into open markets to procure contracts for power services via the web server718 andcontract manager720. Thesystem100 then resolves these requests into specific power requirements upon dispatch from thegrid operator404, and communicates these requirements tovehicle owners408 by one of several communication techniques.
• Delivery. Thegrid interaction manager712 accepts real-time grid control signals714 fromgrid operators404 through a power-delivery device, and responds to thesesignals714 by delivering power services from connectedelectric vehicles200 to thegrid114.
• Reporting. After a power delivery event is complete, a transaction manager can report power services transactions stored in the database716. A billing manager resolves these requests into specific credit or debit billing transactions. These transactions may be communicated to a grid operator's or utility's billing system for account reconciliation. The transactions may also be used to make payments directly toresource owners408.
• Matching Load to Generation. It is possible to match energy generation and load by either increasing/decreasing generation to match the load, or by increasing/decreasing the load to match the generation.Electric resources112, such as electric vehicles, may present a large, flexible load to thegrid114 when they are charging. The load may be flexible because there may be little penalty for interrupting the charging of aresource112, the charging interruption can be executed almost instantaneously, and because theresources112 are typically plugged in for much more time than it takes to charge them. To utilize the possibility of a flexible load,flow control servers106 may control the charging behavior of a plurality ofelectric resources112. By increasing the number ofelectric resources112 that are charging, theflow control servers106 can increase the amount of load on the system, and by decreasing the number ofelectric resources112 that are charging, theflow control servers106 can decrease the amount of load on the system.
• Up or Down Regulation on Load-Only Resources. In various embodiments,power aggregation system100 may aggregate the electric power capacity of one or more distributed, electric load and storage resources, such as electric vehicles, into an amount sufficient to supply ancillary services, such as system regulation or spinning reserves, to apower grid114 operator. Such a service can be supplied based uponelectric resources112 that are capable of bi-directional power flows, or based even solely upon load-only electric resources112 (i.e., resources that are only capable of consuming and/or storing power, not providing it).
• In various embodiments, aflow control center102 may fulfill a capacity call from a grid operator based on a current load set-point of one or moreelectric resources112 and on upper and lower rails of the one or more electric resources. The upper rail may be a maximum amount of charge the one or moreelectric resources112 can consume. This amount may be the maximum capacity of theelectric resources112 or some lower value based on cost, environmental, and/or user-preference considerations. The lower rail—for load-only resources—may be a minimum amount that the electric resources may consume. This minimum amount may be a minimum capacity—such as consuming no power at all—or some higher value based on cost, environmental, and/or user-preference considerations.
• For example, if a group of tenresources112 are each consuming 5 kW (i.e., 50 kW total), and each has a maximum capacity of 10 kW and a minimum capacity of 0 kW, theflow control center102 may answer capacity calls for up-regulation by bidding to take up to 50 kW less or capacity calls for down-regulation by bidding to take up to 50 kW more. The amount bid (i.e., answer to capacity call) may be determined by a variety of cost, environmental, and/or user preference factors, in some embodiments.
• If theflow control center102 bids to take 30 kW less, then theflow control center102 may reduce the charge taken by each of the tenelectric resources112 by 3 kW, or may stop six of theelectric resources112 from charging altogether. In other embodiments, other combinations of reducing the power taken and/or stopping charging may be utilized based on cost, environmental, and/or user-preference factors.
• If theflow control center102 bids to take 30 kW more, then theflow control center102 may increase the charge taken by each of the tenelectric resources112 by 3 kW, or may increase the power consumed by six of theelectric resources112 to their maximum capacity. In other embodiments, other combinations of increasing the power taken by some or all of theelectric resources112 may be utilized based on cost, environmental, and/or user-preference factors.
• In yet another example, allelectric resources112 may be offered to the grid operator as regulation-down capacity, charged to the greatest degree possible by satisfying grid operator capacity calls, and then incrementally charged only to the minimum degree necessary using normally purchased electricity.
• Charge Control Management Based on Price Fluctuations. In some embodiments, utilities such asgrid114 may offer tariffs where the energy prices vary over time, such as time of use (TOU), critical peak pricing (CPP), and real time pricing (RTP).Flow control servers106 may learn of this information from the utilities during negotiations for buying or selling power (described above) or at a later time or times. Based on the information, theflow control servers106 may automatically control when theelectric resources112 recharge to ensure that theresources112 are charging when it is cheaper to do so. Besides the rate structure and prices obtained from the utility, theflow control servers106 may also take into account the type of theelectric resource112, its state of charge, as well as user needs/preferences (i.e., when the user will need to use theresource112 again, how tolerant the user is of theresource112 not being fully charged, etc.). This additional information can be provided by the user or estimated based on historical data associated withresource112 or withresources112 of other similar users.
• Green Charging. In various embodiments, thepower aggregation system100 may offer users ofelectric resources112 metrics of the amount of clean energy used and mechanisms for charging only with clean energy.
• Thepower aggregation system100 can meter the amount of net energy put into anelectric resource112, such as anelectric vehicle200, from thegrid114 and then offer the resource owner the option of “greening” that power, meaning using clean, renewable energy. In one embodiments, this could be accomplished by buying RECs (renewable energy credits) to match the amount of energy used.
• While there are services, such websites, where users can self report their energy usage, there is often no way to know how much electrical energy has been used with Plug-in Hybrid Electric Vehicles (PHEVs)200 and Electric Vehicles (EVs)200. This may be particularly hard withPHEVs200 because of the mixed energy source approach (e.g., fuel plus electricity). By metering exactly the power into theelectric resource112, including in scenarios where theresource112 may recharge at any number of different locations, potentially from different utility accounts, thepower aggregation system100 can give the user a guarantee that he or she is using only clean electricity. In some embodiments, this may be accomplished by associating a resource identifier with a clean charging setting. When the resource identifier is presented to theflow control server106, theserver106 may, for example only charge if clean energy is available. Or if energy may be obtained from different sources (e.g., coal, wind) associated with different prices,flow control server106 may elect to use the clean energy (subject perhaps to additional prices constraints provided by the user, etc.).
• In some embodiments, thepower aggregation system100 may enableelectric resources112 to charge only when they are being used to firm renewable resources such as wind generation. Also, in another implementation, thepower aggregation system100 may enableresources112 to charge only when the grid-mix is more environmentally friendly. In such an implementation, theflow control servers106 may create grid-mix predictions and use those predictions to charge theresources112 in a more environmentally aware manner.
• Efficiency Metrics. In various embodiments, the power aggregation system may provide users ofelectric resources112, such aselectric vehicles200, with various efficiency metrics. In some embodiments, one or more of the efficiency metrics may be used as a replacement for or supplement to the miles per gallon metric typically used for cars. Since that metric divides total miles driven by fuel used, it may be misleading for PHEVs, which run off both fuel and electricity. In various embodiments, metrics determined by thepower aggregation system100 might include an energy/distance metric (measured, for example, in Joules per mile), a cost/distance metric (measured, for example, in dollars spent of energy per mile), and/or a CO2-equivalent greenhouse gas emissions/distance metric.
• In some embodiments, efficiency metrics may be calculated by aremote IPF module134 or acharging component214, or calculated by aflow control server106 and provided to theremote IPF module134 or chargingcomponent214. To calculate the efficiency metrics, a number of other metrics may be obtained. For example, a distance driven may be obtained from an electric vehicle's odometer. Energy metrics may be obtained from apower flow meter824 and/or from avehicle200 gas gauge or fuel flow meter. Cost metrics may be obtained directly from a self reporting user, from electric bill data tracked by theremote IPF module134, chargingcomponent214, or flowcontrol server106, from credit card data, and/or from average user price information. CO2 metrics may be obtained from a self-reporting user, fromgrid114 mix data, from RECs, frompower flow meters824, and/or from CO2 use averages. Once the efficiency metrics are calculated, they may be displayed to a user in thevehicle200, on aremote IPF module134 or chargingcomponent214, via the website of aflow control center102, and/or via other data access means. In some embodiments, this may involve generating a graph or some other chart.
• In some embodiments, to achieve accurate measurements for the efficiency metrics, features may be added tovehicles200. For example,vehicles200 may include lifetime and trip counters for gallons of fuel used and lifetime and trip counters for kWh of electricity used, captured by power flow meter824 (accounting for regenerative braking, the fuel engine recharging batteries, etc.—thepower aggregation system100 may need to meter various battery inputs and outputs and do some accounting).
• In various embodiments, if acharging component214 is used, thecomponent214 orflow control server106 could back-calculate the amount of fuel used given a user's self-reported miles driven per year. From this, with gas and electricity cost and CO2 info for the user's area (average), thecharging component214 orflow control server106 could calculate efficiency metrics. In other embodiments, rather than requiring self-reporting, thecharging component214 orflow control server106 could utilize a user's electric bill, local rate structure, grid mix, and/or greening preferences.
• Low Carbon Fuel Standard (LCFS) Tracking. In some embodiments, thepower aggregation system100 may utilize the CO2 efficiency metrics described above to determine whether low carbon fuel standards are being met. Various governmental entities may increasingly impose such standards on users andvehicle200 manufactures. By calculating CO2 efficiency metrics for individual users,system100 might also collectivize the metrics based on avehicle200 type, such as a make and/or model, and report the metrics to governmental entities, electric utilities, vehicle owners/drivers, and/or manufacturers.
Exemplary User Interfaces (UI)
• 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 thegrid114, 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 grid114 (either total or per hour), etc. Theinformation acquisition engine414 communicates with theelectric resource112 and with public and/orprivate data networks722 to acquire the data used in calculating this information.
• The types of information gathered from theelectric resource112 could include an electric resource identifier (resource ID) and state information like the state of charge of theelectric resource112. The resource ID could be used to obtain knowledge of the electric resource type and capabilities, preferences, etc. through lookup with theflow control server106.
• 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.
• User Charge Control UI Mechanisms. In various embodiments, by default,electric resources112 may receive charge control management viapower aggregation system100. 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 theremote IPF module134, thecharging component214, of the electric resource (for example, if electric resource is avehicle200, the user interface control may be integrated with dash controls of the vehicle200) or even via a web page offered byflow control server106. 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 byFIG. 23 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.
• 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.
• UI Mechanism for Management Preferences. In various embodiments, a user interface mechanism of theremote IPF module134, thecharging component214, of the electric resource (for example, if electric resource is avehicle200, the user interface control may be integrated with dash controls of the vehicle200) or even via a web page offered byflow control server106 may enable a user to enter and/or edit management preferences to affect charge control management of the user'selectric resource112. 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 theelectric resource112 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 theelectric resource112, 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, ifresource112 is avehicle200, the schedule would be for when thevehicle200 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.
• Simple User Interface.FIG. 23 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,UI2300 includes the categories “green”, “fast”, and “cheap” (with what is considered “green”, “fast”, and “cheap” varying from embodiment to embodiment). The categories shown inUI2300 are selected only for the sake of illustration and may instead includes these and/or any other categories applicable toelectric resource112 charging known in the art. As shown, theUI2300 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 aflow control server106.
Electric Resource Communication Protocol
• FIG. 9 illustrates an exemplary resource communication protocol. As shown, aremote IPF module134 or chargingcomponent214 may be in communication with aflow control server106 over theInternet104 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 theremote IPF module134 or chargingcomponent214 andflow control server106.
• In some embodiments, the protocol may include two channels, one for messages initiated by theremote IPF module134 or chargingcomponent214 and for replies to those messages from theflow control server106, and another channel for messages initiated by theflow control server106 and for replies to those messages from theremote IPF module134 or chargingcomponent214. 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).
• As shown, theremote IPF module134 or chargingcomponent214 may initiatecommunication902 with theflow control server106. In some embodiments,communication902 may be initiated when, for example, anelectric resource112 first plugs in/connects to thepower grid114. In other embodiments,communication902 may be initiated at another time or times. Theinitial message902 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.
• Upon receipt of the initial message by theflow control server106, a connection may be established between theremote IPF module134 or chargingcomponent214 andflow control server106. Upon establishing a connection, theremote IPF module134 or chargingcomponent214 may register withflow control server106 through asubsequent communication903.Communication903 may include a location identifier scheme, a latitude, a longitude, a max power value that theremote IPF module134 or chargingcomponent214 can draw, a max power value that theremote IPF module134 or chargingcomponent214 can provide, a current power value, and/or a current state of charge.
• After theinitial message902, the protocol may require or allowmessages904 from theflow control server106 to theremote IPF module134 or chargingcomponent214 or messages906 fromremote IPF module134 or chargingcomponent214 to theflow control server106. Themessages904 may include, for example, one or more of commands, messages, and/or updates.Such messages904 may be provided at any time after theinitial message902. In one embodiment,messages904 may include a command setting, a power level and/or a ping to determine whether theremote IPF module134 or chargingcomponent214 is still connected.
• The messages906 may include, for example, status updates to the information provided in theregistration message903. Such messages906 may be provided at any time after theinitial message902. In one embodiment, the messages906 may be provided on a pre-determined time interval basis. In various embodiments, messages906 may even be sent when theremote IPF module134 or chargingcomponent214 is connected, but not registered. Such messages906 may include data that is stored byflow control server106 for later processing. Also, in some embodiments,messages904 may be provided in response to amessage902 or906.
Exemplary Safety and Remote Smart-Islanding
• The exemplarypower aggregation system100 can include methods and components for implementing safety standards and safely actuating energy discharge operations. For example, the exemplarypower aggregation system100 may use in-vehicle line sensors as well as smart-islanding equipment installed at particular locations. Thus, thepower aggregation system100 enables safe vehicle-to-grid operations. Additionally, thepower aggregation system100 enables automatic coordination of resources for backup power scenarios.
• In one implementation, anelectric vehicle200 containing aremote IPF module134 or transceiver212 (with a local charging component214) stops vehicle-to-grid upload of power if theremote IPF module134 or chargingcomponent214 senses no line power originating from thegrid114. This halting of power upload prevents electrifying a cord that may be unplugged, or electrifying apowerline206 that is being repaired, etc. However, this does not preclude using theelectric vehicle200 to provide backup power if grid power is down because the safety measures described below may be used to ensure that an island condition is not created.
• Additional smart-islanding equipment installed at a charging location can communicate with theremote IPF module134 or chargingcomponent214 to coordinate activation of power upload to thegrid114 if grid power drops. One particular implementation of this technology is a vehicle-to-home backup power capability.
• Also, in a further implementation,electric vehicle200 may be a PHEV (i.e., hybrid vehicle) partially powered by fuel or some other non-electric energy source. In such an implementation, theelectric vehicle200 may be started, subject to safeguards, to provide additional energy to enhance the vehicle-to-home backup power capability.
• FIG. 10 shows exemplary safety measures in a vehicle-to-home scenario, in which anelectric resource112, and potentially aPHEV1008 comprising theelectric resource112, is used to provide power to a load or set of loads (as in a home). Abreaker box1000 is connected to the utilityelectric meter1002. When anelectric resource112/PHEV1008 is flowing power into the grid (or local loads), an islanding condition should be avoided for safety reasons. Theelectric resource112 should not energize a line that would conventionally be considered de-energized in a power outage by line workers.
• A locally installed smart grid disconnect (switch)1004 senses the utility line in order to detect a power outage condition and coordinates with theelectric resource112 to enable vehicle-to-home power transfer. In the case of a power outage, thesmart grid disconnect1004 disconnects thecircuit breakers1006 from theutility grid114 and communicates with theelectric resource112/PHEV1008 to begin power backup services. When the utility services return to operation, thesmart grid disconnect1004 communicates with theelectric resource112/PHEV1008 to disable the backup services and reconnect the breakers to theutility grid114.
• In various embodiments, theelectric resource112 may be part of aPHEV1008. As mentioned above,PHEV1008 may include not only the electric power source ofelectric resource112, but also at least one additional power source, such as a fuel-driven engine. To enhance the backup power provided, the fuel engine and/or other power source of thePHEV1008 may be started. In some embodiments, thePHEV1008 may only be manually started by a user in order to reduce the hazards posed by exhaust and/or other potentially dangerous conditions. In other embodiments,PHEV1008 may be started automatically. For example, aremote IPF module134 or chargingcomponent214 may receive an instruction from theswitch1004 to turn on thePHEV1008 to provide additional power. In such other embodiments, thePHEV1008 may possess additional safeguards, such as a carbon monoxide sensor, safety interlocks to make sure thatPHEV1008 is in park with the break on, and/or a location awareness to determine whether the current location is safe for runningPHEV1008. Also, automatic starting ofPHEV1008 may be conditioned based on user preferences (such as preferences entered through the exemplary user interfaces discussed above).PHEV1008 may then only run subject to compliance with the safeguards and/or preferences.
• FIG. 11 shows exemplary safety measures when multipleelectric resources112, and potentially PHEVs1008 comprising theelectric resources112, power a home. In this case, thesmart grid disconnect1004 coordinates with all connectedelectric resources112. Oneelectric resource112 is deemed the “master”1100 for purposes of generating areference signal1102 and the other resources are deemed “slaves”1104 and follow the reference of themaster1100. In a case in which themaster1100 disappears from the network, thesmart grid disconnect1004 assigns anotherslave1104 to be the reference/master1100.
• FIG. 12 shows thesmart grid disconnect1004 ofFIGS. 10 and 11, in greater detail. In one implementation, thesmart grid disconnect1004 includes aprocessor1202, acommunicator1204 coupled with connectedelectric resources112, avoltages sensor1206 capable of sensing both the internal and utility-side AC lines, abattery1208 for operation during power outage conditions, and abattery charger1210 for maintaining the charge level of thebattery1208. A controlled breaker orrelay1212 switches between grid power and electric resource-provided power when signaled by theprocessor1202.
Exemplary Methods
• FIG. 13 shows anexemplary method1300 of power aggregation. In the flow diagram, the operations are summarized in individual blocks. Theexemplary method1300 may be performed by hardware, software, or combinations of hardware, software, firmware, etc., for example, by components of the exemplarypower aggregation system100.
• Atblock1302, communication is established with each of multiple electric resources connected to a power grid. For example, a central flow control service can manage numerous intermittent connections with mobile electric vehicles, each of which may connect to the power grid at various locations. An in-vehicle remote agent orlocal charging component214 andtransceiver212 connect each vehicle to the Internet when the vehicle connects to the power grid.
• Atblock1304, the electric resources are individually signaled to provide power to or take power from the power grid.
• FIG. 14 is a flow diagram of an exemplary method of communicatively controlling an electric resource for power aggregation. In the flow diagram, the operations are summarized in individual blocks. Theexemplary method1400 may be performed by hardware, software, or combinations of hardware, software, firmware, etc., for example, by components of the exemplary intelligent power flow (IPF)module134 or by components of thecharging component214.
• Atblock1402, communication is established between an electric resource and a service for aggregating power.
• Atblock1404, information associated with the electric resource is communicated to the service.
• Atblock1406, a control signal based in part upon the information is received from the service.
• Atblock1408, the resource is controlled, e.g., to provide power to the power grid or to take power from the grid, i.e., for storage.
• Atblock1410, bidirectional power flow of the electric device is measured, and used as part of the information associated with the electric resource that is communicated to the service atblock1404.
• FIG. 15 is a flow diagram of an exemplary method of communication between a transceiver and charge component and charge control management by the charge component. In the flow diagram, the operations are summarized in individual blocks. Theexemplary method1500 may be performed by hardware, software, or combinations of hardware, software, firmware, etc., for example, by components of theexemplary transceiver212 and chargingcomponent214.
• Atblock1502, atransceiver212 may about information about anelectric resource112 to which the transceiver is coupled through a data port.
• Atblock1504, thetransceiver212 may provide the obtained electric resource information to acharging component214, thecharging component214 being communicatively coupled to thetransceiver212 and physically coupled to theelectric resource212 by a charging medium.
• Atblock1506, thecharging component214 may receive the electric resource information from thetransceiver212.
• Atblock1508, thecharging component214 may provide the electric resource information to aflow control server106.
• Atblock1510, thecharging component214 may receive, in response, one or more commands from theflow control server106 to cause thecharging component214 to effectuate charge control management.
• Atblock1512, thecharging component214 may effectuate charge control management by starting or stopping a flow of power between theelectric resource112 and apower grid114 or by providing the commands to theelectric resource112 through thetransceiver212.
• FIG. 16 is a flow diagram of an exemplary method of estimating a state of charge. In the flow diagram, the operations are summarized in individual blocks. Theexemplary method1600 may be performed by hardware, software, or combinations of hardware, software, firmware, etc., for example, by components of theexemplary charging component214.
• Atblock1602, thecharging component214,remote IPF module134, or flowcontrol server106 may determine that current state-of-charge information about anelectric resource112 is unavailable.
• Atblock1604, the current state-of-charge may be estimated by monitoring a current flow of power from thegrid114 to theresource112 or by tracking the time since the resource was last charged.
• FIG. 17 is a flow diagram of an exemplary method of controlling charging of load-only electric resources. In the flow diagram, the operations are summarized in individual blocks. Theexemplary method1700 may be performed by hardware, software, or combinations of hardware, software, firmware, etc., for example, by components of the exemplaryremote IPF module134 or chargingcomponent214.
• Atblock1702, aflow control server106 may receive a capacity call from agrid operator116 requesting an up or down regulation to take more of less power from thegrid114.
• Atblock1704, in response to the call, theflow control server106 may cause one or more of a plurality of load-onlyelectric vehicles200 to start or stop charging in order to meet the capacity call.
• FIG. 18 is a flow diagram of an exemplary method for a resource communication protocol. In the flow diagram, the operations are summarized in individual blocks. Theexemplary method1800 may be performed by hardware, software, or combinations of hardware, software, firmware, etc., for example, by components of the exemplarypower aggregation system100.
• Atblock1802, aremote IPF module134 or chargingcomponent214 may initiate communication with aflow control server106 through a message required by a resource communication protocol to include one or more of a resource identifier, a location identifier, and/or a state-of-charge of anelectric resource112.
• Atblock1804, at any point after communication is initiated, theflow control server106 may send one or more commands, messages, or updates to theremote IPF module134 or chargingcomponent214.
• Atblock1806, at any point after communication is initiated, theremote IPF module134 or chargingcomponent214 may send updated information to theflow control server106.
• FIG. 19 is a flow diagram of an exemplary method of offline behavior for an electric resource. In the flow diagram, the operations are summarized in individual blocks. Theexemplary method1900 may be performed by hardware, software, or combinations of hardware, software, firmware, etc., for example, by components of the exemplaryremote IPF module134 or chargingcomponent214.
• Atblock1902, aremote IPF module134 or chargingcomponent214 may determine that no communication path to aflow control server106 exists.
• Atblock1904, in response to the determination, theremote IPF module134 or chargingcomponent214 may follow a pre-programmed or learned behavior of offline operation.
• FIG. 20 is a flow diagram of an exemplary method of calculating an efficiency metric for an electric resource. In the flow diagram, the operations are summarized in individual blocks. Theexemplary method2000 may be performed by hardware, software, or combinations of hardware, software, firmware, etc., for example, by components of the exemplarypower aggregation system100.
• Atblock2002, aremote IPF module134, chargingcomponent214, or flowcontrol server106 may gather vehicle, energy, cost, and CO2 metrics.
• Atblock2004, one or more efficiency metrics may be calculated based on the gathered metrics.
• FIG. 21 is a flow diagram of an exemplary method of smart islanding. In the flow diagram, the operations are summarized in individual blocks. Theexemplary method2100 may be performed by hardware, software, or combinations of hardware, software, firmware, etc., for example, by components of the exemplarypower aggregation system100.
• Atblock2102, a power outage is sensed.
• Atblock2104, a local connectivity—a network isolated from the power grid is created.
• Atblock2106, local energy storage resources are signaled to power the local connectivity.
• FIG. 22 is a flow diagram of an exemplary method of extending a user interface for power aggregation. In the flow diagram, the operations are summarized in individual blocks. Theexemplary method2200 may be performed by hardware, software, or combinations of hardware, software, firmware, etc., for example, by components of the exemplarypower aggregation system100.
• Atblock2202, a user interface is associated with an electric resource. The user interface may displayed in, on, or near an electric resource, such as an electric vehicle that includes an energy storage system or a charging station, or the user interface may be displayed on a device associated with the owner of the electric resource, such as a cell phone or portable computer.
• Atblock2204, power aggregation preferences, charge control management preferences, and constraints are input via the user interface. In other words, a user may control a degree of participation of the electric resource in a power aggregation scenario via the user interface. Or, the user may control the characteristics of such participation.
CONCLUSION
• Although exemplary 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 exemplary forms of implementing the claimed methods, devices, systems, etc.

Claims (20)

1. A system, comprising:

a transceiver device, physically coupled to an electric resource, to provide information about the electric resource; and

a charging component, physically coupled to the electric resource via a charging medium and communicatively coupled to the transceiver device, to receive the information about the electric resource from the transceiver and, in response, effectuate charge control management of the electric resource.

2. The system ofclaim 1, wherein the transceiver device is a radio frequency identification (RFID) tag containing an electric resource identifier or a device that connects to a data port of the electric resource.

3. The system ofclaim 1, wherein the charging component is:

an intelligent plug device that is physically connected to the charging medium and an outlet of a power grid,

a charging station, or

another external control system.

4. The system ofclaim 1, wherein the information about the electric resource includes at least one of an electric resource identifier, a state of charge of the electric resource, and/or a time since a last charge.

5. The system ofclaim 1, wherein effectuating charge control management comprises starting, stopping, or level-setting, by the charging component, a flow of power between a power grid and the electric resource.

6. The system ofclaim 1, wherein the electric resource is a mobile electric vehicle that is connectable to a power grid.

7. The system ofclaim 1, wherein the transceiver device is communicatively coupled to the charging component via the charging medium, a separate conductor, or a wireless connection.

8. A method, comprising:

obtaining information about an electric resource via a data port of the electric resource; and

providing the information to a charging component that is coupled to the electric resource via a charging medium and to a power grid via an outlet of the power grid and is able effectuate charge control management based at least in part on the provided information.

9. The method ofclaim 8, wherein the charging component is one of a plurality of geographically dispersed charging components, and the providing includes providing the information to the one of the charging components that the electric resource is coupled to.

10. The method ofclaim 8, further comprising providing security for the information provided to the charging component, the charging component being specifically paired with the transceiver device.

11. The method ofclaim 8, further comprising:

receiving charging commands from the charging component or flow control server; and

providing the charging commands to the electric resource, the electric resource having charge control management capabilities.

12. The method ofclaim 8, wherein the electric resource is a mobile electric vehicle that is connectable to a power grid and the data port is an OBD-II connector of the electric vehicle.

13. The method ofclaim 8, wherein the providing comprises providing the information to the charging component via the charging medium, a separate conductor, or a wireless connection.

14. A charging component, comprising:

a computer readable medium having a plurality of programming instructions which, when executed, perform operations including

receiving information about an electric resource that is connectable to the charging component via a charging medium,

providing the information to a flow control server, and

in response, receiving one or more commands from the flow control server to cause the charging component to effectuate charge control management of the electric resource.

15. The charging component ofclaim 14, wherein the instructions, when executed, effectuate charge control management based at least in part on the received commands, and the effectuating includes starting, stopping, or level-setting a flow of power between a power grid and the electric resource.

16. The charging component ofclaim 14, wherein the charging component is portable and may be physically coupled to any of a plurality of power grid outlets and/or charging stations.

17. The charging component ofclaim 14, wherein the information is entered by a user associated with the electric resource.

18. The charging component ofclaim 14, wherein the information is entered by the user via swiping a credit card or other identifier of the user through a reader associated with the charging component.

19. The charging component ofclaim 14, wherein the instructions, when executed, estimate a state of charge of the electric resource based at least in part on a charging current flowing to the electric resource.

20. The charging component ofclaim 14, wherein the instructions, when executed, estimate a state of charge of the electric resource based at least in part on a duration of time since the electric resource was last coupled to the charging component via the charging medium.

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