UNITED STATES PATENT AND TRADEMARK OFFICE
`_____________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`_____________
`
`HONEYWELL INTERNATIONAL, INC.
`
`Petitioner
`
`v.
`
`ALLURE ENERGY, INC.
`
`Patent Owner
`_____________
`
`Case No. IPR2016-___
`Patent No. 8,509,954
`
`PETITIONER’S EXHIBIT NO. 1004
`
`

`
`(19) United States
`(12) Patent Application Publication (10) Pub. No.: US 2010/0250590 A1
`Galvin
`(43) Pub. Date:
`Sep. 30, 2010
`
`US 20100250590A1
`
`(54) SYSTEM AND METHOD FOR MANAGING
`ENERGY
`
`Publication Classi?cation
`
`(51) Int. Cl.
`G06F 17/30
`
`(2006.01)
`
`(76) Inventor:
`
`
`
`Brian R. Galvin, Seabeck, WA (Us)
`
`(52) US. Cl.
`
`707/770; 709/217; 700/295; 707/E17.044
`
`Correspondence Address:
`Brian R. Galvin
`PO. BOX 2360
`SILVERDALE, WA 98383-2360 (US)
`
`(21) App1.No.:
`
`12/383,993
`
`(22) Filed:
`
`Mar. 30, 2009
`
`ABSTRACT
`(57)
`A system for managing energy, comprising a digital exchange
`With a communications interface adapted to alloW connec
`tions from remote users over a data network, Wherein the
`digital exchange receives preferences from a plurality of
`exchange participants and these preferences are used at least
`in part to create response pro?les relevant to the participants,
`at least some of the response pro?les are aggregated into
`response packages With de?ned statistical properties, and at
`least some of the response packages are made available for
`use by participants in the digital exchange, is disclosed.
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`
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`

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`US 2010/0250590 A1
`
`Sep. 30, 2010
`
`SYSTEM AND METHOD FOR MANAGING
`ENERGY
`
`CROSS-REFERENCE TO RELATED
`APPLICATIONS
`
`[0001] None.
`
`BACKGROUND OF THE INVENTION
`
`[0002] 1. Field of the Invention
`[0003] The present invention is in the ?eld of electric power
`utilities, and in particular in the sub?eld of smart grid sys
`tems. Yet more particularly, the present invention pertains to
`demand management systems and systems for managing dis
`tributed energy resources.
`[0004] 2. Discussion of the State of the Art
`[0005] While a robust electric poWer grid is Widely recog
`niZed as a vital infrastructure component of a developed
`economy, technological progress in the ?eld of electricity
`grid systems has not kept up With the pace of other important
`technological ?elds such as telecommunications. Most of the
`electric grid infrastructure has been in place for decades, and
`the basic architecture conceived by Thomas Edison and
`enhanced by the likes of George Westinghouse and Samuel
`Insull still prevails. Additionally, the current regulatory
`scheme in the United States discourages large-scale invest
`ment in transmission and distribution infrastructure, With the
`unfortunate result that the grid is often running near capacity.
`[0006] A number of techniques have been devised to assist
`in maintaining grid stability during times of high stress,
`Which normally means peak usage hours but also includes
`periods during normal usage When part of the grid goes
`o?iine, thus reducing the effective capacity of the grid or a
`region of it. It is commonplace for “peaking generators”,
`often operated by independent poWer producers, to be placed
`online at peak periods to give the grid greater capacity; since
`periods of high demand tend to lead to high Wholesale poWer
`prices, the business model of peaking generator operators is
`premised on operating their generators only When the price
`that can be obtained is high. Large utilities, desiring to avoid
`the use of high-priced peaking generators When possible, also
`routinely participate in demand response programs. In these
`programs, arrangements are made by independent third par
`ties With large commercial, industrial, or institutional users of
`poWer to give control to the third parties over certain electric
`loads belonging to large users. These third parties make
`complementary arrangements With electric utilities to pro
`vide “negative load” during peak periods, on demand, by
`shedding some portion of the loads under their control When
`requested by the utility. Typically the cost to the utility of
`paying these aggregators of “negaWatts” (negative mega
`Watts, or negative load available on demand) is much less than
`the corresponding costs the utilities pay to peak generators for
`actual megaWatts. That is, the utilities pay for “dispatchable
`load reduction” instead of for “dispatchable peak genera
`tion”, and they do so at a loWer rate. This arrangement is
`attractive to the utilities not only because of the immediate
`price arbitrage opportunity it presents, but also because, by
`implementing demand reduction, the utilities are often able to
`defer expensive capital improvements Which might otherWise
`be necessary to increase the capacity of the grid.
`[0007] A problem With the current state of the art in demand
`reduction is that it is only practical, in the art, to incorporate
`very large users in demand reduction programs. Large com
`
`mercial and industrial users of electricity tend to use far more
`poWer on a per-user basis than small commercial and residen
`tial users, so they have both the motive (large savings) and the
`means (experienced facilities management) to take advantage
`of the ?nancial reWards offered by participation in demand
`management programs. Additionally, large users of electric
`ity already are accustomed to paying a price for poWer that
`depends on market conditions and varies throughout the day,
`and they often have already invested in advanced building
`automation systems to help reduce the cost of electricity by
`conserving.
`[0008] Unfortunately, a large portion (roughly 33%) of the
`electric poWer used during peak periods goes to small users,
`Who do not normally participate in demand management.
`These users often are unaWare of their energy usage habits,
`and they rarely pay for electricity at varying rates. Rather,
`they pay a price per unit of electricity used that is tightly
`regulated and ?xed. Partly this is due to the fact that the large
`majority of small businesses and homes do not have “smart
`meters”; the amount of poWer used by these consumers of
`electricity is measured only once per month and thus there is
`no Way to charge an interval price (typically pricing is set at
`intervals of l 5 minutes When interval pricing is in effect) that
`varies based on market conditions. Furthermore, the loads in
`the homes and businesses of small electricity users are invis
`ible to the utilities; it is generally not possible for utilities to
`“see”, much less to control, loads in homes and small busi
`nesses. Loads here refers to anything that uses electricity,
`including but not limited to lighting, heating ventilation and
`air conditioning (HVAC), hot Water, “White goods” (large
`appliances such as Washers, driers, refrigerators and the like),
`hot tubs, computers, and so forth.
`[0009] One approach in the art to improving the situation
`With small users is to install smart meters at homes small
`businesses. While the primary motivation for doing so is to
`enable interval -based usage measurement and the communi
`cation of interval-based prices to the users, it is also possible
`to provide the consumer With much more information on hoW
`she uses energy than Was possible Without a smart meter.
`Given this granular usage information, utilities and some
`third parties also hope to be able to send signals, either via
`pricing or “code red” messages (Which ask consumers to turn
`off unnecessary loads due to grid constraints), or both. In
`some cases, third parties seek to provide visibility and control
`to utilities so that, When consumers alloW it, the utilities can
`turn loads off during peak demand to manage the peak. A
`related method involves the use of “gateWay” devices to
`access a consumer’s (again, referring to residences, busi
`nesses, and institutions) home area netWorks (HAN) to com
`municate With or turn off local devices.
`[0010] It is a disadvantage of the techniques knoWn in the
`art that the consumers and small businesses are not, in gen
`eral, provided With any substantial ?nancial incentives to
`participate in demand reduction programs (other than merely
`by saving because they use less poWer). The “virtual poWer
`provider” generally sells “negaWatts” as previously described
`by aggregating demand response capability of many small
`users and selling demand response services to the utility. This
`method similarly discourages consumer participation,
`because the majority of the ?nancial reWards associated With
`the demand response are not generally passed along to the
`consumer. The companies that aggregate demand typically
`charge utilities for the peak reduction, but the consumer is
`unable to sell their available “negaWatts” directly to a utility.
`
`Honeywell Exhibit 1004, Page 4
`
`

`
`US 2010/0250590 A1
`
`Sep. 30, 2010
`
`This is problematic because this methodology reduces con
`sumer incentives to participate in demand side management,
`Which is a necessary component of modern grid management.
`And adoption is hampered by the general lack of Willingness
`on the part of consumers to alloW utilities to control signi?
`cant portions of their electricity usage With the consumer
`having little “say” in the matter. And, from the utilities’ point
`of vieW, the large variations in consumer usage patterns
`means that it is much harder for utilities to gage hoW much
`demand reduction is enough, in advance; compared to large,
`stable users such as large of?ce buildings or industrial facili
`ties, utilities face a complex mix of user patterns that are
`dif?cult to predict and virtually impossible to control. As a
`result, at the present time almost no demand reduction takes
`place among consumers and small business users of the elec
`tric grid.
`[0011] Another problem in the art today is the incorpora
`tion of distributed generation and storage systems, Which are
`proliferating, into grid demand management systems. In
`many cases, consumers are unable to do more than to offset
`their oWn electric bills With generation units (such as micro
`turbines poWered by Wind, or solar panels on a roof, orplug-in
`electric hybrid vehicles that could add energy to the grid When
`needed), because utilities have neither the means nor the
`motivation to pay them for the extra electricity they generate.
`Many states require utilities to buy excess poWer generated;
`but, Without an ability to sell that generated poWer at a price
`that represents a more holistic vieW of its value that includes
`“embedded bene?ts” (i .e. at a rate that may consider, but is not
`limited to, the effect on enhancing local poWer quality, prox
`imity to loads, type of poWer generated and the associated
`reduction in carbon and other negative extemalitiesilike
`sulfur dioxide and nitrogen dioxideiand the reduced capital
`costs resulting from the reduction of required capital invest
`ments in infrastructure), most distributed poWer generation
`remains economically unfeasible, to the detriment of all par
`ties. With the groWing number of markets associated With
`trading negative externalities associated With electrical poWer
`generation (most prominently including carbon, but also
`nitrogen dioxide and sulfur dioxide), it is necessary to fully
`account for the value of such energy sources and storage
`options, and to ensure that double counting of environmental
`bene?ts that are related to the generation and distribution of
`the electricity itself is not conducted. Sulfur dioxide and
`nitrogen dioxide became regulated in the US. under the 1990
`Clean Air Act Amendments, Which established the EPA’s
`Acid Rain Program to implement a cap-and-trade method to
`reduce harmful emissions from the electric poWer industry.
`Additionally, While storage units may alloW users to avoid
`peak charges and to even the How of locally generated poWer
`(for instance, by storing Wind poWer during high Wind con
`ditions and returning it When the Wind conditions are loW), it
`is generally not possible for users to sell stored poWer to the
`grid operator at its true value for the same reasons.
`[0012] An additional challenge associated With integrating
`distribute energy resources With the grid is the lack of a
`cost-effective means of aggregating distributed poWer gen
`eration into a form that canbe traded in a manner similar to the
`large blocks of poWer that are bought and sold by more
`traditional commercial poWer plants like coal and nuclear.
`Complex industry rules discourage participation and even
`consolidators have been hesitant to enter the market given the
`high set up costs associated With communications, staf?ng,
`and industry monitoring. A mechanism is needed to enable
`
`equal participation of distributed energy generators (e. g. solar
`panels on the roof of a home) and traditional poWer generators
`in order to encourage the development of these resources.
`[0013] It is an object of the present invention to provide an
`effective means of enabling consumers and small businesses
`to fully participate in, and bene?t from, demand reduction
`programs used by the utilities that serve them. It is a further
`object of the present invention to provide a means for
`enabling oWners of distributed generation and storage sys
`tems to make their poWer available for sale and distribution
`across the grid. It is a further object of the present invention to
`make the embedded bene?ts associated With the reduction of
`demand and/or the generation of poWerito include, but not
`limited to, collaborative Greenhouse Gas Programs, carbon
`credits, sulfur dioxide emissions (SO2), and nitrogen dioxide
`emissions (N Ox )ifrom a distributed resource available for
`sale and trading.
`
`SUMMARY OF THE INVENTION
`
`[0014] In a preferred embodiment of the invention, a sys
`tem for managing energy, comprising a digital exchange With
`a communications interface adapted to alloW connections
`from remote users over a data netWork, is disclosed. Accord
`ing to the embodiment, the digital exchange receives prefer
`ences from a plurality of exchange participants, and these
`preferences are used at least in part to create response pro?les
`relevant to the participants, and at least some of the response
`pro?les are aggregated into response packages With de?ned
`statistical properties. Also according to the embodiment, at
`least some of the response packages are made available for
`use by participants in the digital exchange.
`[0015] In another preferred embodiment of the invention, a
`method for managing energy is disclosed, comprising the
`steps of receiving preferences from participants in a digital
`exchange, using those preferences at least in part to create
`response pro?les relevant to the participants, aggregating at
`least some of the response pro?les into response packages
`With de?ned statistical properties, and making at least some
`of the response packages available for use by participants in a
`digital exchange.
`
`BRIEF DESCRIPTION OF THE DRAWING
`FIGURES
`
`[0016] FIG. 1 is a block diagram of components of the
`invention in one embodiment, illustrating a netWork architec
`ture pertaining to the embodiment.
`[0017] FIG. 2 is a block diagram of a digital exchange
`according to an embodiment of the invention.
`
`DETAILED DESCRIPTION
`
`[0018] The inventors provide, in a preferred embodiment of
`the invention, a system for managing energy particularly
`adapted for managing electric poWer demand and distributed
`generation capacity among a large number of small users,
`such as consumers and small businesses. The method is based
`on collecting detailed data about usage patterns from large
`numbers of such users, including hoW these usage patterns
`vary during various time periods, including peak demand
`periods and periods When sources of reneWable energy (such
`as Wind or solar) are unavailable or are available in abun
`dance. Additionally, detailed data on hoW each user reacts,
`either automatically or otherWise, to management signals
`sent during peak demand or other periods, is collected. For
`
`Honeywell Exhibit 1004, Page 5
`
`

`
`US 2010/0250590 A1
`
`Sep. 30, 2010
`
`example, some users may signi?cantly reduce demand When
`requested, and may do so promptly. Other users, conversely,
`may not react at all, or may react sporadically. The same
`variations in response may occur among operators of distrib
`uted generation or storage facilities. There are many reasons
`Why reactions Will vary, and even Why reactions may signi?
`cantly deviate from demand reductions that Were explicitly
`volunteered by a user. For example, When a peak period
`arrives, a user Who volunteered to participate in demand
`reduction might be on vacation, or out of their home for any
`reason, and so many of the loads that Would be targeted may
`already be secured (turned off). Similarly, some user-oWned
`distributed generation facilities may be able to react to man
`agement signals by changing the generation pro?le, While
`others (for instance, solar systems) may not be able to change
`in response to demand management signals (because they are
`dependent on the sun or another uncontrolled factor).
`[0019] According to the invention, this usage data is ana
`lyZed to create response pro?les for each affected user. A
`response pro?le re?ects the amount of load likely to be actu
`ally reduced (or generated) by a user, When requested. The
`pro?le may be quite complex, re?ecting the varying predicted
`behaviors for a user on different days, at different times,
`during different seasons, and so forth. Response pro?les can
`also be generated, according to the invention, on classes of
`users, large or small, Who behave in similar Ways; it is not
`necessary for each user to have an individual response pro?le.
`Furthermore, response pro?les can be quite dynamic; for
`example, a response pro?le may express a conditional behav
`ior such as “if there has beenusage of at least X kWh in the tWo
`hours prior to the period of interest, then the user is likely at
`home and the expected response is Y; otherWise the expected
`response is Z”. In the example given, Z Would likely (but not
`necessarily) be less thanY, and Would re?ect the fact that both
`feWer loads are likely to be active (because the user is aWay, as
`inferred by lack of use in the earlier period) and that no user
`reaction to any demand reduction request is possible because
`the user is likely not at home. In other embodiments of the
`invention, users may have home automation systems imple
`mented and could receive noti?cation via email, SMS text
`message or other means While aWay from home, and thus be
`enabled to take actions to reduce load When needed; this
`capability Would be re?ected in the response pro?le for such
`users or classes of users.
`[0020] In an embodiment of the invention, consumers and
`small businesses participate voluntarily in supply (generation
`and storage) or demand (consumption) management pro
`grams by establishing preferences. Preferences can take
`many forms. In some cases, users may state that certain loads
`are “off limits” or “critical”, and can never be turned off
`remotely for any load conditions. Other loads may be given
`one or more attributes that can used to determine if the load is
`available in any given situation for remote deactivation.
`Attributes could include time of day, length of time since the
`load Was turned on, length of time since the load Was last
`remotely deactivated, level of criticality of the demand reduc
`tion effort, price to be paid for shedding the load (“don’t take
`this load of?ine remotely unless I Will be paid $1 for the
`sacri?ce”), or even the communication required to con?rm
`(for example, “this load can only be turned off if a message is
`sent to its automatic controller and the automatic controller
`states that it is safe to turn off the device”). Another user might
`express the preference that stored solar energy Will be placed
`on the grid When the price is at a certain level, or When the
`
`level of criticality of the peak is su?iciently great. It Will be
`appreciated that any number of consumer or small business
`preferences are possible for controlling When and Whether
`one or more loads are made available for remote deactivation.
`Moreover, the same considerations that apply for deactivation
`can also be applied for activation in the case Where generating
`capacity or storage capacity is available. Consumers and
`small businesses may have, in aggregate, substantial amounts
`of poWer in storage or ready to be generated on demand, if the
`management system Was in place to request it and to manage
`it. Again, each user’s supply-side resources (generation and
`storage capacity) can be made available according to prefer
`ences established by a user. Each response pro?le also re?ects
`the geographic location of the user or class of users to Whom
`it pertains. This information is important for determining
`Which utility, and Which particular grid locations (such as
`substations, tie lines, or regions) Will be affected by the acti
`vation of the response pro?le, and to What extent.
`[0021] In an embodiment of the invention, a number of
`response pro?les are combined to create a response package.
`Because the statistical behavior of users Whose pro?les are
`combined in the response package is knoWn, and because a
`large number of pro?les are normally combined into a pack
`age, it is possible according to the invention to estimate With
`good accuracy hoW much load reduction (or generation) each
`response package represents. For example, a response pack
`age made up of the collected response pro?les of 10,000
`consumers might be expected to yield 1.5 MWh (megaWatt
`hours) of load reduction during a particular 15-minute peak
`load period. Each time this response package is “invoked”
`(that is, each time a signal is sent to all the users represented
`by the response package), the actual demand change effected
`is measured, and used to re?ne the statistical model for each
`response pro?le and for the response package as a Whole. In
`this Way, according to the invention, the system for energy
`management continually adjusts to maintain highly accurate
`models of supply and demand changes in response to invo
`cations of response packages (reductions through load shed
`ding or additions through generation of poWer or release of
`poWer from storage). As With response pro?les, each response
`package has a geographic element. For instance, it may rep
`resent elements (loads and generation/ storage elements)
`spread across a particular utility’s area of responsibility, or it
`may represent elements in a particular urban region.
`[0022] In a preferred embodiment of the invention,
`response packages are made available for purchase by third
`parties. The purchasers could be utilities Who desire to
`directly manage demand, or they could be aggregators Who
`resell demand management to utilities at peak period.
`According to the invention, a given response package can be
`sold for any time period at any time in the future (or indeed for
`the current time period). Thus a response package for reduc
`ing load in San Francisco by 10 MWh for the 15-minute
`interval starting at noon on Friday, Mar. 31, 2010 could be
`sold at any time before 12:15 on that day. Because the pack
`age is sold, according to a preferred embodiment of the inven
`tion, on an open market, it is likely that the price Would vary
`over time based on market participants’ estimates of the likely
`demand for poWer at the critical time for this package (that is,
`at 12:00 on March 31“). In principle, the package can be sold
`more than once according to the invention, although in the
`end only one “oWner” is able to actually elect to invoke the
`demand response action represented by the package. It should
`be noted that actual exercise of the demand response action
`
`Honeywell Exhibit 1004, Page 6
`
`

`
`US 2010/0250590 A1
`
`Sep. 30, 2010
`
`represented by any given response package is necessary
`according to the invention; if load conditions are markedly
`different from What the ?nal purchaser expected, that entity
`may elect not to incur additional costs (described beloW) by
`actually exercising the demand response action.
`[0023] According to an embodiment of the invention, con
`sumers make their preferences concerning their Willingness
`to participate in energy management actions (that is, load
`reductions or provision of poWer from generators or storage
`systems) on demand. Since consumers are unlikely to be
`Willing to enter into long-term forWard contracts for electric
`poWer actions that they may ?nd quite unpalatable When the
`critical day arrives (for instance, if the Weather is much
`Warmer than expected, consumers may balk at letting their air
`conditioners be turned off), it is possible according to the
`invention for consumers to override their preferences at any
`time. Indeed this is one of the reasons that relying on con
`sumers for demand response is so problematic, and Why
`utilities seek to have remote control Whenever possible (al
`though this is rarely possible, and is even illegal in some
`jurisdictions because of regulatory requirements). In order to
`provide a level of control that consumers Will Want or require,
`and to provide a reasonable energy management capability to
`utilities, the combination of a number of consumers’ (again,
`these can also be businesses) response pro?les into response
`packages of su?icient siZe that they Will be large enough to be
`useful and Will have predictable statistical behavior, is carried
`out. According to a preferred embodiment, When a utility or
`other entity actually invokes a response package (for instance,
`by actually requesting the demand to be reduced by 10 MWh
`during the critical period), all of the end users that make up the
`response package are sent signals directing them to take the
`appropriate actions Which they previously volunteered to
`take. While some Will fail or refuse to do so, this has generally
`already been taken into account by building the response
`pro?les and the response package to re?ect the statistical
`patterns that this particular package of users has shoWn in the
`past, so according to the invention the actual demand
`response seen should closely approximate that speci?ed as
`the “rating” of the response package (in the example above,
`the rating Would be 10 MWh of demand reduction in the
`target time period).
`[0024] Actual responses that occur When a response pack
`age is invoked is measured according to the invention. This
`measurement is used to re?ne statistical models used for
`response pro?les, as described above. Also, according to an
`embodiment of the invention, an invoking entity (an entity
`Which invoked a supply or demand response action associated
`With the response package) may optionally only be charged
`according to a supply or demand response that actually took
`place. For instance, While 10 MWh Was forecasted and
`requested, if only 9.5 MWh Was actually achieved, the price
`paid by an invoking entity Would be reduced. The reduction
`could be linear, so that in the example given the entity’s actual
`price is reduced by 5%, or it could be set by any formula
`agreed in advance by the parties in the marketplace (for
`instance, the price difference could be set at 5% reduction for
`any shortfall from 0% to 5%, 10% for any shortfall above 5%
`but less than or equal to 10%, and so forth). It should be
`appreciated that any price adjustment schema can be used
`according to the invention, and that similar adjustments (or no
`adjustment) could be made if the response action exceeded
`What Was requested (typically, one Would expect that any
`
`overage Would not be charged to an invoking entity, but this is
`not required according to the invention).
`[0025] FIG. 1 illustrates a netWork architecture according
`to a preferred embodiment of the invention. A digital
`exchange 100 acts as a control point according to an embodi
`ment. Users such as small businesses and consumers partici
`pate by interacting With the digital exchange 100. Interaction
`is normally conducted by connecting to the digital exchange
`100 via the Internet 101, although this is not necessary
`according to the invention. Interaction betWeen users and the
`digital exchange 100 can be conducted by any suitable com
`munications medium, such as Wired or Wireless telephony. In
`various embodiments of the invention, users interact With the
`digital exchange 100 through the use of mobile phones 122,
`personal computers (PCs) 120, or a home area netWork
`(HAN) keypad 121 such as might be used as part of a home
`automation system. While according to a preferred embodi
`ment of the invention interaction data such as preferences or
`requested actions are passed over the Internet 101 to and from
`users via one or more of these various devices, it should be
`appreciated that Web-based services can today be delivered
`over a large and groWing number of device types and com
`munications netWorks Without departing from the scope of
`the invention. For instance, a user could establish a multimo
`dal voice-and-data session from a “smart mobile phone” over
`both the Internet 1 01 and the Wireless telephony netWork, and
`use both voice and data channels to interact With a digital
`exchange 100 according to the invention. Furthermore, some
`market participants (that is, participants in an energy market
`established according to the invention through a digital
`exchange 100), such utilities or energy aggregators, may
`interact With a digital exchange 1 00 either directly or over the
`Internet 101 from a market interface 150. In some embodi
`ments, market interface 150 is a dedicated server operating
`softWare adapted to communicate With the digital exchange
`100 via hypertext transfer protocol (HTTP), extensible
`markup language @(ML) or a specialiZed protocol using
`XML, remote procedure calls (RPC), the SOAP Web services
`protocol, or any of a number of Well-established data integra
`tion methods Well-knoWn in the art. Consumers and small
`business oWners interact With a digital exchange 100 in order
`to identify and authenticate themselves, to identify energy
`resources (for example, loads such as appliances, computers,
`hot tubs, etc., supply-side resources such as storage devices or
`generators, although the invention should be understood to
`encompass any energy resources capable of being controlled
`by homeoWners or small business operators), and to establish
`preferences concerning hoW and When any resources so iden
`ti?ed are to be available actions requested by the digital
`exchange 100. Examples of preferences that might be
`expressed according to the invention are levels of criticality of
`loads, aminimum prices at Which resources are to be consid
`