DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This Office Action is in response to Applicant’s amendment filed on 7/29/2026.
Claims 2-3 and 16-17 are canceled. Claims 1, 4-15 and 18-23 are pending.
Response to Amendment
Applicant’s amendments have fixed the deficiencies set forth in the previous Office Action hence the respective rejections/objections have been withdrawn, except for those rejections/objections if still maintained or newly added in this Office Action.
Response to Arguments
Regarding Applicant’s arguments about the rejections for claims under 35 U.S.C § 102/103, the arguments have been fully considered but are deemed moot, in view of new grounds of rejections necessitated by Applicant’s amendments.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 4, 5, 6, 9, 10, 11, 12, 13, 15, 18, 19, 20, 21, 22 and 23 are rejected under 35 U.S.C. 103 as being unpatentable over Bruschi (US 2014/0062195 A1, prior art of record, hereinafter as “Bruschi”) in view of Kim (US 20120310860 A1, hereinafter as “Kim”), and in further view of HONG (US 2018/0083483 A1, prior art of record, hereinafter as “HONG”).
Regarding claim 1, Bruschi teaches:
An aggregation engine (Aggregator 12 in FIG. 1) to coordinate a change in power of one or more sites ([0021, 0035]), the aggregation engine comprising:
a memory (memory 1008 in FIG. 3) to store one or more parameters ([0035]), the one or more parameters including a target change in power ([0036-0037]); and
one or more processors (CPU 1001 in FIG. 3) operably coupled to the memory, the one or more processors to iteratively, until an aggregate change in power is within a threshold of the target change in power (FIG. 2 and [0019, 0056]: the aggregator repeatedly negotiate with participants/sites until an aggregate change in power is accepted, i.e., is within a “satisfied” threshold of the target change in power):
transmit apportionment information (Applicant discloses in [0053] of the specification that “the apportionment information may include separate values for the site change in power and the site benefit”. In its broadest reasonable interpretation, the term “apportionment information” is construed as any information comprising a change in power and benefit associated with it. Bruschi teaches in [0040] that the DR event comprises a change in power, teaches in [0045] that the DR event also comprises a benefit, i.e., avoidance of fines, associated with it) to each of a plurality of site controllers, and each of the plurality of site controllers controlling one or more distributed energy resources (DERs) of an electrical system at a site of the one or more sites to optimize operation of the electrical system according to the apportionment information (FIG. 1 and [0038, 0039]);
receive commitment information from each of the plurality of site controllers indicating a level of the site change in power to contribute to bringing the aggregate change in power toward the target change in power ([0042,0043]: aggregator 12 receives from site controllers 16 “alternative proposal” which indicates how much site change in power can be done), the commitment information determined by the site controller of a site according to the apportionment information and an impact of the site change in power on operation of the site ([0021, 0024]), and the aggregate change in power indicating a sum of the levels of the site changes in power of the commitment information ([0021, 0035]); and
wherein the one or more DERs are to be controlled by the plurality of site controllers at the one or more sites to change power based on the commitment information ([0039]).
Bruschi teaches specifically (underlines are added by Examiner for emphasis):
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[0019] The negotiating the new request to reduce power when the evaluated cost is greater than a threshold of acceptability may be performed automatically and electronically using a bidirectional line of data communication.
[0021] A system for managing allocation of electrical power includes an aggregator for receiving a request for power load reduction. The aggregator includes a demand response management system (DRMS) for evaluating the received request for power load reduction and generating one or more demand response (DR) events for requesting power load reduction at one or more participant sites. A database stores historic performance and program parameters, the DRMS generating the one or more DR events based on the historic performance and program parameters retrieved from the database. At least one DRMS site controller is located at least one participant site for receiving the DR event, negotiating terms of power reduction with the aggregator, returning a commitment to the aggregator to shed a particular load, and executing the load shedding commitment.
[0024] A computer system includes a processor and a non-transitory, tangible, program storage medium, readable by the computer system, embodying a program of instructions executable by the processor to perform method steps for managing allocation of electrical power. The method includes selecting one or more power consuming entities for receiving a request modify electrical power usage, generation or retrieval. A customized request to modify electrical power usage, generation or retrieval for each of the selected one or more power consuming entities is generated. The generated customized request is received at a corresponding power consuming entity. A cost associated with complying with the received customized request is evaluated. A commitment to comply with the received customized request is returned when the evaluated cost is within a threshold of acceptability and negotiating a new request to modify electrical power usage, generation or retrieval when the evaluated cost is greater than a threshold of acceptability.
[0035] The call for load reduction may be passed to an aggregator 12. The aggregator may be embodied as a computer system such as one or more servers executing various programs of instructions. The aggregator 12 may be located at a facility of the ISO/utility 11 or may be remotely hosted. The responsibility of the aggregator 12 is to interpret the call for load reduction and generate one or more DR events. The DR events may include requests for a particular participant of the DR program to shed a particular quantity of load. In generating the DR events, the aggregator 12 may utilize a demand response management system (DRMS) 13. The DRMS 13 may include the logic necessary to evaluate the call for load reduction received by the ISO/utility 11 and to create and distribute the DR events to the one or more participant sites 15-1, 15-2, . . . , 15-n. The DRMS 13 may be embodied as one or more software modules executing on the aggregator 12 or the DRMS 13 may be a distinct hardware element in communication with the aggregator 12. The DRMS 13 may recall historic performance and
program parameters from a database 14. This database may, according to one exemplary embodiment of the present invention, be embodied within the aggregator 12.
[0036] Historic performance may be information pertaining to the history of DR events sent to each participant and that participant's history of responding to the DR events and meeting its past load shedding obligations. The parameters may include practical information such as statistics pertaining to the energy usage and flexibility of each participant and various other factors that may relate to the ability of the corresponding participant to shed load upon request. Additionally, the parameters may include information pertaining to the ability of corresponding participants to offset load usage by independent generation of power or by the use on onsite storage and retrieval of power.
[0037] By utilizing this information from the database 14, the DRMS 13 may be able to generate DR events that have a high likelihood of successful execution and a high degree of equitability among the many participants. In this way, the aggregator 12 may be able to avoid having to issue DR events to reduce more load than is truly required as each DR event has a greater likelihood of successful execution than those of other approaches.
[0038] Each generated DR event may be sent from the aggregator 12 to the one or more participant sites 15-1, 15-2, . . . , 15-n. Each participant site may have a similar structure for
accommodating DR events and accordingly, only the structure of participant site 15-1 will be
described. It is to be understood that the other participant sites may have identical or similar
structures.
[0039] The participant site 15-1 may include a DRMS site controller 16. The responsibility of
the DRMS site controller 16 is to receive and evaluate DR events, determine the capacities and
flexibilities of the corresponding participant site, negotiate the DR events, where necessary, return a commitment to the aggregator 12 to shed a particular load, generate a particular quantity of power, store and/or retrieve a quantity of power. The DRMS site controller may
also be responsible for optimizing a strategy for meeting the load shedding commitment and
executing the load shedding commitment. The DRMS site controller 16 may be embodied as a
computer system, for example, one or more servers executing various programs of instructions.
The servers may be located either within the confines of the participant site 15-1 or may be remotely hosted.
[0040] The DR event may detail a quantity of load to shed or maximum load utilization as a
function of time. Additionally, or alternatively, the DR event may detail a quantity of electrical
power to be supplied by the corresponding site, by either power generation or the release of
stored power, and a time frame in which the power is to be supplied. For example, the DR
event may ask that a particular quantity of power be provided by the site from independent
generation of electricity or the DR event may ask that a site charge batteries or other electrical
storage devices at a first time and then release the stored electrical power at a second time. This release of stored electrical power may be used to offset the power needs of that particular site or the released electrical power may be sent back onto the power grid for use by other sites. In this way, the DR event may request that a particular site become a net producer of power for a limited time. According to one exemplary embodiment of the present invention, a site may utilize a fleet of electrical vehicles to store and release power. However, a site may utilize independent generation of power either from renewable resources such as wind turbines, photovoltaic cells, kinetic hydro power generators, etc. or the site may utilize independent
generation of power from fossil fuel sources such as natural gas or petroleum-based fuels.
[0042] The DRMS site controller 16 according to exemplary embodiments of the present invention may determine an optimal strategy for satisfying the DR event. If satisfaction of the
DR event in its entirety is either not possible or prohibitively expensive, the DRMS site controller 16 may negotiate the DR event with the aggregator 12. Negotiation may include the DRMS 16 informing the aggregator 12 what portions of the DR event may be easily accommodated and what portions of the DR event are problematic. The DRMS 16 may also provide the aggregator 12 with an indication of how problematic various aspects of the DR event may be so that the aggregator 12 can efficiently reduce load and/or offset load with power generation/release of stored power across all participant sites in a least disruptive manner.
[0043] Negotiation between the DRMS site controller 16 and the aggregator 12 may be implemented, for example, by the sending and receiving of electronic communications between the DRMS 13 and the DRMS site controller 16. These electronic communications may be carried accords a dedicated line of communication or over a wide area network (WAN), for example, over the Internet. The electronic communications may be encrypted and/or digitally signed to maintain security and integrity. Negotiation may be performed automatically and need not involve human intervention. Negotiation may include, for example, a message sent from the DRMS site controller 16 to the DRMS 13 that the DR event is not accepted and an alternative proposal may be provided. The DRMS 13 may then return an acceptance of the counter proposal or an insistence upon the original terms of the DR event, as the needs require.
[0045] The DRMS site controller 16 may include a DR event evaluator 17 for receiving the DR event, consulting the database of enrolled programs, verifying the legitimacy of the DR event, and passing along legitimate DR events to a decision selector 18. The decision selector 18 may
determine how best to satisfy the DR event or in the alternative, how to negotiate for modifications to the DR event, where necessary. As failure to satisfy the entire DR event may
have consequences such as assessment of fines, the decision selector 18 may take into
consideration the cost of shedding load under present conditions and the applicable fines.
[0056] The aggregator may then determine whether the commitments and/or optimized strategies received from the various participants satisfy the shortage forecast (Step S27). Where they do not (No, Step S27), the process may be repeated to generate additional DR events or modify existing DR events. Where the forecasted shortage is satisfied (Yes, Step
S27), the process may be ended.
[0058] The computer system referred to generally as system 1000 may include, for example, a central processing unit (CPU) 1001, random access memory (RAM) 1004, a printer interface 1010, a display unit 1011, a local area network (LAN) data transmission controller 1005, a LAN interface 1006, a network controller 1003, an internal bus 1002, and one or more input devices 1009, for example, a keyboard, mouse etc. As shown, the system 1000 may be connected to a data storage device, for example, a hard disk, 1008 via a link 1007.
Bruschi teaches all the limitations except the apportionment information indicating a proposed site benefit per unit of proposed site change in power, and to modify the apportionment information by changing a ratio between the site change in power and the site benefit toward achieving the target change in power and toward minimizing the aggregate benefit to the one or more sites.
However, Kim teaches in analogous art:
apportionment information indicating a proposed site benefit per unit of proposed site change in power (the “incentive price” recited in [0022, 0024, 0025], which is an addition money payment increase or reduction per unit of power reduction), and
to modify the apportionment information by changing a ratio between the site change in power and the site benefit toward achieving the target change in power ([0022]: “the incentive price range may be updated based on the received bids. Then, after a number of iterations, the bidding process may be designed to converge to an optimal incentive price that would best fulfill the demand response request”; and [0025]: “the incentive price is lower than the optimal price so the committed load reduction is less than what is needed. Hence the incentive price should be increased”. All these teach to modify the “incentive price” to achieve target load power reduction).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bruschi based on the teaching of Kim, to make the aggregation engine wherein the apportionment information indicates a proposed site benefit per unit of proposed site change in power, and wherein the one of more processors modify the apportionment information by changing a ratio between the site change in power and the site benefit toward achieving the target change in power. One of ordinary skill in the art would have been motivated to do this modification since it can help “fulfill the demand response request”, as Kim suggests in [0022].
Bruschi-Kim teach all the limitations except to modify the apportionment information by changing a ratio between the site change in power and the site benefit toward minimizing the aggregate benefit to the one or more sites.
However, HONG teaches in an analogous art:
Modify toward minimizing the aggregate benefit to the one or more sites (Equation 26 and [0042]: “When anticipating the resource deficiency with the quantity Dreq, the GO will try to compensate the deficiency either by running generators or purchasing load reduction from the demand side. Accordingly, the objective of a GO is to minimize the procurement cost (CGO) composed of two parts: the generation cost caused by running generators and incentive payments paid to SPs”. According to Equation 26, the more the aggregate change in power is , the less the generation cost caused by running generators is. The less the aggregate incentive payment is, the less the procurement cost is. Therefore, this teaches to decrease the aggregate benefit to the sites, to minimize the procurement cost CGO).
Since Bruschi-Kim teach to modify the apportionment information, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bruschi-Kim based on the teaching of HONG, to make the aggregation engine wherein the one of more processors modify the apportionment information by changing a ratio between the site change in power and the site benefit toward minimizing the aggregate benefit to the one or more sites. One of ordinary skill in the art would have been motivated to do this modification since it can help “provide optimal system solution”, as HONG teaches in the [Abstract].
Regarding claim 4, Bruschi-Kim-HONG teach(es) all the limitations of its base claim from which the claim depends.
HONG further teaches:
to optimize attaining the target change in power by seeking to increase the aggregate change in power and seeking to reduce an aggregate benefit to the one or more sites (Equation 26 and [0042]: “When anticipating the resource deficiency with the quantity Dreq, the GO will try to compensate the deficiency either by running generators or purchasing load reduction from the demand side. Accordingly, the objective of a GO is to minimize the procurement cost (CGO) composed of two parts: the generation cost caused by running generators and incentive payments paid to SPs”. According to Equation 26, the more the aggregate change in power is , the less the generation cost caused by running generators is. The less the aggregate incentive payment is, the less the procurement cost is. Therefore, this teaches to increase the aggregate change in power and decrease the aggregate benefit to the sites, to minimize the procurement cost CGO).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Bruschi-Kim based on the teaching of HONG, to make the aggregation engine wherein the one or more processors modify the apportionment information to optimize attaining the target change in power by seeking to increase the aggregate change in power and seeking to reduce an aggregate benefit to the one or more sites. One of ordinary skill in the art would have been motivated to do this modification since it can help “provide optimal system solution”, as HONG teaches in the [Abstract].
Regarding claim 5, Bruschi-Kim-HONG teach(es) all the limitations of its base claim from which the claim depends.
HONG further teaches:
to optimize attaining the target change in power by seeking to maximize the aggregate change in power and minimize an aggregate benefit to the one or more sites (Equation 26 and [0042]: “When anticipating the resource deficiency with the quantity Dreq, the GO will try to compensate the deficiency either by running generators or purchasing load reduction from the demand side. Accordingly, the objective of a GO is to minimize the procurement cost (CGO) composed of two parts: the generation cost caused by running generators and incentive payments paid to SPs”. According to Equation 26, the more the aggregate change in power is, the less the generation cost caused by running generators is. The less the aggregate incentive payment is, the less the procurement cost is. Therefore, this teaches to maximize the aggregate change in power and minimize the aggregate benefit to the sites, in order to minimize the procurement cost CGO).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Bruschi-Kim based on the teaching of HONG, to make the aggregation engine wherein the one or more processors modify the apportionment information to optimize attaining the target change in power by seeking to maximize the aggregate change in power and minimize an aggregate benefit to the one or more sites. One of ordinary skill in the art would have been motivated to do this modification since it can help “provide optimal system solution”, as HONG teaches in the [Abstract].
Regarding claim 6, Bruschi-Kim-HONG teach(es) all the limitations of its base claim from which the claim depends.
HONG further teaches:
to optimize attaining the target change in power by seeking to maximize the site change in power and minimize the associated benefit (Equation 26 and [0042]: “When anticipating the resource deficiency with the quantity Dreq, the GO will try to compensate the deficiency either by running generators or purchasing load reduction from the demand side. Accordingly, the objective of a GO is to minimize the procurement cost (CGO) composed of two parts: the generation cost caused by running generators and incentive payments paid to SPs”. According to Equation 26, the more the aggregate change in power is , the less the generation cost caused by running generators is. The less the aggregate incentive payment is, the less the procurement cost is. To maximize the aggregate change in power, every site change is power needs to be maximized. To minimize the aggregate benefit to the sites, every benefit associated with a site needs to be minimized. Therefore, this teaches to maximize the site change in power and minimize the associated benefit, in order to minimize the procurement cost CGO).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Bruschi-Kim based on the teaching of HONG, to make the aggregation engine wherein the one or more processors modify the apportionment information to optimize attaining the target change in power by seeking to maximize the site change in power and minimize an associated benefit. One of ordinary skill in the art would have been motivated to do this modification since it can help “provide optimal system solution”, as HONG teaches in the [Abstract].
Regarding claim 9, Bruschi-Kim-HONG teach(es) all the limitations of its base claim from which the claim depends.
HONG further teaches:
an aggregate benefit to be received by bringing the aggregate change in power to the target change in power (FIG. 2 and [0009]: “there is provided an incentive-based DR method in a DR system including a GO, a plurality of service providers (SPs), and a plurality of customers enrolling each SP. The method includes a first step of updating, by the GO, a GO incentive and transmitting the GO incentive that has been updated to the plurality of SPs; a second step of determining, by each of the plurality of SPs, an SP incentive based on the GO incentive”. This teaches the GO (grid operator) sends a GO incentive, which is an aggregate benefit, to the customers through service providers for complying with the requested demand response).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Bruschi-Kim based on the teaching of HONG, to make the aggregation engine wherein the one or more parameters include an aggregate benefit to be received by bringing the aggregate change in power to the target change in power. One of ordinary skill in the art would have been motivated to do this modification since it can help “provide optimal system solution”, as HONG teaches in the [Abstract].
Regarding claim 10, Bruschi-Kim-HONG teach(es) all the limitations of its base claim from which the claim depends.
HONG further teaches:
a sum of the associated benefits to the one or more sites is smaller than the aggregate benefit (FIG. 2 and [0046]: “For an SPkεK, when offered the GO incentive (πGO), it aims to maximize the revenue from trading with the GO in the wholesale market, while minimizing incentive payments to enrolled customers”. This teaches since the service providers keep part of the incentive received from the GO and send the rest of the incentive to the enrolled customers at different sites, therefore a sum of the incentives associated with the enrolled customers is less than the total aggregate benefit from the GO).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Bruschi-Kim based on the teaching of HONG, to make the aggregation engine wherein a sum of the associated benefit to the one or more sites is smaller than the aggregate benefit. One of ordinary skill in the art would have been motivated to do this modification since it can help “provide optimal system solution”, as HONG teaches in the [Abstract].
Regarding claim 11, Bruschi-Kim-HONG teach(es) all the limitations of its base claim from which the claim depends.
Bruschi further teaches:
the associated benefit to the one or more sites is monetary ([0045]: “As failure to satisfy the entire DR event may have consequences such as assessment of fines, the decision selector 18 may take into consideration the cost of shedding load under present conditions and the applicable fines”. This teaches the associated benefit to the sites is a monetary fine).
Regarding claim 12, Bruschi-Kim-HONG teach(es) all the limitations of its base claim from which the claim depends.
Bruschi further teaches:
the one or more processors, in response to determining the aggregate change in power is within the threshold of the target change in power ([0056]: “The aggregator may then determine whether the commitments and/or optimized strategies received from the various participants satisfy the shortage forecast (Step S27). Where they do not (No, Step S27), the process may be repeated to generate additional DR events or modify existing DR events. Where the forecasted shortage is satisfied (Yes, Step S27), the process may be ended”), transmit a message to each of the plurality of site controllers, the message comprising instructions to operate according to the commitment information each of the plurality of site controllers provided, wherein the plurality of site controllers each control the one or more DERs of the electrical system controlled by the site controller according to the message ([0043]: “Negotiation may include, for example, a message sent from the DRMS site controller 16 to the DRMS 13 that the DR event is not accepted and an alternative proposal may be provided. The DRMS 13 may then return an acceptance of the counter proposal …”. This teaches the negotiation continues until the aggregate DR meets the target goal based on the received feedbacks from the sites, then a message is transmitted to the sites which indicates the committed proposal is accepted, i.e., which instructs the site to conduct the DR event based on its accepted commitment proposal. After that, each site controller controls its DERS according to its commitment proposal from the message of acceptance).
Regarding claim 13, Bruschi-Kim-HONG teach(es) all the limitations of its base claim from which the claim depends on.
Bruschi further teaches:
the apportionment information comprises energy delivered over a defined timeframe ([0040]: “the DR event may detail a quantity of electrical power to be supplied by the corresponding site, by either power generation or the release of stored power, and a time frame in which the power is to be supplied”), and the commitment information comprises a quantity of energy committed ([0039]: “return a commitment to the aggregator 12 to shed a particular load, generate a particular quantity of power, store and/or retrieve a quantity of power”).
Kim further teaches:
the apportionment information comprises an offered price per unit of energy delivered over a defined timeframe (the “incentive price” recited in [0022, 0024, 0025], which is an offered price of addition money payment increase or reduction per unit of power reduction over a defined timeframe)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Bruschi-HONG based on the teaching of Kim, to make the aggregation engine wherein the apportionment information comprises an offered price per unit of energy delivered over a defined timeframe, and the commitment information comprises a quantity of energy committed at the offered price per unit. One of ordinary skill in the art would have been motivated to do this modification since it can help “fulfill the demand response request”, as Kim suggests in [0022].
Claim 15 recites a computer implemented method comprising operational steps conducted by the aggregation engine in claim 1 with patentably the same limitations. Therefore, claim 15 is rejected for the same reason recited in the rejection of claim 1.
Claims 18, 19 and 20 recite a computer implemented method comprising operational steps conducted by the aggregation engine in claims 4, 5 and 6 respectively with patentably the same limitations. Therefore, claims 18, 19 and 20 are rejected for the same reasons recited in the rejections of claims 4, 5 and 6, respectively.
Claim 21 recites an electrical system controller similar to the aggregation engine in claim 1 with substantially similar limitations. The only additional limitation “determine an extended control plan to control operation of the electrical system over an upcoming time domain according to the modified apportionment information received from the aggregation engine” is also taught by Bruschi.
Bruschi teaches:
determine an extended control plan to control operation of the electrical system over an upcoming time domain according to the modified apportionment information received from the aggregation engine (FIG. 2 and [0056]: “The aggregator may then determine whether the commitments and/or optimized strategies received from the various participants satisfy the shortage forecast (Step S27). Where they do not (No, Step S27), the process may be repeated to generate additional DR events or modify existing DR events. Where the forecasted shortage is satisfied (Yes, Step S27), the process may be ended”).
Therefore, claim 21 is unpatentable over Bruschi-Kim-HONG.
Regarding claim 22, Bruschi-Kim-HONG teach(es) all the limitations of its base claim from which the claim depends.
HONG further teaches:
optimizes both a cost of the level of the site change in power and an associated benefit (Equation 26 and [0042]: “When anticipating the resource deficiency with the quantity Dreq, the GO will try to compensate the deficiency either by running generators or purchasing load reduction from the demand side. Accordingly, the objective of a GO is to minimize the procurement cost (CGO) composed of two parts: the generation cost caused by running generators and incentive payments paid to SPs”. This teaches to optimize both cost of change in power and associated benefit to the sites/(subscription customers)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Bruschi-Him based on the teaching of HONG, to make the electrical system controller wherein the one or more processors determine the extended control plan by determining an optimal extended control plan that optimizes both a cost of the level of the site change in power and an associated benefit. One of ordinary skill in the art would have been motivated to do this modification since it can help “provide optimal system solution”, as HONG teaches in the [Abstract].
Regarding claim 23, Bruschi-Kim-HONG teach(es) all the limitations of its base claim from which the claim depends on.
HONG further teaches:
constructing a cost function including a sum of cost elements of operating the electrical system and performing an optimization algorithm on the cost function, wherein the cost elements include a cost element for both the cost of the level of the site change in power and the associated benefit (Equation 26 and [0042]: “When anticipating the resource deficiency with the quantity Dreq, the GO will try to compensate the deficiency either by running generators or purchasing load reduction from the demand side. Accordingly, the objective of a GO is to minimize the procurement cost (CGO) composed of two parts: the generation cost caused by running generators and incentive payments paid to SPs”. GO is a cost function including a sum of cost for power change and the associated benefit).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Bruschi-Kim based on the teaching of HONG, to make the electrical system controller wherein the one or more processors determine the optimal extended control plan by constructing a cost function including a sum of cost elements of operating the electrical system and performing an optimization algorithm on the cost function, wherein the cost elements include a cost element for both the cost of the level of the site change in power and the associated benefit. One of ordinary skill in the art would have been motivated to do this modification since it can help “provide optimal system solution”, as HONG teaches in the [Abstract].
Claims 7 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Bruschi in view of Kim and HONG, and in further view of Yuki Kawano (JP 2018207745 A, prior art of record, hereinafter as “Yuki”).
Regarding claim 7, Bruschi-Kim-HONG teach(es) all the limitations of its base claim from which the claim depends, but do not teach the apportionment information indicates how an associated benefit per unit of the site change in power is to vary for time points of a future period of time.
However, Yuki teaches in an analogous art:
associated benefit per unit for the site change in power is to vary for time points of a future period of time (FIG. 16 and [0076]: “FIG. 16 illustrates an incentive variation graph of an incentive. In this graph, time is taken on the horizontal axis and incentive I [Yen / 30 minute power] is taken on the vertical axis. An incentive I is derived from, for example, the DR result database 34 based on past results”. This teaches the associated incentive for demand response/(the site change in power) is to vary at different times of a future period of time).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bruschi-Kim-HONG based on the teaching of Yuki, to make the aggregation engine wherein the apportionment information indicates how an associated benefit per unit of the site change in power is to vary for time points of a future period of time. One of ordinary skill in the art would have been motivated to do this modification since it can help “create a demand response plan which reduces the total power cost”, as Yuki teaches in [0017].
Regarding claim 8, Bruschi-Kim-HONG-Yuki teach(es) all the limitations of its base claim from which the claim depends.
Yuki further teaches:
the associated benefit varies over the future period of time based on expected fluctuations in a demand for electrical power over the future period of time (FIG. 16 and [0076]: “when a plurality of contract data is present in an incentive to be displayed, such as when a plurality of power supply business providers and a demand response contract (power supply and demand adjustment contract) are connected, a plurality of graphs may be displayed”. This teaches the variation of the incentive graph is based on expected demand response which fluctuates over the future period of time).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Bruschi-Kim-HONG based on the teaching of Yuki, to make the aggregation engine wherein the associated benefit varies over the future period of time based on expected fluctuations in a demand for electrical power over the future period of time. One of ordinary skill in the art would have been motivated to do this modification since it can help “create a demand response plan which reduces the total power cost”, as Yuki teaches in [0017].
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Bruschi in view of Kim and HONG, and in further view of WAKI (US 20130289773 A1, prior art of record, hereinafter as “WAKI”).
Regarding claim 14, Bruschi-Kim-HONG teach(es) all the limitations of its base claim from which the claim depends.
Bruschi further teaches:
the apportionment information comprises energy delivered over a defined timeframe ([0040]: “the DR event may detail a quantity of electrical power to be supplied by the corresponding site, by either power generation or the release of stored power, and a time frame in which the power is to be supplied”), and the commitment information comprises a quantity of power to be delivered ([0039]: “return a commitment to the aggregator 12 to shed a particular load, generate a particular quantity of power, store and/or retrieve a quantity of power”).
Kim further teaches:
the apportionment information comprises a price per unit of power delivered over a defined timeframe (the “incentive price” recited in [0022, 0024, 0025], which is an offered price of addition money payment increase or reduction per unit of power reduction over a defined timeframe).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have further modified Bruschi-HONG based on the teaching of Kim, to make the aggregation engine wherein the apportionment information comprises a price per quantity of power delivered over a defined timeframe, and the commitment information comprises a quantity of power to be delivered at the price per quantity. One of ordinary skill in the art would have been motivated to do this modification since it can help “fulfill the demand response request”, as Kim suggests in [0022].
Bruschi-Kim-HONG teach all the limitations except the power is average power delivered over the defined timeframe.
However, WAKI teaches in an analogous art that an Demand Response event in implemented adaptively instead of uniformly so an average power during a defined timeframe is within a limit (FIG. 5 and [0089-0094]: “The power P3 is an average power obtained by averaging the predetermined limit by the DR period”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Bruschi-Kim-HONG based on the teaching of WAKI, to make the aggregation engine wherein the apportionment information comprises a price per quantity of average power delivered over a defined timeframe, and the commitment information comprises a quantity of average power to be delivered at the price per quantity. One of ordinary skill in the art would have been motivated to do this modification so that “the total power amount consumed during the DR period to be equal to or lower than the predetermined limit” while achieve more favorable result, as WAKI teaches in [0092, 0093].
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
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/CHARLES CAI/
Primary Patent Examiner, Art Unit 2115
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