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 .
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 2-12 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claims 2-12 recite a limitation “The system of claim …” which lacks sufficient antecedent basis. Since claim 1 recites “An electrical system controller”, for continuing examination purpose, the limitation has been construed as “The system controller of claim …”
Claim 12 recites a phrase “the one or more processors are configured to determine the associated benefit for the site change in power of the participation opportunity information reduces the cost value of the cost function as a function of a reduction in power consumption by site or an increase in power generation by the site”, which is unclear about its meaning. For continuing examination purpose, the phrase has been construed as “the one or more processors are configured to determine the associated benefit for the site change in power of the participation opportunity information to reduce the cost value of the cost function as a function of a reduction in power consumption by site or an increase in power generation by the site”
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim 1, 8, 10, 11, 12, 13 and 18 are rejected under 35 U.S.C. 102(a)(1) as being unpatentable over Bruschi (US 20140062195 A1, hereinafter as “Bruschi”).
Regarding claim 1, Bruschi teaches:
An electrical system controller (site controller 16 in FIG. 1 and [0039]) of an electrical system at a site, the electrical system controller configured to communicate with one or more distributed energy resources (DERs) of the site ([0039]), and comprising one or more processors configured to:
receive participation opportunity information ([0039]) from an aggregation engine (aggregator 12 in FIG. 1), the aggregation engine in communication with a plurality of electrical system controllers at a plurality of sites (FIG. 1), and the participation opportunity information indicating one or more parameters for a site change in power to contribute to bringing an aggregate change in power toward a target change in power ([0040, 0041]) and indicating an associated benefit for the site change in power ([0045]: associated benefit of avoiding “fines”);
identify a set of control parameters configured to be used to control the one or more DERs of the site for a defined time period (FIG. 1 and [0046]);
iteratively execute a cost function based at least on the associated benefit for the site change in power of the participation opportunity information to generate a set of values for the set of control parameters for the defined time period that reduces a cost value of the cost function, the set of values corresponding to a committed site change in power ([0047]); and
transmit the committed site change in power to the aggregation engine ([0044]); and
control the one or more DERs according to the set of values for the set of control parameters for the defined time period to contribute the committed site change in power toward the aggregate change in power ([0014, 0021]).
Bruschi teaches specifically (underlines are added by Examiner for emphasis):
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[0014] The commitment to comply with the request or the negotiated new request may be executed by curtailing power utilization, independently generating power, or storing and releasing power. Execution of the commitment or the negotiated new request may include storing power within one or more electrical vehicles and releasing the stored power for general use.
[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.
[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.
[0041] The DR event may provide for various degrees of load shedding/offsetting at various times. Where the DR event details maximum load utilization, this information may be represented, for example, as a number of kilowatts/megawatts that must not be exceeded by the participant site for various times. Where the DR event details a quantity of load to shed, the baseline used may be either a quantification of current or forecasted energy usage. The DR event may also detail a peak load utilization that must not be exceeded, regardless of time of day, for the span of the period in question, which may be, for example, one day.
[0044] When negotiations between the DRMS site controller 16 and the aggregator 12 are complete, the DRMS site controller 16 will return a commitment to the aggregator 12. The commitment may indicate the extent of load to be shed, generated, stored and released, etc., and/or peak load thresholds over various periods of time. Where the negotiated commitment falls short of the original DR event, the aggregator 12 may make up for this shortfall in DR events issued to other participants. Conversely, where the DRMS site controller 16 accepts the DR event, it may remain a possibility that the aggregator 12 issues a revised DR event to the DRMS site controller 16, for example, to make up for a shortfall with in other DR events to other participants.
[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.
[0046] The decision selector 18 may have several options in determining how best to satisfy the DR event and/or what new DR event to negotiate for. The decision selector 18 may reduce load, bring alternative power generation means online, or utilize available energy storage facilities to reduce load demand at certain times by increasing load demand at more convenient times. The decision selector may refer to a load selector 19 to determine how and from where load may be reduced.
[0047] The decision selector 18 may be aware of the full range of available power generation means and energy storage facilities at the disposal of the participant site. For example, the participant site may have oil or gas electrical generators and/or renewable energy generators such as photovoltaic cells or wind turbines. The cost and availability of each means of power generation may be known to the decision selector 18 so that an optimum plan for DR event fulfillment may be devised. The decision selector 18 may be embodied as a software optimization engine.
Regarding claim 8, Bruschi teach(es) all the limitations of its base claim from which the claim depends.
Bruschi further teaches:
the one or more processors are further configured to:
determine a predicted power load ([0049]: “The decision selector 18 may accordingly optimize the amount of load reduction that may be met at the corresponding participant site 15-1 by the combination of using distributed power generation, electric vehicles, and load. The decision selector 18 may generate various different load reduction strategies and may provide these strategies to a load selector 19 to address the DR event”) and power generation ([0047]: “The decision selector 18 may be aware of the full range of available power generation means and energy storage facilities at the disposal of the participant site. For example, the participant site may have oil or gas electrical generators and/or renewable energy generators such as photovoltaic cells or wind turbines. The cost and availability of each means of power generation may be known to the decision selector 18 so that an optimum plan for DR event fulfillment may be devised”) of the one or more DERs during the defined time period,
wherein the one or more processors are configured to iteratively execute the cost function to generate the set of values for the set of control parameters for the defined time period based further on the predicted power load and power generation for the defined time period (see [0049, 0047] recited above).
Regarding claim 10, Bruschi teach(es) all the limitations of its base claim from which the claim depends.
Bruschi further teaches:
the one or more processors are further configured to:
identify one or more objectives associated with controlling the electrical system for the time period ([0054]: “The customized DR events may be received and evaluated by the respective participants (Step S25). Evaluation of the DR event may include determining the authenticity and integrity of the DR request and comparing the DR request against the power needs of the participant and the costs of power curtailment, generation, storage, etc.”. This teaches to identify DR event, i.e., objective of controlling the electrical system for the time period); and
generate the cost function based on the identified one or more objectives for the time period (as recited in [0054] above, cost function is generated based on the identified DR event).
Regarding claim 11, Bruschi teach(es) all the limitations of its base claim from which the claim depends.
Bruschi further teaches:
the one or more processors are configured to iteratively execute the cost function by:
executing the cost function for a plurality of iterations with a different candidate set of values for each iteration until determining an iteration that corresponds to a minimum cost value based at least on the associated benefit for the site change in power of the participation opportunity information reducing the cost value of the cost function ([0047]: “The decision selector 18 may be aware of the full range of available power generation means and energy storage facilities at the disposal of the participant site. For example, the participant site may have oil or gas electrical generators and/or renewable energy generators such as photovoltaic cells or wind turbines. The cost and availability of each means of power generation may be known to the decision selector 18 so that an optimum plan for DR event fulfillment may be devised”; and [0045]: “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”. These teach to try different combinations of power generation, energy storage facilities and load shedding, and find the “optimum plan” to reduce the cost based on associated benefit of fine avoidance).
Regarding claim 12, Bruschi teach(es) all the limitations of its base claim from which the claim depends.
Bruschi further teaches:
the one or more processors are configured to determine the associated benefit for the site change in power of the participation opportunity information to reduce the cost value of the cost function as a function of a reduction in power consumption by site or an increase in power generation by the site ([0047]: “The decision selector 18 may be aware of the full range of available power generation means and energy storage facilities at the disposal of the participant site. For example, the participant site may have oil or gas electrical generators and/or renewable energy generators such as photovoltaic cells or wind turbines. The cost and availability of each means of power generation may be known to the decision selector 18 so that an optimum plan for DR event fulfillment may be devised”; and [0045]: “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”. These teach to determine the associated benefit of fine avoidance to reduce the cost by load shedding).
Claim 13 recites a computer implemented method comprising operational steps conducted by the electrical system controller in claim 1 with patentably the same limitations. Therefore, claim 13 is rejected for the same reason recited in the rejection of claim 1.
Claim 18 recites Non-transitory computer-readable media comprising instructions of operational steps conducted by the electrical system controller in claim 1 with patentably the same limitations. Therefore, claim 18 is rejected for the same reason recited in the rejection of claim 1.
Claim Rejections - 35 USC § 103
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 2-7, 14-17 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Bruschi in view of Asghari (US 20140005852 A1, hereinafter as “Asghari”).
Regarding claim 2, Bruschi teach(es) all the limitations of its base claim from which the claim depends, but does not teach to receive one or more constraints each identifying a different cost of operating the electrical system, wherein the one or more processors are configured to iteratively execute the cost function to generate the set of values for the set of control parameters for the defined time period based further on the one or more constraints identifying costs of operating the electrical system.
However, Asghari teaches in an analogous art:
to receive one or more constraints each identifying a different cost of operating the electrical system, wherein the one or more processors are configured to execute the cost function to generate the set of values for the set of control parameters for the defined time period based further on the one or more constraints identifying costs of operating the electrical system ([0016]: “a method for managing demand or load includes, upon receipt of a demand response signal or a load management request from a utility to change the price of electricity, determining the cost of energy from a local battery, and if the cost of energy from battery is higher than the cost of electricity from the utility, shedding power from one or more devices based on the utility price, and otherwise discharging power from the battery to reduce a net load on the grid without any actual load reduction”. This teaches to receive constraints identifying cost of generating power from battery and cost of powering load from utility electricity, and to minimize the total cost by setting control parameters for the system operation).
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 Asghari, to make the system controller wherein the one or more processors are further configured to receive one or more constraints each identifying a different cost of operating the electrical system, wherein the one or more processors are configured to iteratively execute the cost function to generate the set of values for the set of control parameters for the defined time period based further on the one or more constraints identifying costs of operating the electrical system. One of ordinary skill in the art would have been motivated to do this modification since it can help “minimize the operational cost”, as Asghari teaches in [0019].
Regarding claim 3, Bruschi-Asghari teach(es) all the limitations of its base claim from which the claim depends.
Asghari further teaches:
receiving one or more of an electricity cost ([0016]: “determining the cost of energy from a local battery, and if the cost of energy from battery is higher than the cost of electricity from the utility ….”), a battery degradation cost ([0018]: “The controller collects information about different DG generation power, storage state of charge, and the end-user demand This will determine discharge pattern of the storage at the time of management which is used to estimate the battery lifetime and consequently calculating the cost of energy from the battery based on a levelized cost model”), an equipment degradation cost, a tariff definition, a cost of local generation, penalties associated with deviating from an operating plan, or costs or benefits associated with a change in energy, and
wherein the one or more processors are configured to execute the cost function to generate the set of values for the set of control parameters for the defined time period based further on the one or more of the electricity cost, the battery degradation cost, the equipment degradation cost, the tariff definition, a cost of local generation, the penalties associated with deviating from an operating plan, or the costs or benefits associated with a change in energy ([0016, 0018]: based on cost of utility electricity and cost of battery energy comprising battery degradation cost, the total cost is minimized by setting control parameters for the system operation).
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 based on the teaching of Asghari, to make the system controller wherein the one or more processors are configured to receive the one or more constraints by receiving one or more of an electricity cost, a battery degradation cost, an equipment degradation cost, a tariff definition, a cost of local generation, penalties associated with deviating from an operating plan, or costs or benefits associated with a change in energy, and wherein the one or more processors are configured to iteratively execute the cost function to generate the set of values for the set of control parameters for the defined time period based further on the one or more of the electricity cost, the battery degradation cost, the equipment degradation cost, the tariff definition, a cost of local generation, the penalties associated with deviating from an operating plan, or the costs or benefits associated with a change in energy. One of ordinary skill in the art would have been motivated to do this modification since it can help “minimize the operational cost”, as Asghari teaches in [0019].
Regarding claim 4, Bruschi-Asghari teach(es) all the limitations of its base claim from which the claim depends.
Asghari further teaches:
receiving one or more parameters indicating how to calculate a cost value for each of one or more cost elements ([0018]: “The controller collects information about different DG generation power, storage state of charge, and the end-user demand This will determine discharge pattern of the storage at the time of management which is used to estimate the battery lifetime and consequently calculating the cost of energy from the battery based on a levelized cost model”), and
wherein the one or more processors are configured to iteratively execute the cost function to generate the set of values for the set of control parameters for the defined time period based further on the one or more parameters indicating how to calculate the cost value for each of the one or more cost elements ([0016, 0018]: based on cost of utility electricity and cost of battery energy comprising battery degradation cost, the total cost is minimized by setting control parameters for the system operation).
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 based on the teaching of Asghari, to make the system controller wherein the one or more processors are configured to receive the one or more constraints by receiving one or more parameters indicating how to calculate a cost value for each of one or more cost elements, and wherein the one or more processors are configured to iteratively execute the cost function to generate the set of values for the set of control parameters for the defined time period based further on the one or more parameters indicating how to calculate the cost value for each of the one or more cost elements. One of ordinary skill in the art would have been motivated to do this modification since it can help “minimize the operational cost”, as Asghari teaches in [0019].
Regarding claim 5, Bruschi teach(es) all the limitations of its base claim from which the claim depends, but does not teach the one or more processors are further configured to receive one or more measurements of each of one or more process variables indicating a state of the electrical system, and wherein the one or more processors are configured to identify the set of control parameters by determining the set of control parameters based on the one or more measurements of each of the one or more process variables.
However, Asghari teaches in an analogous art:
to receive one or more measurements of each of one or more process variables indicating a state of the electrical system ([0018]: “a real-time power and load management controller can be used. The controller collects information about different DG generation power, storage state of charge, and the end-user demand. This will determine discharge pattern of the storage at the time of management which is used to estimate the battery lifetime and consequently calculating the cost of energy from the battery based on a levelized cost model”), and
wherein the one or more processors are configured to identify the set of control parameters by:
determining the set of control parameters based on the one or more measurements of each of the one or more process variables ([0018]: “a real-time power and load management controller can be used. The controller collects information about different DG generation power, storage state of charge, and the end-user demand This will determine discharge pattern of the storage at the time of management which is used to estimate the battery lifetime and consequently calculating the cost of energy from the battery based on a levelized cost model. The cost of energy from the battery is then compared to the grid price signal. In this way the end-user can determine whether it is more cost-effective to use its own storage unit or to buy the power from the grid to balance the electric supply and demand In case that the purchase of power from the grid is recommended”. This teaches to determine control parameters of the battery to discharge based on the measured process variables including “storage state of charge”).
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 Asghari, to make the system controller wherein the one or more processors are further configured to receive one or more measurements of each of one or more process variables indicating a state of the electrical system, and wherein the one or more processors are configured to identify the set of control parameters by determining the set of control parameters based on the one or more measurements of each of the one or more process variables. One of ordinary skill in the art would have been motivated to do this modification since it can help “minimize the operational cost”, as Asghari teaches in [0019].
Regarding claim 6, Bruschi-Asghari teach(es) all the limitations of its base claim from which the claim depends.
Asghari further teaches:
determining the set of control parameters based on the one or more measurements of each of the one or more process variables and one or more historic measurements of each of the one or more process variables ([0018]: “The controller collects information about different DG generation power, storage state of charge, and the end-user demand This will determine discharge pattern of the storage at the time of management which is used to estimate the battery lifetime and consequently calculating the cost of energy from the battery based on a levelized cost model”. This teaches to use the present measurement of “state of charge” and historic measurements of “state of charge” to calculate battery lifetime and the cost of battery energy, and then to determine the control parameters of the battery).
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 based on the teaching of Asghari, to make the system controller wherein the one or more processors are configured to determine the set of control parameters by determining the set of control parameters based on the one or more measurements of each of the one or more process variables and one or more historic measurements of each of the one or more process variables. One of ordinary skill in the art would have been motivated to do this modification since it can help “minimize the operational cost”, as Asghari teaches in [0019].
Regarding claim 7, Bruschi-Asghari teach(es) all the limitations of its base claim from which the claim depends.
Asghari further teaches:
determining a subset of control parameters for each of a plurality of time segments within the time period based on the one or more measurements of each of the one or more process variables ([0018]: “a real-time power and load management controller can be used. The controller collects information about different DG generation power, storage state of charge, and the end-user demand This will determine discharge pattern of the storage at the time of management which is used to estimate the battery lifetime and consequently calculating the cost of energy from the battery based on a levelized cost model. The cost of energy from the battery is then compared to the grid price signal. In this way the end-user can determine whether it is more cost-effective to use its own storage unit or to buy the power from the grid to balance the electric supply and demand In case that the purchase of power from the grid is recommended”. This teaches to determine battery control parameters for discharge in real 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 based on the teaching of Asghari, to make the system controller wherein the one or more processors are configured to determine the set of control parameters based on the one or more measurements of each of the one or more process variables by determining a subset of control parameters for each of a plurality of time segments within the time period based on the one or more measurements of each of the one or more process variables. One of ordinary skill in the art would have been motivated to do this modification since it can help “minimize the operational cost”, as Asghari teaches in [0019].
Claims 14, 15, 16 and 17 recite a computer implemented method comprising operational steps conducted by the electrical system controller in claims 2, 3, 4 and 5 respectively with patentably the same limitations. Therefore, claims 14, 15, 16 and 17 are rejected for the same reason recited in the rejection of claims 2, 3, 4 and 5, respectively.
Claims 19 and 20 recite a non-transitory computer-readable media comprising instructions of operational steps conducted by the electrical system controller in claims 2 and 3 respectively with patentably the same limitations. Therefore, claims 19 and 20 are rejected for the same reason recited in the rejection of claims 2 and 3, respectively.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Bruschi in view of Sun (US 20170244250 A1, hereinafter as “Sun”).
Regarding claim 9, Bruschi teach(es) all the limitations of its base claim from which the claim depends, but does not teach the one or more processors are configured to determine the predicted power load and power generation during the defined time period by determining the predicted power load and power generation based on historical power load and historical power generation of the one or more DERs.
However, Sun teaches in an analogous art:
determining the predicted power load and power generation based on historical power load and historical power generation (FIG. 4B and [0054]: “The method determines 460 an equivalent power generation based on one or combination of historical information of the power generation in the PDS and a current measurement of the power generation in the PDS and determines 470 an equivalent load demand based on one or combination of historical information of the load demand in the PDS and a current measurement of the load demand in the PDS”).
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 Sun, to make the system controller wherein the one or more processors are configured to determine the predicted power load and power generation during the defined time period by determining the predicted power load and power generation based on historical power load and historical power generation of the one or more DERs. One of ordinary skill in the art would have been motivated to do this modification since it can help “provide sufficient accurate estimation results”, as Sun suggests in [0004].
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHARLES CAI whose telephone number is (571)272-7192. The examiner can normally be reached on M-F 8-5 EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kamini Shah can be reached on 571-272-2279. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHARLES CAI/Primary Patent Examiner, Art Unit 2115
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