DETAILED ACTION
Examiner acknowledges receipt of amendment to application 18/675,499 filed on April 1, 2026. 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
Claims 21-40 are still pending, with claims 21, 23, 39 and 40 being currently amended.
Status of Objections and Non-Prior Art Rejections
I. Double Patenting Rejections
The double patenting rejections of claims 21, 39 and 40 still apply and are updated below.
Due to the Terminal Disclaimer over U.S. Patents Nos. 11,117,486 and 11,993,171, which was filed and approved on April 1, 2026, the double patenting rejections no longer apply and are therefore withdrawn.
Response to Arguments
On page 9 of the remarks filed April 1, 2026, Applicant argues:
Further, a transactive energy model is generally understood as a system that uses economic signals (e.g., real-time prices) to manage the generation, consumption, and flow of electricity within a power grid. Instead of the traditional one-way system where a central utility company generates power and sends it to passive consumers at a fixed rate, a transactive energy model creates a decentralized, two-way marketplace. It allows anyone connected to the grid to seamlessly buy and sell energy based on real-time supply and demand.
Nowhere do the other cited references, alone and/or in combination, disclosure or suggest a programmatic method for providing a virtual power plant (VPP) that includes determining a charging schedule for the plurality of electric vehicles (EVs) based on a transactive energy model and a needed availability of the VPP for a microgrid using hierarchical aggregation.
As such amended independent claim 21 is allowable.
Claims 22-38 depend, either directly or indirectly, from amended independent claim 1 and are allowable at least by virtue of their dependence from amended independent claim 21.
Independent claims 39-40 have been amended to include features similar to amended independent claim 1. In addition to paragraph [0009], support may also be found in paragraph [0010] of the published application. As such amended independent claims 19- 20 are also allowable.
Examiner respectfully disagrees. Examiner notes that the cited portions of the specification do not amount to a special definition of “transactive energy model”. The citations indicate examples of what the transactive energy model could be (“the transactive energy model may be determined based on transactive energy information”) but do explicitly define what it is or isn’t to the level that the term. The MPEP states “[t]o act as their own lexicographer, the applicant must clearly set forth a special definition of a claim term in the specification that differs from the plain and ordinary meaning it would otherwise possess.” See MPEP 2111.01 (IV). Thus, the term is interpreted according to the broadest reasonable interpretation.
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 (i.e., changing from AIA to pre-AIA ) 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.
Claims 21-30, 32, 34-35 and 39-40 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Gadh et al. US PGPUB 2013/0179061.
Regarding claims 21 and 40, Gadh discloses a programmatic method for providing a virtual power plant (VPP) [Examiner notes that the only definition in Applicant’s specification for a “virtual power plan” is “a logical construct that represents a sum of decisions rather than a specific power plan” (see [0077] of the PGPUB); in other words, if a prior art reference teaches a logical construct, i.e. a program, which consists of various decisions to create a power plan, it meets the definition of a “virtual power plant”—the “hierarchical” designation is defined as various layers in the network [0025]; so, a system with various levels of control which teaches the taking of various decisions to create a charging schedule teaches a “virtual power plant” with hierarchical control by Applicant’s definition; Gadh teaches such a system which has various layers, including the charging stations (fig. 1, 112), demand response for the grid at large (fig. 1, 122), individual EVs and users (fig. 1, 114a & 110a) and thus teaches making decisions (“virtual power plant”) regarding the schedule based on these layers (hierarchical control) vi an aggregator; pars. 12-14, 65, 102 & 258-259], the programmatic method comprising:
receiving, over a communication network, charging availability information indicating current and expected charging operating status for a plurality of charging apparatuses configured for providing the VPP using a plurality of electric vehicles (EVs) coupled with the plurality of charging apparatuses [fig. 2B; pars. 233-236; a control center aggregates information from charging stations including real time availability and capability of charging stations (par. 61) as well as location of available charging stations (pars. 248 & 254) and future status (pars. 338-340, scheduling of charge for vehicles)];
determining a charging schedule for the plurality of electric vehicles (EVs) based on a transactive energy model and a needed availability of the VPP for a microgrid using hierarchical aggregation [pars. 12-14, 65, 102 & 258-259; see above response to preamble; Gadh teaches such a system which has various layers, including the charging stations (fig. 1, 112), demand response for the grid at large (fig. 1, 122), individual EVs and users (fig. 1, 114a & 110a) and thus teaches making decisions (“virtual power plant”) regarding the schedule based on these layers (hierarchical control) via an aggregator; pars. 258-268 & 271-272, decisions are made to schedule EV charging based on various layers like demand response for the grid, user preferences and demands, available of parking space, local power capabilities; thus included based on charging available information (vehicle availability and charger availability) and needed availability of the VPP (local power capabilities, demand local and grid); pars. 61, 65, 77, 117, 243, 271, 336, “dynamic pricing”, “peak pricing”, “pricing models”, “real-time price”, “minimum price” (for a user selling power back, V2G) and user price and time requirements are used to dynamically schedule charging, thus a “transactive energy model”]; and
transmitting, over the communication network, a charging instruction signal to a first charging apparatus of the plurality of charging apparatuses based on the charging schedule [pars. 65, 102, 107, 112, 239 & 258; based on a charging schedule, electric vehicles are charged, thus a signal is sent to begin the charging].
Regarding claim 40, the method steps would have been obvious to one of ordinary skill based on the teachings of the Gadh reference, above, as pertains to rejection of the apparatus of claim 21. Furthermore, the Gadh reference teaches a non-transitory computer readable storage medium storing instructions that when executed by a computer, perform the claimed method steps [fig. 1; pars. 53-54, 351 & 353; WINSmartEV and control is executed on at least one client computer with memory and a processor].
Regarding claim 22, Gadh discloses wherein the hierarchical aggregation is a logical construct representing a sum of decisions [pars. 12-14, 65, 102 & 258-259; see above response to preamble of claim 21; Gadh teaches such a system which has various layers, including the charging stations (fig. 1, 112), demand response for the grid at large (fig. 1, 122), individual EVs and users (fig. 1, 114a & 110a) and thus teaches making decisions (“virtual power plant”) regarding the schedule based on these layers (hierarchical control) vi an aggregator; pars. 258-268 & 271-272, decisions are made to schedule EV charging based on various layers like demand response for the grid, user preferences and demands, available of parking space, local power capabilities].
Regarding claim 23, Gadh discloses wherein the transactive energy model includes [pars. 61, 65, 77, 117, 243, 271, 336, “dynamic pricing”, “peak pricing”, “pricing models”, “real-time price”, “minimum price” (for a user selling power back, V2G) and user price and time requirements are used to dynamically schedule charging, thus a “transactive energy model”].
Regarding claim 24, Gadh discloses wherein the transactive energy information is determined based on charging availability information [pars. 61, 65, 102, 258, 263, 271 and 336; scheduling for charging an EV is determined based on numerous factors including availability information and power resource information (i.e. “selection of charge parameters e.g. fast charge, cheap charge, fully customizable selection of price, time”)].
Regarding claim 25, Gadh discloses wherein the transactive energy information is determined based on alternative power resource information indicating availability and pricing of electric power for supply to the microgrid from an alternative power resource [pars. 11, 133, 280-282, 286-288, 296 & 327; solar and renewable energy resources are considered as supply to the local microgrid (“it can be directed to be stored within the external battery system installed or to power the lighting of the parking structure, or to backfill into the grid, or charge the EVs that are connected to the charging station”) based on availability of the power and the cost of energy usage].
Regarding claim 26, Gadh discloses wherein the transactive energy information is further determined from a transactive energy model [pars. 258-268, 271-272 & 339; the charging schedule is adapted to meet demand response (transactive information) and altered based on price information (transactive information); thus a transactive energy model as defined by Applicant in [0026] of the PGPUB; a model based on market information].
Regarding claim 27, Gadh discloses receiving, over the communication network, other power resource information indicating availability and pricing of electric power from a plurality of other microgrids associated with the microgrid [pars. 61, 243, 271, 286-307; information regarding availability of power at various other microgrids (locations at which “EV solar power sources” are located and locations at which EVs are charged) is used to for “local grid balancing and management”
Regarding claim 28, Gadh discloses wherein the plurality of other microgrids extends from at least one of a distribution power grid and a premises distribution network [pars. 15-17, 53, 57, 61, 84, 98-99, 273-281 & 336; fig. 9; a plurality of sub-grids (fig. 9, areas 1-4) with charging stations 904 can each charge with grid power or feed power back to the power grid (pars. 17-18) based on central control, thus the sub-grids extend from a distribution power grid].
Regarding claim 29, Gadh discloses wherein the plurality of other microgrids extends from different electric power distribution nodes [pars. 15-17, 53, 57, 61, 84, 98-99, 273-281 & 336; fig. 9; each sub-grid can have a separate grid-tie inverter, thus different electric power distribution nodes].
Regarding claim 30, Gadh discloses wherein the charging schedule is configured for maintaining a load balance at the microgrid and the plurality of other microgrids [pars. 64-69, 100, 116, 258, 261-265 & 315; charging schedule is determined to dynamically schedule charging at the charging stations to balance the grid (and thus the connected microgrids) using time restrictions and load limits to provide grid stability; par. 116, the central controller can device the “charging capacity of each area”)].
Regarding claim 32, Gadh discloses wherein the plurality of charging apparatuses is configured to provide local ancillary services for the microgrid [par. 75; backfill into the local grid during times of peak demand].
Regarding claim 34, Gadh discloses wherein the microgrid is associated with an alternative power resource [pars. 286-288; a particular microgrid (parking structure with charging station) may have solar resources].
Regarding claim 35, Gadh discloses wherein the alternative power resource is a renewable energy resource [pars. 286-288; a particular microgrid (parking structure with charging station) may have solar resources].
Regarding claim 39, Gadh discloses a device configured for providing a virtual power plant (VPP) using a plurality of charging apparatuses [Examiner notes that the only definition in Applicant’s specification for a “virtual power plan” is “a logical construct that represents a sum of decisions rather than a specific power plan” (see [0077] of the PGPUB); in other words, if a prior art reference teaches a logical construct, i.e. a program, which consists of various decisions to create a power plan, it meets the definition of a “virtual power plant”—the “hierarchical” designation is defined as various layers in the network [0025]; so, a system with various levels of control which teaches the taking of various decisions to create a charging schedule teaches a “virtual power plant” with hierarchical control by Applicant’s definition; Gadh teaches such a system which has various layers, including the charging stations (fig. 1, 112), demand response for the grid at large (fig. 1, 122), individual EVs and users (fig. 1, 114a & 110a) and thus teaches making decisions (“virtual power plant”) regarding the schedule based on these layers (hierarchical control) vi an aggregator; pars. 12-14, 65, 102 & 258-259], the device comprising:
a memory; and at least one processor [fig. 1; pars. 53-54, 351 & 353; WINSmartEV and control is executed on at least one client computer with memory and a processor] configured for:
receiving, over a communication network, charging availability information indicating current and expected charging operating status for the plurality of charging apparatuses configured for providing the VPP using a plurality of electric vehicles (EVs) coupled with the plurality of charging apparatuses [fig. 2B; pars. 233-236; a control center aggregates information from charging stations including real time availability and capability of charging stations (par. 61) as well as location of available charging stations (pars. 248 & 254) and future status (pars. 338-340, scheduling of charge for vehicles)];
determining a charging schedule for the plurality of EVs based on the a transactive energy model and a needed availability of the VPP using hierarchical aggregation [pars. 12-14, 65, 102 & 258-259; see above response to preamble ; Gadh teaches such a system which has various layers, including the charging stations (fig. 1, 112), demand response for the grid at large (fig. 1, 122), individual EVs and users (fig. 1, 114a & 110a) and thus teaches making decisions (“virtual power plant”) regarding the schedule based on these layers (hierarchical control) via an aggregator; pars. 258-268 & 271-272, decisions are made to schedule EV charging based on various layers like demand response for the grid, user preferences and demands, available of parking space, local power capabilities; thus included based on charging available information (vehicle availability and charger availability) and needed availability of the VPP (local power capabilities, demand local and grid); pars. 61, 65, 77, 117, 243, 271, 336, “dynamic pricing”, “peak pricing”, “pricing models”, “real-time price”, “minimum price” (for a user selling power back, V2G) and user price and time requirements are used to dynamically schedule charging, thus a “transactive energy model”]; and
transmitting, over the communication network, a charging instruction signal to a first charging apparatus of the plurality of charging apparatuses based on the charging schedule [pars. 65, 102, 107, 112, 239 & 258; based on a charging schedule, electric vehicles are charged, thus a signal is sent to begin the charging].
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.
Claim 31 is rejected under 35 U.S.C. 103 as being unpatentable over Gadh et al. US PGPUB 2013/0179061 in view of Ansari et al. US PGPUB
Regarding claim 31, Gadh does not explicitly disclose wherein the transactive energy information is received over the communication network from an auctioning agent that establishes pricing for supply of electric power for the microgrid and the plurality of other microgrids.
However, Ansari further discloses wherein the transactive energy information is received over the communication network from an auctioning agent that establishes pricing for supply of electric power for the microgrid and the plurality of other microgrids [fig. 1, pars. 12, 19, 47-51 & 55; computers on a network communicate information regarding an auctioning process including bids for power to charge electric vehicles at a plurality of charging stations 112, thus establishing pricing for charging].
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to modify Gadh to further include wherein the transactive energy information is received over the communication network from an auctioning agent that establishes pricing for supply of electric power for the microgrid and the plurality of other microgrids for the purpose of resolving a capacity shortfall using competitive pricing, as taught by Ansari (pars. 18-19).
Claims 33 are rejected under 35 U.S.C. 103 as being unpatentable over Gadh et al. US PGPUB 2013/0179061 in view of Gadh II US PGPUB 2014/0203077.
Regarding claim 33, Gadh does not explicitly disclose wherein the local ancillary services include frequency stabilization and voltage control for the microgrid.
However, Gadh II discloses an electric vehicle charging system wherein the local ancillary services include frequency stabilization and voltage control for the microgrid [abs.; par. 18 & 77; frequency stabilization and voltage control].
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to modify Gadh to further include wherein the local ancillary services include frequency stabilization and voltage control for the microgrid for the purpose of stabilizing and smoothing the local grid, as taught by Gadh II (pars. 18 & 77).
Claims 36-38 are rejected under 35 U.S.C. 103 as being unpatentable over Gadh et al. US PGPUB 2013/0179061 in view of North et al. US PGPUB 2016/0332527.
Regarding claim 36, Gadh does not explicitly disclose wherein the plurality of EVs is at least a portion of an EV fleet.
However, North discloses an electric vehicle charging system wherein the plurality of EVs is at least a portion of an EV fleet [pars. 8-9, 11, 22, 31, 46 & 52].
It would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to modify Gadh to further include wherein the plurality of EVs is at least a portion of an EV fleet for the purpose of enabling the control of charging/discharging for an entire fleet of vehicles, as taught by North (pars. 8-9, 11, 22, 31, 46 & 52).
Regarding claims 37 and 38, Gadh does not explicitly disclose wherein the plurality of charging apparatuses are associated with a depot for the EV fleet or wherein the EV fleet is an EV bus fleet.
However, Admitted Prior Art discloses charging a fleet of public vehicles like buses and conduct the charging or storage in a depot, like is done in cities with fleets of electric buses in Asia. Therefore, it would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to modify Gadh to further include wherein the plurality of charging apparatuses are associated with a depot for the EV fleet or wherein the EV fleet is an EV bus fleet for the purpose of reducing pollution by using electric vehicles for public transport and storing them in a large enough facility that protects them from the elements, and since it has been held to be within the general skill of a worker in the art to apply a known technique to a known device (method, or product) ready for improvement to yield predictable results is obvious. KSR International Co. v Teleflex Inc., 550 U.S. 398, 127 S. Ct. 1727, 82 USPQ2d 1385, 1395-97 (2007).
NB: Examiner took Official Notice with respect to the above limitation of claims 37-38 in the Non-Final Rejection mailed October 1, 2025. Applicant did not traverse or did not adequately traverse. Thus, the limitation is being treated as taught by admitted prior art. See MPEP 2144.03.
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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID V HENZE whose telephone number is (571)272-3317. The examiner can normally be reached M to F, 9am to 7pm.
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/DAVID V HENZE/Primary Examiner, Art Unit 2859
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