DETAILED ACTION
Examiner acknowledges receipt of amendment to application 18/675,499 filed on September 8, 2026. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on September 8, 2026 has been entered.
Status of Claims
Claims 21-22, 24-25, 28-30 and 32-40 are still pending, with claims 21, 24-25, 28-30 and 39-40 being currently amended. Claims 23, 26-27 and 31 are cancelled.
Response to Arguments
On pages 7-8 of the remarks filed May 6, 2026, Applicant argues:
The Office has already found, in rejecting former claim 31 under § 103, that Gadh does not disclose this limitation standing alone, relying on Ansari solely for the auctioning concept. Gadh discloses dynamic, peak, and real-time pricing (Gadh at paragraphs 0061, 0065, 0077, 0117, 0243, 0271, and 0336) but does not disclose or suggest an auctioning agent of any kind. Because Gadh alone does not disclose this newly-added limitation, Gadh alone can no longer anticipate amended independent claims 21, 39, or 40, or the claims depending therefrom. The Gadh and Ansari Combination Does Not Reach the Amended Claims
To the extent the Office maintains that the combination of Gadh and Ansari renders the amended claims obvious, Applicant respectfully submits that neither reference, alone or in combination, discloses or suggests an auctioning agent that establishes pricing for supply of electric power across a microgrid and a plurality of other microgrids, as now required.
Ansari's auctioning mechanism is expressly scoped to resolving a solar-generation capacity shortfall at a single charging system: Ansari discloses determining a requested charge and a requested charge time for a plurality of electric vehicles at one charging system, comparing those values against that system's own solar charge capacity and charge time capacity, and, only when a shortfall is found, auctioning that system's own solar charge capacity to the operators of the electric vehicles at that same system. Ansari contains no disclosure of, and provides no motivation to extend its auction beyond, a single charging installation.
Gadh, for its part, discloses an aggregator coordinating charging across a network of microgrids based on dynamic and peak pricing, but nowhere discloses or suggests an auctioning mechanism of any kind, whether confined to a single site or extended across a network. A person of ordinary skill combining Gadh and Ansari would, at most, arrive at Ansari's single-site solar- shortfall auction bolted onto Gadh's pricing-aware scheduler; there is no disclosure in either reference, and no articulated reasoning in the Office Action, that would have led a person of ordinary skill to extend Ansari's single-system auction across the plurality of separately-operated microgrids that Gadh's aggregator coordinates. Absent such a showing, the rejection cannot be sustained as to the amended claims. See KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398, 418 (2007) (obviousness requires "some articulated reasoning with some rational underpinning" to support the combination).
Examiner respectfully disagrees. Examiner notes that Ansari teaches a charging system which auctions off energy based on bids (thus an auctioning agent which receives and sends transactive energy and establishes pricing) sent over a communication network (par. 51, “over a network such as the internet or satellite or cell phone networks”), the bids establishing pricing for supply of energy to any of the charging stations 112 (microgrids) that would supply energy to one of the vehicles bidding for energy. Thus Ansari teaches 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. One would be motivated to apply the auctioning agent to Gadh for the purpose of allowing operators to bid against each other to resolve the capacity shortfall, as taught by Ansar in paragraph 18.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). In this case, Gadh teaches all of the claim except for the auctioning agent establishing pricing for a plurality of microgrids, which is taught by Ansar. Furthermore, the test for obviousness is not whether the secondary reference could be bodily incorporated in the primary reference, but rather, whether the teachings of the prior art as a whole render the claimed invention obviousness. See MPEP 2145(III).
The “articulated reason” is simple, establishing a competitive system for pricing by using bids, as taught by Ansari. Thus, a prima facie case for obviousness has been made.
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 21-22, 24-25, 28-30, 32, 34-35 and 39-40 are 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 2012/0259723.
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 plant” isv “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)];
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”];
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, wherein the transactive energy model is determined based on transactive energy information [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; 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; thus a “transactive energy model” based on transactive energy information] 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].
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).
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 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 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)];
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”];
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, wherein the transactive energy model is determined based on transactive energy information [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; 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; thus a “transactive energy model” based on transactive energy information] 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].
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 Ansari et al. US PGPUB 2012/0259723 and 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 Ansari et al. US PGPUB 2012/0259723 and 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
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/DAVID V HENZE/Primary Examiner, Art Unit 2859
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