DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 Information Disclosure Statement, filed 25 January 2024 has been fully considered by the examiner. A signed copy is attached.
Claims 1-20 are pending.
Claims 1-20 are rejected, grounds follow.
Claim Rejections - 35 USC § 102
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(s) 1-3, 6-11, and 14-20 is/are rejected under 35 U.S.C. 102(a)(1)/102(a)(2) as being anticipated by Chen et al., US Pg-Pub 2013/0257372.
Regarding Claim 1, Chen discloses:
A system (see figs. 1-4) comprising: a computer-readable storage medium (see e.g. fig. 4 and [0043]) having executable instructions ([0044] “processor 802 may retrieve (or fetch) the instructions”) for providing charging control to a plurality of electric controllable assets (fig. 1, EVs 115) which include at least some electric vehicles (EVs); (([0004] “determining optimal recharging schedules for electric vehicles within an electricity distribution network”) and one or more computer processors ([0044] “processor 802”, see fig. 1, server 120)
configured to execute the instructions to: determine, by a power flow analyzer, (e.g. [0033] “suitable power flow analysis method”) power flow information of a power grid, (fig. 1, grid 101; see [0019] “Particular embodiments may optimize electric vehicle recharging within the power system by optimizing the total demand of the power system. … Total Demand (t) and H(t), the base demand profile (e.g. in kW) for all households at a particular time step (t).”)
the power grid for providing power to the controllable assets for charging, ([0011] “An electrical substation 102 at the edge of power grid 101 may transform electricity from power grid 101 from a high voltage (e.g., 110 kV or higher) to an intermediate voltage (e.g., 50 kV or less), and deliver electricity to end customers through an electricity distribution network 120.”)
the power flow information including technical constraint information relating to the power grid; ([0033] “In particular embodiments, server 120 may determine whether any system constraint violation exists (at 303).”)
generate, by a charging controller, charging control information ([0031] “server 120 may determine optimal recharging schedules for electric vehicles within the power system without system constraints over a pre-determined period of time T (at 301).”) for providing charging control to the controllable assets based on the power flow information; ([0031] “For example, server 120 may determine optimal recharging schedules by optimizing the total demand of the power system based on customer recharging schedules (defined by the plug-in time TP.sub.i and the unplug time TUP.sub.i for each i-th node connecting to an electric vehicle) described earlier.”)
provide the charging control information to at least some of the controllable assets; ([0040] “server 120 may transmit messages to charging equipment 111; the messages may include optimal recharging schedules determined by the example method of FIG. 3, causing charging equipment 111 to recharge respectively connected electric vehicles accordingly.”)
provide at least part of the charging control information to the power flow analyzer; (see fig. 3, particularly the lines from 305 and 306 back to 302, and [0035] “for each system constraint violation for the m-th component, the charging loads for the i-th electric vehicles identified with the highest sensitivity coefficient .alpha..sub.im may be adjusted first. In other embodiments, the charging loads for all electric vehicles with positive sensitivity coefficients may be adjusted.”)
and determine, by the power flow analyzer, new power flow information of the power grid for a subsequent time period based on the at least part of the charging control information. (see fig. 3, and [0038] “After adjusting recharging schedules for identified electric vehicles at the current time step t, server 120 may determine system outputs for the current time step (at 302), and determine whether any system constraint violation exists (at 303). In some embodiments, if there are no system constraint violations, the adjusted recharging schedule is the optimal solution; in other embodiments, it may be the near-optimal solution. Server 120 may increment time step (at 306), determine system outputs (at 302), and determine whether any system constraint exists for the next time step (at 303).”)
Regarding Claims 9 and 17, these claims recite substantively the same subject matter, except embodied as a method and a non-transitory computer readable medium, respectively; Mutatis mutandis, these claims are likewise anticipated by Chen for the same reasons articulated with respect to claim 1.
Regarding Claims 2, 10, and 18, Chen discloses all of the limitations of parent claims 1, 9 and 17, respectively;
Chen further discloses:
(claim 2 representative) generate, by the charging controller, new charging control information associated with the subsequent time period based on the new power flow information. ([0034] “If there is no system constraint violation, server 120 may increment time step t (at 306). Server 120 may continue determining system outputs (at 302), and determining whether any system constraint violation exists for the next time step (at 303).”)
Regarding Claims 3 and 11, Chen discloses all of the limitations of parent claims 1, 9, and 10, respectively;
Chen further discloses:
(claim 3 representative) wherein the determining the power flow information of the power grid by the power flow analyzer ([0029] “The determining of the power system's outputs based on a set of inputs may be implemented using power flow analysis algorithms”) is based on topology information and electrical measurement information of the power grid. ([0026] “The example method of FIG. 2 may determine sensitivity of the power system (e.g., voltages or currents at bus nodes and components) caused by each potential electric vehicle-connecting node.” [0028] “Particular embodiments may determine a sensitivity coefficient .alpha..sub.im for the m-th bus node or component in response to electric vehicle recharging at the i-th node by calculating the ratio between the change in voltage or current at the m-th bus node or component and the change in load at the i-th node”)
Regarding Claims 6 and 14, Chen discloses all of the limitations of parent claims 1 and 9, respectively;
Chen further discloses:
(Claim 6 representative) wherein the generating charging control information is further based on predicted load information of the power grid, wherein the predicted load information includes a predicted electric load in a section of the power grid in a future time period. ([0019] “wherein H(t) is the base demand profile (e.g., in kW) for all households of the power system at the particular time step t (without electric vehicle recharging). H(t) may be a measured number or a predicted number based on previous energy consumption.”)
Regarding Claims 7, 15 and 19, Chen discloses all of the limitations of parent claims 1, 9, and 17, respectively;
Chen further discloses:
wherein the technical constraint information of the power grid comprises operational limit information of one or more distribution transformers in the power grid. ([0024] “Meanwhile, optimization of the total demand may be subject to system constraints at components such that the components (e.g., power lines, transformers, switches, etc.) should be operated within the maximum-rated capacity (e.g., maximum-allowable current level).”)
Regarding Claims 8, 16, and 20, Chen discloses all of the limitations of parent claims 1, 9, and 17, respectively;
Chen further discloses:
wherein the generating charging control information is based at least in part on an optimization for minimizing violations of the technical constraint information in the power grid. ([0037] “In some embodiments, if there are multiple system constraint violations, charging loads for electric vehicles identified with the most significant system constraint violations may be adjusted first.” [0038] “After adjusting recharging schedules for identified electric vehicles at the current time step t, server 120 may determine system outputs for the current time step (at 302), and determine whether any system constraint violation exists (at 303).”)
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.
Claim(s) 4-5 and 12-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen in view of Bhargava et al., US Pg-Pub 2022/0009372.
Regarding Claims 4 and 12, Chen teaches all of the limitations of parent claims 1 and 9, respectively;
Chen differs from the claimed invention in that:
Chen does not appear to clearly articulate: (claim 4 representative) generate, by a demand-response recommender, recommended load curtailment information,
the recommended load curtailment information including details for load curtailment in the power grid,
wherein at least one of:
the recommended load curtailment information is provided to the charging controller, and wherein the generating charging control information is based on the recommended load curtailment information;
and wherein the recommended load curtailment information is provided an operator of the power grid.
That is, Chen does not refer to demand-response events in the power grid when calculating the charging schedules.
However, Bhargava teaches a power utility which includes generating recommended demand-response events (Bhargava [0057] “specified demand response events”) which including information regarding recommend load curtailment (e.g. [0057] “utility load management objectives and distribution system constraints.”; [0064] “periods during which EV charging cannot occur”) where the load curtailment information can be provided to the charging controller ([0064] “the load manager 605 can implement the capability to respond to demand response (DR) events generated by the utility 601 that indicate periods during which EV charging cannot occur, by communicating directly with vehicles to carry out utility requirements. DR events can be received from a utility 601 in formats that can include simple email notification or more elaborate protocols such as an Open Automated Demand Response (OpenADR), depending on the embodiment.”) for generating charge control information ([0053] “load manager 605 to manage charging under specified demand response events, and subsequently for daily charge scheduling in coordination with utility load management objectives and distribution system constraints.”)
Bhargava and Chen are analogous art because they are from the same field of endeavor as the claimed invention of EV charging scheduling in power distribution systems.
Accordingly, Examiner finds 1) the prior art contained a ‘base’ device (method, or product) upon which the claimed invention can be seen as an “improvement”– the system (method, etc.) of Chen, upon which the incorporation of Demand Response load curtailment features can be regarded as an “improvement”; 2) the prior art contained a “comparable” device (method, or product, that is not the same as the base device) that has been improved in the same way as the claimed invention; - the teachings of Bhargava, which are an EV Charge scheduling system that has been improved by the incorporation of Demand Response load curtailment features in the scheduler; 3) one of ordinary skill in the art before the effective filing date of the application could have applied the known “improvement” technique in the same way to be the “base” device (method or product) and the results would have been predictable to one of ordinary skill in the art as a means to coordinate charging schedules with overall utility load management objectives as suggested by Bhargava ([0057] “These capabilities can be used by load manager 605 to manage charging under specified demand response events, and subsequently for daily charge scheduling in coordination with utility load management objectives and distribution system constraints.”) and because Chen teaches receiving a system constraint from the utility for total power delivery at each bus ([0024] “That is, optimization of the total demand may be subject to system constraints at the PQ buses where the real power |P| and the reactive power |Q| are specified”) and accordingly the improvement would have been obvious to one having ordinary skill in the art before the effective filing date of the application (See MPEP 2143.I.C).
Regarding Claims 5 and 13, Chen in view of Bhargava teaches all of the limitations of parent claims 4 and 12, respectively;
Bhargava further teaches:
wherein the recommended load curtailment information is provided to the power flow analyzer, ([0062] “The utility 601 can convey demand response events to load manager 605. Smart meter data can be used for verifying EV load measurements and reductions through an independent monitoring channel, and to enable more comprehensive analysis and additional system context. Distribution network information, including relational and asset data, can be used to support advanced system awareness tools and associated load management strategies.”)
Chen further teaches:
and wherein the determining new power flow information of the power grid for the subsequent time period is based on the recommended load curtailment information; (Chen teaches constraints including maximum delivered real power (P) and reactive power (Q); [0024] “That is, optimization of the total demand may be subject to system constraints at the PQ buses where the real power |P| and the reactive power |Q| are specified”)
and wherein the generating, by the charging controller, of the new charging control information associated with the subsequent time period is based on the new power flow information. ([0041] “Particular embodiments may optimize total demand of the power system further based on fairness among electric vehicle recharging customers. For example, assume that the charging load for a particular electric vehicle is reduced for time step t as at 305 of the example method of FIG. 3. Particular embodiments may compensate (or penalize less) the particular electric vehicle for the next time step t+1 to avoid service starvation for the particular electric vehicle.”)
Accordingly, Examiner finds 1) the prior art contained a ‘base’ device (method, or product) upon which the claimed invention can be seen as an “improvement”– the system (method, etc.) of Chen, upon which the incorporation of Demand Response load curtailment features can be regarded as an “improvement”; 2) the prior art contained a “comparable” device (method, or product, that is not the same as the base device) that has been improved in the same way as the claimed invention; - the teachings of Bhargava, which are an EV Charge scheduling system that has been improved by the incorporation of Demand Response load curtailment features in the scheduler; 3) one of ordinary skill in the art before the effective filing date of the application could have applied the known “improvement” technique in the same way to be the “base” device (method or product) and the results would have been predictable to one of ordinary skill in the art as a means to coordinate charging schedules with overall utility load management objectives as suggested by Bhargava ([0057] “These capabilities can be used by load manager 605 to manage charging under specified demand response events, and subsequently for daily charge scheduling in coordination with utility load management objectives and distribution system constraints.”) and because Chen teaches receiving a system constraint from the utility for total power delivery at each bus ([0024] “That is, optimization of the total demand may be subject to system constraints at the PQ buses where the real power |P| and the reactive power |Q| are specified”) and accordingly the improvement would have been obvious to one having ordinary skill in the art before the effective filing date of the application (See MPEP 2143.I.C).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Tate, Jr. et al., US Pg-Pub 2010/0280675 – teaching many of the features of the independent claims (see figs. 3 and 4).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOSHUA T SANDERS whose telephone number is (571)272-5591. The examiner can normally be reached Generally Monday through Friday.
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/J.T.S./Examiner, Art Unit 2119
/MOHAMMAD ALI/Supervisory Patent Examiner, Art Unit 2119