DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This Office Action is responsive to communication filed on 6/21/2024.
Claims 1-20 are pending and presented for examination.
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim 9 is rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the enablement requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention.
Regarding claim 9
Claim 9 is rejected for lack of enablement because, under the broadest reasonable interpretation, the recited “zonal adaptive policy” that “includes standard rules for using zonal control resources to mitigate operation and non-operational violations in the at least one transmission zone” is drafted broadly to cover rules that utilize unspecified “zonal control resources” (note: the specification does not define or provide any example of what a zonal control resource is and thus could encompass any piece of hardware, software, policy or organization related to the zone) to mitigate/address a wide variety of operation and non-operational violations. The specification merely states that non-operational violations “may relate to at least one of a power grid maintenance, hardware, software, or a communication, operator, or cybersecurity related issue.” The specification lacks any concrete examples or teachings of rules that use a particular zonal control resource to mitigate non-operational violations, specifically relating to issues tied to human operators, grid maintenance, or cybersecurity, such that a person of ordinary skill in the art would be required to engage in extensive trial-and-error and additional inventive effort to devise and implement rules for using zonal control resources to mitigate all of the claimed species of non-operational violations (note that the preceding paragraph addresses at least the following Wands factors: (A) the breadth of the claims, (B) the nature of the invention, (D) the level of one of ordinary skill in the art, (F) the amount of direction provided by the inventor, and (H) the quantity of experimentation needed to make or use the invention based on the content of the disclosure).
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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 1
“The examiner’s focus during examination of claims for compliance with the requirement for definiteness of 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph, is whether the claim meets the threshold requirements of clarity and precision set forth in the statute, not whether more suitable language or modes of expression are available. […] In reviewing a claim for compliance with 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph, the examiner must consider the claim as a whole to determine whether the claim apprises one of ordinary skill in the art of its scope and, therefore, serves the notice function required by 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph, by providing clear warning to others as to what constitutes infringement of the patent.” MPEP 2173.02(II).
The claim language, when read as a whole, includes ambiguous relationships among the recited method steps and actors such that the cooperative interactions of the “zonal operational data”, “zonal forecast data,” “zonal adaptive policy” and “intervention command” are not clearly defined. Thus, the claim fails to particularly point out and distinctly claim the subject matter regarded as the invention and does not apprise one of ordinary skill of its scope with reasonably certainty. For example, the first limitation of claim 1 recites “receiving zonal operational data from a power grid comprising a plurality of transmission zones”. However, this is unclear. Is the zonal operational data associated with a specific transmission zone of the plurality of transmission zones of the power grid; for example, is the zonal operational data collected from the zonal controllers (like that of the zonal forecast data) or is the zonal operational data collected directly (e.g., by an unclaimed actor such as a grid controller)? The fourth limitation of the claim recites “communicating the zonal adaptive policy to at least one of the plurality of zonal controllers”. However, in view of the third limitation of the claim, this is unclear. The third limitation recites “determining a zonal adaptive policy for at least one transmission zone of the plurality of transmission zones” indicating that the zonal adaptive policy is a policy specific to an identified zone and thus associated with a specific zonal controller. However, the fourth limitation recites that the zonal adaptive policy is communicated to any zonal controller. The last limitation of the claim recites “to interview with the normal mode of operation”. However, the intervention command is sent to “the zonal controller associated with the at least one transmission zone.” On the other hand, the normal mode of operation is recited as being associated with the zonal adaptive policy, which is sent to an unspecified zonal controller (i.e., not necessarily the zonal controller receiving the intervention command). The relationship between these is unclear because it appears that the policy intervention is potentially going to a different controller than the one with the normal mode policy.
Dependent claims are likewise rejected.
Regarding claim 4
Claim 4 recites “a federated grid modelling agent”, which is new terminology and does not have a recognized meaning in the art and is not clearly defined in the specification, but is instead only described in terms of what it “may” do. MPEP 2173.05(a).
Claim 4 recites “the power grid is modeled”, but it’s not clear whether this is a required method step or not. Dependent claims are likewise rejected.
Regarding claim 9
Claim 9 recites “using zonal control resources to mitigate operation and non-operation violations”, however, this is unclear. The term “zonal control resource” is new terminology and the specification does provide a definition or any example(s) of what a zonal control resource is or may be. Thus, one of ordinary skill in the art would not be apprised of the scope of the claimed “zonal control resources” or how such resources are utilized within the method, and therefore would not be reasonably informed of the metes and bounds of the claim.
Regarding claim 18
Claim 18 recites “generating at least one of a short-term forecast or a long-term forecast” however “short-term” and “long-term” are relative terminology. MPEP 2173.05(b).
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 1-3, 7-9, 14, 16, 17 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over DUAN (US20210143639A1) in view of YONEZAWA (US20130079940A1) (hereinafter – “DUAN-YONEZAWA”).
Regarding claim 1
DUAN teaches a method comprising:
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DUAN, Fig. 4
receiving zonal operational data from a power grid comprising a plurality of transmission zones (Abstract, [0011]: method includes acquiring state information at buses of the electric power system; [0052], [0084], [0085]: “a power grid is partitioned into different regions and assigned an artificial intelligent (AI) agent for each region in step 410. Then state information of the power grid is inputted to the MA-AVC system instep 420. The state information includes phasor measurement unit (PMU) and supervisory control and data acquisition (SCADA) measurements, such as bus voltage magnitude” i.e., the power grid is partitioned into different regions/transmission zones and thus the power grid comprises a plurality of transmission zones, [0053]: each transmission zone is associated with an AI agent that functions as a controller, Fig. 1A zones A-F);
determining a zonal adaptive policy for at least one transmission zone of the plurality of transmission zones based on the zonal operational data and the zonal forecast data, the zonal adaptive policy defining a rule for a zonal controller associated with at least one transmission zone in a normal mode of operation (Abstract, [0011]: “maintaining a second action setting by a second AI agent assigned to a second region of the electric power system where no substantial state violation is detected” [0084]: “MA-AVC system determines which AI agent(s)should take actions based on the input state information, e.g., a bus voltage violation”, i.e., when no state violation is detected the transmission zone is in a normal mode of operation and in response to no violation/normal mode of operation the zonal adaptive policy is to maintain the current setting);
communicating the zonal adaptive policy to at least one of the plurality of zonal controllers ([0009]: “what is desired is effective voltage control systems and methods implemented in a decentralized and data-driven fashion” [0011]: “maintaining a second action setting by a second AI agent assigned to a second region of the electric power system where no substantial state violation is detected” [0043]: “decentralized execution mechanism in the proposed MA-AVC scheme can be applied to large-scale intricate energy networks with low computational complexity for each agent. Meanwhile, it addresses the communication delay and the single-point failure issue of the centralized control scheme”, Fig. 4 #430 “determine specific agent(s) that should take actions based on the state information” implies decentralized execution)
communicating an intervention command to the a zonal controller associated with the at least one transmission zone to intervene with the normal mode of operation and adjust an operational parameter of the at least one transmission zone (Abstract, [0011]: “generating a first action setting based on the state violation using a deep reinforcement learning (DRL) algorithm by a first artificial intelligent (AI) agent assigned to a first region of the electric power system where the state violation occurs” [0084]: “MA-AVC system determines which AI agent(s) should take actions based on the input state information, e.g., a bus voltage violation”, Fig. 4 #440, 450, i.e., when a state violation is detected in a zone the associated agent/controller generates a first action to bring zonal parameters within limits, thereby intervening in the normal mode of operation).
In summary, DUAN teaches to partition and receive zonal operational data from a plurality of transmission zones of a power grid such that zonal agents/controllers generate specific actions to alter operations of that zone. DUAN further teaches to maintain settings in one zone if there are no violations detected, and also teaches to change settings in a different zone when is/are violation(s) detected. DUAN does not explicitly teach to maintain settings in one zone if there are no violations detected and then to change settings in that same zone when there is a violation detected. However, before the effective filing date of the claimed invention, one of ordinary skill in the art would have found it obvious to alter DUAN such that the zonal agent/controller associated with a zone would receive and implement an intervention command to the zonal agent/controller in response to a detected violation such that the violation would be corrected, by altering the normal mode of operation, before a power flow failure would occur as a result of the violation, thereby intervening with the normal mode of operation as the claim requires, as suggested by DUAN ([0052]: for automatic voltage control “the goal is to bring the system voltage profiles back to normal after unexpected disturbances”).
DUAN is not relied on to receive zonal forecast data from the plurality of zonal controllers. However, YONEZAWA in an analogous art teaches a method of collecting data in an energy management system comprising collecting demand forecast data from a plurality of nodes ([0023], [0032], Claim 8). DUAN teaches a method automatic voltage control for a power grid comprising collecting operational data such that the system can respond to disturbances for the purposes of voltage control. YONEZAWA teaches to collect forecasted load data for an energy management system. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify DUAN’s method to include YONEZAWA’s step of receiving forecast data from a plurality of zones because such a modification is the result of applying a known technique to a known dev ice ready for improvement to yield predictable results. More specifically, YONEZAWA’s step of receiving forecast data from a plurality of zones permits initial configuration of the system. This known benefit is applicable to DUAN’s method as they both share characteristics and capabilities, namely, they are directed to management of energy systems. Therefore, it would have been recognized that modifying DUAN’s method to include YONEZAWA’s forecasted loads would have yielded predictable results because (i) the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate YONEZAWA’s forecasted loads in energy management systems and (ii) the benefits of such a combination would have been recognized by those of ordinary skill in the art.
Regarding claim 2
DUAN-YONEZAWA teaches the elements of claim 1 as outlined above.
DUAN also teaches wherein the zonal controller communicates a command to adjust the operational parameter of the at least one transmission zone in accordance with the zonal adaptive policy in the normal mode of operation (Fig. 4, #450, [0085]).
Regarding claim 3
DUAN-YONEZAWA teaches the elements of claim 1 as outlined above.
DUAN also teaches receiving load data from a plurality of distribution zones in a power grid and wherein the zonal adaptive policy is determined based, at least in part, on the load data ([0041]: “DRL-based agent in the proposed MA-AVC scheme can […] adapt its behavior to new changes including load” [0055]: states are used to define loads, [0083], [0095]).
Regarding claim 7
DUAN-YONEZAWA teaches the elements of claim 1 as outlined above.
DUAN also teaches to determine a zonal orchestration index associated with a particular zone ([0062]: performance measure of policy for agent). DUAN also teaches that a known problem associated with centralized control is that they require “sophisticated communication networks to collect global operating conditions and requires a powerful central controller to process a huge amount of information” ([0006]). Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify DUAN-YONEZAWA in view of DUAN such that DUAN-YONEZAWA’s zonal controllers/agents would determine the orchestration index/performance measure such that a vector representing a performance measure would be transmitted with the operational data rather than transmitting all data required to determine the orchestration index for the purposes reducing the burden on the communication system and reducing the workload of the central processor, as taught by DUAN.
Regarding claim 8
DUAN-YONEZAWA teaches the elements of claim 1 as outlined above.
DUAN also teaches wherein the zonal adaptive policy is generated by a zonal autonomous control and management engine that includes an adaptive policy machine learning model trained on historical zonal operational data for the plurality of zonal controllers ([0040]: “a novel multi-agent AVC (MA-AVC) scheme is proposed to maintain voltage magnitudes within their operation limits […] the MA-AVC problem is formulated as a Markov Game with a bi-layer reward design considering the cooperation level. Third, a multi-agent deep deterministic policy gradient (MADDPG) algorithm, which is a multi-agent, off-policy and actor-critic DRL algorithm, is modified and reformulated for the AVC problem” [0047]: “DRL-based agent in the proposed MA-AVC scheme can learn its control policy through massive offline training without needs to model complicated physical systems and adapt its behavior to new changes including load/generation variations and topological changes”).
Regarding claim 9
DUAN-YONEZAWA teaches the elements of claim 1 as outlined above.
DUAN also teaches wherein the zonal adaptive policy includes standard rules for using zonal control resources to mitigate operation and non-operational violations in the at least one transmission zone (Fig. 4, [0085]: “MA-AVC system determines which AI agent(s)should take actions based on the input state information, e.g., a bus voltage violation”).
Regarding claim 14
DUAN-YONEZAWA teaches the elements of claim 1 as outlined above.
DUAN also teaches to determine a zonal orchestration index associated with a particular zone ([0062]: performance measure of policy for agent). DUAN also teaches that a known problem associated with centralized control is that they require “sophisticated communication networks to collect global operating conditions and requires a powerful central controller to process a huge amount of information” ([0006]). Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify DUAN-YONEZAWA in view of DUAN such that DUAN-YONEAWAZA’s zonal controllers/agents would determine the orchestration index/performance measure such that a vector representing a performance measure would be transmitted with the operational data rather than transmitting all data required to determine the orchestration index for the purposes reducing the burden on the communication system and reducing the workload of the central processor, as taught by DUAN.
Regarding claim 16
DUAN-YONEZAWA teaches the elements of claim 1 as outlined above.
YONEZAWA also teaches the forecast data includes a prediction of how at least one of the plurality of transmission zones will perform in a future time interval ([0028], [0033]: “demand data request requests demand data in a future predetermined time range, more specifically, demand forecast data in the future predetermined time range”).
Regarding claim 17
DUAN-YONEZAWA teaches the elements of claim 1 as outlined above.
DUAN also teaches to collected operational data from an intelligent electronic device ([0085]: “state information includes phasor measurement unit (PMU) and supervisory control and data acquisition (SCADA) measurements”).
Regarding claim 20
DUAN-YONEZAWA teaches the elements of claim 1 as outlined above.
DUAN also teaches to communicate an operational control command to at least one of the plurality of zonal controllers based on the zonal operational data and the zonal adaptive policy (Fig. 4, [0085]: “MA-AVC system determines which AI agent(s)should take actions based on the input state information, e.g., a bus voltage violation”).
Claims 4-6 are rejected under 35 U.S.C. 103 as being unpatentable over REF1-REF2 in view of TAFT (US20120310424A1) (hereinafter – “DUAN-YONEZAWA-TAFT”).
Regarding claim 4
DUAN-YONEZAWA teaches the elements of claim 1 as outlined above.
DUAN is not relied on to teach that power grid is modeled using a federated grid modelling agent in which the plurality of transmission zones are modeled with a unified structure within a transmission grid. However, TAFT in an analogous art at least suggests this limitation as TAFT discloses a computer executable method of federating a power grid ([0147]: embodiments herein can be implemented as software [0024]: “a federation device receives one or more grid control-based signals over a computer network, applies one or more utility grid control policies to the one or more grid control-based signals, and federates the one or more signals and/or the one or more utility grid control policies into one or more federated control-based signals”) in which the transmission zones are modeled with a unified structure within a transmission grid (Fig. 1).
TAFT is analogous art to the claimed invention because they are from the same field of energy management systems. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to apply the teachings of TAFT to the teachings of DUAN-YONEZAWA such that MA-AVC system of DUAN-YONEZAWA’s would be incorporate TAFT’s federation device to model the power grid as a federated gird in which the plurality of transmission zones are modeled with a unified structure. DUAN provides the motivation to combine in the teaching of “the distributed or decentralized control strategy has attracted more and more attention to mitigating disadvantages in the centralized control strategy” ([0007]).
Regarding claim 5
DUAN-YONEZAWA-TAFT teaches the elements of claim 4 as outlined above.
TAFT also discloses wherein a plurality of distribution zones in the power gridd are modeled in the federated grid modeling agent with a unified structure as loads in the transmission grid (Fig. 1 shows a plurality of distribution zones in the power grid, [0027], [0028], [0038]-[0048]: “By establishing the network as a platform (NaaP) to support distributed applications, and understanding the key issues around sensing and measurement for dynamic physical network systems, key capabilities of smart communication networks may be defined (e.g., as described below) that support current and future grid applications.”)
Regarding claim 6
DUAN-YONEZAWA-TAFT teaches the elements of claim 4 as outlined above.
TAFT also discloses wherein the plurality of zonal controllers are organized, mapped, stored, and learned in a unified manner, and wherein the plurality of zonal controllers are in communication with the federated grid modelling agent (Fig. 1 shows a plurality of transmission substations in the power grid, [0027]: “Primary distribution substations may be controlled by a transmission EMS in some cases and are controlled by a distribution control center”, [0028], [0038]-[0048]: “By establishing the network as a platform (NaaP) to support distributed applications, and understanding the key issues around sensing and measurement for dynamic physical network systems, key capabilities of smart communication networks may be defined (e.g., as described below) that support current and future grid applications.”)
Claims 10-13 are rejected under 35 U.S.C. 103 as being unpatentable over DUAN-YONEZAWA in view of PARUCHURI (US20190109891A1) (hereinafter – “DUAN-YONEZAWA-PARUCHURI”).
Regarding claim 10
DUAN-YONEZAWA teaches the elements of claim 1 as outlined above.
DUAN-YONEZAWA are not relied on for receiving at least one grid addition for the power grid. However, PARUCHURI in an analogous art teaches an energy management system comprising virtual electrical network that is configured to receiving at least one grid addition for a power grid ([0084]: “At operation 415, the main system controller 302 and/or the VEN engine 305 generates a record for the new physical node”). PARUCHURI also teaches to determine a zonal predictive policy based on the at least one grid addition ([0085]: “Concurrent with or after operation 430, the VEN engine 305 proceeds to operation 435 to update the VEN 105/200 exposed to the other subsystems of the EMS 300, such as the load balancer 307” [0038]: “The load balancer 110 is used to determine when and how to allocate electricity from certain producers to individual consumers, including when to store excess electrical power and when to release electrical power to individual consumers”).
PARUCHURI is analogous art to the claimed invention because they are from the same field of energy management systems. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to apply the teaching of PARUCHURI to the teachings of DUAN-YONEZAWA such that DUAN-YONEZAWA’s MA-AVC system would be configured to accept additions to the grid. DUAN teaches that the distributed/decentralized grid control strategy has improved scalability as compared to centralized grid control ([0007]) thus providing the motivation to combine.
Regarding claim 11
DUAN-YONEZAWA-PARUCHURI teaches the elements of claim 10 as outlined above.
DUAN in view of PARUCHURI at least suggests wherein the zonal predictive policy is generated based on a predictive policy machine learning model trained on historical operational data for the plurality of transmission zones and at least one of historical grid addition for the power grid (DUAN also teaches wherein the zonal adaptive policy is generated by a zonal autonomous control and management engine that includes an adaptive policy machine learning model trained on historical zonal operational data for the plurality of zonal controllers ([0040]: “a novel multi-agent AVC (MA-AVC) scheme is proposed to maintain voltage magnitudes within their operation limits […] the MA-AVC problem is formulated as a Markov Game with a bi-layer reward design considering the cooperation level. Third, a multi-agent deep deterministic policy gradient (MADDPG) algorithm, which is a multi-agent, off-policy and actor-critic DRL algorithm, is modified and reformulated for the AVC problem” [0047]: “DRL-based agent in the proposed MA-AVC scheme can learn its control policy through massive offline training without needs to model complicated physical systems and adapt its behavior to new changes including load/generation variations and topological changes”).
Regarding claim 12
DUAN-YONEZAWA-PARUCHURI teaches the elements of claim 10 as outlined above.
PARUCHURI also teaches wherein the at least one gird addition is a generation resource, a load, an energy storage device, or a piece of equipment ([0086]: “the VEN engine 305 may determine whether the physical nodes are physical energy consumer nodes or physical energy producer nodes”).
Regarding claim 13
DUAN-YONEZAWA-PARUCHURI teaches the elements of claim 12 as outlined above.
PARAUCHURI also teaches wherein the generation resource includes a renewable generation resource or a distributed energy resource ([0086]: VEN determines is node is energy producing node [0029]: “DERs include different technologies that allow small-scale energy/electricity generation, which may take advantage of renewable energy resources (RESs) such as solar, wind, hydro, or other like RESs. These DERs may supply emergency power and change energy storage elements”).
Claims 15 are rejected under 35 U.S.C. 103 as being unpatentable over DUAN-YONEZAWA in view of TAFT_2017 (US20170170685A1).
Regarding claim 15
DUAN-YONEZAWA teaches the elements of claim 14 as outlined above.
DUAN-YONEZAWA are not relied on for wherein the zonal orchestration index represents real-time performance relative to a baseline. However, TAFT_2017 in an analogous art teaches to determine the current health of a portion of a grid by collecting real time data and comparing the data to a baseline ([0142]: “one or more sensors may measure and transmit to remote asset monitoring processes in order to determine the current health of the particular portion of the grid. For example, a sensor on a power transform may provide an indicator of its health by measuring the dissolved gases on the transformer. The remote asset monitoring processes may then use analytic tools to determine if the particular portion of the grid (such as the power transform is healthy or not healthy), determining current health implies determining real-time performance, health or not healthy implies comparing to a baseline, i.e., if data representing the dissolved gases of a transformer are above the baseline then the transformer is unhealthy).
TAFT_2017 is analogous art to the claimed invention because they are from the same field of energy management systems. DUAN-YONEZAWA teaches a computer-implemented system configured to monitor grid operations. TAFT_2017 teaches a computer-implemented sub-routine configured to determine grid health by comparing real-time measurements to a baseline. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to apply the teachings of TAFT_2017 to DUAN-YONEZAWA such that DUAN-YONEZAWA’s system would have a computer-implemented sub-routine to determine the zonal orchestration index/policy performance measure by comparing real-time data measurements to a baseline according to known methods to yield predictable result. One of ordinary skill in the art would have recognized that the results of the combination were predictable as comparing a value to a baseline line in or to determine a healthy or unhealthy state is a well-established method (e.g., see DUAN [0084]: a state violation is determined by comparing the measured voltage to a baseline).
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over DUAN-YONEZAWA in view of JAYAN (US20220344934A1).
Regarding claim 18
DUAN-YONEZAWA teaches the elements of claim 1 as outlined above.
DUAN-YONEZAWA are not relied on for generating a long-term forecast for at least one transmission zone of the plurality of transmission zones. However, JAYAN in an analogous art teaches to include an annual demand forecast when determining an energy plan corresponding to a region ([0088]).
JAYAN is analogous art to the claimed invention because they are from the same field of energy management systems. DUAN-YONEZAWA teaches an intelligent power grid energy management system configured to receive demand forecasts from a plurality of zones such that autonomous voltage control can be implemented. JAYAN teaches that an energy plan for corresponding to a region includes an annual demand forecast. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to apply the teachings of JAYAN to DUAN-YONEZAWA’s MA-AVC system such that the system would be configured to generate a long-term forecast for at least one of the transmission zones for the purposes of determining the system configuration required to deliver the forecasted load such that the threshold parameters for the autonomous voltage control would be parameterized according to the system configuration such that autonomous voltage control could be accomplished.
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over DUAN-YONEZAWA in view of FALEY (US20190081479A1).
Regarding claim 19
DUAN-YONEZAWA teaches the elements of claim 1 as outlined above.
DUAN-YONEZAWA are not relied on for providing a user interface. However, FALEY in an analogous art teaches to provide a user interface for a power control system (Abstract: power supply system comprising a device controller and a user interface device operatively connected to the device controller) configured to receive a first input via the user interface identifying a user for the power grid ([0266]: user interface 160 is configured to allow remote login [0270]: “public remote user would be required to login using the remote login password before they could go to the home screen”), and at least suggests receive a second input via the user interface identifying a location and a level of the power grid ([0294]-[0295]: solar tile of home page is interactive and provides an overview of solar power being harvested in real time), and teaches determining grid data to display via the user interface based on the first input and the second input ([0296]: tapping any part of the tile navigates to the solar status screen).
FALEY is analogous art to the claimed invention because they are from the same field of energy management systems. DUAN-YONEZAWA teaches a MA-AVC system to configure and monitor a decentralized power grid system. FALEY teaches a user interface that allows users to configure and/or monitor the status of a power supply system such as a grid ([0200]). Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to apply the teachings of FALEY to DUAN-YONEZAWA such that the MA-AVC system of DUAN-YONEZAWA would have provided a user interface configured to receive a first input of login information (first input), receive a second input of a location and a level of a component to be monitored, and to display grid data in response to the user inputs. DUAN teaches an operator should confirm decisions of the DRL agent of the MA-AVC system ([0082]), implying motivation for the system to include a user interface.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
CHERIAN (US20110106321A1) teaches supervisory control and data acquisition systems for a transmission/distribution power grid.
BOARDMAN (US20180107691A1) teaches an intelligent multi-level (federated) control system for a power grid.
Ding, F., et al., (“Distributed Energy Resource Management Solutions (FAST-DERMS)”, published January 2022, retrieved on 7/13/2026, retrieved from https://www.academia.edu/129738275/Federated_Architecture_for_Secure_and_Transactive_Distributed_Energy_Resource_Management_Solutions_FAST_DERMS_) teaches flexible resource scheduling.
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/M.V.F./Examiner, Art Unit 2115
/KAMINI S SHAH/Supervisory Patent Examiner, Art Unit 2115
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