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 .
Response to Amendments
Applicant’s amendments filed on 03/17/2026 have been entered. Claims 1-20 are pending in the application of which claims 1, 9, and 17 are independent.
Response to Arguments
Applicant’s arguments in view of amendments, filed on 03/17/2026 have been fully considered and Examiner response is as follows:
Applicant’s arguments, Page 1, 2, and 3, regarding 35 USC 102 and 35 USC 103 rejections are considered but are moot because the new grounds of rejection, necessitated by applicant’s amendments, relies on additional prior art as shown below.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 2-4, and 6-7 are rejected under 35 U.S.C. 103 as being anticipated over Zhou et al. “InterPSS: A New Generation Power System Simulation Engine” (2017) [herein “Zhou”] and Krishnamoorthy et al. “Transmission-Distribution Co-Simulation: Analytical Methods for Iterative Coupling” (2019) [herein “Krishnamoorthy”].
Regarding Claim 1, Zhou teaches
A computer-implemented method comprising:selecting, from a unified model of an electrical power grid, a first proper subset of elements of the unified model that correspond to a first proper subset of components of the electrical power grid for which the first electrical grid simulation model simulates operation;“In the T&D co-simulation implementation, each transmission or distribution system is represented by one InterPSS network object model (see Fig.4). Thanks to the model algorithm decoupled architecture, each network can be solved individually and their solutions can be flexibly exchanged and coordinated.” (Pg.6 Section VI.).
The paper selects the transmission system as the “first proper subset”, which is part of the unified power grid model. Each subset uses different simulation approaches appropriate to its domain.
selecting a first electrical grid simulation model that simulates operation of electrical power grid components;“Thanks to the model algorithm decoupled architecture, each network can be solved individually and their solutions can be flexibly exchanged and coordinated.” (Pg.6 Section VI.).
Each subset uses its own selected simulation model.selecting, from the unified model of the electrical power grid, a second proper subset of elements of the unified model that correspond to the second proper subset components of the electrical power grid for which the second electrical grid simulation model simulates operation, wherein the second proper subset of elements differs from the first proper subset of elements;“The developed integrated T&D co-simulation program has been tested on a large-scale integrated T&D system which consists of a modified IEEE 300-bus system [24], and 43 distribution systems (for the 43 load buses with loads greater than 50 MW each in the area 1 of the transmission system) that are built based on the IEEE 13-bus feeder [25]. The T&D system has combined 22920 buses in total with 1740 feeders.” (Pg. 7 Section VI.).
The distribution system is the “second” model associated with a second subset of elements which is distinct from the transmission model. This is exemplified by the reference of 3 phase versus 3 sequence modeling as shown in figure 8.
selecting a second electrical grid simulation model that differs from the first electrical grid simulation model and that simulates operation of electrical power grid components;“Three-phase modeling in ABC coordinate and three-sequence modeling in 012 coordinate TS simulation features of InterPSS simulation engine facilitated the integration with the EMT simulators, especially under the unbalanced system condition.” (Pg. 7 Section VI. C).
The distribution system uses 3-phase simulation models, which differ from the 3-sequence simulation model. This is the second model selected.
determining, from at least the first proper subset of elements and the second proper subset of elements of the unified model, a set of boundary conditions common to the first electrical grid simulation model and the second electrical grid simulation model;“At each iteration of during the loadflow calculation, the transmission system provides the three-phase voltages at the boundary buses, denoted by , abc VBi , to the corresponding distribution systems to update their boundary bus voltages. The distribution systems send their three-sequence equivalents (equivalent load for positive sequence, equivalent current injections for both negative- and zero-sequence) to the transmission system. The data exchange process is illustrated in Fig. 8.” (Pg. 6 and Please see Fig. 8).
The boundary conditions are for example voltages at the buses where the T&D systems connect. These are determined from the separate subsets which have their own models, and then exchange data between each other over common elements.
simulating operation of the electrical power grid, the simulating comprising:
at each of one or more iterations:simulating, using the first electrical grid simulation model, the first proper subset of elements of the unified model, and the set of boundary conditions, [[and]] operation of the first proper subset of components the electrical power grid,
“At each iteration of during the loadflow calculation, the transmission system provides the three-phase voltages at the boundary buses, denoted by , abc VBi , to the corresponding distribution systems to update their boundary bus voltages.” (Pg. 6 and Please see Fig. 8).
“During the dynamic simulation, the Multi-area Thévenin Equivalent (MATE) approach [23] is employed to solve the network solution step, which is illustrated in Fig. 9. Transmission and distribution system are solved independently at each integration step.” (Pg. 7)
In this case the transmission system (first subset) is simulated using its model to produce values like voltages that are provided to another system such as the distribution system. This is done iteratively if necessary.
simulating, using the second electrical grid simulation model and the second proper subset of elements of the unified model, [[and]] the set of boundary conditions, operation of the second proper subset of components the electrical power grid,
“The distribution systems send their three-sequence equivalents (equivalent load for positive sequence, equivalent current injections for both negative- and zero-sequence) to the transmission system.” (Pg.6 and Please see Fig. 8).
In this case the distribution system (second subset) is simulated using its model to produce values like voltages that are provided to another system such as the transmission system.
Zhou does not explicitly teach but Krishnamoorthy teaches
to obtain a first set of operational values representing an update to an initial state of one or more of the elements in the first proper subset of elements; [[and]]
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. (Pg.4 Algorithm 1).
This shows updating the state of the subsets of either the transmission or distribution simulator. Transmission or distribution can interchangeably be considered “first subset”.
to obtain a second set of operational values representing an update to an initial state of one or more of the elements in the second proper subset of elements;
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. (Pg.4 Algorithm 1).
This shows updating the state of the subsets of either the transmission or distribution simulator. Transmission or distribution can interchangeably be considered “second subset”.
determining whether the simulation of the electrical power grid is complete based on comparing the set of boundary conditions for the first set of operational values and the second set of operation values; and
“After decoupled T&D systems are solved, boundary variables are tested for convergence.”. (Pg. 3). (Algorithm 1 Pg. 4).
“The co-simulation interface provides two types of output to all interacting simulators: a timing signal and boundary variable updates. The timing signal ensures that none of the simulators advance to the next time step until the integrated T&D model has converged for the current time step. The co-simulation interface also includes an algorithm for co-iteration that updates the boundary variables and uses internal logic to evaluate if the convergence has reached and should the simulation advance to the next time step.”. (Pg. 3).
This shows iterating until the boundary conditions fall within an acceptable convergence of the boundary values. Thus, determining the completion of the simulation.
determining that the simulation of the electrical power grid is complete when the set of boundary conditions for the first set of operational values are within a tolerance value of the boundary condition for the second set of operation values.
“A global interface residual vector (R) is defined to evaluate the condition for the convergence of the co-simulation framework, where 1 and 2 are predefined tolerance parameters (9). The objective is to iteratively solve interface equations defined in (5) and (6) until the residual evaluated using (7) and (8) are within a permissible error tolerance. If convergence criteria is not met, the boundary variables are updated. The update rules for boundary variables are derived in sections III-B and III C for FPI and Newton’s method, respectively. The process is repeated until the boundary variables converge.”. (Pg. 4).
This shows checking if the simulation is done by concluding its iterating when the boundary conditions are within the tolerance by comparing two sets of values.
It would have been obvious to one of the ordinary skills in the art before the effective filing date of the claimed invention to incorporate the teachings of Krishnamoorthy tolerance-based T&D algorithm with Zhou T&D system. The motivation for doing so would have been “…to provide an open simulation engine and the associated software development platform to the power engineering community where researchers and developers can easily extend the simulation engine or the platform to develop domain-specific or cross-domain power system simulation applications.”. (Pg. 1).
Regarding Claim 2, Krishnamoorthy does not explicitly teach but Zhou teaches
The computer-implemented method of claim 1 wherein the first proper subset of elements comprise transmission elements.
“Thanks to the model algorithm decoupled architecture, each network can be solved individually and their solutions can be flexibly exchanged and coordinated.” (Pg. 6).
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(Please see Fig.9 and Fig. 8 that show bi directional exchange. Showing transmission or distribution being first or second.) In this bi directional exchange either T or D can be first or second since they can be “flexibly exchanged”. The first subset is the transmission system that comprises transmission elements.
Regarding Claim 3, Krishnamoorthy does not explicitly teach but Zhou teaches
The computer-implemented method of claim 1 wherein the first proper subset of elements comprise distribution elements.
“Thanks to the model algorithm decoupled architecture, each network can be solved individually and their solutions can be flexibly exchanged and coordinated.” (Pg. 6).
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(Please see Fig.9 and Fig. 8 that show bi directional exchange. Showing transmission or distribution being first or second.) In this bi directional exchange either T or D can be first or second since they can be “flexibly exchanged”. The first subset is the distribution system that comprises distribution elements.
Regarding Claim 4, Krishnamoorthy does not explicitly teach but Zhou teaches
The computer-implemented method of claim 1 wherein the first proper subset of elements comprise transmission elements and the second proper subset of elements comprise distribution elements.
“The developed integrated T&D co-simulation program has been tested on a large-scale integrated T&D system which consists of a modified IEEE 300-bus system [24], and 43 distribution systems (for the 43 load buses with loads greater than 50 MW each in the area 1 of the transmission system) that are built based on the IEEE 13-bus feeder [25]. The T&D system has combined 22920 buses in total with 1740 feeders.” (Pg. 6).
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(Please see Fig.9 and Fig. 8 that show bi directional exchange. Showing transmission or distribution being first or second.) The first subset is the 300 bus system and the second is the 43 distribution system.
Regarding Claim 6, Krishnamoorthy does not explicitly teach but Zhou teaches
The computer-implemented method of claim 1 wherein the boundary conditions comprise intersections between elements in the first proper subset of elements of the unified model and the second proper subset of elements of the unified model.
“At each iteration of during the loadflow calculation, the transmission system provides the three-phase voltages at the boundary buses, denoted by, abc VBi, to the corresponding distribution systems to update their boundary bus voltages. The distribution systems send their three-sequence equivalents (equivalent load for positive sequence, equivalent current injections for both negative- and zero-sequence) to the transmission system. The data exchange process is illustrated in Fig. 8.” (Pg. 6).
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(Fig. 8 shows bi directional relation for boundary conditions.) The boundary conditions are the boundary buses where the first subset and the second subset connect for exchange.
Regarding Claim 7, Krishnamoorthy does not explicitly teach but Zhou teaches
The computer-implemented method of claim 1 wherein boundary conditions comprise conditions at one or more elements present in both the first proper subset of elements of the unified model and the second proper subset of elements of the unified model.
“At each iteration of during the loadflow calculation, the transmission system provides the three-phase voltages at the boundary buses, denoted by, abc VBi, to the corresponding distribution systems to update their boundary bus voltages. The distribution systems send their three-sequence equivalents (equivalent load for positive sequence, equivalent current injections for both negative- and zero-sequence) to the transmission system. The data exchange process is illustrated in Fig. 8.” (Pg. 6).
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(Fig. 8 shows bi directional relation for boundary conditions being present in each subset.) The boundary buses exist in both subsets. The boundary conditions are defined and shared at the boundary bus.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Zhou et al.
“InterPSS: A New Generation Power System Simulation Engine” (2017) [herein “Zhou”], Krishnamoorthy et al. “Transmission-Distribution Co-Simulation: Analytical Methods for Iterative Coupling” (2019) [herein “Krishnamoorthy”], and in view of Prabadevi et al. “Deep Learning for Intelligent Demand Response and Smart Grids: A Comprehensive Survey” (2021) [herein “Prabadevi”].
Regarding Claim 5, Zhou and Krishnamoorthy do not explicitly teach but Prabadevi teaches
The computer-implemented method of claim 1 wherein simulating operation comprises processing an input comprising loads using a machine learning model that is configured to produce as output predicted loads the power grid.
“A deep RNN with a gated recurrent unit (GRU) system was developed for predicting energy supply-demand in residential apartments for a small to medium duration of time [37]. The integrated DRNN-GRU model is a five-layered neural network consisting of optimized hyperparameters with normalized input. The first layer is an input layer, fed with daily hourly load consumption data samples. The second layer referred to the first GRU layer to produce output for each point time. The third layer referred to the second GRU layer to produce a higher dimension output than the previous layer. This layer has tuned more number of weights and bias. The fourth layer is a simple hidden layer. The fifth layer is an output layer that produces prediction results.” (Pg. 5).
It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to incorporate the teachings of Prabadevi a machine learning model to predict loads of a power grid with the teachings of Zhou-Krishnamoorthy that teaches selecting different subsets of the grid, applying two distinct simulation models with common boundary conditions, and combining the operational values obtained from each simulation to apply machine learning techniques on the model/simulation data to find insights in order to improve electrical grid resilience. The motivation for doing so would have been to “…address challenges and issues in the transmission of electricity through the traditional grid, the concepts of smart grids and demand response have been developed. In such systems, a large amount of data is generated daily from various sources such as power generation (e.g., wind turbines), transmission and distribution (microgrids and fault detectors), load management (smart meters and smart electric appliances). Thanks to recent advancements in big data and computing technologies, Deep Learning (DL) can be leveraged to learn the patterns from the generated data and predict the demand for electricity and peak hours. Motivated by the advantages of deep learning in smart grids, this paper sets to provide a comprehensive survey on the application of DL for intelligent smart grids and demand response.” (Abstract).
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Zhou et al.
“InterPSS: A New Generation Power System Simulation Engine” (2017) [herein “Zhou”], Krishnamoorthy et al. “Transmission-Distribution Co-Simulation: Analytical Methods for Iterative Coupling” (2019) [herein “Krishnamoorthy”], and in view of Cremona et al. “Hybrid Co-simulation: It's About Time” (2017) [herein “Cremona”].
Regarding Claim 8, Zhou and Krishnamoorthy do not explicitly teach but Cremona teaches
The computer-implemented method of claim 1 wherein boundary conditions are expressed as Boolean expressions.
“FMI for co-simulation is more focused on tool interoperability; the host simulator provides input values to the FMU, requests that the FMU advance its state variables and output values in time, and then queries for the updated output values.” (Pg. 3).
“To make it possible to express discrete events, FMI needs to have functions for setting and getting values, where the values can be stated to be either present or absent. By extending the current standard get and set functions, we obtain the following signatures:” (Section 3.1.3 and Image of Function Declaration with Boolean flag).
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It would have been obvious to one skilled in the art before the effective filing date of the claimed invention to incorporate the teachings of Cremona of using a Boolean defined standards for co-simulation to exchange data with the teachings of Zhou-Krishnamoorthy that teaches selecting different subsets of the grid, applying two distinct simulation models with common boundary conditions, and combining the operational values obtained from each simulation to improve the boundary condition framework in co-simulation of electrical grids. The motivation for doing so would have been to “…support discrete signals, an FMU must be able to output or take in discrete events” (Section 3.1.3).
Claims 9-16 recite substantially the same limitations as claims 1-8 except these claims are directed to a “A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising:” or “The system of claim 9”. Therefore, these claims are rejected under the same rationale as addressed above.
Claims 17-20 recite substantially the same limitations as claims 1, 4, 5, and 6 except these claims are directed to a “One or more non-transitory computer-readable storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:” or “The one or more non-transitory computer-readable storage media”. Therefore, these claims are rejected under the same rationale as addressed above.
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.
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/N.E.M./Examiner, Art Unit 2189
/REHANA PERVEEN/Supervisory Patent Examiner, Art Unit 2189
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