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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 7/10/2026 has been entered.
Response to Amendment
The RCE filed July 10, 2026 has been entered and considered. Claims 1, 2, 4-10, and 12-22 remain pending in the instant application.
Response to Arguments
Applicant’s arguments with respect to amended claims 1, 2, 4-10, and 12-22 have been considered but are moot because the new grounds of rejection, necessitated by Applicant’s amendments, rely 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, 6-7, 9-10, 12, 14-15, 17-18, and 20-22 are 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 Sun et al. “Master–Slave-Splitting Based Distributed Global Power Flow Method for Integrated Transmission and Distribution Analysis” (2015) [herein “Sun”].
Regarding Claim 1, Zhou teaches
A computer-implemented method comprising:selecting, from a unified model of an electrical power grid comprising a plurality of transmission elements and a plurality of distribution elements, 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 a 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.).
“InterPSS object model supports modeling multiple networks of different types, for example, a mix of positive sequence, 012 sequence, ABC 3-phase network models in a simulation application model. As shown in Fig.4, a parent Network class might contain 0 to many child networks (child Net). The relationship is nested, which means a child network, in turn, can contain its grand-child networks.”. (Pg. 4 Section III).
“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).
This shows a unified model of an electrical power grid comprising a plurality of transmission elements and a plurality of distribution elements. The “integrated T&D system” is a single parent network object model whose nested child networks are the 300-bus transmission system (plurality of transmission elements) and the 43 distribution systems (plurality of distribution elements), combined into one model.
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 of components of the electrical power grid for which a second electrical grid simulation model simulates operation, wherein the second proper subset of elements comprises one or more elements that differ 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.
The second proper subset comprises elements that differ from the first proper subset i.e. the buses, branches, and loads of the 43-distribution system are distribution elements of the unified model that are not part of the 300-bus transmission system.
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.
… from at least the first proper subset of elements and the second proper subset of elements of the unified model … determining a set of boundary conditions existing at one or more overlapping elements 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, 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
and one or more overlapping elements that are included in the first proper subset;
“At a given time step of the
quasi-static simulation, the T&D systems are solved separately
using their respective solvers. This step solves decoupled
T&D models where the transmission system solver models
the connected distribution network as an equivalent load and
the distribution solver models the upstream transmission bus
as a voltage source. The bus voltages and angles obtained
from transmission network solver and active and reactive
power flow obtained from distribution network solver at the
point-of-common-coupling (PCC) are referred to as boundary
variables (see Fig. 1).”. (Pg. 3 Section III).
“Two integrated T&D test systems are developed. Test System-1 (TS1) is obtained by replacing the aggregated load at bus 6 of the 9-bus transmission system with EPRICkt-24. Test System-2(TS2) is obtained by replacing all the load points, L5, L6, and L8, of the IEEE9-bus system with Ckt-24.”. (Pg. 6 Section V).
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;
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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).
ZHOU and KRISHNAMOORTHY do not explicitly teach but SUN teaches
Identifying … the one or more overlapping elements among the first proper subset of elements and the second proper subset of elements of the unified model;
“To achieve a global unified power flow solution to support an integrated analysis for both transmission and distribution grids, we propose a global power flow (GPF) method that considers transmission and distribution grids as a whole in this paper.”. (Abstract).
“Suppose that xB ∈ DB ⊂ RnB is a boundary state separating M and S completely; a mathematical model for the whole system can be formulated as follows: ⎧ ⎨ ⎩ (1) GM(xM,xB) = 0 GB(xM,xB,xS) = 0 GS (xB,xS) = 0”. (Pg. 1485 Section II).
“A general MSS iterative method can be constructed as follows. Step 1: Initialization: determine the boundary state x(0) B and set the iteration counter k =0.”. (Pg. 1485 Section II).
“Here, the transmission grid is the master system with a detailed structure of the aggregated power supply seen from the distribution side, while the distribution grid is the slave system with a detailed structure of the aggregated load seen from the transmission side. In Fig. 1, the load nodes in the transmission grid are taken to be the root nodes of the distribution feeders, which makeup the node set of the boundary system CB. The remaining nodes of the transmission grid make up the node set CM, and the remaining nodes of distribution grid make up the node set CS.”. (Pg. 1486 Section III).
“Due to space limitation, only the results for transmission bus 30 (a boundary bus connecting to Feeder #5) in the two cases are shown in Table I.”. (Pg. 1489).
This shows identifying the one or more overlapping elements among the first and second proper subsets of the unified model. SUN’s global power system is the unified model by the master (transmission) and slave (distribution) sub-systems are the first and proper subsets. SUN identifies, from the transmission node set and the distribution node set, the nodes belonging to both (the transmission load nodes that are also the root nodes of the distribution feeders) as the boundary node set C<sub> B</sub> and expressly determines that boundary state in step 1. Those boundary nodes, such as transmission bus 30, are the overlapping elements included in both subsets.
It would have been obvious before the effective filing date of the claimed invention to incorporate SUN’s teaching of splitting a global transmission and distribution model at an identified set of boundary nodes with ZHOU’s and KRISHNAMOORTHY’s method of iterative T&D co-simulation exchanging boundary quantities between separately solved transmission and distribution models. The reason for doing so would have been to define the nodes at which the two models overlap so that the boundary quantities are exchanged, and convergence is evaluated, at the correct elements. As expressed by SUN, “… power and voltage mismatches will arise at the boundary nodes when the load flows are considered separately.” and “to alleviate boundary mismatches between the transmission and distribution grids.”. (Pg. 1).
Regarding Claim 2, Krishnamoorthy and Sun do not explicitly teach but Zhou teaches
The computer-implemented method of claim 1 wherein the first proper subset of elements comprises 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.
Krishnamoorthy and Sun do not explicitly teach but Zhou teaches
operated by the first entity, and the second proper subset of elements comprises elements operated by a second entity, wherein the first entity is distinct from the second entity.
“However, the transmission and distribution grids usually belong to different utilities and are operated by different control centers. The transmission control centers are equipped with energy management systems (EMSs) [1], and many distribution control centers have also deployed distribution management systems (DMSs) [2].”. (Pg. 1484 Section I).
“In Fig. 5, the solutions for TPF and DPFs calculations are carried out in the EMS and DMSs, respectively. The EMS communicates with the DMSs using a wide area network (WAN) in each MSS iteration step.”. (Pg. 1488-1489 and FIG. 5).
This shows the transmission elements operated by a first entity and the distribution elements are operated by a second, distinct entity, with the transmission power flow solved in the transmission utility’s EMS and each distribution power flow solved in the distribution utility’s DMS.
Regarding Claim 4, Krishnamoorthy and Sun do 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 and Sun do not explicitly teach but Zhou teaches
The computer-implemented method of claim 1 wherein the comprises identifying 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.
Zhou and Krishnamoorthy do not explicitly teach but Sun teaches
identifying … the one or more overlapping elements among the first proper subset of elements and the second proper subset of elements of the unified model
“In Fig. 1, the load nodes in the transmission grid are taken to be the root nodes of the distribution feeders, which makeup the node set of the boundary system CB. The remaining nodes of the transmission grid makeup the node set CM, and the remaining nodes of distribution grid make up the node set CS.”. (Pg. 1486 Section III).
This shows identifying the overlapping elements comprises identifying intersections between elements of the two subsets. SUN’s boundary node set C<sub> B</sub> is the intersection of the transmission node set and the distribution node set: the nodes that are both load nodes of the transmission grid and root nodes of the distribution feeders, with the non-interesting nodes of each grid assigned to C<sub> M </sub> and C <sub> S</sub>.
Regarding Claim 7, Krishnamoorthy does not explicitly teach but Zhou teaches
The computer-implemented method of claim 1 wherein the set of boundary conditions comprise … conditions at the one or more overlapping elements 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).
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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.
ZHOU and SUN do not explicitly teach but KRISHNAMOORTH teaches
… consistent …
“After decoupled T&D systems are solved, boundary variables are tested for convergence. If the tolerance limit is not satisfied, the co-simulation stage begins. At a given co-simulation iteration (co-iteration), T&D systems have partially correct information about the boundary variables that need updating. The decoupled representations for T&D networks are updated at each co-iteration using the proposed update rules for boundary variables, further detailed in Section III. With updated boundary variables, the decoupled T&D models are solved again. The co-iterations are repeated until the errors in boundary variables obtained from decoupled models are within the pre-specified tolerance.”. (Pg. 3 Section III).
This shows the boundary conditions at the overlapping elements are consistent conditions. The boundary variables at the point of common coupling obtained from the transmission model and from the distribution model are iterated until the errors between them are within the pre-specified tolerance, at which point the conditions at the overlapping element agree between the two simulation models.
Regarding Claim 21, ZHOU and SUN do not explicitly teach but KRISHNAMOORTHY teaches
The method of claim 7, wherein the consistent conditions at each overlapping element of the one or more overlapping elements comprises one of a same property value at the overlapping element, or a specified range of a property value at the overlapping element.
“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 Section IV).
This shows the consistent conditions at the overlapping element comprise a specified range of a property value at the overlapping element. The boundary variables (voltage and complex power at the PCC) from the two models are iterated until their residual is within a permissible error tolerance, which is a specified range of the property value at the overlapping element.
Claim 5, 13, and 19 are 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”], Sun et al. “Master–Slave-Splitting Based Distributed Global Power Flow Method for Integrated Transmission and Distribution Analysis” (2015) [herein “Sun”], 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, Krishnamoorthy, and Sun 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-Sun 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 and 16 are 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”], Sun et al. “Master–Slave-Splitting Based Distributed Global Power Flow Method for Integrated Transmission and Distribution Analysis” (2015) [herein “Sun”], and in view of Cremona et al. “Hybrid Co-simulation: It's About Time” (2017) [herein “Cremona”].
Regarding Claim 8, Zhou, Krishnamoorthy, and Sun do not explicitly teach but Cremona teaches
The computer-implemented method of claim 1 wherein the set of 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-Sun 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 9-10 and 12-16 recite substantially the same limitations as claims 1-2 and 4-8 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 and 22 recite substantially the same limitations as claims 1, 2, and 4-6 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
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US20180004867A1 teaches power production simulation and power distribution simulation, and more specifically, the integration of power production simulation with power distribution simulation.
US11239658B2 dispatching method and a dispatching device for an integrated transmission and distribution network.
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/N.E.M./Examiner, Art Unit 2189
/REHANA PERVEEN/Supervisory Patent Examiner, Art Unit 2189
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