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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 3/24/2026 has been entered.
Claims 1-18 are pending.
Response to Amendment
Applicant’s amendments have fixed the deficiencies set forth in the previous Office Action hence the respective rejections/objections have been withdrawn, except for those rejections/objections if still maintained or newly added in this Office Action.
Response to Arguments
Regarding Applicant’s arguments about the rejections for claims 1-18 under 35 U.S.C § 102/103, the arguments have been fully considered but are deemed moot, in view of new grounds of rejections necessitated by Applicant’s amendments.
Independent claims 1, 8, 13 and 16 have been amended to include new limitation “an active or reactive power generation command”. Reference Franke teaches in FIG. 1 and [0079] that commands are sent to IEDs 21, 22 and 23 to control switches 31, 32 and 33 connected to power generators 11, 12 and 13. These commands control the output power of the power generators 11, 12 and 13 which output either active power or reactive power or combination of them. Therefore, these commands comprise an active or reactive power generation command. So the newly added limitation is taught by Franke. Please see details in the 102/103 rejection section.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
“digital twin simulation module”, “state estimation module” and “optimization module” in claims 1, 8;
“digital twin simulation module”, “state estimator” and “optimization module” in claim 13;
“digital twin simulation module” and “optimization module” in claim 16.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Objections
In claim 16, the phrase “power system equipment or distributed energy resources in the electrical power system” at end of the claim should be deleted, to correct the error.
Appropriate correction is required.
Double Patenting
The double-patenting rejection is maintained in this Office action.
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
Claim 1 is rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claim 1 of U.S. Patent No. 11,881,713 (hereinafter as “Pat_713”) in view of Ropp (US 2017/0077703 A1, hereinafter as “Ropp”).
Table has been created below to compare claim 1 of the instant application and claim 1 of the Pat_713.
Instant application
Pat_713
1. A controller for power system equipment and distributed energy resources in an electrical power system, comprising:
a digital twin simulation module;
a state estimation module;
an optimization module;
wherein the digital twin simulation module receives one or more inputs from the electrical power system to update the digital twin simulation module while simulating the electrical power system;
wherein the state estimation module receives one or more inputs from the digital twin simulation module to calculate the operational states of the power system;
wherein the optimization module receives one or more inputs from the state estimation module representing the current operational conditions of the power system; and
wherein the optimization module provides two or more control commands comprising a binary command to one or more power system equipment or distributed energy resources in the electrical power system.
1. A controller for power system equipment and distributed energy resources in an electrical power system, comprising:
a digital twin simulation module;
a state estimation module; and
an optimization module;
wherein the digital twin simulation module receives one or more inputs from one or more sensors in the electrical power system to update the digital twin simulation module while simulating the electrical power system, and
wherein the state estimation module receives one or more real-time pseudo-measurements, selected from the group consisting of an active power, a reactive power, a voltage, a current, a frequency, a power factor, and phasor data, from the digital twin simulation module to calculate operational states of the electrical power system; and
wherein the optimization module receives one or more inputs from the state estimation module representing current operational conditions of the electrical power system; and
wherein the optimization module provides one or more control commands to one or more of the power system equipment or one or more of the distributed energy resources in the electrical power system, the one or more control commands comprising control setpoints, the control setpoints simulated in the digital twin simulation module in real-time with the one or more commands provided to the one or more of the power system equipment or the one or more of the distributed energy resources; and
wherein the digital twin simulation model comprises power system equipment and simulations.
In the table above, all matching elements of the claim limitations are underlined.
As illustrated in the table above, claim 1 of Pat_713 teaches all the limitations of claim 1 of the instant application, except the control commands comprise a binary command. However, Ropp teaches in an analogous art that control commands comprise a binary command ([0048]: “the signal may be used to communicate commands to DERs from substation controls or utility operations centers. …. In another embodiment, the signal may be modulated to communicate binary numbers that correspond to commands”). It would have been obvious to one of ordinary skill in the art, before the effective filling date of the claimed invention, to have modified the controller in claim 1 of Pat_713, to make the controller wherein the optimization module provides one or more control commands comprising a binary command to one or more power system equipment or distributed energy resources in the electrical power system. One of ordinary skill in the art would have been motivated to do this modification since it can facilitate communicating commands to DERs, as Ropp teaches in [0048].
Similarly, claims 2-18 of instant application are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 2-18 of Pat_713 in view of Ropp, respectively.
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim 16-18 are rejected under 35 U.S.C. 102(a)(2) as being unpatentable over Franke (US 2020/0201314 A1, prior art of record, hereinafter as “Franke”).
Regarding claim 16, Franke teaches:
A method for controlling one or more power system devices and/or distributed energy resources (DER 11, 12 and 13 in FIG. 1 and described in [0077]) in an electrical power grid (FIG. 1 and [0085]: the industrial system 10/(electrical power grid)), comprising:
simulating the electrical power grid in real-time in a digital twin simulation module (digital twin 41 in FIG. 1 and described in [0092]), wherein the simulation module includes power system equipment and controller simulations (FIG. 1 and [0077, 0079]: the digital twin mimic the electrical power grid 10 which includes power system equipment and controller);
providing one or more inputs to the digital twin simulation module from one or more sensors in the electrical power grid (FIG.1 and [0080, 0116]: the digital twin receives inputs from the electrical power grid comprising sensors, and the inputs inherently comprise sensor measurements); and
providing one or more inputs from the digital twin simulation module to an optimization module (FIG. 1 and [0084]: “The optimization engine 42 uses the digital twin data of the digital twin 41 to explore possible changes in system settings that can be applied to the industrial system 10”) that determines two or more control commands to one or more power system equipment and controllers of the electrical power grid (FIG. 4 and [0121]: “At step 74, if the system settings are to be transferred to the real-world industrial system 10, the system settings may be applied to the industrial system 10. Applying the system settings may comprise adapting settings of intelligent electronic devices, IEDs, 21, 22, 23 of the industrial system 10”. This teaches the control commands with system settings are provided to the electrical power grid comprising power system equipment and controllers. IEDs 21, 22 and 23 all need settings so 3 control commands are sent for them);
wherein in real-time means that the digital simulation module is run contemporaneously with providing the one or more inputs to the digital twin simulation module, the determination of two or more control commands provided to the one or more power system equipment and controllers in the electric power grid ([0092]: “The computing system 40 has a data interface 43. The data interface 43 allows the digital twin 41 to be continuously updated so as to mimic the industrial system 10 during operation of the industrial system 10. This allows the computing system 40 to be used for identifying suitable system settings not only during commissioning, i.e. prior to operation of the industrial system 10, but also during ongoing operation of the industrial system 10”; And [0123]: “The application of the system settings at step 74 may be performed on-the-fly, essentially in real time”. All these teach the digital simulation module is run contemporaneously with providing the inputs and the determination of the control commands during the ongoing operation in real-time);
wherein the two or more control commands comprise an active or reactive power generation command that is simulated in the digital twin simulation module in real-time (FIG.1 and [0092]: “The computing system 40 has a data interface 43. The data interface 43 allows the digital twin 41 to be continuously updated so as to mimic the industrial system 10 during operation of the industrial system 10”. This teaches the control commands are simulated in the digital twin 41 in real-time. The limitation “an active or reactive power generation command” is recited at high level of generality without any detail. In its broadest reasonable interpretation, the limitation is construed as any command associated with any energy resources to impact their active/reactive power. Franke teaches in FIG. 4 and [0121]: “At step 74, if the system settings are to be transferred to the real-world industrial system 10, the system settings may be applied to the industrial system 10. Applying the system settings may comprise adapting settings of intelligent electronic devices, IEDs, 21, 22, 23 of the industrial system 10”. All these teach the optimization module determines the system settings and provides the settings to the electrical power system. IEDs 21, 22 and 23 all need settings so 3 control commands are sent for them. As Franke teaches in FIG. 1 and [0079], the commands sent to IEDs control the switches 31, 32 and 33 therefore control active and/or reactive power generation of the generators 11, 12 and 13).
Regarding claim 17, Franke teaches all the limitations of claim 16.
Franke further teaches:
the one or more commands provide optimal power system operations or grid support services for the electrical power grid ([0086]: “The optimization engine 42 is operative to extract possible system settings with respect to different objectives and/or different constraints. The different objectives may include one or several of cost, stability criteria, redundancy criteria, energy consumption, emission minimization, customer reliability etc. of the operation of the industrial system 10”. This teaches the optimization module provides commands to achieve optimal power system operations according to objectives).
Regarding claim 18, Franke teaches all the limitations of claim 16.
Franke further teaches:
the two or more commands regulate one or more parameters of the electrical grid selected from the group consisting of voltage, peak shaving and loss minimization ([0086]: “The optimization engine 42 is operative to extract possible system settings with respect to different objectives and/or different constraints. The different objectives may include one or several of cost, stability criteria, redundancy criteria, energy consumption, emission minimization, customer reliability etc. of the operation of the industrial system 10”. This teaches the optimization module provides commands to regulate the industrial system 10 to achieve emission minimization. Since emission causes power loss, therefore achieving emission minimization is to achieve a loss minimization).
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, 3-4, 6-8 and 10-12 are rejected under 35 U.S.C. 103 as being unpatentable over Franke in view of Brunell (US 2005/0193739 A1, prior art of record, hereinafter as “Brunell “).
Regarding claim 1, Franke teaches:
A controller (computing system 40 in FIG. 1) for power system equipment and distributed energy resources in an electrical power system (DER 11, 12 and 13 of industrial system 10 in FIG. 1 and described in [0077]), comprising:
a digital twin simulation module (digital twin 41 in FIG. 1);
an optimization module (optimization routine 42 in FIG. 1);
wherein the digital twin simulation module receives one or more inputs from the electrical power system to update the digital twin simulation module while simulating the electrical power system (FIG. 1 and [0092]: “The computing system 40 has a data interface 43. The data interface 43 allows the digital twin 41 to be continuously updated so as to mimic the industrial system 10 during operation of the industrial system 10”. This teaches the digital twin receives inputs from the industrial system 10 to continuously update the detail twin in real time);
wherein the optimization module receives one or more inputs representing the current operational conditions of the power system (FIG. 1 and [0084]: “The optimization engine 42 uses the digital twin data of the digital twin 41 to explore possible changes in system settings that can be applied to the industrial system 10 and to determine in optimum one among plural candidate system settings”; And [0085]: “The digital twin 41 mimics the behavior of the industrial system 10”. All these teach that the optimization module received inputs from the digital twin which representing the current operation conditions of the electrical power system);
wherein the optimization module provides two or more control commands comprising an active or reactive power generation command to one or more power system equipment or distributed energy resources in the electrical power system (the limitation “an active or reactive power generation command” is recited at high level of generality without any detail. In its broadest reasonable interpretation, the limitation is construed as any command associated with any energy resources to impact their active/reactive power. Franke teaches in [0084]: “The optimization engine 42 uses the digital twin data of the digital twin 41 to explore possible changes in system settings that can be applied to the industrial system 10”; And FIG. 4 and [0121]: “At step 74, if the system settings are to be transferred to the real-world industrial system 10, the system settings may be applied to the industrial system 10. Applying the system settings may comprise adapting settings of intelligent electronic devices, IEDs, 21, 22, 23 of the industrial system 10”. All these teach the optimization module determines the system settings and provides the settings to the electrical power system. IEDs 21, 22 and 23 all need settings so 3 control commands are sent for them. As Franke teaches in FIG. 1 and [0079], the commands sent to IEDs control the switches 31, 32 and 33 therefore control active and/or reactive power generation of the generators 11, 12 and 13); and
wherein the digital twin simulation module receives one or more inputs from the electrical power system ([0092]: “The computing system 40 has a data interface 43. The data interface 43 allows the digital twin 41 to be continuously updated so as to mimic the industrial system 10 during operation of the industrial system 10. This allows the computing system 40 to be used for identifying suitable system settings not only during commissioning, i.e. prior to operation of the industrial system 10, but also during ongoing operation of the industrial system 10”. This teaches the inputs to the digital twin are provided in real-time to update the digital twin continuously) and wherein the optimization module provides two or more control commands to one or more power system equipment or distributed energy resources in the electrical power system in real-time ([0092] and [0123]: “The application of the system settings at step 74 may be performed on-the-fly, essentially in real time”. These teach the optimization module provides control commands during the ongoing operation in real-time).
Franke teaches all the limitations except a state estimation module wherein the state estimation module receives one or more inputs from the digital twin simulation module to calculate the operational states of the power system, wherein the optimization module receives one or more inputs from the state estimation module representing the current operational conditions of the power system.
However, Brunell teaches in an analogous art:
a state estimation module (state estimator 120 in FIG. 3 and described in [0022]); and
wherein the state estimation module receives one or more inputs from a digital model to calculate the operational states of the power system ([0022]: “The model 130 is used by the state estimator 120 to generate state parameters which include estimates of unmeasured and unsensed parameters”. This teaches the state estimator receives inputs from the model 130 to calculate the operational states/parameters of the electrical system);
wherein the optimization module receives one or more inputs from the state estimation module representing current operational conditions of the electrical power system (FIG. 3 an [0023]: “The state parameters from the state estimator 120 are transmitted to a model-based predictive control module 140. The control module 140 uses the state parameters to perform an optimization to determine commands for the actuators of the plant 110”. This teaches an optimizer receives inputs from the state estimator representing current operation conditions of the electrical system).
Since the digital twin in Franke is a also digital model to represent an electrical system, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Franke based on the teaching of Brunell, to make the controller to further comprise a state estimation module wherein the state estimation module receives one or more inputs from the digital twin simulation module to calculate operational states of the electrical power system; and wherein the optimization module receives one or more inputs from the state estimation module representing current operational conditions of the electrical power system. One of ordinary skill in the art would have been motivated to do this modification since having a state estimation module can help generate operational state parameters including “unmeasured and unsensed parameters”, as Brunell teaches in [0023].
Regarding claim 3, Franke-Brunell teach all the limitations of claim 1.
Franke further teaches:
the digital twin simulation module comprises model simulations of actuators and sensors of the electrical power system (FIG. 1 and [0057]: “The computer implemented representation of the digital twin may reflect both primary components of an electric power system and secondary components of the electric power system, …. The secondary components may comprise IEDs and/or merging units”; And [0080]: “Data from merging units 16, 17, 18 or sensors may be provided to the control devices 21, 22, 23 via the communication system 20”. All these teach the digital twin comprises model simulations of IEDs/actuators and sensors).
Regarding claim 4, Franke-Brunell teach all the limitations of claim 1.
Franke further teaches:
the one or more inputs from the electrical power system to the digital twin simulation module comprise one or more sensor measurements from one or more corresponding sensors in the electrical power system ([0080]: “Data from merging units 16, 17, 18 or sensors may be provided to the control devices 21, 22, 23 via the communication system 20”; And [0116]: “the digital twin 41 is synchronized with the industrial system 10 during operation of the industrial system 10. This may involve monitoring, by the computing system 40, messages transmitted in the communication network 20 of the industrial system 10. Synchronizing the digital twin 41 with the industrial system 10 may comprise adapting the digital twin 41 to changes in physical devices of the industrial system 10….Synchronizing the digital twin 41 with the industrial system 10 may comprise adapting the digital twin 41 to changes in internal states of IEDs 21, 22, 23”. All these teach the digital twin receives inputs from the electrical power system comprising sensors, and the inputs inherently comprise sensor measurements).
Regarding claim 6, Franke-Brunell teach all the limitations of claim 1.
Franke further teaches:
the one or more control commands are selected from the group consisting of demand response signals, IEEE 1547-2018, active power setting, reactive power setting, constant power factor, voltage-reactive power mode, on/off commands, and other analog or digital control set points ([0121]: “0121] At step 74, if the system settings are to be transferred to the real-world industrial system 10, the system settings may be applied to the industrial system 10. Applying the system settings may comprise adapting settings of intelligent electronic devices, IEDs, 21, 22, 23 of the industrial system 10”. This teaches the control commands are analog or digital control set points for the industrial system 10).
Regarding claim 7, Franke-Brunell teach all the limitations of claim 1.
Franke further teaches:
the one or more inputs to the digital twin simulation module ([0092]: “The computing system 40 has a data interface 43. The data interface 43 allows the digital twin 41 to be continuously updated so as to mimic the industrial system 10 during operation of the industrial system 10”. This teaches the inputs to the digital twin are provided in real-time to update the digital twin continuously) and the one or more control commands are provided in real-time ([0123]: “The application of the system settings at step 74 may be performed on-the-fly, essentially in real time”).
Claim 8 recites a controller similar to the controller of claim 1 with similar limitations except “wherein the state estimation module receives one or more inputs from the digital twin simulation module to calculate operational states of the electrical power system”. Therefore, claim 8 is also rejected for the reasons recited in the rejection of claim 1.
Claims 10, 11 and 12 recite a controller similar to the controller of claims 3, 4 and 6 with similar limitations respectively. Therefore, claims 10, 11 and 12 are rejected for the same reason recited in the rejection of claims 3, 4 and 6 respectively.
Claims 13, 14 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Franke in view of Brunell, and in further view of Benitez (US 2011/0213739 A1, prior art of record, hereinafter as “Benitez”).
Regarding claim 13, Franke teaches:
A method for controlling one or more power system devices and/or distributed energy resources (DER 11, 12 and 13 in FIG. 1 and described in [0077]) in an electrical power grid (FIG. 1 and [0085]: the industrial system 10/(electrical power grid)), comprising:
simulating the electrical power grid in real-time in a digital twin simulation module (digital twin 41 in FIG. 1 and described in [0092]), wherein the simulation module includes power system equipment and controller simulations (FIG. 1 and [0077, 0079]: the digital twin mimic the electrical power grid 10 which includes power system equipment and controller);
providing one or more inputs to the digital twin simulation module from one or more sensors in the electrical power grid (FIG.1 and [0080, 0116]: the digital twin receives inputs from the electrical power grid comprising sensors, and the inputs inherently comprise sensor measurements);
an optimization module that determines two or more control commands comprising an active or reactive power generation command in addition to at least one other command that are provided to one or more power system equipment and controllers of the electrical power grid (the limitation “an active or reactive power generation command” is recited at high level of generality without any detail. In its broadest reasonable interpretation, the limitation is construed as any command associated with any energy resources to impact their active/reactive power. The limitation “at least one other command” is construed, in its broadest reasonable interpretation, as any command provide to the power equipment. Franke teaches in FIG. 4 and [0121]: “At step 74, if the system settings are to be transferred to the real-world industrial system 10, the system settings may be applied to the industrial system 10. Applying the system settings may comprise adapting settings of intelligent electronic devices, IEDs, 21, 22, 23 of the industrial system 10”. This teaches the control commands with system settings are provided to the electrical power grid comprising power system equipment and controllers. IEDs 21, 22 and 23 all need settings so two control commands are sent to IEDs 21 and 22, in additional to 1 other command is sent to IED 23. As Franke teaches in FIG. 1 and [0079], the commands sent to IEDs 21 and 22 control the switches 31 and 32 therefore control active and/or reactive power generation of the generators 11 and 12).
Franke teaches all the limitations except providing one or more inputs to a state estimator from the digital twin simulation module, the one or more inputs from the digital twin simulation module selected from the group consisting of active power, reactive power, voltage, current, frequency, power factor, or phasor data; and determining a state estimation solution at the state estimator that is provided to an optimization module that determines the two or more control commands.
However, Brunell teaches in an analogous art:
providing one or more inputs to a state estimator (state estimator 120 in FIG. 3 and described in [0022]) from a digital model ([0022]: “The model 130 is used by the state estimator 120 to generate state parameters which include estimates of unmeasured and unsensed parameters”. This teaches the state estimator receives inputs from the model 130 to calculate the operational states/parameters of the electrical system);
determining a state estimation solution at the state estimator that is provided to an optimization module that determines two or more control commands (FIG. 3 an [0023]: “The state parameters from the state estimator 120 are transmitted to a model-based predictive control module 140. The control module 140 uses the state parameters to perform an optimization to determine commands for the actuators of the plant 110”. This teaches an optimizer receives inputs from the state estimator representing current operation conditions of the electrical system).
Since the digital twin in Franke is a also digital model to represent an electrical system, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Franke based on the teaching of Brunell, to make the method to further comprise providing one or more inputs to a state estimator from the digital twin simulation module and determining a state estimation solution at the state estimator that is provided to an optimization module that determines the two or more control commands. One of ordinary skill in the art would have been motivated to do this modification since having a state estimation module can help generate operational state parameters including “unmeasured and unsensed parameters”, as Brunell teaches in [0023].
Franke-Brunell teaches all the limitations except the one or more inputs from the digital twin simulation module selected from the group consisting of active power, reactive power, voltage, current, frequency, power factor, or phasor data.
However, Benitez teaches in an analogous art:
the one or more inputs from the digital twin simulation module selected from the group consisting of active power, reactive power, voltage, current ([0056]: “the estimator 102 executes a stored program 116 to learn a model for an electrical device. By way of example, the estimator may be used to obtain signals from the sensor device 114 while an electrical device, such as electrical device 138 for purpose of this example, is changed from an "off" condition to an "on" condition. In the event that the sensor device 114 is monitoring voltage and current of the power source 130, the estimator 102 executes a stored program 116 to generate a model wherein for a given input voltage to the electrical device 138, the observed change in current in the power source 130 is the output of the model”. This teaches a model is constructed and simulated, and the model outputs a simulated/pseudo-measured current value), frequency, power factor, or phasor data.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Franke-Brunell based on the teaching of Benitez, to make the method wherein the one or more inputs from the digital twin simulation module are selected from the group consisting of active power, reactive power, voltage, current, frequency, power factor, or phasor data. One of ordinary skill in the art would have been motivated to do this modification since it can help “determine ..operational stages of the plurality of electrical devices”, as Benitez teaches in the Abstract.
Regarding claim 14, Franke-Brunell-Benitez teach all the limitations of claim 13.
Franke further teaches:
the two or more commands further comprise one or more commands that provide optimal power system operations or grid support services for the electrical power grid ([0086]: “The optimization engine 42 is operative to extract possible system settings with respect to different objectives and/or different constraints. The different objectives may include one or several of cost, stability criteria, redundancy criteria, energy consumption, emission minimization, customer reliability etc. of the operation of the industrial system 10”. This teaches the optimization module provides commands to achieve optimal power system operations according to objectives. Franke also teaches in [0085] that the industrial system 10 is an electrical power grid).
Regarding claim 15, Franke-Brunell-Benitez teach all the limitations of claim 13.
Franke further teaches:
the two or more commands regulate one or more parameters of the electrical grid selected from the group consisting of voltage, peak shaving and loss minimization ([0086]: “The optimization engine 42 is operative to extract possible system settings with respect to different objectives and/or different constraints. The different objectives may include one or several of cost, stability criteria, redundancy criteria, energy consumption, emission minimization, customer reliability etc. of the operation of the industrial system 10”. This teaches the optimization module provides commands to regulate the industrial system 10 to achieve emission minimization. Since emission causes power loss, therefore achieving emission minimization is to achieve a loss minimization. Franke also teaches in [0085] that the industrial system 10 is an electrical power grid).
Claims 2 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Franke in view of Brunell, and in further view of Cella (US 2021/0272394 A1, prior art of record, hereinafter as “Cella”).
Regarding claim 2, Franke-Brunell teach all the limitations of claim 1, but they don’t teach the digital twin simulation module comprises a database of historical operations of the electrical power system.
However, Cella teaches in an analogous art:
the digital twin simulation module comprises a database of historical operations of the electrical system ([0502]: “digital twin 60136 of the vehicle 60104 is a virtual replication of hardware, software, and processes in the vehicle 60104 that combines real-time and historical operational data”. This teaches a digital twin of a vehicle( which comprises electrical system) comprises historical operational data stored inherently in a database).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Franke-Brunell based on the teaching of Cella, to make the controller wherein the digital twin simulation module comprises a database of historical operations of the electrical power system. One of ordinary skill in the art would have been motivated to do this modification since the digital twin can use the historical data to predict the operation to avoid unplanned downtime, as Cella teaches in [0523].
Claim 9 recites a controller similar to the controller of claim 2 with similar limitations. Therefore, claim 9 is also rejected for the reason recited in the rejection of claim 2.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Franke in view of Brunell, and in further view of Benitez.
Regarding claim 5, Franke-Brunell teach all the limitations of claim 1, but they don’t teach the one or more inputs from the digital twin simulation module to the state estimation module are one or more power system pseudo-measurements selected from the group consisting of an active power, a reactive power, a voltage, a current, a frequency, a power factor, or phasor data.
However, Benitez teaches in an analogous art:
the one or more inputs from the digital twin simulation module are one or more power system pseudo-measurements selected from the group consisting of an active power, a reactive power, a voltage, a current ([0056]: “the estimator 102 executes a stored program 116 to learn a model for an electrical device. By way of example, the estimator may be used to obtain signals from the sensor device 114 while an electrical device, such as electrical device 138 for purpose of this example, is changed from an "off" condition to an "on" condition. In the event that the sensor device 114 is monitoring voltage and current of the power source 130, the estimator 102 executes a stored program 116 to generate a model wherein for a given input voltage to the electrical device 138, the observed change in current in the power source 130 is the output of the model”. This teaches a model is constructed and simulated, and the model outputs a simulated/pseudo-measured current value), a frequency, a power factor, or phasor data.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Franke-Brunel based on the teaching of Benitez, to make the controller wherein the one or more inputs from the digital twin simulation module to the state estimation module are one or more power system pseudo-measurements selected from the group consisting of an active power, a reactive power, a voltage, a current, a frequency, a power factor, and phasor data. One of ordinary skill in the art would have been motivated to do this modification since it can help “determine ..operational stages of the plurality of electrical devices”, as Benitez teaches in the Abstract.
Conclusion
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/CHARLES CAI/Primary Patent Examiner, Art Unit 2115
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