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 .
Examiner Notes
Examiner cites particular columns, paragraphs, figures and line numbers in the
references as applied to the claims below for the convenience of the applicant. Although
the specified citations are representative of the teachings in the art and are applied to the
specific limitations within the individual claim, other passages and figures may apply as well. It
is respectfully requested that, in preparing responses, the applicant fully consider the
references in their entirety as potentially teaching all or part of the claimed invention, as well as
the context of the passage as taught by the prior art or disclosed by the examiner. The entire
reference is considered to provide disclosure relating to the claimed invention. The claims &
only the claims form the metes & bounds of the invention. Office personnel are to give
the claims their broadest reasonable interpretation in light of the supporting disclosure.
Unclaimed limitations appearing in the specification are not read into the claim. Prior art was
referenced using terminology familiar to one of ordinary skill in the art. Such an approach is
broad in concept and can be either explicit or implicit in meaning. Examiner's Notes are
provided with the cited references to assist the applicant to better understand how the
examiner interprets the applied prior art. Such comments are entirely consistent with the
intent & spirit of compact prosecution.
Drawings
The drawings are objected to because figures 1, 2, and 5 are missing text labels for the numerical labels. The lack of text descriptions for these figures creates clarity issues. Therefore, drawings should be corrected.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
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 following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
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 limitations are: “…a subsystem module…”, “…a simulation module…”, and “…an optimization module…” in claim 10.
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 Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 18-20 are directed to non-statutory subject matter. The claims do not fall within at least one of the four categories of patent eligible subject matter because these claims are directed to a computer readable storage medium. Applicant’s specification does not define the computer readable storage medium. Since the specification is silent about the definition of the term, the computer readable storage medium may include transitory signals. Transitory signals do not fall under any of the four statutory categories of invention. Therefore claims 18-20 are rejected under 35 USC 101.
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 nonobviousness.
Claims 1, 3-9, 10, 12-17, 18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Masselski et al. “Conception and optimization of an ammonia synthesis superstructure for energy storage” (2021) [herein “Masselski”], in view of Armijo et al. “Flexible production of green hydrogen and ammonia from variable solar and wind energy: Case study of Chile and Argentina” (2020) [herein “Armijo”], and in view of KOLODZIEJCZYK et al. WO 2021163769 A1 (2021) [herein “KOLODZIEJCZYK”].
Regarding Claim 1, Masselski teaches
A method of configuring an industrial gas production complex superstructure comprising one or more plant subsystems and being powered at least in part by one or more renewable power subsystems, the method being executed by at least one hardware processor and comprising:“Ammonia has a potential as carbon-free and high-energy density compound for chemical storage of renewable energies and its synthesis from green H2 requires to be as energetically efficient as possible. In this work, a superstructure optimization methodology for process synthesis is proposed and applied to an ammonia production process.”. (Abstract).
“The superstructure can be divided into four main stages, as seen in Fig. 3: compression, reaction, separation and recycle. In the compression and reaction stages…”. (Section 3.2).
“In the present work, a methodology for process synthesis using superstructure optimization is presented, which is applied to the case of ammonia production, using H2 and N2 issued from the use of wind energy.”. (Section 1.0).
“…as it has proven to be useful for its integration to ProSimPlus software for other applications of superstructure optimization…”. (Section 2.3).
This shows a configurable superstructure industrial plant being powered by various renewable energies to be implemented as a method to be ran.
providing a model of the industrial gas production complex superstructure having a plurality of selectable configurations representative of potential configurations of the industrial gas production complex superstructure;“…a superstructure can be defined as the process architecture built to evaluate several process alternatives simultaneously, to find the optimal configuration in terms of equipment interconnection and operating conditions, allowing to optimize a unique or a set of objective functions. This means that instead of being a fixed process flowsheet, the superstructure has the flexibility for evaluating all existing process paths.”. (Section 2.1).
“The superstructure can be divided into four main stages, as seen in Fig. 3: compression, reaction, separation and recycle. In the compression and reaction stages, the intermediate opening and closing switches are included. Their objective is to bypass certain zones of the process when evaluating a specific path.”. (3.2).
This shows a superstructure that can be changed and configured to find an optimal configuration.
Masselski does not explicitly teach but Armijo teaches,specifying, in the model, a plurality of selectable modelled renewable power subsystems, each modelled renewable power subsystem having predicted time series power profile data for a predetermined time period associated therewith;“For each location, our modelling estimates the short-term costs of mass production of H2 and NH3 based on full meteorological yearly data with hourly resolution, determining the optimal relative sizes of the solar, wind and NH3-synthesis units”. (Introduction).
“Our model considers a fixed electrolyser nominal size PH2, powered by dedicated solar and/or wind farms of capacities Psolar and Pwind.”. (Section: Description of the model).
This shows modelled renewable power subsystems with associated time data.
specifying, in the model, a plurality of selectable modelled plant subsystems, each selectable modelled plant subsystem having a plurality of selectable modelled components associated therewith;
“The superstructure can be divided into four main stages…”. (Section 3.2).“the superstructure makes possible to evaluate 2, 3 or 4 compressors. If only two compressors are required, the switch A1 will connect with the closing switch A. For evaluating three compressors, switch A1 will connect to intercooler 5”. (Section 3.2).
“The possibility of using up to three adiabatic reactors filled with Fe-based or Ru-based catalyst is included… Two reactor configurations are analyzed…”. (Section 3.2).
This shows different subsystems that have different possible configurations.
Masselski and Armijo do not teach but KOLODZIEJCZYK teaches,associating a plurality of operational parameters and a plurality of operational constraints with each of the plurality of modelled renewable power subsystems, with each of the plurality of modelled plant subsystems and with the each of the plurality of selectable modelled components;“…inputting technical information to the model to simulate the plant, including a plurality of values relating to configuration of the plant…”. (Abstract).
“454 (1) e.g. electrolyser power consumption, Haber-Bosch plant ramp-up time, etc.;”. (LIST OF REFERENCE NUMERALS).
“The model can choose between two types of electrolysers. A deionizer step and subsequent storage modelling are only required when the proton exchange membrane (PEM) electrolyser is used. However, if an alkaline electrolyser is used, water from reverse osmosis is sufficient.”. (Pg. 10 Lines 23-26).
“The model uses a minimum function to ensure the most optimal operation. The minimum function evaluates available feedstock commodities that are necessary in a given process and converts them into energy equivalent for fair comparison. By doing so the process not only operates at the most optimal performance, but also makes sure that output commodities are produced only when sufficient feedstock commodities are available.”. (Pg. 14 Lines 9-14).
This shows associated operational parameters of the subsystems and selectable components.
selecting a plurality of configurations of the model by selecting, for each configuration: one or more modelled renewable power subsystems; one or more modelled plant subsystems; and one or more components associated with the selected one or more modelled plant subsystems;“selecting an optimization criteria; and optimizing the criteria by varying the selected variables using an algorithm to identify a set of optimum values.”. (Abstract).
“At each step, the optimisation algorithm will sample from the priors over all the optional system components.”. (Pg. 11 Lines 12-13).
“The model uses one of the available and embedded optimization algorithms to work in a loop and to find the lowest levelized cost of ammonia (LCOA), by scaling up, scaling down all or removing the optional subsystem components.”. (Pg. 11 Lines 8-10).
This shows being able to configure power subsystems, components, and optimization criteria.
determining, for each selected configuration, the predicted operation of the selected configuration of an industrial gas production complex superstructure over a predetermined time period to determine a maximum value of a predetermined operational output parameter for the selected configuration and for the predetermined time period, the predicted operation utilizing the power profile data associated with the one or more selected renewable power subsystems and the operational parameters and operational constraints associated with the selected configuration;“Figure 1 shows example annual output plots and commodity flow 10 for each hour of an entire year which may be used as data for the modelling.”. (Pg. 6 Lines 11-12).
“Complex optimization is performed on given intermittent energy and material profiles with selected data interval granularity, i.e., hourly interval.”. (Pg. 16 Lines 2-4).
“…inputting technical information for each component to the model to simulate the plant, including a plurality of values relating to configuration of the plant…”. (Claim 20).
This shows configurations of the plant with associated energy, material, and time data / profiles.
utilizing a surrogate model to identify, based on the operational output parameter data and the selected configuration data for each configuration, one or more configurations of the industrial gas production complex superstructure operable to maximize the value of the operational output parameter whilst meeting the predefined operational constraints; and“The surrogate function can be any chosen regression function which estimates the value of the objective function for points in the search space not yet sampled. The optimiser can use the surrogate function's estimates to select points in the search space that are more likely to yield the best LCOA.”. (Pg. 11 Lines 15-18).
This shows the surrogate optimizing based on the given criteria.
generating one or more designs for the industrial gas production complex superstructure based on the identified one or more configurations.
“The optimisation output may be in the form of, for example, levelised cost of hydrogen (LCOH) 650, size and utilisation of every component in the process 652, and inputs and outputs for each component 654.”. (Pg. 7 Lines 13-15).
This shows generating the optimization design of the plant based on the criteria selected.
It would have been obvious to one of the ordinary skills in the art before the effective filing date of the applicants claimed invention to combine Masselski, Armijo, and KOLODZIEJCZYK. Masselski discloses a method for configuring a modelled plant superstructure. Armijo discloses a way to specify and model subsystems with associated time data and components. As Armijo states “In this paper, we present a techno-economic model that plainly addresses these questions, using four example locations in Chile and Argentina, two countries having world-class variable renewable energy (VRE) resources, and thus tremendous potentials for becoming leading RE producers, and exporters of RE stored in H-rich chemicals [8,18].”. Combining these teachings of Masselski’s plant superstructure method would allow a PHOSITA with the ability to apply an optimization based on configurable plant subsystems.
A PHOSITA would have been further motivated to add KOLODZIEJCZYK’s generation of an optimized plant based on a configurable model to speed up analysis and optimize plant qualities. KOLODZIEJCZYK states “…it would be beneficial to have a system and method to facilitate the adaptation of a system or method such that a renewable energy source is able to be used to power such a process, including the planning of the system location, the planning of the system components and/or the sizing of the system components.”. Combining with Masselski’s teaching “In this work, a superstructure optimization methodology for process synthesis is proposed and applied to an ammonia production process. The approach covers three different scales: process, equipment, and molecules. Process scale refers to finding the optimal process structure..." would lead to improved optimization in a combination of Masselski-Armijo-KOLODZIEJCZYK by enabling the further granular selection of optimization values to reach the target goals.
Regarding Claim 3, Masselski, Armijo, do not explicitly teach but KOLODZIEJCZYK teaches
A method according to claim 2, wherein within each of said groups a plurality of selectable modelled renewable power subsystems are available to be selected, each selectable modelled renewable power subsystem sharing the same profile of the predicted time series power profile data but varying in the magnitude of the available maximum power.
“…system subcomponents can be independently scaled up and/or down affecting its generation capacity and associated investment cost. All components are independent from each other in a sense that only commodity flow and their availability (water, energy, hydrogen, nitrogen, etc.) affect the next component along the value chain. The cascading build of the system and unique interaction of the components through commodity streams makes this modelling framework completely flexible…”. (Pg. 5 Lines 23-28).
This shows different power subsystems with configurable components and criteria.
Regarding Claim 4, Masselski, Armijo, do not explicitly teach but KOLODZIEJCZYK teaches
A method according to claim 2, wherein a plurality of selectable modelled renewable power subsystems may be selected from at least two different groups.
“Preferably, the intermittent energy source includes a plurality of renewable energy sources.”. (Pg. 2 Lines 4-5).
“As such, some other approaches attempted to simplify the optimization process by focusing solely on finding the optimal mix of power generation components (i.e., wind and solar).”. (Pg. 8 Lines 13-15).
This shows multiple renewable power systems being able to be mixed and matched.
Regarding Claim 5, Masselski, Armijo, do not explicitly teach but KOLODZIEJCZYK teaches
A method according to claim 1, wherein the plurality of selectable modelled plant subsystems is arranged in groups of: gas production plant subsystems and gas storage subsystems.
“…supplied to an electrolyser 322, where together with electric energy, it is converted into hydrogen 326... Cascading energy output from the hydrogen compressor 334 is then supplied to an Air Separation Unit (ASU) 332 where atmospheric air is liquefied to produce pure nitrogen 312.”. (Pg. 10 Lines 7-14).
This shows arrangement of separate gas production and gas storage systems.
Regarding Claim 6, Masselski, Armijo, do not explicitly teach but KOLODZIEJCZYK teaches
A method according to claim 5, wherein the gas production plant subsystems comprise one or more of: hydrogen production plant; air separation unit; and ammonia production plant, and wherein the gas storage subsystems comprise one or more of: hydrogen gas storage; hydrogen liquefier; nitrogen storage; and ammonia storage.
“…supplied to an electrolyser 322, where together with electric energy, it is converted into hydrogen 326… supplied to an Air Separation Unit (ASU) 332 where atmospheric air is liquefied to produce pure nitrogen 312… The final step is the Haber-Bosch plant 306 where, under high pressure and temperature, hydrogen and nitrogen feedstocks are converted into ammonia 304.”. (Pg. 10 Lines 7-17).
This shows gas production subsystems and storage subsystems.
Regarding Claim 7, Masselski, Armijo, do not explicitly teach but KOLODZIEJCZYK teaches
A method according to claim 6, wherein at least one selected gas production plant subsystem comprises a hydrogen production plant and wherein the selectable modelled components for the hydrogen production plant are selectable from one or more of: electrolyser type; electrolyser capacity; compressor systems; purifier systems.
“The model can choose between two types of electrolysers. A deionizer step and subsequent storage modelling are only required when a proton exchange membrane (PEM) electrolyser is used. However, if an alkaline electrolyser is used, reverse osmosis water is sufficient.”. (Pg. 10 Para 5).
“Low pressure 330 and medium pressure hydrogen storage 338 can be omitted as hydrogen produced in the electrolyser 322 can be supplied directly to the hydrogen compressor 334 and later to the Haber-Bosch plant 306. • Low 328 and medium pressure 316 nitrogen storages can also be omitted if energy quality is high.”. (Pg.11 Para 1).
“The model uses one of the available and embedded optimization algorithms to work in a loop and to find the lowest levelized cost of ammonia (LCOA), by scaling up, scaling down all or removing the optional subsystem components.”. (Pg.11 Para 4).
This shows a possible hydrogen plant with selectable mentioned subsystems.
Regarding Claim 8, Masselski, Armijo, do not explicitly teach but KOLODZIEJCZYK teaches
A method according to claim 1, wherein the predetermined operational output parameter comprises the amount of gas produced by the industrial gas production complex superstructure.
“454 (1) e.g. electrolyser power consumption, Haber-Bosch plant ramp-up time, etc.; 456 (2) e.g., price per unit, discount rates, inflation rates, etc.; 458 (3) e.g., LCOE, LCOH, LCOA, LCOS, produced hydrogen, produced ammonia, carbon tax, etc.; 460 (4) e.g., size of reverse osmosis plant, solar farm capacity, wind farm capacity, energy storage capacity, etc.;”. (Pg. 26).
“In addition, the optimum values 492 may be provided in the form of an optimisation output table 540 as shown in Figure 11.”. (Pg.7 Para. 2).
This shows being able to output produced gas volumes.
Regarding Claim 9, Masselski, Armijo, do not explicitly teach but KOLODZIEJCZYK teaches
A method according to claim 1, further comprising: constructing an industrial gas production complex superstructure according to the design.
“A plant optimised using a method as claimed in any one of claims 1 to 12 or 20 to 29.”. (Claim 30).
“Other optimisation algorithms have been tested and are applicable to be used with the framework. A non-exclusive list of such optimisation algorithms includes evolutionary algorithms, machine learning algorithms and brute-force. This framework is not limited to green hydrogen, green ammonia or green steel production. The model and optimization strategy can be applied to optimize any value chain and design a working facility with the lowest levelized cost of produced commodity. This invention can be applied in the mining industry, mineral processing and other chemical industries, other than ammonia. Effectively this invention can be applied in any value chain optimization process.”. (Pg. 7-8 Lines 28-29 and 1-6).
This shows a method to produce an optimized plant design based on selected criteria.
Regarding Claim 10, Masselski teaches
A system for configuring an industrial gas production complex superstructure comprising one or more plant subsystems and being powered at least in part by one or more renewable power subsystems, the system comprising:“Ammonia has a potential as carbon-free and high-energy density compound for chemical storage of renewable energies and its synthesis from green H2 requires to be as energetically efficient as possible. In this work, a superstructure optimization methodology for process synthesis is proposed and applied to an ammonia production process.”. (Abstract).
“The superstructure can be divided into four main stages, as seen in Fig. 3: compression, reaction, separation and recycle. In the compression and reaction stages…”. (Section 3.2).
“In the present work, a methodology for process synthesis using superstructure optimization is presented, which is applied to the case of ammonia production, using H2 and N2 issued from the use of wind energy.”. (Section 1.0).
“…as it has proven to be useful for its integration to ProSimPlus software for other applications of superstructure optimization…”. (Section 2.3).
This shows a configurable superstructure industrial plant being powered by various renewable energies to be implemented as a method to be ran.
Masselski does not explicitly teach but Armijo teaches,specify a plurality of selectable modelled renewable power subsystems, each modelled renewable power subsystem having predicted time series power profile data for a predetermined time period associated therewith; and“For each location, our modelling estimates the short-term costs of mass production of H2 and NH3 based on full meteorological yearly data with hourly resolution, determining the optimal relative sizes of the solar, wind and NH3-synthesis units”. (Introduction).
“Our model considers a fixed electrolyser nominal size PH2, powered by dedicated solar and/or wind farms of capacities Psolar and Pwind.”. (Section: Description of the model).
This shows modelled renewable power subsystems with associated time data.
specify a plurality of selectable modelled plant subsystems, each selectable modelled plant subsystem having a plurality of selectable modelled components associated therewith;“The superstructure can be divided into four main stages…”. (Section 3.2).“the superstructure makes possible to evaluate 2, 3 or 4 compressors. If only two compressors are required, the switch A1 will connect with the closing switch A. For evaluating three compressors, switch A1 will connect to intercooler 5”. (Section 3.2).
“The possibility of using up to three adiabatic reactors filled with Fe-based or Ru-based catalyst is included… Two reactor configurations are analyzed…”. (Section 3.2).
This shows different subsystems that have different possible configurations.
Masselski and Armijo do not teach but KOLODZIEJCZYK teaches,
at least one hardware processor;a subsystem module operable to:provide a model of the industrial gas production complex superstructure having a plurality of selectable configurations representative of potential configurations of the industrial gas production complex superstructure;“…using a computer to model the plant; inputting data to the model relating to historical availability of the intermittent energy source; inputting technical information to the model to simulate the plant, including a plurality of values relating to configuration of the plant; inputting financial information to the model; selecting one or more of the values to be variables; selecting an optimization criteria; and optimizing the criteria by varying the selected variables using an algorithm to identify a set of optimum values.”. (Abstract).
This shows using computer hardware to model an industrial plant.
a simulation module operable to:associate a plurality of operational parameters and a plurality of operational constraints with each of the plurality of modelled renewable power subsystems, with each of the plurality of modelled plant subsystems and with the each of the plurality of selectable modelled components;
“…using a computer to model the plant…”. (Abstract).“…inputting technical information to the model to simulate the plant, including a plurality of values relating to configuration of the plant…”. (Abstract).
“454 (1) e.g. electrolyser power consumption, Haber-Bosch plant ramp-up time, etc.;”. (LIST OF REFERENCE NUMERALS).
“Turning to Figure 8 and Figure 9, the method may include the steps of generating a mathematical model 446 of the plant; inputting data 432 to the model relating to historical availability of the intermittent energy source; inputting technical information 450 to the model to simulate the plant…”. (Pg.6 Para. 5)
“The model can choose between two types of electrolysers. A deionizer step and subsequent storage modelling are only required when the proton exchange membrane (PEM) electrolyser is used. However, if an alkaline electrolyser is used, water from reverse osmosis is sufficient.”. (Pg. 10 Lines 23-26).
“The model uses a minimum function to ensure the most optimal operation. The minimum function evaluates available feedstock commodities that are necessary in a given process and converts them into energy equivalent for fair comparison. By doing so the process not only operates at the most optimal performance, but also makes sure that output commodities are produced only when sufficient feedstock commodities are available.”. (Pg. 14 Lines 9-14).
This shows associated operational parameters of the subsystems and selectable components.
select a plurality of configurations by selecting, for each configuration: one or more modelled renewable power subsystems; one or more modelled plant subsystems; and one or more components associated with the selected one or more modelled plant subsystems; and“selecting an optimization criteria; and optimizing the criteria by varying the selected variables using an algorithm to identify a set of optimum values.”. (Abstract).
“At each step, the optimisation algorithm will sample from the priors over all the optional system components.”. (Pg. 11 Lines 12-13).
“The model uses one of the available and embedded optimization algorithms to work in a loop and to find the lowest levelized cost of ammonia (LCOA), by scaling up, scaling down all or removing the optional subsystem components.”. (Pg. 11 Lines 8-10).
This shows being able to configure power subsystems, components, and optimization criteria.
determine, for each selected configuration, the predicted operation of the selected configuration of an industrial gas production complex superstructure over a predetermined time period to determine a maximum value of a predetermined operational output parameter for the selected configuration and for the predetermined time period, the predicted operation utilizing the power profile data associated with the one or more selected renewable power subsystems and the operational parameters and operational constraints associated with the selected configuration; and“Figure 1 shows example annual output plots and commodity flow 10 for each hour of an entire year which may be used as data for the modelling.”. (Pg. 6 Lines 11-12).
“Complex optimization is performed on given intermittent energy and material profiles with selected data interval granularity, i.e., hourly interval.”. (Pg. 16 Lines 2-4).
“…inputting technical information for each component to the model to simulate the plant, including a plurality of values relating to configuration of the plant…”. (Claim 20).
This shows configurations of the plant with associated energy, material, and time data / profiles.
an optimization module operable to:utilize a surrogate model to identify, based on the operational output parameter data and the selected configuration data for each configuration, one or more configurations of the industrial gas production complex superstructure operable to maximize the value of the operational output parameter whilst meeting the predefined operational constraints; and
“…using a computer to model the plant…”. (Abstract).
“The optimization method deployed to perform optimization on this unique model uses a surrogate function…”. (Pg. 7 Para. 4).“The surrogate function can be any chosen regression function which estimates the value of the objective function for points in the search space not yet sampled. The optimiser can use the surrogate function's estimates to select points in the search space that are more likely to yield the best LCOA.”. (Pg. 11 Lines 15-18).
This shows the surrogate optimizing based on the given criteria.
generate one or more designs for the industrial gas production complex superstructure based on the identified one or more configurations.
“The optimisation output may be in the form of, for example, levelised cost of hydrogen (LCOH) 650, size and utilisation of every component in the process 652, and inputs and outputs for each component 654.”. (Pg. 7 Lines 13-15).
This shows generating the optimization design of the plant based on the criteria selected.
Claims 12-17 recite substantially the same limitations as claims 3-9 except these claims are directed to a “A system”. Therefore, these claims are rejected under the same rationale as addressed above.
Claims 18 and 20 recite substantially the same limitations as claims 1 and 3 except these claims are directed to a “A computer readable storage medium”. Therefore, these claims are rejected under the same rationale as addressed above.
Claims 2, 11, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Masselski et al. “Conception and optimization of an ammonia synthesis superstructure for energy storage” (2021) [herein “Masselski”], in view of Armijo et al. “Flexible production of green hydrogen and ammonia from variable solar and wind energy: Case study of Chile and Argentina” (2020) [herein “Armijo”], in view of KOLODZIEJCZYK et al. WO 2021163769 A1 (2021) [herein “KOLODZIEJCZYK”], and in view of MARCUS et al. WO 2013109890 A2 (2013) [herein “MARCUS”].
Regarding Claim 2, Masselski, Armijo, and KOLODZIEJCZYK do not explicitly teach but Marcus teaches
A method according to claim 1, wherein the plurality of selectable modelled renewable power subsystems is arranged in groups of: wind farm subsystems, solar farm subsystem, tidal power subsystems and hydroelectric power subsystems.
“The method of claim 1, wherein the power source is an intermittent power source selected from the group consisting of wind energy, solar energy, wave energy, tidal energy, falling water, hydro energy, biomass energy, and geothermal energy.”. (Claim 22).
This shows varied selectable renewable power subsystems.
It would have been obvious to one of the ordinary skills in the art to combine Marcus, and the Masselski-Armijo-KOLODZIEJCZYK combination to use the renewable energy storage and delivery system of Marcus with the implementation of a configurable gas superstructure optimizer of Masselski-Armijo-KOLODZIEJCZYK to incorporate “…a system and method for encouraging the use of renewable energy sources and the conservation of non-renewable resources through the efficient management of energy storage and delivery.”. (Marcus, Para. 2).
Claim 11 recites substantially the same limitations as claims 2 except this claim is directed to a “A system”. Therefore, this claim is rejected under the same rationale as addressed above.
Claim 19 recites substantially the same limitations as claim 2 except this claim is directed to a “A computer readable storage medium”. Therefore, this claim is 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. WO 2022194688 A1 by SAMAL et al, US 20210157312 A1 by Cella et al, US 20200387818 A1 by Chan et al, US 20180357343 A1 by KLENNER et al, and US 20180247000 A1 by VESTØL et al.
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/N.E.M./Examiner, Art Unit 2189
/REHANA PERVEEN/Supervisory Patent Examiner, Art Unit 2189