DETAILED ACTION
Notice of 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 .
Claims 1-19 are pending and are rejected.
Priority
Provisional:
Acknowledgment is made of applicant’s claim for priority to provisional application no. 63587364 filled on 10/02/2023.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 10/22/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement(s) is/are being considered by the examiner.
Drawings
Drawings filled on 09/10/2024 are acceptable for the examination purpose.
Claim Objections
Claims 2-6, 8-12 and 14-19 are objected to because of the following informalities:
Claims 2-6, 8-12 and 14-19 recite the word “Claim” where C is capitalized that is a typographical error.
For the examination purpose, the “Claim” is construed as, claim.
Claims 2-6 recite, The energy generation verification computer system. However, the parent claim 1 recites, energy generation authentication and verification computer system. Therefore, the energy generation verification computer system recited by claims 2-6 include typographical error.
For the examination purpose, the limitation is construed as, The energy generation authentication and verification computer system.
Claim 16 recites, The energy generation verification computer system as defined in claim 13, The computer system as defined in claim 13.
However, the parent claim 13 recites, A computer system. Therefore, claim 16 includes typographical error.
For the examination purpose, the limitation is construed as, The computer system as defined in claim 13.
Appropriate correction is required.
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 fall within the judicial exception of an abstract idea:
Claims 1-19 are rejected under 35 U.S.C. 101 because the claimed subject matter is directed to an abstract idea without significantly more.
Step 1:
Claims 1-19 are directed to system/method that fall within one of the four statutory categories (i.e., process, machine, manufacture, or composition of matter).
Step 2A:
The claims 1-19 fall within the judicial exception of an abstract idea. Specifically, Mental processes (see MPEP § 2106.04(a)(2), subsection III) such that concepts performed in the human mind or with pen and paper including observation, evaluation, judgment and opinion and/or Mathematical concepts (see MPEP § 2106.04(a)(2), subsection I) such as mathematical relationships, mathematical formulas or equations, mathematical calculations.
Step 2A – Prong 1:
Claim 1:
determine if the encrypted authentication data purporting to be from the first device associated with the power generation source is valid;
use the accessed configuration data associated with the power generation source and the accessed environmental data associated with the first location to calculate a predicted power quantity data for the power generation source at the first location;
compare the predicted power quantity data with the received power quantity data to determine if they correspond;
at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data, and that the encrypted authentication data purporting to be from the first device associated with the power generation source is valid, generate a corresponding validation indicator and transfer an electronic token to a first destination.
These limitations describe, determining, comparing, predicting and calculating using various data.
These limitations given its broadest reasonable interpretation in light of the specification is a Mental Process since this procedure can be performed in the human mind and/or using pen and paper and is a determination, comparison, prediction and using comparison data to determine results; and is Mathematical concepts such as mathematical calculations (validation indicator).
Claim 6:
…initiate a power generation remediation process at least partly in response to a determination that a second received power quantity data is less than a second predicted power quantity data by at least a threshold amount
This limitation describes, initiate a power generation remediation process based on determination.
Applicant’s specification ¶56 describes these remediation can be one of the cleaning of PV panels, component replacement, and/or the like.
These limitations given its broadest reasonable interpretation in light of the specification a Mental Process since this procedure can be performed by a human such as cleaning or replacing a component based on the determination performed in human mind.
Claim 7:
determining,…if the authentication data purporting to be from the first device associated with the power generation source is valid;
using the accessed configuration data associated with the power generation source and the accessed environmental data associated with the first location to calculate, using the computer system, a predicted power quantity data for the power generation source at the first location;
comparing the predicted power quantity data with the received power quantity data to determine if they correspond;
at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data, and that the authentication data purporting to be from the first device associated with the power generation source is valid, generating a corresponding validation indicator and transferring an electronic token to a first destination.
These limitations describe, determining, comparing, predicting and calculating using various data.
These limitations given its broadest reasonable interpretation in light of the specification is a Mental Process since this procedure can be performed in the human mind and/or using pen and paper and is a determination, comparison, prediction and using comparison data to determine results; and is Mathematical concepts such as mathematical calculations (validation indicator).
Claim 12:
…initiating a power generation remediation process at least partly in response to a determination that a second received power quantity data is less than a second predicted power quantity data by at least a threshold amount.
This limitation describes, initiate a power generation remediation process based on determination.
Applicant’s specification ¶56 describes these remediation can be one of the cleaning of PV panels, component replacement, and/or the like.
These limitations given its broadest reasonable interpretation in light of the specification a Mental Process since this procedure can be performed by a human such as cleaning or replacing a component based on the determination performed in human mind.
Claim 13:
determine if the authentication data purporting to be from the first device associated with the power generation source is valid;
at least partly in response to determining that the data purporting to be from the first device associated with the power generation source is valid, generating a corresponding validation indicator.
These limitations describe, determination and judgment to perform validation using data.
These limitations given its broadest reasonable interpretation in light of the specification is a Mental Process since this procedure can be performed in the human mind and/or using pen and paper and is a determination, validation and/or judgment.
Claim 14:
use the accessed configuration data associated with the power generation source and the accessed environmental data associated with the first location to calculate a predicted power quantity data for the power generation source at the first location;
compare the predicted power quantity data with the received power quantity data to determine if they correspond;
wherein the validation indicator is generated at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data.
These limitations describe, determining, comparing, predicting and calculating using various data.
These limitations given its broadest reasonable interpretation in light of the specification is a Mental Process since this procedure can be performed in the human mind and/or using pen and paper and is a determination, comparison, prediction and using comparison data to determine results, validation and or judgment; and is Mathematical concepts such as mathematical calculations (validation indicator).
Claim 15:
use the accessed configuration data associated with the power generation source and the accessed environmental data associated with the first location to calculate a predicted power quantity data for the power generation source at the first location;
compare the predicted power quantity data with the received power quantity data to determine if they correspond;
wherein the validation indicator is generated at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data, and
These limitations describe, determining, comparing, predicting and calculating using various data.
These limitations given its broadest reasonable interpretation in light of the specification is a Mental Process since this procedure can be performed in the human mind and/or using pen and paper and is a determination, comparison, prediction and using comparison data to determine results, validation and or judgment; and is Mathematical concepts such as mathematical calculations (validation indicator).
Claim 16:
use the accessed configuration data associated with the power generation source and the accessed environmental data associated with the first location to calculate a predicted power quantity data for the power generation source at the first location;
compare the predicted power quantity data with the received power quantity data to determine if they correspond;
wherein the validation indicator is generated at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data, and
These limitations describe, determining, comparing, predicting and calculating using various data.
These limitations given its broadest reasonable interpretation in light of the specification is a Mental Process since this procedure can be performed in the human mind and/or using pen and paper and is a determination, comparison, prediction and using comparison data to determine results, validation and or judgment; and is Mathematical concepts such as mathematical calculations (validation indicator).
Claim 17:
use the accessed configuration data associated with the power generation source and the accessed environmental data associated with the first location to calculate a predicted power quantity data for the power generation source at the first location;
compare the predicted power quantity data with the received power quantity data to determine if they correspond;
wherein the validation indicator is generated at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data,
These limitations describe, determining, comparing, predicting and calculating using various data.
These limitations given its broadest reasonable interpretation in light of the specification is a Mental Process since this procedure can be performed in the human mind and/or using pen and paper and is a determination, comparison, prediction and using comparison data to determine results, validation and or judgment; and is Mathematical concepts such as mathematical calculations (validation indicator).
Claim 18:
use the accessed configuration data associated with the power generation source and the accessed environmental data associated with the first location to calculate a predicted power quantity data for the power generation source at the first location;
compare the predicted power quantity data with the received power quantity data to determine if they correspond;
wherein the validation indicator is generated at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data
These limitations describe, determining, comparing, predicting and calculating using various data.
These limitations given its broadest reasonable interpretation in light of the specification is a Mental Process since this procedure can be performed in the human mind and/or using pen and paper and is a determination, comparison, prediction and using comparison data to determine results, validation and or judgment; and is Mathematical concepts such as mathematical calculations (validation indicator).
Claim 19:
…initiate a power generation remediation process at least partly in response to a determination that a second received power quantity data is less than a second predicted power quantity data by at least a threshold amount.
This limitation describes, initiate a power generation remediation process based on determination.
Applicant’s specification ¶56 describes these remediation can be one of the cleaning of PV panels, component replacement, and/or the like.
These limitations given its broadest reasonable interpretation in light of the specification a Mental Process since this procedure can be performed by a human such as cleaning or replacing a component based on the determination performed in human mind.
Step 2A – Prong 2 and Step 2B:
This judicial exception is not integrated into a practical application because the additional elements including the following limitations computer system (claims 1-7 and 13-19), network interface (claims 1 and 13-18), processing device (claims 1 and 13) as recited in the claims are mere instructions to implement an abstract idea on a general purpose computer (apply it; corresponding structure disclosed in the specification is a general purpose computer implementing the claimed functions characterized as abstract ideas above. See MPEP 2106.05(a)). The claim limitations are implemented on these generic elements such that the following are merely applying the abstract idea on a generic computer: determining, evaluating, analyzing, and determining etc.
Claim(s) 1 recites, “An energy generation authentication and verification computer system, the computer system comprising:” and “at least one processing device operable to:”. This is generally linking the use of a judicial exception to a particular technological environment or field of use (such as energy generation and energy management field). See MPEP 2106.05(h).
Claim(s) 2, 8 and 15 recite, “wherein the power generation source comprises a photovoltaic panel and the configuration data associated with the power generation source comprises solar panel size data and solar panel efficiency data.” This is generally linking the use of a judicial exception to a particular technological environment or field of use (such as energy generation and energy management field). See MPEP 2106.05(h).
Claim(s) 3, 9 and 16 recite, “wherein the power generation source comprises a wind turbine, and the configuration data associated with the power generation source comprises blade size data.” This is generally linking the use of a judicial exception to a particular technological environment or field of use (such as energy generation and energy management field). See MPEP 2106.05(h).
Claim(s) 4, 10 and 17 recite, “wherein the environmental data comprises cloud cover, sun position, and time of year.” This is generally linking the use of a judicial exception to a particular technological environment or field of use (such as energy generation and energy management field). See MPEP 2106.05(h).
Claim(s) 5, 11 and 18 recite, “wherein the environmental data comprises wind speed.” This is generally linking the use of a judicial exception to a particular technological environment or field of use (such as energy generation and energy management field). See MPEP 2106.05(h).
Claim(s) 6 and 19 recite, “wherein the computer system is configured to initiate a power generation remediation process.” This is generally linking the use of a judicial exception to a particular technological environment or field of use (such as energy generation and energy management field). See MPEP 2106.05(h).
Claim(s) 7 recites, “A computer implemented method, the method comprising:” This is generally linking the use of a judicial exception to a particular technological environment or field of use (such as energy generation and energy management field). See MPEP 2106.05(h).
Claim(s) 13 recites, “A computer system comprising:” “at least one processing device operable to:” and “wherein the first device is physically coupled to a photovoltaic panel, a wind turbine, or an inverter.” This is generally linking the use of a judicial exception to a particular technological environment or field of use (such as energy generation and energy management field). See MPEP 2106.05(h).
Claim(s) 14-19 recite, “the computer system is configured to:” This is generally linking the use of a judicial exception to a particular technological environment or field of use (such as energy generation and energy management field). See MPEP 2106.05(h).
The claim(s) recite the additional elements of,
(Claims 1) “receive…encrypted authentication data purporting to be from a first device associated with a power generation source at a first location;
receive…power quantity data purportedly generated by the power generation source at the first location;
access configuration data associated with the power generation source;
access environmental data associated with the first location;
transfer an electronic token to a first destination.”
(Claims 7) “receiving…authentication data purporting to be from a first device associated with a power generation source at a first location;
receiving power quantity data purportedly generated by the power generation source at the first location;
accessing configuration data associated with the power generation source;
accessing environmental data associated with the first location;
transferring an electronic token to a first destination.”
(Claim 13) “receive…authentication data purporting to be from a first device associated with a power generation source at a first location”
(Claims 14-18) “receive…power quantity data purportedly generated by the power generation source at the first location;
access configuration data associated with the power generation source;
access environmental data associated with the first location;”
These additional elements are recited at a high level of generality and as a form of insignificant extra solution activity recognized by court as well-understood, routine, conventional activity.
The receiving, accessing, transferring/outputting data are claimed in a merely generic manner (e.g., at a high level of generality) and as an insignificant extra solution activity such as mere data gathering, input and output that are recognized by the court as well-understood, routine, and conventional MPEP 2106.05(d)(ii)).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Therefore, the claims are directed to an abstract idea.
The additional elements in the claim amount to no more than insignificant extra solution activity and do not amount to significantly more than the judicial exception, because receiving, accessing, transferring/outputting are data gathering, inputting/outputting (MPEP 2106.05(d)(ii)). As explained above, the claim limitations are implemented on these generic elements such that the following are merely applying the abstract idea on a generic computer: determining, comparing, predicting, judging and mathematical calculation steps be done by at least one processor. Further, the use of the claimed invention in a power/energy generation and management field is simply an attempt to limit the use of the abstract idea to a particular technological environment (MPEP 2106.05(h)). The claim does not include any further additional elements that are sufficient to amount to significantly more than the judicial exception.
Even when combined with all of the claim limitations as a whole, it is still directed to the abstract idea of Mental processes and Mathematical concepts. Therefore, the claims are not patent eligible.
Dependent claim(s) when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claim(s) is/are not directed to an abstract idea, as they recite further embellishment of the judicial exception.
Viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Claims 1-19 do not include any further additional elements that are sufficient to amount to significantly more than the judicial exception.
Therefore, the claim(s) 1-19 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Interpretation
It is noted that, at this time, the claims 1 and 13 are not examined under the claim interpretation 35 USC § 112(f) and therefore the 35 USC §101 rejections are applied. See the 35 USC §101 rejections as applied above.
Claim Rejections - 35 USC § 112
35 U.S.C. 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claim(s) 3, 9 and 14-19 are rejected under 35 U.S.C. 112(a) as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor at the time the application was filed, had possession of the claimed invention.
Claim(s) 3 and 9:
Claim recites: wherein the power generation source comprises a wind turbine, and the configuration data associated with the power generation source comprises blade size data.
The corresponding independent claims 1 and 7 recites, use the accessed configuration data associated with the power generation source and the accessed environmental data associated with the first location to calculate a predicted power quantity data for the power generation source. Claims 3 and 9 describe power generation source comprises a wind turbine.
However, the specification doesn’t disclose, any specific equation for calculating predicted power quantity data for the power generation source where the power generation source is a wind turbine.
Applicant’s specification ¶30-¶36 describes, predict the power output, E=A*r*H*PR, Where: E=Energy (kWh), A=Total solar panel area (m2), r=solar panel yield or efficiency (%), given by the ratio: electrical power (in kWp) of one solar panel divided by the area of one panel, H=Annual average solar radiation on tilted panels (excluding shadings), PR=Performance ratio, coefficient for losses (e.g., in a range between 0.5 and 0.9), which may account for performance regardless of panel orientation or tilt, and which may include losses.
The specification describes an equation that is used for calculating predicted power output for a solar panel in which all the parameters are related to solar panel and none of the parameters are related to wind turbine. Specifically there are no parameters related to blade size of the wind turbine to determine a predicted power of the wind turbine power source.
Predicting power output of a power source is not a predictable art, and requires specific equations that uses parameters and variables specific to the type of power source (e.g.; wind turbine). In a case when the wind turbine is the power source, the specific equations that uses parameters and variables specific to the wind turbine are not described in the specification in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor possessed the claimed subject matter at the time of filing.
The scope of the claim is broad, covering predicting power output of a wind turbine. The claim is not enabled because one of the ordinary skilled in the art, upon reading the specification, would not know how to predict power the power output of a wind turbine based on the claimed received/accessed data (e.g.; blade size or any other wind turbine related data/parameter/variables). The claim is not enabled because one of the ordinary skilled in the art will require undue experimentation to determine the necessary, but undisclosed, equations/models.
Appropriate correction is required.
Claim(s) 14-15 and 17-19:
Claims recite, predicted power quantity data for the power generation source and the parent claim 13 describes, power generation source can be a wind turbine.
However, the specification doesn’t disclose, calculating predicted power quantity data for the power generation source where the power generation source is a wind turbine.
Therefore, these claims are rejected for similar reasons as described above for claims 3 and 9.
Appropriate correction is required.
Claim(s) 16:
Claim recites, predicted power quantity data for the power generation source, and wherein the power generation source comprises a wind turbine, and the configuration data associated with the power generation source comprises blade size data. and the parent claim 13 describes, power generation source can be a wind turbine.
For the same reasons as described above in claims 3 and 9, claim 16 is rejected.
Appropriate correction is required.
35 U.S.C. 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 3, 9 and 14-19 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
-Unclear limitations:
Claim 3, 9 and 14-19:
As described above in the 35 U.S.C. 112(a) section, the specification doesn’t disclose, calculating predicted power quantity data for the power generation source where the power generation source is a wind turbine.
Therefore, in light of the specification, it is not clear, what exact equation, calculation steps with what specific parameters and variables to use to determine predicted power output of the wind turbine. The claim is not enabled because one of the ordinary skilled in the art, upon reading the specification, would not know how to predict power output of a wind turbine based on the claimed received/accessed data where data may include wind turbine blade size (for claims 3, 9 and 16) or any other wind turbine related configuration data (for 14-15 and 17-19).
For the examination purpose, in light of the specification, it cannot be determined how the power output of the wind turbine is predicted.
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 (i.e., changing from AIA to pre-AIA ) 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.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 13 and 19 is/are rejected under 35 U.S.C. 102(a)(1)/102(a)(2) as being anticipated by Eizips et al. (US20150340983A1) [hereinafter Eizips].
Regarding claim 13:
Eizips discloses, A computer system comprising: [¶21: a system and method for the operation of distributed local management units (LMUs) in a photovoltaic energy system.];
a network interface; [¶53: Modem 407 and/or wireless network interface 408 are coupled to controller 402 to permit communications with the LMUs.];
at least one processing device operable to: [¶52: FIG. 4 shows an exemplary local controller or LMU 400 according to one embodiment…Wires 421 a,b are used to chain the LMUs together to form a string, as in the serial configuration illustrated in FIG. 1. The hardware of LMU 400 is configured for use in such a serial connection.
¶62: FIG. 6 shows an exemplary overview of a computer or data processing system 600 as may be used, in some embodiments, at various locations (e.g., for use as an MMU or an LMU) throughout system 100. It is generally exemplary of any computer that may execute code to process data…];
receive, via the network interface, encrypted authentication data purporting to be from a first device associated with a power generation source at a first location; [¶22: Each LMU is coupled to control one solar module of a plurality of solar modules in the system…
¶26: Master management unit (MMU) 130 (e.g., a master controller) is coupled to control each of the LMUs…
¶83: communication process 700 for identification and authentication between a master controller 720 and a local controller 730 according to one embodiment. As communications between local controllers (e.g., LMUs 111 a . . . 111 n) and the master controller (e.g., MMU 130) in a photovoltaic energy system… secure communications and to verify that the solar panels used are legitimate, registered panels appropriate or authorized…
¶87: In step 706, the LMU sends back the encrypted message. If this panel is not the panel it is supposed to be];
wherein the first device is physically coupled to a photovoltaic panel, a wind turbine, or an inverter; [Examiner notes that claim requires only one of the optional elements separated by “or” and only one of them is given the patentable weight.
Accordingly, Eizips discloses, the first device is physically coupled to a photovoltaic panel as described below:
¶22: Each LMU is coupled to control one solar module of a plurality of solar modules in the system…
¶52: FIG. 4 shows an exemplary local controller or LMU 400 according to one embodiment….Wires 421 a,b are used to chain the LMUs together to form a string, as in the serial configuration illustrated in FIG. 1. The hardware of LMU 400 is configured for use in such a serial connection…
¶20: A “solar module” is a device that includes at least one or more solar cells, wherein the solar cells are connected in series or in parallel. A solar panel is one example of a solar module.];
determine if the authentication data purporting to be from the first device associated with the power generation source is valid; at least partly in response to determining that the data purporting to be from the first device associated with the power generation source is valid, generating a corresponding validation indicator. [¶87: In step 706, the LMU sends back the encrypted message…
¶88: If the message contains data that validates the panel, in step 707 the MMU registers this panel as valid,];
Regarding claim 19:
Eizips discloses, The computer system as defined in claim 13, and
Eizips further discloses, wherein the computer system is configured to initiate a power generation remediation process at least partly in response to a determination that a second received power quantity data is less than a second predicted power quantity data by at least a threshold amount. [¶4: Measurements relating to output current and voltage at the least one photovoltaic panel are received. Expected power of the at least one photovoltaic panel is determined…Actual power of the at least one photovoltaic panel is determined based on the measurements relating to output current and voltage. In response to determining that the actual power is not within a predetermined range of the expected power (e.g. at least one photovoltaic panel is dirty), a cleaning of the photovoltaic panel is initiated…
¶64: At step 514, supervisory controller 104 compares P_actual to P_expected to determine if P_actual belongs to the set of P_expected. For example, it may be determined whether P_actual falls within a certain range or threshold of P_expected (e.g. P_actual is 10% less than P_expected)].
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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 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 filling 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:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-2, 4-8 and 10-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over GEVORKIAN et al. (US20120166085A1) [hereinafter GEVORKIAN] and in view of Eizips and further in view of Suresh et al. (US20140100698A1) [hereinafter Suresh].
Regarding claim 1:
Gevorkian discloses, An energy generation authentication and verification computer system, the computer system comprising: [¶22: system and process for generating and using data and information for predicting the level of power production.];
a network interface; [¶31: Block Diagram E describes the process by which the master station receives data from PV modules and weather stations
Also see, Gevorkian figures 7-9, transceivers];
at least one processing device operable to: [¶49: N4 represents the computer-implemented process or algorithm for obtaining weather data (weather conditions)…
Examiner notes that, Gevorkian discloses, data processing device such as computer for processing data];
receive, via the network interface, power quantity data purportedly generated by the power generation source at the first location; [¶53: FIG. 4 b illustrates a flowchart of predicting solar power production according to an embodiment of the invention. A solar power prediction computer receives 430 power output data from the solar power system]
access configuration data associated with the power generation source; [¶33: processing raw data acquired from the field…
¶34: Block Diagram G refers to four sets of data:..
¶36: Spec Data (E10), which refers to manufacturer's photovoltaic module performance specification ATA sheet system performance obtained from the manufacturer of PV modules and other system component…
¶52: The solar power prediction computer 410 is also coupled to an almanac computer 420. The almanac computer provides a predicted number of solar hours for a specified time frame (e.g., a week, a month, a year) and normally provides the daily predicted power output.];
access environmental data associated with the first location; [¶30: Block Diagram D describes a field weather monitoring station and systems for acquiring general information on climate conditions and transmitting it to the master station for processing…
¶52: The solar power production computer 410 is also coupled to a weather prediction computer 415. The weather prediction computer provides data as to the predicted weather for a specified time frame (e.g., a week, two weeks, a month). The data may include cloud cover information, precipitation (rain/snow) or wind information. This information may impact the power output from a solar power generation system.];
use the accessed configuration data associated with the power generation source and [¶52: The solar power prediction computer 410 is also coupled to an almanac computer 420. The almanac computer provides a predicted number of solar hours for a specified time frame (e.g., a week, a month, a year) and normally provides the daily predicted power output.];
the accessed environmental data associated with the first location [¶52: The solar power production computer 410 is also coupled to a weather prediction computer 415. The weather prediction computer provides data as to the predicted weather for a specified time frame (e.g., a week, two weeks, a month). The data may include cloud cover information, precipitation (rain/snow) or wind information. This information may impact the power output from a solar power generation system.];
to calculate a predicted power quantity data for the power generation source at the first location; [¶53: The solar power prediction computer receives 440 solar hour information from an almanac system. The solar power prediction system generates 445 an almanac predicted power output for the solar power system for the specified time period. The solar power prediction system receives 450 weather information for the specified time period from a weather predicting source. The solar power prediction system calculates 455 a weather prediction-to-solar almanac ratio based on a comparison of the solar hour information to the weather information. The solar power prediction computer generates 460 discrepancy data based on the comparison in step 455. The solar power prediction computer generates 465 a predicted power output for the specified time period by multiplying the almanac predicted power output for the solar power system by the weather prediction to solar almanac ratio. The solar power prediction computer stores the predicted power output for the specified time period.
Examiner notes that Gevorkian discloses, using accessed environmental data such as 450 weather information and accessed configuration dara such as 445 an almanac predicted power output for the solar power system, to calculate predicted power quantity data such as to calculate/determine 455 a weather prediction-to-solar almanac ratio], but doesn’t explicitly disclose, and
Eizips discloses, receive, via the network interface, encrypted authentication data purporting to be from a first device associated with a power generation source at a first location; [¶22: Each LMU is coupled to control one solar module of a plurality of solar modules in the system…
¶26: Master management unit (MMU) 130 (e.g., a master controller) is coupled to control each of the LMUs…
¶83: communication process 700 for identification and authentication between a master controller 720 and a local controller 730 according to one embodiment. As communications between local controllers (e.g., LMUs 111 a . . . 111 n) and the master controller (e.g., MMU 130) in a photovoltaic energy system… secure communications and to verify that the solar panels used are legitimate, registered panels appropriate or authorized…
¶87: In step 706, the LMU sends back the encrypted message. If this panel is not the panel it is supposed to be];
determine if the encrypted authentication data purporting to be from the first device associated with the power generation source is valid; at least partly in response to determining…that the encrypted authentication data purporting to be from the first device associated with the power generation source is valid, generate a corresponding validation indicator… [¶87: In step 706, the LMU sends back the encrypted message…
¶88: If the message contains data that validates the panel, in step 707 the MMU registers this panel as valid,];
and transfer an electronic token to a first destination [¶88: If the message contains data that validates the panel, in step 707 the MMU registers this panel as valid, and in step 708 it sends a periodic activation message back to the LMU, keeping the LMU functional (starting or continuing in normal active operation)].
Therefore, it would have been obvious to one of ordinary skill in the art before the filling date of the claimed invention to have combined the capability of receiving, via the network interface, encrypted authentication data purporting to be from a first device associated with a power generation source at a first location; and determining if the encrypted authentication data purporting to be from the first device associated with the power generation source is valid; and generate a corresponding validation indicator at least partly in response to determining that the encrypted authentication data purporting to be from the first device associated with the power generation source is valid and transfer an electronic token to a first destination in order to provide additional benefit of efficient operation of the energy generation source in addition to the providing proper safety and protection of the energy sources by implementing these verification process taught by Eizips with the system taught by GEVORKIAN as discussed above in order to have reasonable expectation of success such as to provide additional benefit of efficient operation of the energy generation source in addition to the providing proper safety and energy source protection by using these verification process [Eizips, ¶31: In addition to the efficiency consideration, the LMUs may also be configured to provide various features, such as safety, panel protection, etc., in various implementations], but doesn’t explicitly disclose, and
Suresh discloses, compare the predicted power quantity data with the received power quantity data to determine if they correspond; [¶74: At step 530, supervisory controller 104 compares P_actual to P_expected to determine if P_actual belongs to the set of P_expected.];
at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data,…generate a corresponding validation indicator and transfer an electronic token to a first destination. [¶74: At step 530, supervisory controller 104 compares P_actual to P_expected to determine if P_actual belongs to the set of P_expected. For example, it may be determined whether P_actual falls within a certain range or threshold of P_expected (e.g. P_actual is 10% less than P_expected). In response to determining that P_actual belongs to the set of P_expected (i.e. a “yes” results from decision box 530), data log 204 is updated to reflect that the decrease in power is due to weather related variations and a message indicating the reason for the decrease in power is displayed on the HMI].
Therefore, it would have been obvious to one of ordinary skill in the art before the filling date of the claimed invention to have combined the capability of comparing the predicted power quantity data with the received power quantity data to determine if they correspond; generating a corresponding validation indicator and transfer an electronic token to a first destination at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data in order to increase the efficiency of the power generation farm and reduce the maintenance hours and resource usage with the additional benefits of low cost implementation, increased efficiency, less resource waste, flexibility in terms of having an automated feedback based maintenance system, and increased safety taught by Suresh with the system taught by GEVORKIAN and Eizips as discussed above in order to have reasonable expectation of success such as to provide additional benefit of efficient operation of the energy generation source in addition to the providing proper safety and energy source protection by using these verification process [Suresh, ¶87: The PV cleaning system provides a low-cost, highly efficient automated cleaning procedure of PV panels. This in turn can increase the efficiency of the PV farm and reduce the maintenance hours and water usage…low cost implementation, increased efficiency, less water waste, flexibility in terms of having an automated or scheduled cleaning, practical approach,…and increased safety.].
Regarding claim 2:
Gevorkian, Eizips and Suresh disclose, The energy generation verification computer system as defined in claim 1, and
Gevorkian further discloses, wherein the power generation source comprises a photovoltaic panel [¶7: Block Diagram C describes the process by which the data collection mechanism at each PV module sends or transmits information to the master station;];
and the configuration data associated with the power generation source comprises solar panel size data and solar panel efficiency data. [¶33: Block Diagram G describes the method for processing raw data acquired from the field
¶34: Block Diagram G refers to four sets of data:…
¶36: (ii) Spec Data (E10), which refers to manufacturer's photovoltaic module performance specification ATA sheet system performance obtained from the manufacturer of PV modules and other system components;
Examiner notes that, Gevorkian discloses photovoltaic system that includes photovoltaic panels, and the received specification data includes manufacturer's photovoltaic module performance specification ATA sheet, and one of the ordinary skilled in the art will understand that this Photovoltaic panel manufacturer’s specification sheet contains panel dimension (i.e.; size) and Efficiency data (e.g.; 15% for example and can vary by system, size, irradiance, cell temperature and rating conditions such as Standard or Nominal Operating Cell Temperature)].
Regarding claim 4:
Gevorkian, Eizips and Suresh disclose, The energy generation verification computer system as defined in claim 1, and
Gevorkian further discloses, wherein the environmental data comprises cloud cover, sun position, and time of year. [¶52: The almanac computer provides a predicted number of solar hours for a specified time frame (e.g., a week, a month, a year) and normally provides the daily predicted power output… weather prediction computer provides data as to the predicted weather for a specified time frame (e.g., a week, two weeks, a month). The data may include cloud cover information…
¶48: The almanac provides information on the average number of solar hours (or solar irradiance) per month which is then used to produce an insolation profile or curve (i.e. graph showing the average number of solar hours and the solar pattern based on the almanac). Insolation profile refers to a graph showing the average number of solar hours for a specified interval or time period.
Examiner notes that Gevorkian discloses, environmental data such as cloud cover, sun position such as solar hours/irradiance where solar irradiance is dependent on sun position, and time of the year such as at particular month of year the average solar irradiance since solar irradiance is dependent on average sun position at that month of year].
Regarding claim 5:
Gevorkian, Eizips and Suresh disclose, The energy generation verification computer system as defined in claim 1, and
Gevorkian further discloses, wherein the environmental data comprises wind speed. [¶30: The data collected includes such data as ambient temperature, barometric pressure, solar irradiance and wind speed etc.].
Regarding claim 6:
Gevorkian, Eizips and Suresh disclose, The energy generation verification computer system as defined in claim 1, and
Eizips further discloses, wherein the computer system is configured to initiate a power generation remediation process at least partly in response to a determination that a second received power quantity data is less than a second predicted power quantity data by at least a threshold amount. [¶4: Measurements relating to output current and voltage at the least one photovoltaic panel are received. Expected power of the at least one photovoltaic panel is determined…Actual power of the at least one photovoltaic panel is determined based on the measurements relating to output current and voltage. In response to determining that the actual power is not within a predetermined range of the expected power (e.g. at least one photovoltaic panel is dirty), a cleaning of the photovoltaic panel is initiated…
¶64: At step 514, supervisory controller 104 compares P_actual to P_expected to determine if P_actual belongs to the set of P_expected. For example, it may be determined whether P_actual falls within a certain range or threshold of P_expected (e.g. P_actual is 10% less than P_expected)].
Regarding claim 7:
Gevorkian discloses, A computer implemented method, the method comprising: [¶22: system and process for generating and using data and information for predicting the level of power production.];
receiving power quantity data purportedly generated by the power generation source at the first location; [¶53: FIG. 4 b illustrates a flowchart of predicting solar power production according to an embodiment of the invention. A solar power prediction computer receives 430 power output data from the solar power system]
accessing configuration data associated with the power generation source; [¶33: processing raw data acquired from the field…
¶34: Block Diagram G refers to four sets of data:..
¶36: Spec Data (E10), which refers to manufacturer's photovoltaic module performance specification ATA sheet system performance obtained from the manufacturer of PV modules and other system component…
¶52: The solar power prediction computer 410 is also coupled to an almanac computer 420. The almanac computer provides a predicted number of solar hours for a specified time frame (e.g., a week, a month, a year) and normally provides the daily predicted power output.];
accessing environmental data associated with the first location; [¶30: Block Diagram D describes a field weather monitoring station and systems for acquiring general information on climate conditions and transmitting it to the master station for processing…
¶52: The solar power production computer 410 is also coupled to a weather prediction computer 415. The weather prediction computer provides data as to the predicted weather for a specified time frame (e.g., a week, two weeks, a month). The data may include cloud cover information, precipitation (rain/snow) or wind information. This information may impact the power output from a solar power generation system.];
using the accessed configuration data associated with the power generation source and [¶52: The solar power prediction computer 410 is also coupled to an almanac computer 420. The almanac computer provides a predicted number of solar hours for a specified time frame (e.g., a week, a month, a year) and normally provides the daily predicted power output.];
the accessed environmental data associated with the first location [¶52: The solar power production computer 410 is also coupled to a weather prediction computer 415. The weather prediction computer provides data as to the predicted weather for a specified time frame (e.g., a week, two weeks, a month). The data may include cloud cover information, precipitation (rain/snow) or wind information. This information may impact the power output from a solar power generation system.];
to calculate, using the computer system, a predicted power quantity data for the power generation source at the first location; [¶53: The solar power prediction computer receives 440 solar hour information from an almanac system. The solar power prediction system generates 445 an almanac predicted power output for the solar power system for the specified time period. The solar power prediction system receives 450 weather information for the specified time period from a weather predicting source. The solar power prediction system calculates 455 a weather prediction-to-solar almanac ratio based on a comparison of the solar hour information to the weather information. The solar power prediction computer generates 460 discrepancy data based on the comparison in step 455. The solar power prediction computer generates 465 a predicted power output for the specified time period by multiplying the almanac predicted power output for the solar power system by the weather prediction to solar almanac ratio. The solar power prediction computer stores the predicted power output for the specified time period.
Examiner notes that Gevorkian discloses, using accessed environmental data such as 450 weather information and accessed configuration dara such as 445 an almanac predicted power output for the solar power system, to calculate predicted power quantity data such as to calculate/determine 455 a weather prediction-to-solar almanac ratio], but doesn’t explicitly disclose, and
Eizips discloses, receiving, at a computer system, authentication data purporting to be from a first device associated with a power generation source at a first location; [¶22: Each LMU is coupled to control one solar module of a plurality of solar modules in the system…
¶26: Master management unit (MMU) 130 (e.g., a master controller) is coupled to control each of the LMUs…
¶83: communication process 700 for identification and authentication between a master controller 720 and a local controller 730 according to one embodiment. As communications between local controllers (e.g., LMUs 111 a . . . 111 n) and the master controller (e.g., MMU 130) in a photovoltaic energy system… secure communications and to verify that the solar panels used are legitimate, registered panels appropriate or authorized…
¶87: In step 706, the LMU sends back the encrypted message. If this panel is not the panel it is supposed to be];
determining, using the computer system, if the authentication data purporting to be from the first device associated with the power generation source is valid; at least partly in response to determining…that the authentication data purporting to be from the first device associated with the power generation source is valid, generating a corresponding validation indicator [¶87: In step 706, the LMU sends back the encrypted message…
¶88: If the message contains data that validates the panel, in step 707 the MMU registers this panel as valid,];
transferring an electronic token to a first destination. [¶88: If the message contains data that validates the panel, in step 707 the MMU registers this panel as valid, and in step 708 it sends a periodic activation message back to the LMU, keeping the LMU functional (starting or continuing in normal active operation)].
Therefore, it would have been obvious to one of ordinary skill in the art before the filling date of the claimed invention to have combined the capability of receiving, at a computer system, authentication data purporting to be from a first device associated with a power generation source at a first location; determining, using the computer system, if the authentication data purporting to be from the first device associated with the power generation source is valid; generating a corresponding validation indicator at least partly in response to determining…that the authentication data purporting to be from the first device associated with the power generation source is valid and transferring an electronic token to a first destination in order to provide additional benefit of efficient operation of the energy generation source in addition to the providing proper safety and protection of the energy sources by implementing these verification process taught by Eizips with the system taught by GEVORKIAN as discussed above in order to have reasonable expectation of success such as to provide additional benefit of efficient operation of the energy generation source in addition to the providing proper safety and energy source protection by using these verification process [Eizips, ¶31: In addition to the efficiency consideration, the LMUs may also be configured to provide various features, such as safety, panel protection, etc., in various implementations], but doesn’t explicitly disclose, and
Suresh discloses, comparing the predicted power quantity data with the received power quantity data to determine if they correspond; [¶74: At step 530, supervisory controller 104 compares P_actual to P_expected to determine if P_actual belongs to the set of P_expected.];
at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data,…generating a corresponding validation indicator and…transferring an electronic token to a first destination [¶74: At step 530, supervisory controller 104 compares P_actual to P_expected to determine if P_actual belongs to the set of P_expected. For example, it may be determined whether P_actual falls within a certain range or threshold of P_expected (e.g. P_actual is 10% less than P_expected). In response to determining that P_actual belongs to the set of P_expected (i.e. a “yes” results from decision box 530), data log 204 is updated to reflect that the decrease in power is due to weather related variations and a message indicating the reason for the decrease in power is displayed on the HMI].
Therefore, it would have been obvious to one of ordinary skill in the art before the filling date of the claimed invention to have combined the capability comparing the predicted power quantity data with the received power quantity data to determine if they correspond; generating a corresponding validation indicator at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data and transferring an electronic token to a first destination in order to increase the efficiency of the power generation farm and reduce the maintenance hours and resource usage with the additional benefits of low cost implementation, increased efficiency, less resource waste, flexibility in terms of having an automated feedback based maintenance system, and increased safety taught by Suresh with the system taught by GEVORKIAN and Eizips as discussed above in order to have reasonable expectation of success such as to provide additional benefit of efficient operation of the energy generation source in addition to the providing proper safety and energy source protection by using these verification process [Suresh, ¶87: The PV cleaning system provides a low-cost, highly efficient automated cleaning procedure of PV panels. This in turn can increase the efficiency of the PV farm and reduce the maintenance hours and water usage…low cost implementation, increased efficiency, less water waste, flexibility in terms of having an automated or scheduled cleaning, practical approach,…and increased safety.].
Regarding claim 8:
Gevorkian, Eizips and Suresh disclose, The computer implemented method as defined in claim 7, and
Gevorkian further discloses, wherein the power generation source comprises a photovoltaic panel [¶7: Block Diagram C describes the process by which the data collection mechanism at each PV module sends or transmits information to the master station;];
and the configuration data associated with the power generation source comprises solar panel size data and solar panel efficiency data. [¶33: Block Diagram G describes the method for processing raw data acquired from the field
¶34: Block Diagram G refers to four sets of data:…
¶36: (ii) Spec Data (E10), which refers to manufacturer's photovoltaic module performance specification ATA sheet system performance obtained from the manufacturer of PV modules and other system components;
Examiner notes that, Gevorkian discloses photovoltaic system that includes photovoltaic panels, and the received specification data includes manufacturer's photovoltaic module performance specification ATA sheet, and one of the ordinary skilled in the art will understand that this Photovoltaic panel manufacturer’s specification sheet contains panel dimension (i.e.; size) and Efficiency data (e.g.; 15% for example and can vary by system, size, irradiance, cell temperature and rating conditions such as Standard or Nominal Operating Cell Temperature)].
Regarding claim 10:
Gevorkian, Eizips and Suresh disclose, The computer implemented method as defined in claim 7, and
Gevorkian further discloses, wherein the environmental data comprises cloud cover, sun position, and time of year. [¶52: The almanac computer provides a predicted number of solar hours for a specified time frame (e.g., a week, a month, a year) and normally provides the daily predicted power output… weather prediction computer provides data as to the predicted weather for a specified time frame (e.g., a week, two weeks, a month). The data may include cloud cover information…
¶48: The almanac provides information on the average number of solar hours (or solar irradiance) per month which is then used to produce an insolation profile or curve (i.e. graph showing the average number of solar hours and the solar pattern based on the almanac). Insolation profile refers to a graph showing the average number of solar hours for a specified interval or time period.
Examiner notes that Gevorkian discloses, environmental data such as cloud cover, sun position such as solar hours/irradiance where solar irradiance is dependent on sun position, and time of the year such as at particular month of year the average solar irradiance since solar irradiance is dependent on average sun position at that month of year].
Regarding claim 11:
Gevorkian, Eizips and Suresh disclose, The computer implemented method as defined in claim 7, and
Gevorkian further discloses, wherein the environmental data comprises wind speed. [¶30: The data collected includes such data as ambient temperature, barometric pressure, solar irradiance and wind speed etc.].
Regarding claim 12:
Gevorkian, Eizips and Suresh disclose, The computer implemented method as defined in claim 7, and
Eizips further discloses, the method further comprising initiating a power generation remediation process at least partly in response to a determination that a second received power quantity data is less than a second predicted power quantity data by at least a threshold amount. [¶4: Measurements relating to output current and voltage at the least one photovoltaic panel are received. Expected power of the at least one photovoltaic panel is determined…Actual power of the at least one photovoltaic panel is determined based on the measurements relating to output current and voltage. In response to determining that the actual power is not within a predetermined range of the expected power (e.g. at least one photovoltaic panel is dirty), a cleaning of the photovoltaic panel is initiated…
¶64: At step 514, supervisory controller 104 compares P_actual to P_expected to determine if P_actual belongs to the set of P_expected. For example, it may be determined whether P_actual falls within a certain range or threshold of P_expected (e.g. P_actual is 10% less than P_expected)].
Claim(s) 3 and 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gevorkian, Eizips and Suresh and further in view of Wang et al. (US20080140263A1) [hereinafter Wang].
Regarding claim 3:
Gevorkian, Eizips and Suresh disclose, The energy generation verification computer system as defined in claim 1, but they do not explicitly disclose, and
Wang discloses, wherein the power generation source comprises a wind turbine, and the configuration data associated with the power generation source comprises blade size data. [¶25: mechanical power P captured from the wind is given by
PNG
media_image1.png
35
102
media_image1.png
Greyscale
wherein ρ is air density, v is wind speed and R is rotor radius.
Examiner notes the 35 USC 112(a) and 112(b) rejections of the claim as described in the current office action. The claim is given the broadest reasonable interpretations, and plain meaning of the claim is construed as predicted power can be any calculated predicted power of the wind turbine].
Therefore, it would have been obvious to one of ordinary skill in the art before the filling date of the claimed invention to have combined the power generation source comprises a wind turbine, and the configuration data associated with the power generation source comprises blade size data in order to obtain improved power output prediction taught by Wang with the system taught by Gevorkian, Eizips and Suresh as discussed above in order to have reasonable expectation of success such as to obtain improved power output prediction [Wang, ¶7: the quality of annual power output predictions as well as turbine control can be considerably improved].
Regarding claim 9:
Gevorkian, Eizips and Suresh disclose, The computer implemented method as defined in claim 7, but they do not explicitly disclose, and
Wang discloses, wherein the power generation source comprises a wind turbine, and the configuration data associated with the power generation source comprises blade size data. [¶25: mechanical power P captured from the wind is given by
PNG
media_image1.png
35
102
media_image1.png
Greyscale
wherein ρ is air density, v is wind speed and R is rotor radius.
Examiner notes the 35 USC 112(a) and 112(b) rejections of the claim as described in the current office action. The claim is given the broadest reasonable interpretations, and plain meaning of the claim is construed as predicted power can be any calculated predicted power of the wind turbine].
Therefore, it would have been obvious to one of ordinary skill in the art before the filling date of the claimed invention to have combined the above described teachings of Wang with the method taught by Gevorkian, Eizips and Suresh for the same reasons as discussed above in claim 3.
Claim(s) 14-15 and 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Eizips in view of Gevorkian and further in view of Suresh.
Regarding claim 14:
Eizips discloses, The computer system as defined in claim 13, but doesn’t explicitly discloses, and
Gevorkian discloses, wherein the computer system is configured to:
receive, via the network interface, power quantity data purportedly generated by the power generation source at the first location; [¶53: FIG. 4 b illustrates a flowchart of predicting solar power production according to an embodiment of the invention. A solar power prediction computer receives 430 power output data from the solar power system…
¶31: Block Diagram E describes the process by which the master station receives data from PV modules and weather stations
Also see, Gevorkian figures 7-9, network interfaces such as transceivers]
access configuration data associated with the power generation source; [¶33: processing raw data acquired from the field…
¶34: Block Diagram G refers to four sets of data:..
¶36: Spec Data (E10), which refers to manufacturer's photovoltaic module performance specification ATA sheet system performance obtained from the manufacturer of PV modules and other system component…
¶52: The solar power prediction computer 410 is also coupled to an almanac computer 420. The almanac computer provides a predicted number of solar hours for a specified time frame (e.g., a week, a month, a year) and normally provides the daily predicted power output.];
access environmental data associated with the first location; [¶30: Block Diagram D describes a field weather monitoring station and systems for acquiring general information on climate conditions and transmitting it to the master station for processing…
¶52: The solar power production computer 410 is also coupled to a weather prediction computer 415. The weather prediction computer provides data as to the predicted weather for a specified time frame (e.g., a week, two weeks, a month). The data may include cloud cover information, precipitation (rain/snow) or wind information. This information may impact the power output from a solar power generation system.];
use the accessed configuration data associated with the power generation source and [¶52: The solar power prediction computer 410 is also coupled to an almanac computer 420. The almanac computer provides a predicted number of solar hours for a specified time frame (e.g., a week, a month, a year) and normally provides the daily predicted power output.];
the accessed environmental data associated with the first location [¶52: The solar power production computer 410 is also coupled to a weather prediction computer 415. The weather prediction computer provides data as to the predicted weather for a specified time frame (e.g., a week, two weeks, a month). The data may include cloud cover information, precipitation (rain/snow) or wind information. This information may impact the power output from a solar power generation system.];
to calculate a predicted power quantity data for the power generation source at the first location; [¶53: The solar power prediction computer receives 440 solar hour information from an almanac system. The solar power prediction system generates 445 an almanac predicted power output for the solar power system for the specified time period. The solar power prediction system receives 450 weather information for the specified time period from a weather predicting source. The solar power prediction system calculates 455 a weather prediction-to-solar almanac ratio based on a comparison of the solar hour information to the weather information. The solar power prediction computer generates 460 discrepancy data based on the comparison in step 455. The solar power prediction computer generates 465 a predicted power output for the specified time period by multiplying the almanac predicted power output for the solar power system by the weather prediction to solar almanac ratio. The solar power prediction computer stores the predicted power output for the specified time period.
Examiner notes that Gevorkian discloses, using accessed environmental data such as 450 weather information and accessed configuration dara such as 445 an almanac predicted power output for the solar power system, to calculate predicted power quantity data such as to calculate/determine 455 a weather prediction-to-solar almanac ratio].
Therefore, it would have been obvious to one of ordinary skill in the art before the filling date of the claimed invention to have combined the capability of receiving, via the network interface, power quantity data purportedly generated by the power generation source at the first location; accessing configuration data associated with the power generation source; accessing environmental data associated with the first location; using the accessed configuration data associated with the power generation source and the accessed environmental data associated with the first location to calculate a predicted power quantity data for the power generation source at the first location in order to achieve more accurate predicted power quantity data by implementing synchronized collection of information and data throughout the system taught by GEVORKIAN with the system taught by Eizips as discussed above in order to have reasonable expectation of success such as to achieve more accurate predicted power quantity data by implementing synchronized collection of information and data throughout the system [GEVORKIAN, ¶28: process can be repeated as frequently as needed to ensure synchronized collection of information and data throughout the system.], but doesn’t explicitly disclose, and
Suresh discloses, compare the predicted power quantity data with the received power quantity data to determine if they correspond; [¶74: At step 530, supervisory controller 104 compares P_actual to P_expected to determine if P_actual belongs to the set of P_expected.];
wherein the validation indicator is generated at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data. [¶74: At step 530, supervisory controller 104 compares P_actual to P_expected to determine if P_actual belongs to the set of P_expected. For example, it may be determined whether P_actual falls within a certain range or threshold of P_expected (e.g. P_actual is 10% less than P_expected). In response to determining that P_actual belongs to the set of P_expected (i.e. a “yes” results from decision box 530), data log 204 is updated to reflect that the decrease in power is due to weather related variations and a message indicating the reason for the decrease in power is displayed on the HMI].
Therefore, it would have been obvious to one of ordinary skill in the art before the filling date of the claimed invention to have combined the capability of comparing the predicted power quantity data with the received power quantity data to determine if they correspond; wherein the validation indicator is generated at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data in order to increase the efficiency of the power generation farm and reduce the maintenance hours and resource usage with the additional benefits of low cost implementation, increased efficiency, less resource waste, flexibility in terms of having an automated feedback based maintenance system, and increased safety taught by Suresh with the system taught by GEVORKIAN and Eizips as discussed above in order to have reasonable expectation of success such as to provide additional benefit of efficient operation of the energy generation source in addition to the providing proper safety and energy source protection by using these verification process [Suresh, ¶87: The PV cleaning system provides a low-cost, highly efficient automated cleaning procedure of PV panels. This in turn can increase the efficiency of the PV farm and reduce the maintenance hours and water usage…low cost implementation, increased efficiency, less water waste, flexibility in terms of having an automated or scheduled cleaning, practical approach,…and increased safety.].
Regarding claim 15:
Eizips, Gevorkian and Suresh disclose, The computer system as defined in claim 13, and
Gevorkian discloses, as described above in claim 14, wherein the computer system is configured to:
receive, via the network interface, power quantity data purportedly generated by the power generation source at the first location;
access configuration data associated with the power generation source;
access environmental data associated with the first location;
use the accessed configuration data associated with the power generation source and the accessed environmental data associated with the first location to calculate a predicted power quantity data for the power generation source at the first location;
Gevorkian further discloses, wherein the power generation source comprises a photovoltaic panel [¶7: Block Diagram C describes the process by which the data collection mechanism at each PV module sends or transmits information to the master station;];
and the configuration data associated with the power generation source comprises solar panel size data and solar panel efficiency data. [¶33: Block Diagram G describes the method for processing raw data acquired from the field
¶34: Block Diagram G refers to four sets of data:…
¶36: (ii) Spec Data (E10), which refers to manufacturer's photovoltaic module performance specification ATA sheet system performance obtained from the manufacturer of PV modules and other system components;
Examiner notes that, Gevorkian discloses photovoltaic system that includes photovoltaic panels, and the received specification data includes manufacturer's photovoltaic module performance specification ATA sheet, and one of the ordinary skilled in the art will understand that this Photovoltaic panel manufacturer’s specification sheet contains panel dimension (i.e.; size) and Efficiency data (e.g.; 15% for example and can vary by system, size, irradiance, cell temperature and rating conditions such as Standard or Nominal Operating Cell Temperature)].
Therefore, the above described teachings of GEVORKIAN is combinable with the system taught by Eizips, Gevorkian and Suresh for the same reasons as described above in claim 14, and
Suresh discloses, as described above in claim 14,
compare the predicted power quantity data with the received power quantity data to determine if they correspond;
wherein the validation indicator is generated at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data, and
Therefore, the above described teachings of Suresh is combinable with the system taught by Eizips, Gevorkian and Suresh for the same reasons as described above in claim 14.
Regarding claim 17:
Eizips, Gevorkian and Suresh disclose, The computer system as defined in claim 13, and
Gevorkian discloses, as described above in claim 14, wherein the computer system is configured to:
receive, via the network interface, power quantity data purportedly generated by the power generation source at the first location;
access configuration data associated with the power generation source;
access environmental data associated with the first location;
use the accessed configuration data associated with the power generation source and the accessed environmental data associated with the first location to calculate a predicted power quantity data for the power generation source at the first location;
Gevorkian further discloses, wherein the environmental data comprises cloud cover, sun position, and time of year. [¶52: The almanac computer provides a predicted number of solar hours for a specified time frame (e.g., a week, a month, a year) and normally provides the daily predicted power output… weather prediction computer provides data as to the predicted weather for a specified time frame (e.g., a week, two weeks, a month). The data may include cloud cover information…
¶48: The almanac provides information on the average number of solar hours (or solar irradiance) per month which is then used to produce an insolation profile or curve (i.e. graph showing the average number of solar hours and the solar pattern based on the almanac). Insolation profile refers to a graph showing the average number of solar hours for a specified interval or time period.
Examiner notes that Gevorkian discloses, environmental data such as cloud cover, sun position such as solar hours/irradiance where solar irradiance is dependent on sun position, and time of the year such as at particular month of year the average solar irradiance since solar irradiance is dependent on average sun position at that month of year].
Therefore, the above described teachings of GEVORKIAN is combinable with the system taught by Eizips, Gevorkian and Suresh for the same reasons as described above in claim 14, and
Suresh discloses, as described above in claim 14,
compare the predicted power quantity data with the received power quantity data to determine if they correspond;
wherein the validation indicator is generated at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data, and
Therefore, the above described teachings of Suresh is combinable with the system taught by Eizips, Gevorkian and Suresh for the same reasons as described above in claim 14.
Regarding claim 18:
Eizips, Gevorkian and Suresh disclose, The computer system as defined in claim 13, and
Gevorkian discloses, as described above in claim 14, wherein the computer system is configured to:
receive, via the network interface, power quantity data purportedly generated by the power generation source at the first location;
access configuration data associated with the power generation source;
access environmental data associated with the first location;
use the accessed configuration data associated with the power generation source and the accessed environmental data associated with the first location to calculate a predicted power quantity data for the power generation source at the first location;
Gevorkian further discloses, wherein the environmental data comprises wind speed. [¶30: The data collected includes such data as ambient temperature, barometric pressure, solar irradiance and wind speed etc.].
Therefore, the above described teachings of GEVORKIAN is combinable with the system taught by Eizips, Gevorkian and Suresh for the same reasons as described above in claim 14, and
Suresh discloses, as described above in claim 14,
compare the predicted power quantity data with the received power quantity data to determine if they correspond;
wherein the validation indicator is generated at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data, and
Therefore, the above described teachings of Suresh is combinable with the system taught by Eizips, Gevorkian and Suresh for the same reasons as described above in claim 14.
Claim(s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Eizips, Gevorkian and Suresh and further in view of Wang.
Regarding claim 16:
Eizips, Gevorkian and Suresh disclose, The computer system as defined in claim 13, and
Gevorkian discloses, as described above in claim 14, wherein the computer system is configured to:
receive, via the network interface, power quantity data purportedly generated by the power generation source at the first location;
access configuration data associated with the power generation source;
access environmental data associated with the first location;
use the accessed configuration data associated with the power generation source and the accessed environmental data associated with the first location to calculate a predicted power quantity data for the power generation source at the first location;
Therefore, the above described teachings of GEVORKIAN is combinable with the system taught by Eizips, Gevorkian and Suresh for the same reasons as described above in claim 14, and
Suresh discloses, as described above in claim 14,
compare the predicted power quantity data with the received power quantity data to determine if they correspond;
wherein the validation indicator is generated at least partly in response to determining that the predicted power quantity data corresponds with the received power quantity data, and
Therefore, the above described teachings of Suresh is combinable with the system taught by Eizips, Gevorkian and Suresh for the same reasons as described above in claim 14, but Eizips, Gevorkian and Suresh do not explicitly disclose, and
Wang discloses, wherein the power generation source comprises a wind turbine, and the configuration data associated with the power generation source comprises blade size data. [¶25: mechanical power P captured from the wind is given by
PNG
media_image1.png
35
102
media_image1.png
Greyscale
wherein ρ is air density, v is wind speed and R is rotor radius.
Examiner notes the 35 USC 112(a) and 112(b) rejections of the claim as described in the current office action. The claim is given the broadest reasonable interpretations, and plain meaning of the claim is construed as predicted power can be any calculated predicted power of the wind turbine].
Therefore, it would have been obvious to one of ordinary skill in the art before the filling date of the claimed invention to have combined the power generation source comprises a wind turbine, and the configuration data associated with the power generation source comprises blade size data in order to obtain improved power output prediction taught by Wang with the system taught by Eizips, Gevorkian and Suresh as discussed above in order to have reasonable expectation of success such as to obtain improved power output prediction [Wang, ¶7: the quality of annual power output predictions as well as turbine control can be considerably improved].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure is listed in the PTO-892 Notice of Reference Cited document.
Orsini (US20190050949A1): Exergy token:
¶19: utilizes a blockchain-based token system to reduce barriers and facilitate the optimal coupling of local electric generation with parties that can evaluate, generate, store, trade, and utilize this generation most efficiently.
Xie et al. (US20240257148A1): Blockchain-based green power certification method, apparatus, and system:
¶74: Control the certification chain to call a green power certification model and the proof-of-existence data to obtain constraints of the green power certification model, determine, based on the constraints and the proof-of-existence data, whether an attribute of electric energy generated by a power station is a green power attribute, and if the attribute of the electric energy generated by the power station is the green power attribute, generate a green power attribute certificate by using the certification chain.
Miller et al. (US20210142426A1): Sustainable Energy Tracking System Utilizing Blockchain Technology and Merkle Tree Hashing Structure:
¶61: Predetermined transmission and consumption validation rules 530 are executed on the energy block representing validated digital renewable energy consumed by a facility. If the consumption and transmission data is validated 535 (e.g., that the renewable energy block is confirmed as transmitted to and consumed by a given facility), the digital renewable energy credit token is associated (or “enriched”) 540 with the associated transmission and consumption data.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMMED SHAFAYET whose telephone number is (571)272-8239. The examiner can normally be reached M-F 8:30 AM-5:00 PM.
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/M.S./
Patent Examiner,
Art Unit 2116
/KENNETH M LO/Supervisory Patent Examiner, Art Unit 2116
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