DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Specifically, representative Claim 1 recites:
“A computer implemented method for evaluating localized atmospheric conditions for selected cloud seeding to enhance localized electrical power generation from wind turbines, comprising: receiving, at a computer, wind farm data related to a plurality of wind turbines for generating electrical power at a location, the wind farm data collected from sensors at the location; receiving, at the computer, data of atmospheric conditions at least in part at the location, the data including atmospheric wind speed; assessing, using the computer, an atmospheric condition in the atmosphere at the location using the wind farm data and the data of the atmospheric conditions; predicting, using the computer, an impact of the atmospheric condition on the atmospheric wind speed resulting in a wind turbine power output reduction; determining, using the computer, when to initiate cloud seeding to generate rain at the location and reduce the atmospheric condition, in response to the prediction of the impact on the atmospheric wind speed meeting a threshold for the wind turbine power output reduction; and generating a communication to a control system, the communication including a recommendation to initiate the cloud seeding based on the prediction of the impact on the atmospheric wind speed meeting the threshold for the wind turbine power output reduction.”
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements”.
Under the Step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: Process, machine, manufacture, or composition of matter. The above claim is considered to be in a statutory category (process).
Under the Step 2A, Prong One, we consider whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitations that fall into/recite an abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject matter Eligibility Guidance, it falls into the groupings of subject matter when recited as such in a claim limitation that falls into the grouping of subject matter when recited as such in a claim limitation, that covers mental processes — concepts performed in the human mind including an observation, evaluation, judgement, and/or opinion.
For example, the steps of “assessing, an atmospheric condition in the atmosphere at the location using the wind farm data and the data of the atmospheric conditions; predicting, an impact of the atmospheric condition on the atmospheric wind speed resulting in a wind turbine power output reduction; determining, when to initiate cloud seeding to generate rain at the location and reduce the atmospheric condition, in response to the prediction of the impact on the atmospheric wind speed meeting a threshold for the wind turbine power output reduction; and the communication including a recommendation to initiate the cloud seeding based on the prediction of the impact on the atmospheric wind speed meeting the threshold for the wind turbine power output reduction” are treated as belonging to mental process grouping because a human has the ability to assess, make predictions, determine, and make recommendations from the data.
With regards to the steps of “assessing, an atmospheric condition in the atmosphere at the location using the wind farm data and the data of the atmospheric conditions; predicting, an impact of the atmospheric condition on the atmospheric wind speed resulting in a wind turbine power output reduction; determining, when to initiate cloud seeding to generate rain at the location and reduce the atmospheric condition, in response to the prediction of the impact on the atmospheric wind speed meeting a threshold for the wind turbine power output reduction; and the communication including a recommendation to initiate the cloud seeding based on the prediction of the impact on the atmospheric wind speed meeting the threshold for the wind turbine power output reduction”, these mental steps represents a processes that, under its broadest reasonable interpretation, cover performance of the limitations in the mind. That is, nothing in the claim element precludes the step from practically being performed in the mind. In the context of this claim, it encompasses the user making mental decisions (evaluation/judgement) with regards to determining the wind turbine power output reduction.
Next, under the Step 2A, Prong Two, we consider whether the claim that recites a judicial exception is integrated into a practical application.
In this step, we evaluate whether the claim recites additional elements that
integrate the exception into a practical application of that exception.
The above claims comprise the following additional elements:
Claim 1: A computer implemented method for evaluating localized atmospheric conditions for selected cloud seeding to enhance localized electrical power generation from wind turbines, comprising: receiving, at a computer, wind farm data related to a plurality of wind turbines for generating electrical power at a location, the wind farm data collected from sensors at the location; receiving, at the computer, data of atmospheric conditions at least in part at the location, the data including atmospheric wind speed, using the computer, and generating a communication to a control system
Claim 17: A system for evaluating localized atmospheric conditions for selected cloud seeding to enhance localized electrical power generation from wind turbines, which comprises: a computer system comprising; a computer processor, a computer-readable storage medium, and program instructions stored on the computer-readable storage medium being executable by the processor, to cause the computer system to perform the following functions to; receive, at a computer, wind farm data related to a plurality of wind turbines for generating electrical power at a location, the wind farm data collected from sensors at the location; receive, at the computer, data of atmospheric conditions at least in part at the location, the data including atmospheric wind speed; using the computer, and generate a communication to a control system
Claim 20: A computer program product for evaluating localized atmospheric conditions for selected cloud seeding to enhance localized electrical power generation from wind turbines, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform functions, by the computer, comprising the functions to; receive, at a computer, wind farm data related to a plurality of wind turbines for generating electrical power at a location, the wind farm data collected from sensors at the location; receive, at the computer, data of atmospheric conditions at least in part at the location, the data including atmospheric wind speed; and generate a communication to a control system
The above additional elements in Claim 1 such as a computer implemented method for evaluating localized atmospheric conditions for selected cloud seeding to enhance localized electrical power generation from wind turbines, comprising: receiving, at a computer, wind farm data related to a plurality of wind turbines for generating electrical power at a location, the wind farm data collected from sensors at the location; receiving, at the computer, data of atmospheric conditions at least in part at the location, the data including atmospheric wind speed are examples of data gathering and are generically recited and are not meaningful. The additional element of generating a communication to a control system is an example of a post solution activity and is generically recited and are not meaningful.
The additional elements in Claims 17 and 20 such a computer, a processor, and a non-transitory computer-readable medium comprising instructions that are executable by a processor for causing the processor is an example of generic computer equipment (components) that is generally recited and, therefore, is not qualified as a particular machine.
Therefore, the claims are directed to a judicial exception and require further analysis under the Step 2B.
However, the above claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception (Step 2B analysis) because these additional elements/steps are well-understood and conventional in the relevant art based on the prior art of record including references in the submitted IDS (10/24/2023) by the Applicant (Caldwell and Defelice).
The independent claims, therefore, are not patent eligible.
With regards to the dependent claims, claims 2-16 and 18-19 provide additional features/steps which are either part of an expanded abstract idea of the independent claims (additionally comprising mathematical (Claims 2-16 and 18-19) or adding additional elements/steps that are not meaningful as they are recited in generality and/or not qualified as particular machine/ and/or eligible transformation and, therefore, do not reflect a practical application as well as not qualified for “significantly more” based on prior art of record.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable Caldwell et al. (US20090046289), hereinafter referred to as ‘Caldwell’ and in further view of Defelice et al.(US20210176925), hereinafter referred to as ‘Defelice’.
Regarding Claim 1, Caldwell discloses a computer implemented method for evaluating localized atmospheric conditions to enhance localized electrical power generation from wind turbines, comprising (A computer processes signals from the one or more transceivers to distinguish molecular scattered laser radiation from aerosol scattered laser radiation and determines air temperatures, wind speeds, and wind directions based on the scattered laser radiation. Applications of the method to wind power site evaluation, wind turbine control, weather monitoring, aircraft air data sensing, and airport safety are presented [0009]): receiving, at a computer, wind data related to a plurality of wind turbines for generating electrical power at a location (A computer processes signals from the one or more transceivers to distinguish molecular scattered laser radiation from aerosol scattered laser radiation and determines air temperatures, wind speeds, and wind directions based on the scattered laser radiation. Applications of the method to wind power site evaluation, wind turbine control, weather monitoring, aircraft air data sensing, and airport safety are presented [0009]; Since wind may vary with season, as well as with terrain, it is desirable to record wind conditions at brief intervals over an extended time--extending over at least several months to a year--to determine suitable locations and optimum wind-turbine specifications for construction of wind power systems or wind-farms [0117]), the wind farm data collected from sensors at the location (Applications of the method to wind power site evaluation, wind turbine control, weather monitoring, aircraft air data sensing, and airport safety are presented [0009]); receiving, at the computer, data of atmospheric conditions at least in part at the location, the data including atmospheric wind speed (It is desirable to obtain wind speed and direction data at multiple altitudes at each proposed site, including at the surface, at hub altitude, and at blade minimum and maximum altitudes; obtaining this data is part of a site survey for a wind power system [0117]); assessing, using the computer, an atmospheric condition in the atmosphere at the location using the wind farm data and the data of the atmospheric conditions (Computer 950 receives information from all three (or more) receiver electronics 940, 942, 944 and calculates windspeed and wind direction at various ranges from the apparatus 900 from the received Rayleigh and Mie-scattering data [0138]); predicting, using the computer, an impact of the atmospheric condition on the atmospheric wind speed resulting in a wind turbine power output reduction (Since unstable air can lead to and powers convective activity, ranging from simple dust-devils to tornadoes all of which may produce gusty conditions; furling thresholds may be reduced by a wind turbine controller when unstable air conditions exist [0140]); determining, using the computer, when to initiate cloud seeding to generate rain at the location and reduce the atmospheric condition, in response to the prediction of the impact on the atmospheric wind speed meeting a threshold for the wind turbine power output reduction (The accumulated data may be used to determine optimum wind-turbine specifications for, and predict expected power output of the wind-power system from, a wind power system or wind farm [0117]); and generating a communication to a control system, the communication including a recommendation to initiate the cloud seeding based on the prediction of the impact on the atmospheric wind speed meeting the threshold for the wind turbine power output reduction (Computer 113 communicatively couples with transceiver 110 and processes signals from transceiver 110 to distinguish a molecular-scattered component 107A from an aerosol-scattered component 107B. Computer 113 determines the air parameters based on laser radiation 107 backscattered from molecules and/or aerosols in air 104 [0026]).
However, does not explicitly disclose a computer implemented method for evaluating localized atmospheric conditions for selected cloud seeding to enhance localized electrical power generation from wind turbines, comprising; determining, using the computer, when to initiate cloud seeding to generate rain at the location and reduce the atmospheric condition, in response to the prediction of the impact on the atmospheric wind speed meeting a threshold for the wind turbine power output reduction and generating a communication to a control system, the communication including a recommendation to initiate the cloud seeding based on the prediction of the impact on the atmospheric wind speed meeting the threshold for the wind turbine power output reduction.
Nevertheless, Defelice discloses a computer implemented method for evaluating localized atmospheric conditions for selected cloud seeding to enhance localized electrical power generation from wind turbines, comprising (One or more embodiments provide a paradigm-shifting methodology and framework for using ‘Intelligent’ Systems during the performance (i.e., identify, conduct, monitor) and evaluation of weather modification, cloud seeding and inadvertent weather modification programs/activities [0034]); determining, using the computer, when to initiate cloud seeding to generate rain at the location and reduce the atmospheric condition (Consider the following exemplary scenario wherein the weather modification program requirement was to apply hygroscopic seeding material. It involves programmed thresholds based on analysis of existing measured drop size distribution and their relationship to the production of rain, and similarly based on analysis of measured below cloud base aerosol size distribution data [0089]; Each ‘Intelligent’ System seamlessly ingests, in near real-time, the sensor payload data (i.e., temperature, relative humidity, wind, updraft velocity, aerosol size distribution and droplet size distribution, and other as required), auxiliary/ancillary data (e.g., cloud locations, topography, seeding locations based on convection or other defined criteria, information from other ‘Intelligent’ Systems, satellites, radar, radiometer, data archives), NWP model data, seeding action data and autopilot or remote control data. The seeding action, where and when to seed, are determined by the seeding system software that extracts ancillary/auxiliary (or ‘other data’), NWP model data and/or platform sensor data inputs [0036]) and generating a communication to a control system, the communication including a recommendation to initiate the cloud seeding (One or more embodiments employ a simulator implementing software in the loop (SIL) technology 281-2, /281-1 to simulate the UAS flight characteristics, UAS payload sensor data 275, 255, 263, 243, data 293 and mission planner output 287-1, 287-2. These outputs are used to optimize the seed/no seed thresholds and targeting algorithm, saving the high cost of trial and error approaches and ensuring success, and should provide a smaller number of false positive seeding condition detections (compared to current practices) [0057]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Caldwell with the teachings of Defelice to optimize the seed/no seed thresholds and targeting algorithm, saving the high cost of trial and error approaches and ensure success, and provide a smaller number of false positive seeding condition detections (Defelice [0057]).
Regarding Claim 2, Caldwell and Defelice disclose the claimed invention discussed in claim 1.
However, Caldwell does not explicitly discloses initiating the cloud seeding using the control system in response to the communication including the recommendation to initiate the cloud seeding.
Nevertheless, Defelice discloses initiating the cloud seeding using the control system in response to the communication including the recommendation to initiate the cloud seeding (One or more embodiments automatically measure such information more accurately and from a more relevant location and use same to automatically initiate the seeding [0023]; Adaptive control refers to the improved performance and increased robustness of an autonomous system by configuring its control system to adjust the autonomous systems' seeding action as a function of measurements [0044]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Caldwell with the teachings of Defelice to optimize seeding at a rate that will yield maximum conversion of cloud water to precipitation and improve accuracy of the control system.
Regarding Claim 3, Caldwell and Defelice disclose the claimed invention discussed in claim 1.
However, Caldwell does not explicitly disclose estimating an amount of cloud seeding to generate rain at the location to reduce the atmospheric condition sending the amount of cloud seeding and the impact prediction to a control system for initiating a cloud seeding technique.
Nevertheless, Defelice discloses estimating an amount of cloud seeding to generate rain at the location to reduce the atmospheric condition; and sending the amount of cloud seeding and the impact prediction to a control system for initiating a cloud seeding technique (The airborne ‘Intelligent’ System is guided, in one or more embodiments, by using the ‘real-time’ in situ-based measurements and flight guidance from the GCS Mission planner 287-1, 287-2 and SIL database 281-1, 281-2 to navigate the ‘Intelligent’ System autonomously to areas of suitable temperature, relative humidity, updraft velocity, aerosol size distribution and droplet size distribution to implement optimal seeding. Optimal seeding means that seeding starts and proceeds at a rate that will yield maximum conversion of cloud water to precipitation that falls in the intended location on the ground, or target area. Software-in-the-loop (SIL) technology, for example, is used in one or more embodiments to integrate the data from past missions of a similar kind and to evaluate them to formulate a mission plan [0059]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Caldwell with the teachings of Defelice to generate rain at the location to reduce the atmospheric condition sending the amount of cloud seeding and the impact prediction to a control system for initiating a cloud seeding technique.
Regarding Claim 4, Caldwell and Defelice disclose the claimed invention discussed in claim 3.
However, Caldwell does not explicitly disclose initiating the cloud seeding technique in response to the sending of the amount of cloud seeding and the impact prediction.
Nevertheless, Defelice discloses initiating the cloud seeding technique in response to the sending of the amount of cloud seeding and the impact prediction (as discussed above).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Caldwell with the teachings of Defelice to generate rain at the location to reduce the atmospheric condition sending the amount of cloud seeding and the impact prediction to a control system for initiating a cloud seeding technique.
Regarding Claim 5, Caldwell and Defelice disclose the claimed invention discussed in claim 1.
However, Caldwell does not explicitly disclose predicting of the impact includes estimating spatio-temporal distribution of aerosol concentration and aerosol propagation in the atmosphere at the location.
Nevertheless, Defelice discloses predicting of the impact includes estimating spatio-temporal distribution of aerosol concentration and aerosol propagation in the atmosphere at the location (One or more embodiments employ improved technologies, detail the configuration of their interfaces, and allow those technologies and relevant software systems to evolve independently of their use. Refer to the table of FIG. 5. The latter contributes to more streamlined cloud seeding operations that have smaller operational footprints and costs (compared to contemporary cloud seeding programs), while enhancing or even optimizing their effectiveness. Furthermore, while at no additional cost, data at temporal and spatial sensitivities to overcome predictability or sparseness issues of environmental parameters that identify conditions suitable for seeding and how such might be implemented are readily available beyond their operational use [0041]; …The seeding action, where and when to seed, are determined by the seeding system software that extracts ancillary/auxiliary (or ‘other data’), NWP model data and/or platform sensor data inputs. What seeding material to dispense, if not pre-determined, is determined by platform sensor data, NWP model data, and, as needed, auxiliary/ancillary data [0036]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Caldwell with the teachings of Defelice to optimize seeding effectiveness and improve cost.
Regarding Claim 6, Caldwell and Defelice disclose the claimed invention discussed in claim 3.
However, Caldwell does not explicitly disclose estimating of the amount of cloud seeding is based on a volumetric analysis of the atmospheric conditions at the location, and a plan is generated, as part of the communication, to deploy cloud seeding to clear aerosol as the atmospheric condition to increase wind power generation.
Nevertheless, Defelice discloses estimating of the amount of cloud seeding is based on a volumetric analysis of the atmospheric conditions at the location, and a plan is generated, as part of the communication, to deploy cloud seeding to clear aerosol as the atmospheric condition to increase wind power generation (One could estimate the rate of seeding required to modify the measured DSD for a seeding effect and a tail effect. This would benefit operations since it provides guidance for optimal seeding based on actual in situ data and not arbitrary or derived multivariable values [0083]; Many different items can be determined via machine learning in one or more embodiments; e.g., what clouds to seed; what seeding material to use; where and when to seed the clouds to be seeded; the path to take to arrive at the location given the in situ meteorological and aviation data; the mass and/or volume of seeding material to be dispersed per kilometer or other linear unit of flight; and the like [0172]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Caldwell with the teachings of Defelice to provide guidance for optimal seeding and estimate the rate of seeding.
Regarding Claim 7, Caldwell and Defelice disclose the claimed invention discussed in claim 1.
Caldwell discloses a cost of wind turbine power output reduction (It is known that thunderstorms, microburst, and dust-devil conditions, as well as other weather conditions, can cause gusty conditions that may result in a wind load on a blade 704 of a wind turbine changing dramatically in a matter of seconds; these conditions can therefore change from good power-generation conditions to conditions requiring altered blade pitch or even rapid furling to avoid excessive wind load and damage to the turbine or tower [0126]).
However, Caldwell does not explicitly disclose generating a cost-benefit analysis between a cost of the cloud seeding and a cost of wind turbine power output reduction.
Nevertheless, Defelice discloses generating a cost-benefit analysis between a cost of the cloud seeding (The latter contributes to more streamlined cloud seeding operations that have smaller operational footprints and costs (compared to contemporary cloud seeding programs), while enhancing or even optimizing their effectiveness. Furthermore, while at no additional cost, data at temporal and spatial sensitivities to overcome predictability or sparseness issues of environmental parameters that identify conditions suitable for seeding and how such might be implemented are readily available beyond their operational use [0041]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Caldwell with the teachings of Defelice to overcome predictability or sparseness issues of environmental parameters that identify conditions suitable for seeding.
Regarding Claim 8, Caldwell and Defelice disclose the claimed invention discussed in claim 1.
Caldwell discloses the impact prediction includes estimating rainfall resulting from the cloud seeding and estimating a reduction amount of aerosol concentration in the atmosphere at the location (These data can be mined, analyzed and features extracted to locate representative time-series of key sensors from research aircraft flying at or below cloud base (e.g., sensors that measure updraft velocity, aerosol size distribution and droplet size distribution). One example for determining thresholds is the analysis of measured aerosol size distributions, hydrometeor size distributions and their relationship to the production of rain [0064]), and estimating an increase in atmospheric wind speed (In an embodiment, windspeed, wind direction, and air temperature are sensed and recorded at several altitudes ranging from zero to two thousand feet, or higher, at periodic time intervals [0132]), and estimating an increase in wind turbine power output resulting from the increase in atmospheric wind speed (Many wind turbines sense changed wind conditions by monitoring power output and/or rotational rate of blades 704, these wind turbines can only respond alter changes have occurred [0127]).
However, Caldwell, does not explicitly disclose the impact prediction includes estimating rainfall resulting from the cloud seeding and estimating a reduction amount of aerosol concentration in the atmosphere at the location.
Nevertheless, Defelice discloses the impact prediction includes estimating rainfall resulting from the cloud seeding (One or more embodiments base cloud seeding decisions on more relevant cloud and environmental data, as compared to prior art techniques, thereby more accurately placing seeding material, obtaining better cloud seeding results, and the like. Refer also to FIG. 7 and accompanying text [0010]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Caldwell with the teachings of Defelice to obtain better cloud seeding results and improve accuracy of placing seeding material (Defelice [0010]).
Regarding Claim 9, Caldwell and Defelice disclose the claimed invention discussed in claim 1.
Caldwell discloses the wind turbine power output reduction includes a reduction in wind turbine power output (as discussed above).
Regarding Claim 10, Caldwell and Defelice disclose the claimed invention discussed in claim 1.
Caldwell discloses the wind turbine power reduction includes a reduction in wind turbine power output resulting from a reduction in blade rotation speed caused by the atmospheric condition (Many wind turbines sense changed wind conditions by monitoring power output and/or rotational rate of blades 704, these wind turbines can only respond alter changes have occurred [0127]).
Regarding Claim 11, Caldwell and Defelice disclose the claimed invention discussed in claim 1.
Caldwell discloses the atmospheric condition includes a spatial hotspot of aerosol concentration causing the impact on the atmospheric wind speed, and the impact is a slowing of the atmospheric wind speed resulting in a slowing of wind turbine blade rotation speeds causing the wind turbine power output reduction (A computer processes signals from the one or more transceivers to distinguish molecular scattered laser radiation from aerosol scattered laser radiation and determines air temperatures, wind speeds, and wind directions based on the scattered laser radiation. Applications of the method to wind power site evaluation, wind turbine control, weather monitoring, aircraft air data sensing, and airport safety are presented [0009]; Many wind turbines sense changed wind conditions by monitoring power output and/or rotational rate of blades 704, these wind turbines can only respond alter changes have occurred [0127]).
Regarding Claim 12, Caldwell and Defelice disclose the claimed invention discussed in claim 1.
Caldwell discloses the atmospheric wind speeds resulting in an increase in wind turbine power output (as discussed above).
However, Caldwell does not explicitly disclose the control system initiates the cloud seeding technique to reduce the atmospheric condition for increasing the atmospheric wind speeds resulting in an increase in wind turbine power output.
Nevertheless, Defelice discloses the control system initiates the cloud seeding technique (as discussed above).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Caldwell with the teachings of Defelice to obtain better cloud seeding results and improve accuracy of placing seeding material (Defelice [0010]).
Regarding Claim 13, Caldwell and Defelice disclose the claimed invention discussed in claim 1.
Caldwell discloses to reduce the distribution of aerosol concentrations in the atmosphere at the location (as discussed above).
However, Caldwell does not explicitly disclose a cloud seeding technique for the cloud seeding which includes using drones to seed clouds to produce rain to reduce the distribution of aerosol concentrations in the atmosphere at the location.
Nevertheless, Defelice discloses a cloud seeding technique for the cloud seeding which includes using drones to seed clouds (As noted, in some instances, real-time video imagery processing is carried out on video feed (or cloud imaging feed using non-visible light) from the unmanned aerial vehicle. This aids, for example, machine learning and/or controlling the drone to dispense seed material. [0149]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Caldwell with the teachings of Defelice to obtain better cloud seeding results and improve accuracy of placing seeding material (Defelice [0010]).
Regarding Claim 14, Caldwell and Defelice disclose the claimed invention discussed in claim 1.
Caldwell discloses generating, using the computer, a digital model using the received data of the atmospheric condition at least in part at the location; and using the model for the predicting of the impact of the atmospheric condition on the atmospheric wind speed (Computer 113 communicatively couples with transceiver 110 and processes signals from transceiver 110 to distinguish a molecular-scattered component 107A from an aerosol-scattered component 107B. Computer 113 determines the air parameters based on laser radiation 107 backscattered from molecules and/or aerosols in air 104. Accordingly, as described below, computer 113 may employ one or more digital signal processing algorithms to determine such parameters [0026]).
Regarding Claim 15, Caldwell and Defelice disclose the claimed invention discussed in claim 14.
Caldwell discloses generating a digital model, using the computer; receiving updated wind data (as discussed above); receiving updated data of the atmospheric condition (Computer 950 receives information from all three (or more) receiver electronics 940, 942, 944 and calculates windspeed and wind direction at various ranges from the apparatus 900 from the received Rayleigh and Mie-scattering data; updating detected windspeed and wind direction measurements every tenth of a second, or faster, as required [0138]); the assessing of the atmospheric condition including using the digital model (as discussed above); the predicting of the impact of the atmospheric condition using the model (Computer 113 determines the air parameters based on laser radiation 107 backscattered from molecules and/or aerosols in air 104. Accordingly, as described below, computer 113 may employ one or more digital signal processing algorithms to determine such parameters [0026]).
However, Caldwell does not explicitly disclose the determining of whether to initiate cloud seeding to generate rain including using the model.
Nevertheless, Defelice discloses the determining of whether to initiate cloud seeding to generate rain including using the model (as discussed above).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Caldwell with the teachings of Defelice to obtain better cloud seeding results and improve accuracy of placing seeding material (Defelice [0010]).
Regarding Claim 16, Caldwell and Defelice disclose the claimed invention discussed in claim 1.
Caldwell discloses iteratively generating the digital model to produce updated models (Computer 113 determines the air parameters based on laser radiation 107 backscattered from molecules and/or aerosols in air 104. Accordingly, as described below, computer 113 may employ one or more digital signal processing algorithms to determine such parameters [0026]; Computer 950 receives information from all three (or more) receiver electronics 940, 942, 944 and calculates windspeed and wind direction at various ranges from the apparatus 900 from the received Rayleigh and Mie-scattering data; updating detected windspeed and wind direction measurements every tenth of a second, or faster, as required [0138]).
Regarding Claim 17, Caldwell discloses a system for evaluating localized atmospheric conditions to enhance localized electrical power generation from wind turbines, which comprises: a computer system comprising (A computer processes signals from the one or more transceivers to distinguish molecular scattered laser radiation from aerosol scattered laser radiation and determines air temperatures, wind speeds, and wind directions based on the scattered laser radiation. Applications of the method to wind power site evaluation, wind turbine control, weather monitoring, aircraft air data sensing, and airport safety are presented [0009]): a computer-readable storage medium, and program instructions stored on the computer-readable storage medium being executable by the processor, to cause the computer system to perform the following functions to; receive, at a computer, wind farm data related to a plurality of wind turbines for generating electrical power at a location, the wind farm data collected from sensors at the location; (A computer processes signals from the one or more transceivers to distinguish molecular scattered laser radiation from aerosol scattered laser radiation and determines air temperatures, wind speeds, and wind directions based on the scattered laser radiation. Applications of the method to wind power site evaluation, wind turbine control, weather monitoring, aircraft air data sensing, and airport safety are presented [0009]; Since wind may vary with season, as well as with terrain, it is desirable to record wind conditions at brief intervals over an extended time--extending over at least several months to a year--to determine suitable locations and optimum wind-turbine specifications for construction of wind power systems or wind-farms [0117]), the wind farm data collected from sensors at the location (Applications of the method to wind power site evaluation, wind turbine control, weather monitoring, aircraft air data sensing, and airport safety are presented [0009]); receive, at the computer, data of atmospheric conditions at least in part at the location, the data including atmospheric wind speed (It is desirable to obtain wind speed and direction data at multiple altitudes at each proposed site, including at the surface, at hub altitude, and at blade minimum and maximum altitudes; obtaining this data is part of a site survey for a wind power system [0117]); assess, using the computer, an atmospheric condition in the atmosphere at the location using the wind farm data and the data of the atmospheric conditions (Computer 950 receives information from all three (or more) receiver electronics 940, 942, 944 and calculates windspeed and wind direction at various ranges from the apparatus 900 from the received Rayleigh and Mie-scattering data [0138]); predict, using the computer, an impact of the atmospheric condition on the atmospheric wind speed resulting in a wind turbine power output reduction; (Since unstable air can lead to and powers convective activity, ranging from simple dust-devils to tornadoes all of which may produce gusty conditions; furling thresholds may be reduced by a wind turbine controller when unstable air conditions exist [0140]); determine, using the computer, whether to initiate cloud seeding to generate rain at the location and reduce the atmospheric condition, in response to the prediction of the impact on the atmospheric wind speed meeting a threshold for the wind turbine power output reduction (The accumulated data may be used to determine optimum wind-turbine specifications for, and predict expected power output of the wind-power system from, a wind power system or wind farm [0117]; This unit therefore can provide a profile of windspeed, direction, and temperature with altitude, these measurements can be compared to limits to provide warning of wind-shear at airports or recorded with a digital recorder to perform site survey for wind power systems [0139]); and generate a communication to a control system, the communication including a recommendation to initiate the cloud seeding based on the prediction of the impact on the atmospheric wind speed meeting the threshold for the wind turbine power output reduction (Computer 113 communicatively couples with transceiver 110 and processes signals from transceiver 110 to distinguish a molecular-scattered component 107A from an aerosol-scattered component 107B. Computer 113 determines the air parameters based on laser radiation 107 backscattered from molecules and/or aerosols in air 104 [0026]).
However, does not explicitly disclose a system for evaluating localized atmospheric conditions for selected cloud seeding to enhance localized electrical power generation from wind turbines, which comprises: a computer system comprising; determine, using the computer, whether to initiate cloud seeding to generate rain at the location and reduce the atmospheric condition, in response to the prediction of the impact on the atmospheric wind speed meeting a threshold for the wind turbine power output reduction; and generate a communication to a control system, the communication including a recommendation to initiate the cloud seeding based on the prediction of the impact on the atmospheric wind speed meeting the threshold for the wind turbine power output reduction.
Nevertheless, Defelice discloses a system for evaluating localized atmospheric conditions for selected cloud seeding, which comprises: a computer system comprising (One or more embodiments provide a paradigm-shifting methodology and framework for using ‘Intelligent’ Systems during the performance (i.e., identify, conduct, monitor) and evaluation of weather modification, cloud seeding and inadvertent weather modification programs/activities [0034]); determine, using the computer, whether to initiate cloud seeding to generate rain at the location (Consider the following exemplary scenario wherein the weather modification program requirement was to apply hygroscopic seeding material. It involves programmed thresholds based on analysis of existing measured drop size distribution and their relationship to the production of rain, and similarly based on analysis of measured below cloud base aerosol size distribution data [0089]; Each ‘Intelligent’ System seamlessly ingests, in near real-time, the sensor payload data (i.e., temperature, relative humidity, wind, updraft velocity, aerosol size distribution and droplet size distribution, and other as required), auxiliary/ancillary data (e.g., cloud locations, topography, seeding locations based on convection or other defined criteria, information from other ‘Intelligent’ Systems, satellites, radar, radiometer, data archives), NWP model data, seeding action data and autopilot or remote control data. The seeding action, where and when to seed, are determined by the seeding system software that extracts ancillary/auxiliary (or ‘other data’), NWP model data and/or platform sensor data inputs [0036]) and generate a communication to a control system, the communication including a recommendation to initiate the cloud seeding (One or more embodiments employ a simulator implementing software in the loop (SIL) technology 281-2, /281-1 to simulate the UAS flight characteristics, UAS payload sensor data 275, 255, 263, 243, data 293 and mission planner output 287-1, 287-2. These outputs are used to optimize the seed/no seed thresholds and targeting algorithm, saving the high cost of trial and error approaches and ensuring success, and should provide a smaller number of false positive seeding condition detections (compared to current practices) [0057]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Caldwell with the teachings of Defelice to optimize the seed/no seed thresholds and targeting algorithm, saving the high cost of trial and error approaches and ensure success, and provide a smaller number of false positive seeding condition detections (Defelice [0057]).
Regarding Claim 18, Caldwell and Defelice disclose the claimed invention discussed in claim 17.
However, Caldwell does not explicitly discloses initiating the cloud seeding using the control system in response to the communication including the recommendation to initiate the cloud seeding.
Nevertheless, Defelice discloses initiating the cloud seeding using the control system in response to the communication including the recommendation to initiate the cloud seeding (One or more embodiments automatically measure such information more accurately and from a more relevant location and use same to automatically initiate the seeding [0023]; Adaptive control refers to the improved performance and increased robustness of an autonomous system by configuring its control system to adjust the autonomous systems' seeding action as a function of measurements [0044]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Caldwell with the teachings of Defelice to optimize seeding at a rate that will yield maximum conversion of cloud water to precipitation and improve accuracy of the control system.
Regarding Claim 19, Caldwell and Defelice disclose the claimed invention discussed in claim 17.
However, Caldwell does not explicitly disclose estimating an amount of cloud seeding to generate rain at the location to reduce the atmospheric condition sending the amount of cloud seeding and the impact prediction to a control system for initiating a cloud seeding technique.
Nevertheless, Defelice discloses estimating an amount of cloud seeding to generate rain at the location to reduce the atmospheric condition; and sending the amount of cloud seeding and the impact prediction to a control system for initiating a cloud seeding technique (The airborne ‘Intelligent’ System is guided, in one or more embodiments, by using the ‘real-time’ in situ-based measurements and flight guidance from the GCS Mission planner 287-1, 287-2 and SIL database 281-1, 281-2 to navigate the ‘Intelligent’ System autonomously to areas of suitable temperature, relative humidity, updraft velocity, aerosol size distribution and droplet size distribution to implement optimal seeding. Optimal seeding means that seeding starts and proceeds at a rate that will yield maximum conversion of cloud water to precipitation that falls in the intended location on the ground, or target area. Software-in-the-loop (SIL) technology, for example, is used in one or more embodiments to integrate the data from past missions of a similar kind and to evaluate them to formulate a mission plan [0059]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Caldwell with the teachings of Defelice to generate rain at the location to reduce the atmospheric condition sending the amount of cloud seeding and the impact prediction to a control system for initiating a cloud seeding technique.
20. A computer program product for evaluating localized atmospheric conditions for selected cloud seeding to enhance localized electrical power generation from wind turbines, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform functions, by the computer, comprising the functions to; receive, at a computer, wind farm data related to a plurality of wind turbines for generating electrical power at a location, the wind farm data collected from sensors at the location; receive, at the computer, data of atmospheric conditions at least in part at the location, the data including atmospheric wind speed; assess, using the computer, an atmospheric condition in the atmosphere at the location using the wind farm data and the data of the atmospheric conditions; predict, using the computer, an impact of the atmospheric condition on the atmospheric wind speed resulting in a wind turbine power output reduction; determine, using the computer, whether to initiate cloud seeding to generate rain at the location and reduce the atmospheric condition, in response to the prediction of the impact on the atmospheric wind speed meeting a threshold for the wind turbine power output reduction; and generate a communication to a control system, the communication including a recommendation to initiate the cloud seeding based on the prediction of the impact on the atmospheric wind speed meeting the threshold for the wind turbine power output reduction.
Regarding Claim 20, Caldwell discloses a computer program product for evaluating localized atmospheric conditions to enhance localized electrical power generation from wind turbines (A computer processes signals from the one or more transceivers to distinguish molecular scattered laser radiation from aerosol scattered laser radiation and determines air temperatures, wind speeds, and wind directions based on the scattered laser radiation. Applications of the method to wind power site evaluation, wind turbine control, weather monitoring, aircraft air data sensing, and airport safety are presented [0009]): the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform functions, by the computer, comprising the functions to; receive, at a computer, wind farm data related to a plurality of wind turbines for generating electrical power at a location, the wind farm data collected from sensors at the location (A computer processes signals from the one or more transceivers to distinguish molecular scattered laser radiation from aerosol scattered laser radiation and determines air temperatures, wind speeds, and wind directions based on the scattered laser radiation. Applications of the method to wind power site evaluation, wind turbine control, weather monitoring, aircraft air data sensing, and airport safety are presented [0009]; Since wind may vary with season, as well as with terrain, it is desirable to record wind conditions at brief intervals over an extended time--extending over at least several months to a year--to determine suitable locations and optimum wind-turbine specifications for construction of wind power systems or wind-farms [0117]; Applications of the method to wind power site evaluation, wind turbine control, weather monitoring, aircraft air data sensing, and airport safety are presented [0009]); receive, at the computer, data of atmospheric conditions at least in part at the location, the data including atmospheric wind speed (It is desirable to obtain wind speed and direction data at multiple altitudes at each proposed site, including at the surface, at hub altitude, and at blade minimum and maximum altitudes; obtaining this data is part of a site survey for a wind power system [0117]); assess, using the computer, an atmospheric condition in the atmosphere at the location using the wind farm data and the data of the atmospheric conditions (Computer 950 receives information from all three (or more) receiver electronics 940, 942, 944 and calculates windspeed and wind direction at various ranges from the apparatus 900 from the received Rayleigh and Mie-scattering data [0138]); predict, using the computer, an impact of the atmospheric condition on the atmospheric wind speed resulting in a wind turbine power output reduction (Since unstable air can lead to and powers convective activity, ranging from simple dust-devils to tornadoes all of which may produce gusty conditions; furling thresholds may be reduced by a wind turbine controller when unstable air conditions exist [0140]); determine, using the computer, prediction of the impact on the atmospheric wind speed meeting a threshold for the wind turbine power output reduction (The accumulated data may be used to determine optimum wind-turbine specifications for, and predict expected power output of the wind-power system from, a wind power system or wind farm [0117]; This unit therefore can provide a profile of windspeed, direction, and temperature with altitude, these measurements can be compared to limits to provide warning of wind-shear at airports or recorded with a digital recorder to perform site survey for wind power systems [0139]); and generate a communication to a control system, the communication including the prediction of the impact on the atmospheric wind speed meeting the threshold for the wind turbine power output reduction (Computer 113 communicatively couples with transceiver 110 and processes signals from transceiver 110 to distinguish a molecular-scattered component 107A from an aerosol-scattered component 107B. Computer 113 determines the air parameters based on laser radiation 107 backscattered from molecules and/or aerosols in air 104 [0026]).
However, does not explicitly disclose a computer program product for evaluating localized atmospheric conditions for selected cloud seeding to enhance localized electrical power generation from wind turbines, the computer program product comprising; determine, using the computer, whether to initiate cloud seeding to generate rain at the location and reduce the atmospheric condition, in response to the prediction of the impact on the atmospheric wind speed meeting a threshold for the wind turbine power output reduction; and generate a communication to a control system, the communication including a recommendation to initiate the cloud seeding based on the prediction of the impact on the atmospheric wind speed meeting the threshold for the wind turbine power output reduction.
Nevertheless, Defelice discloses a system for evaluating localized atmospheric conditions for selected cloud seeding, which comprises: a computer system comprising (One or more embodiments provide a paradigm-shifting methodology and framework for using ‘Intelligent’ Systems during the performance (i.e., identify, conduct, monitor) and evaluation of weather modification, cloud seeding and inadvertent weather modification programs/activities [0034]); determine, using the computer, whether to initiate cloud seeding to generate rain at the location (Consider the following exemplary scenario wherein the weather modification program requirement was to apply hygroscopic seeding material. It involves programmed thresholds based on analysis of existing measured drop size distribution and their relationship to the production of rain, and similarly based on analysis of measured below cloud base aerosol size distribution data [0089]; Each ‘Intelligent’ System seamlessly ingests, in near real-time, the sensor payload data (i.e., temperature, relative humidity, wind, updraft velocity, aerosol size distribution and droplet size distribution, and other as required), auxiliary/ancillary data (e.g., cloud locations, topography, seeding locations based on convection or other defined criteria, information from other ‘Intelligent’ Systems, satellites, radar, radiometer, data archives), NWP model data, seeding action data and autopilot or remote control data. The seeding action, where and when to seed, are determined by the seeding system software that extracts ancillary/auxiliary (or ‘other data’), NWP model data and/or platform sensor data inputs [0036]) and generate a communication to a control system, the communication including a recommendation to initiate the cloud seeding (One or more embodiments employ a simulator implementing software in the loop (SIL) technology 281-2, /281-1 to simulate the UAS flight characteristics, UAS payload sensor data 275, 255, 263, 243, data 293 and mission planner output 287-1, 287-2. These outputs are used to optimize the seed/no seed thresholds and targeting algorithm, saving the high cost of trial and error approaches and ensuring success, and should provide a smaller number of false positive seeding condition detections (compared to current practices) [0057]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Caldwell with the teachings of Defelice to optimize the seed/no seed thresholds and targeting algorithm, saving the high cost of trial and error approaches and ensure success, and provide a smaller number of false positive seeding condition detections (Defelice [0057]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Lulin Xue (US11256000) discloses a method and system for determining cloud seeding potential.
Frederick MacDougall (US20210153442) discloses a system configured for producing a man-made cloud and deliver the man-made cloud into the troposphere at an altitude targeted for downwind delivery of precipitation from the man-made cloud.
Phillip Kaufman (US7965488) discloses an antenna is disclosed to efficiently ionize the atmosphere for the purpose of reducing the aerosol counts, and therefore the number of polluted particles in suspension in the atmosphere, by deposition to ground.
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/SHARAH ZAAB/Examiner, Art Unit 2857
/Catherine T. Rastovski/Supervisory Primary Examiner, Art Unit 2857