CTNF 18/661,708 CTNF 101330 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia 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 § 103 07-20-aia AIA 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. 07-23-aia AIA The factual inquiries set forth in Graham v. John Deere Co. , 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. 07-21-aia AIA Claim s 1, 10, 11, and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Cai et al. (US 20210281077 A1.), and in view of Tsujii et al. (US 20220123739 A1.) . As per claim 1, Cai et al teach A distribution apparatus comprising a controller (Fig.1, para 9) configured to: acquire, for each power source in a plurality of types of power sources used in providing adjustability during a plurality of time periods, information on either a cost by time period or carbon dioxide emissions by time period: (para 9; for first and second time period cost is acquired for plurality of power supply) set, for each time period in the plurality of time periods, with reference to the acquired information, a ratio of use of each power source in the plurality of types of power sources in providing the adjustability : (para 9, para 29, “The power control system 104 uses the power control information to cause the ECMs of the plurality of power resources 102 to control respective amounts of power that are contributed from the plurality of power resources 102 to a load ”; para 30; “output of energy by the plurality of power resources 102 based on a load profile. The load profile indicates a power demand and/or variations in a load over a specified time period”. ) However, Cai et al. do not teach use of distribution ratio and output a setting value of the distribution ratio by time period. However, given that Cai et al. teach the controller is performing “control respective amounts of power that are contributed from the plurality of power resources 102 to a load” (see para 29), it is understood that related setting would be needed. In the same field of endeavor Tsujii et al. teach use of distribution ratio and output a setting value of the distribution ratio by time period (para 84, distribution ratio for different power source/generators. For different time interval {para 72}. They are also based on cost para 82-83; Also see Fig.1, Fig.2 and Fig.3). It would have been obvious to a person ordinary skilled in art, before the effective filing date of the claimed invention, to modify the teaching of Cai et al. and to include the distribution power source ratio by time period taught by Tsujii et al. into the power distribution system taught by Cai et al. This would have been obvious because both Cai et al. and Tsujii et al. teach of power distribution system. By adding the power distribution ratio, the system can balance the power storage and adjust the distribution process to save cost or reduce carbon emission (Tsujii et al. – para 11). As per claim 10, the combination of Cai et al and Tsujii et al. teach A power control system comprising: the distribution apparatus according to claim 1 (Cai et al ., Fig.1, para 9) ; and a power control apparatus configured to control the plurality of types of power sources (Cai et al., para 22, Fig. 1, para 29, “the plurality of power resources 102 to a load”) according to the setting value of the distribution ratio by time period as outputted by the distribution apparatus (Tsujii et al., para 84, distribution ratio for different power source/generators. For different time interval {para 72}. They are also based on cost para 82-83; Also see Fig.1, Fig.2 and Fig.3) . As per claim 11, Cai et al. teach A distribution method comprising: acquiring, by a distribution apparatus, for each power source in a plurality of types of power sources used in providing adjustability during a plurality of time periods, information on either a cost by time period or carbon dioxide emissions by time period (Fig. 1 , para 9, also please see para 22) ; setting, by the distribution apparatus, for each time period in the plurality of time periods, with reference to the acquired information, a ratio of use of each power source in the plurality of types of power sources in providing the adjustability as a distribution ratio (para 9; para 29 “The power control system 104 uses the power control information to cause the ECMs of the plurality of power resources 102 to control respective amounts of power that are contributed from the plurality of power resources 102 to a load ”; para 30; “output of energy by the plurality of power resources 102 based on a load profile. The load profile indicates a power demand and/or variations in a load over a specified time period”.) : However, Cai et al. do not teach and outputting, from the distribution apparatus, a setting value of the distribution ratio by time period. In the same field of endeavor, Tsujii et al. teach and outputting, from the distribution apparatus, a setting value of the distribution ratio by time period (Tsujii et al., para 84, distribution ratio for different power source/generators. For different time interval {para 72}. They are also based on cost, para 82-83; Also, please see Fig.1, Fig.2 and Fig.3) . Please see analysis of claim 1 for further clarification. As per claim 12, the combination of Cai et al. and Tsujii et al. teach A non-transitory computer readable medium storing a distribution program configured to cause a computer to execute operations, the operations comprising (Cai et al. para 43, Fig. 2 ,machine learning techniques used in a computing device): acquiring, for each power source in a plurality of types of power sources used in providing adjustability during a plurality of time periods, information on either a cost by time period or carbon dioxide emissions by time period (Please see analysis of claim 11 above) ; setting, for each time period in the plurality of time periods, with reference to the acquired information, a ratio of use of each power source in the plurality of types of power sources in providing the adjustability as a distribution ratio (Please see analysis of claim 11 above) ; and outputting a setting value of the distribution ratio by time period (Please see analysis of claim 11 above) Please see analysis of claim 11 above for further clarification . 07-21-aia AIA Claim s 2-9 are rejected under 35 U.S.C. 103 as being unpatentable over Cai et al. (US 20210281077 A1.), and in view of Tsujii et al. (US 20220123739 A1), and further in view of Yerli (US 20230350363 A1.) . As per claim 2, Cai et al. teach The distribution apparatus according to claim 1, wherein the plurality of types of power sources includes a power generator and a storage battery (Fig. 1, plurality of power sources 102 includes Battery 110, Engine 108(configured to provide electric power to the load, Engine 108 teaches power generator) , the information on the cost by time period (para 9, para 42, determining cost over the time period) includes information on a fuel price by time period (para 51, “The power control system 104 determines an amount of the type of fuel required for the engine 108 to produce a unit of energy (e.g., a kilowatt-hour), based on the type of the fuel. The unit of energy is being calculated by hour , this teaches the time period., para 52, “The power control system 104 multiplies the total amount of fuel by the cost of the type of fuel per unit to determine an initial engine cost .” Overall, it teaches the fuel cost by time period.) , the controller is configured to set, for each time period, with reference to information on a corresponding fuel price (para 154, Fig. 9 a master controller, power control system 104 may receive load profile indicating a power demand, and based on the power demand the controller is supplying the energy. The amount of energy is multiplying by the per unit cost to determine the total engine cost (see para 51-52) . at least a ratio (para 80, “ The diversity factor is a ratio of a sum of individual, non-coincident maximum loads of a sub-division of the power generation system 100 to a maximum demand of the power generation system 100.The demand factor is a fractional amount of energy being provided by a power resource (e.g., PV energy resource 106, engine 108, and/or battery 110.” , “The utilization is a ratio of a time that a power resource (e.g., PV energy resource 106, engine 108, and/or battery 110”), of use of each of the power generator and the storage battery ratio adjustability for lacking power as the distribution (para 25, fig 1, 108 is configured to adjust power load, the secondary power resource is configured to accept power input from a primary power source and provides the power output to a client. the secondary power resource is a dispatchable energy resource that can be used on demand (e.g., can be turned on or off) and can adjust the power output supplied to the client, also please see para 80 for power distribution.. Also please see para 30-31, Fig. 1, The power control system 104 or the optimizer module determines sufficient (not lacking) energy to meet the power demand.) . However, the combination of Cai et al. and Tsujii et al. do not teach information on a corresponding power purchase price by time period. In the same field of endeavor Yerli teaches, information on a corresponding power purchase price by time period ( para 9, Fig.10 #1008 “optimal revenues”, #1018 “shortfall”; para 78), It would have been obvious to a person ordinary skilled in art, before the effective filing date of the claimed invention, to modify the teaching of Cai et al. and to include the information on power purchase price taught by Yerli into the power distribution system taught by Cai et al. This would have been obvious because the combination of Cai et al. and Tsujii et al. and Yerli teach of power distribution system. By adding the information on power purchase price, the system can balance the power storage and adjust the distribution process to save cost. As per claim 3, The combination of Cai et al., Tsujii et al. and Yerli teach The distribution apparatus according to claim 2, wherein the controller is configured to set the ratio of use of each of the power generator and the storage battery in providing the adjustability for the lacking power by comparing, for each time period (Cai et al., para 30-31, The power control system 104 or the optimizer module determines sufficient (not lacking) energy to meet the power demand ,para 58, the control system104 compares the current voltage to the maximum operating voltage to determine the amount of energy stored in the battery, para 25, fig 1, 108 is configured to adjust power load, the secondary power resource is configured to accept power input from a primary power source and provides the power output to a client. the secondary power resource is a dispatchable energy resource that can be used on demand (e.g., can be turned on or off) and can adjust the power output supplied to the client), ( also please see Tsujii et al., ratio calculation method in Fig, 2, Fig, 3 and Fig, 4 ) , a cost in a case of procuring the lacking power by supplying fuel to the power generator and causing the power generator to generate power with a cost in a case of procuring the lacking power by supplying power obtained by purchasing power to the storage battery and discharging the storage battery ( Tsujii et al., para 27, determining a ratio of output distribution according to economic efficiency. Balancing the load frequency based on ascending and descending value of cost, “The cost may include fuel cost for the regulated power source and procurement cost .” Also please see, Para 26, fig. 1 “The regulated power source can be selected from at least one of a power generator, a storage battery , and a demand response.”) . As per claim 4, Cai et al. teach The distribution apparatus according to claim 1, wherein the plurality of types of power sources includes a power generator and a storage battery (Fig. 1, para 9, para 25, plurality of power sources 102 includes Battery 110, Engine 108 (configured to provide electric power to the load, Engine 108 teaches power generator) However, the combination of Cai et al. and Tsuji et al. do not teach, the information on the cost by time period includes information on a power sale price by time period and information on a power purchase price by time period, and the controller is configured to set, for each time period, with reference to information on a corresponding power sale price and information on a corresponding power purchase price, at least a ratio of use of each of the power generator and the storage battery in providing adjustability for surplus power as the distribution ratio. In the same field of endeavor, Yerli teaches the information on the cost by time period includes information on a power sale price by time period and information on a power purchase price by time period (Yerli, para 9, Fig.10 #1008 “optimal revenues”, #1018 “shortfall”; para 78) , and the controller is configured to set, for each time period, with reference to information on a corresponding power sale price and information on a corresponding power purchase price, at least a ratio of use of each of the power generator and the storage battery in providing adjustability for surplus power as the distribution ratio (Cai teaches a ratio of use as seen in claim 2 above; Yerli, para 9, Fig.10, #1018, para 78 teaches “surplus”) . It would have been obvious to a person ordinary skilled in art, before the effective filing date of the claimed invention, to modify the teaching of Cai et al. and to include the information on power purchase price taught by Yerli into the power distribution system taught by Cai et al. This would have been obvious because the combination of Cai et al. and Yerli teach of power distribution system. By adding the information on power purchase price information by time period, the system can balance the power storage and adjust the distribution process for optimal power usage and respond to future peaks (Yerli, para 78). As per claim 5, The combination of Cai et al., Tsujii et al., and Yerli teach The distribution apparatus according to claim 4, wherein the controller is configured to set the ratio of use of each of the power generator and the storage battery in providing the adjustability for the surplus power by comparing , for each time period, a cost in a case of absorbing the surplus power (Yerli, para 9, Fig.10, #1018 “surplus”; para 78) , by reducing power obtained by causing the power generator to generate power for sale with a cost in a case of absorbing the surplus power by reducing power obtained by purchasing power to charge the storage battery (Tsuji et al. para 84, distribution ratio for different power source/generators is calculated based on cost , also please see para 82-83, Yerli, para 78, using an AI agent to optimize the power generations of a smart home and identify the peak demand of electricity. Using the collected energy from the solar panel and storing the power into the home own’s battery . Therefore, when there is a peak demand in the neighborhood, the demanded power can be supplied from the stored battery) . As per claim 6, Cai et al. teach The distribution apparatus according to claim 1, wherein the plurality of types of power sources includes a power generator and a storage battery (Cai et al., Fig. 1, plurality of power sources 102 includes Battery 110, Engine 108 (configured to provide electric power to the load, Engine 108 teaches power generator)) , and The combination of Cai et el. and Tsujii et al. teach at least a ratio of use of each of the power generator and the storage battery in providing adjustability for lacking power as the distribution ratio at least a ratio (Cai et al. para 30-31, The power control system 104 or the optimizer module determines the sufficient energy to meet the power demand ,para 58, the control system104 compares the current voltage to the maximum operating voltage to determine the amount of energy stored in the battery, para 80, “ The diversity factor is a ratio of a sum of individual, non-coincident maximum loads of a sub-division of the power generation system 100 to a maximum demand of the power generation system 100.The demand factor is a fractional amount of energy being provided by a power resource (e.g., PV energy resource 106, engine 108, and/or battery 110.” , “The utilization is a ratio of a time that a power resource (e.g., PV energy resource 106, engine 108, and/or battery 110”), of use of each of the power generator and the storage battery ratio adjustability for lacking power as the distribution (Cai et al. ,para 25, fig 1, 108 is configured to adjust power load, the secondary power resource is configured to accept power input from a primary power source and provides the power output to a client. the secondary power resource is a dispatchable energy resource that can be used on demand (e.g., can be turned on or off) and can adjust the power output supplied to the client, also please see para 80 for power distribution. also please see, Tsujii et al. para 84, distribution ratio for different power source/generators is calculated based on cost, also please see para 82-83) . However, the combination of Cai et al. and Tsujii et al. do not teach the controller is configured to set, for each time period, with reference to information on corresponding carbon dioxide emissions . In the same field oof endeavor Yerli teaches, the controller is configured to set, for each time period, with reference to information on corresponding carbon dioxide emissions (Yerli, para 9, “carbon emissions”, Fig.10 #1010 “Calculate carbon Footprint”; para 78) . It would have been obvious to a person ordinary skilled in art, before the effective filing date of the claimed invention, to modify the teaching of Cai et al. and Tsujii et al. to include the carbon emissions reduction process taught by Yerli. This would have been obvious because the combination of Cai et al., Tsujii et al. and Yerli teach of power distribution system. By reducing carbon emissions, the system can optimize energy generation by reducing cost and carbon emissions (Yerli, para 9, para 78). As per claim 7, The combination of Cai et al., Tsujii et al., and Yerli teach The distribution apparatus according to claim 6, wherein the controller is configured to set the ratio of use of each of the power generator and the storage battery in providing the adjustability for the lacking power by comparing, for each time period (Cai et al. ,para 30-31, The power control system 104 or the optimizer module determines the sufficient (not lacking) energy to meet the power demand, para 25, fig 1, power control system 104, Engine 108 is configured to adjust power load, the secondary power resource is configured to accept power input from a primary power source and provides the power output to a client. the secondary power resource is a dispatchable energy resource that can be used on demand (e.g., can be turned on or off) and can adjust the power output supplied to the client. Also see Tsujii et al., para 82-83 , and ratio calculation method in Fig, 2, Fig, 3 and Fig, 4) , carbon dioxide emissions in a case of procuring the lacking power by supplying fuel to the power generator and causing the power generator to generate power with carbon dioxide emissions in a case of procuring the lacking power by supplying power obtained by purchasing power to the storage battery and discharging the storage battery (Yerli, para 9, “carbon emissions”, Fig.10 #1010 “Calculate carbon Footprint”; para 78, using an AI agent to optimize the power generations of a smart home and identify the peak demand of electricity. Using the collected energy from the solar panel and storing the power into the home own’s battery . Therefore, when there is a peak demand in the neighborhood, the demanded power can be supplied from the stored battery, also please see para 87,” t he carbon footprint data 518 may be calculated by the DER SCADA from the early stage of energy fuel production ”) . As per claim 8, Cai et al. teach The distribution apparatus according to claim 1, wherein the plurality of types of power sources includes a power generator and a storage battery (Fig. 1, plurality of power sources 102 includes Battery 110, Engine 108(configured to provide electric power to the load, Engine 108 teaches power generator) , and the controller is configured to set, for each time period (para 25, fig 1, power control system 104, Engine 108 is configured to adjust power load , the secondary power resource is configured to accept power input from a primary power source and provides the power output to a client. the secondary power resource is a dispatchable energy resource that can be used on demand (e.g., can be turned on or off) and can adjust the power output supplied to the client, also please see para 34, “The power control system 104 (e.g., the supervisor module) transmits power control information to the PV energy resource 106 to cause the PV energy resource 106 to supply energy to the load during the specified time period ”) , The combination of Cai et al. and Tsujii et al. teach at least a ratio of use of each of the power generator and the storage battery in providing adjustability for surplus power as the distribution ratio (Cai et al., para 80, “ The diversity factor is a ratio of a sum of individual, non-coincident maximum loads of a sub-division of the power generation system 100 to a maximum demand of the power generation system 100.The demand factor is a fractional amount of energy being provided by a power resource (e.g., PV energy resource 106, engine 108, and/or battery 110.”) , “The utilization is a ratio of a time that a power resource (e.g., PV energy resource 106, engine 108, and/or battery 110” ”) ,also see Tsujii et al., ratio calculation method in Fig, 2, Fig, 3 and Fig, 4) . However, the combination of Cai et al. and Tsujii et al. do not teach with reference to information on corresponding carbon dioxide emissions, for surplus power as the distribution ratio. In the same field of endeavor, Yerli teaches with reference to information on corresponding carbon dioxide emissions, for surplus power as the distribution ratio ( Yerli, para 9, “carbon emissions”, Fig.10 #1010 “Calculate carbon Footprint”; para 87, carbon emission cost, also please see Fig. 10, #1018, “surplus”, para 78, using an AI agent to optimize the power generations of a smart home and identify the peak demand of electricity. Using the collected energy from the solar panel and storing the power into the home own’s battery . Therefore, when there is a peak demand in the neighborhood, the demanded power can be supplied from the stored battery. The power supply is determined based on the energy demand ratio. When there is more demand in the neighborhood for a game, the power from the stored battery supply will be increased, and the alternation power supply will be decreased. also please see para 87,” t he carbon footprint data 518 may be calculated by the DER SCADA from the early stage of energy fuel production ”.) . It would have been obvious to a person ordinary skilled in art, before the effective filing date of the claimed invention, to modify the teaching of Cai et al. and to include the carbon emissions reduction process taught by Yerli and ratio calculation method taught by Tsujii et al. into the energy storage system. This would have been obvious because the combination of Cai et al., Tsujii et al., and Yerli teach of power distribution system. By reducing carbon emissions, the system can optimize energy generation by reducing cost and carbon emissions (Yerli, para 9, para 78). As per claim 9, The combination of Cai et al., Tsujii et al., and Yerli teach The distribution apparatus according to claim 8, wherein the controller is configured to set the ratio of use of each of the power generator and the storage battery in providing the adjustability for the surplus power by comparing, for each time period (Cai et al., para 25, fig 1, power control system 104, Engine 108 is configured to adjust power load , the secondary power resource is configured to accept power input from a primary power source and provides the power output to a client. the secondary power resource is a dispatchable energy resource that can be used on demand (e.g., can be turned on or off) and can adjust the power output supplied to the client, also please see para 34, “The power control system 104 (e.g., the supervisor module) transmits power control information to the PV energy resource 106 to cause the PV energy resource 106 to supply energy to the load during the specified time period. ” Also please see, Tsujii et al. para 84,distribution ratio for different power source/generators is calculated based on cost, also please see para 82-83) , carbon dioxide emissions in a case of absorbing the surplus power by reducing power obtained by causing the power generator to generate power for sale with carbon dioxide emissions in a case of absorbing the surplus power by reducing power obtained by purchasing power to charge the storage battery ( Yerli, para 9, “carbon emissions”, Fig.10 #1010 “Calculate carbon Footprint”; para 78 , using an AI agent to optimize the power generations of a smart home and identify the peak demand of electricity. Using the collected energy from the solar panel and storing the energy into the home own’s battery. Therefore, when there is a peak demand in the neighborhood, the demanded power can be supplied from the stored battery. The power supply is determined based on the energy demand ratio. When there is more demand in the neighborhood for a game, the power from the stored battery supply will be increased, and the alternation power supply will be decreased. Also please see para 22 “If there is no shortfall or surplus energy, the coordinated dispatch sends the coordinated forecasted energy to an energy trading command. However, if there is any shortfall or surplus energy, the coordinated dispatch sends a shortfall/surplus request to a peer-to-peer parallel auctioning process.”, also please see Fig. 1, #130, para 43 is an energy storage device that includes batteries. Batteries may be, for example, lithium-ion batteries, lead acid batteries, sodium sulphur batteries, nickel cadmium batteries, vanadium redox flow batteries, zinc bromine flow batteries, polysulphide bromine flow batteries, and residential battery systems.) . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Please refer to the form PTO-892 Notice of References Cited. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Rokeya Alam whose telephone number is (571)-272-0083. The examiner can normally be reached on 7:30am - 4:30pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Mr. Scott Baderman can be reached at telephone number (571-272-3644). The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300. 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To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) Form at https://www.uspto.gov/patents/uspto-automated- interview-request-air-form. /ROKEYA SHAWALI ALAM/Examiner, Art Unit 2118 /SCOTT T BADERMAN/Supervisory Patent Examiner, Art Unit 2118 Application/Control Number: 18/661,708 Page 2 Art Unit: 2118 Application/Control Number: 18/661,708 Page 3 Art Unit: 2118 Application/Control Number: 18/661,708 Page 4 Art Unit: 2118 Application/Control Number: 18/661,708 Page 5 Art Unit: 2118 Application/Control Number: 18/661,708 Page 6 Art Unit: 2118 Application/Control Number: 18/661,708 Page 7 Art Unit: 2118 Application/Control Number: 18/661,708 Page 8 Art Unit: 2118 Application/Control Number: 18/661,708 Page 9 Art Unit: 2118 Application/Control Number: 18/661,708 Page 10 Art Unit: 2118 Application/Control Number: 18/661,708 Page 11 Art Unit: 2118 Application/Control Number: 18/661,708 Page 12 Art Unit: 2118 Application/Control Number: 18/661,708 Page 13 Art Unit: 2118 Application/Control Number: 18/661,708 Page 14 Art Unit: 2118 Application/Control Number: 18/661,708 Page 15 Art Unit: 2118 Application/Control Number: 18/661,708 Page 16 Art Unit: 2118
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