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 .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Examiner’s Note
This Office Action is in response to application filed on 8/28/2024, where claims 1-20 are currently pending.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp. Claims 1 and 11 have been provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 8 respectively of the Co-pending Application Pub. No. 2025/0297756.
Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1 and 11 of the instant application and the corresponding claims of the co-pending application are disclosing the invention of a chiller/heat pump system that adjust the temperature setpoint based on an expected emission level of an energy source that powers the system. Claims 1 and 11 of the instant application includes the additional limitation of change the setpoint such that energy level required to operate the chiller/heat pump system to achieve the setpoint will drop when expected emissions level increases, and adjusts the setpoint in an opposed direction when the expected emissions drops. The US Patent Application Pub. No. 2022/0381471 (Wenzel) teaches such.
The co-pending application and Wenzel are analogous art to the claimed invention because they are concerning with interface for adjusting temperature setpoint (i.e., same field of endeavor).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention having the co-pending application and Wenzel before them to modify the building chiller/heat pump system of the co-pending application to incorporate the function of increasing/decreasing temperature setpoint based on expected emission level as taught by Wenzel. One of ordinary skill in the art would have combined the elements as claimed by known methods as disclosed by Wenzel (¶ [0004]-[0012]), because the function of increasing/decreasing temperature setpoint based on expected emission level does not depend on the building chiller/heat pump system. That is the function of increasing/decreasing temperature setpoint based on expected emission level performs the same function independent on which interface it is incorporated onto, and therefore, the result of the combination would have been predictable to one of ordinary skill in the art. The motivation to combine would have been to achieve a target emissions level as suggested by Wenzel (¶ [0007]).
Therefore, for the above reason(s), the claims are obvious variation of each other.
Claim 12 of the instant application is also rejected under non-statutory obviousness type double patenting over claim 12 of the co-pending application, as the claim of the instant application disclose substantially similar limitations as the corresponding claim of the co-pending application.
Claim Rejections - 35 USC § 102
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)(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.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Wenzel et al., (US 2022/0381471 A1) (hereinafter Wenzel).
Referring to claim 1, Wenzel teaches a building chiller/heat pump system comprising:
a chiller/heat pump system for supplying a conditioned fluid to change a temperature of air being delivered into a building (¶ [0059], figs. 1, 3, and 7, “HVAC system 100 is shown to include a chiller 102, a boiler 104, and a rooftop air handling unit (AHU) 106. Waterside system 120 may use boiler 104 and chiller 102 to heat or cool a working fluid”), said chiller/heat pump system being provided with a control to achieve a desired water temperature setpoint to condition the air delivered into the building (¶ [0059], figs. 1, 3, and 7, “The working fluid can be heated in boiler 104 or cooled in chiller 102, depending on whether heating or cooling is required in building 10.” ¶ [0143], “Predictive chiller controller 704 may include a tracking controller configured to generate temperature setpoints (e.g., an air temperature setpoint T.sub.sp,air, a chilled water temperature setpoint T.sub.sp,water, etc.) that achieve the optimal amount of power consumption at each time step.”); and
the control being programmed to receive a prediction of expected emission levels in energy that will be delivered to power the chiller/heat pump system (¶ [0306], “The optimization problem can include an objective function representing a total economic cost resulting from a selection of particular decision variables (e.g., due to a cost of purchasing electricity from the utility grid and a cost of fuel for the fuel cell 2308) plus a cost or penalty associated with carbon emissions. The cost or penalty associated with carbon emissions may be implemented by adding the cost of purchasing carbon offsets equal to the amount of carbon predicted to be emitted over the optimization period relating to the values of the decision variables being selected (e.g., to achieve net-zero emissions), or relating to a cost of carbon credits associated with the predicted emissions.” ¶ [0328], fig. 31A, “a flowchart of a process 3100 for predictive control with carbon emissions optimization is shown…Process 3100 can also be executed by any of the predictive controllers described above (e.g.,…predictive chiller controller 704”), and the control being programmed to change the setpoint such that an energy level required to operate the chiller/heat pump system to achieve the setpoint will drop when the expected emissions level increases, and adjusts the setpoint in an opposed direction when the expected emissions drops (¶ [0218], fig. 17, “Tracking controller 1712 can use the optimal power setpoints P.sub.sp,grid, P.sub.sp,bat, and/or P.sub.sp,total to determine optimal temperature setpoints (e.g., a sump water temperature setpoint T.sub.sp,sump, a condenser water temperature setpoint T.sub.sp,cond, etc.) and an optimal battery charge or discharge rate (i.e., Bat.sub.C/D). Equipment controller 1714 can use the optimal temperature setpoints T.sub.sp,zone or T.sub.sp,chw to generate control signals for powered cooling tower components 1602 that drive the actual (e.g., measured) temperatures T.sub.zone and/or T.sub.chw to the setpoints (e.g., using a feedback control technique).” ¶ [0231], figs. 16 and 17, “Tracking controller 1712 can use the optimal power setpoints P.sub.sp,grid, P.sub.sp,bat, and/or P.sub.sp,total generated by economic controller 1710 to determine optimal temperature setpoints (e.g., a sump water temperature setpoint T.sub.sp,sump, a condenser water temperature setpoint T.sub.sp,cond, etc.)”)
Referring to claim 2, Wenzel further teaches the system as set forth in claim 1, wherein when the available energy is relatively dirty, and the chiller/heat pump system is operating in a cooling mode, the setpoint is increased for a period of time, and if the chiller/heat pump is operating in a heating mode, the setpoint is decreased for a period of time (¶ [0231], figs. 16 and 17, “Tracking controller 1712 can use the optimal power setpoints P.sub.sp,grid, P.sub.sp,bat, and/or P.sub.sp,total generated by economic controller 1710 to determine optimal temperature setpoints (e.g., a sump water temperature setpoint T.sub.sp,sump, a condenser water temperature setpoint T.sub.sp,cond, etc.)” ¶ [0306], “The optimization problem can include an objective function representing a total economic cost resulting from a selection of particular decision variables (e.g., due to a cost of purchasing electricity from the utility grid and a cost of fuel for the fuel cell 2308) plus a cost or penalty associated with carbon emissions. The cost or penalty associated with carbon emissions may be implemented by adding the cost of purchasing carbon offsets equal to the amount of carbon predicted to be emitted over the optimization period relating to the values of the decision variables being selected (e.g., to achieve net-zero emissions), or relating to a cost of carbon credits associated with the predicted emissions.”)
Referring to claim 3, Wenzel further teaches the system as set forth in claim 2, wherein when the setpoint is changed in the opposed direction, it is changed to a magnitude that exceeds the actual desired setpoint at that time (¶ [0149], “Tracking controller 1012 can use the optimal power setpoints P.sub.sp,grid, and/or P.sub.sp,bat, P.sub.sp,total to determine optimal temperature setpoints (e.g., an air setpoint T.sub.sp,air, a chilled water temperature setpoint T.sub.sp,water, etc.) and an optimal battery charge or discharge rate (i.e., Bat.sub.C/D). Equipment controller 1014 can use the optimal temperature setpoints T.sub.sp,air or T.sub.sp,water to generate control signals for powered chiller components 902 that drive the actual (e.g., measured) temperatures T.sub.air and/or T.sub.water to the setpoints (e.g., using a feedback control technique).” Examiner notes, although not explicitly disclosed, it is implied that the temperature is changed to exceed, e.g., over or below, the setpoint, because the temperature is optimized, which entails the temperature setpoint is changed to make it as effective or optimal as possible.)
Referring to claim 4, Wenzel further teaches the system as set forth in claim 2, wherein the prediction is a prediction of quantity of emissions per a unit of energy (¶ [0304], fig. 26, “At step 2808, utility rates and carbon emissions data is obtained from the utility grid. For example, electricity from the utility grid may be subject to time-of-use pricing, such that pricing varies over time. Other pricing structures, incentive programs, penalties, etc. for example as described elsewhere herein, which may be relevant to energy from the utility grid may also be ascertained in step 2808. Additionally, in some scenarios, the utility grid may make available information indicating an amount of carbon emissions associated with grid power at a particular point in time (e.g., a time-varying power:carbon or carbon:power ratio, tonnes of CO.sub.2 per kWh), which may vary due to the utility grid receiving power from multiple sources which emit carbon at different rates (e.g., where a natural gas plant, wind farm, and solar farm are connected to the energy grid).”)
Referring to claim 5, Wenzel further teaches the system as set forth in claim 3, wherein the change in the setpoint occurs across a plurality of cycles during an extended period of relatively dirty power supply (¶ [0305], fig. 26, “At step 2610, the data from steps 2602, 2604, 2606, and 2608 is used to generate control decisions for components of the modular energy unit, in particular such that the control decisions are predicted to reduce cost and/or carbon emissions associated with serving the electrical demands on the modular energy unit.” ¶ [0306], “The optimization problem can include an objective function representing a total economic cost resulting from a selection of particular decision variables (e.g., due to a cost of purchasing electricity from the utility grid and a cost of fuel for the fuel cell 2308) plus a cost or penalty associated with carbon emissions. The cost or penalty associated with carbon emissions may be implemented by adding the cost of purchasing carbon offsets equal to the amount of carbon predicted to be emitted over the optimization period relating to the values of the decision variables being selected (e.g., to achieve net-zero emissions), or relating to a cost of carbon credits associated with the predicted emissions.”)
Referring to claim 6, Wenzel further teaches the system as set forth in claim 2, wherein the change in the setpoint occurs across a plurality of cycles during an extended period of relatively dirty power supply (¶ [0305], fig. 26, “At step 2610, the data from steps 2602, 2604, 2606, and 2608 is used to generate control decisions for components of the modular energy unit, in particular such that the control decisions are predicted to reduce cost and/or carbon emissions associated with serving the electrical demands on the modular energy unit.” ¶ [0306], “The optimization problem can include an objective function representing a total economic cost resulting from a selection of particular decision variables (e.g., due to a cost of purchasing electricity from the utility grid and a cost of fuel for the fuel cell 2308) plus a cost or penalty associated with carbon emissions. The cost or penalty associated with carbon emissions may be implemented by adding the cost of purchasing carbon offsets equal to the amount of carbon predicted to be emitted over the optimization period relating to the values of the decision variables being selected (e.g., to achieve net-zero emissions), or relating to a cost of carbon credits associated with the predicted emissions.”)
Referring to claim 7, Wenzel further teaches the system as set forth in claim 1, wherein when the setpoint is changed in the opposed direction, it is changed to a magnitude that exceeds the actual desired setpoint at that time (¶ [0149], “Tracking controller 1012 can use the optimal power setpoints P.sub.sp,grid, and/or P.sub.sp,bat, P.sub.sp,total to determine optimal temperature setpoints (e.g., an air setpoint T.sub.sp,air, a chilled water temperature setpoint T.sub.sp,water, etc.) and an optimal battery charge or discharge rate (i.e., Bat.sub.C/D). Equipment controller 1014 can use the optimal temperature setpoints T.sub.sp,air or T.sub.sp,water to generate control signals for powered chiller components 902 that drive the actual (e.g., measured) temperatures T.sub.air and/or T.sub.water to the setpoints (e.g., using a feedback control technique).” Examiner notes, although not explicitly disclosed, it is implied that the temperature is changed to exceed, e.g., over or below, the setpoint, because the temperature is optimized, which entails the temperature setpoint is changed to make it as effective or optimal as possible.)
Referring to claim 8, Wenzel further teaches the system as set forth in claim 1, wherein the prediction is a prediction of quantity of emissions per a unit of energy (¶ [0304], fig. 26, “At step 2808, utility rates and carbon emissions data is obtained from the utility grid. For example, electricity from the utility grid may be subject to time-of-use pricing, such that pricing varies over time. Other pricing structures, incentive programs, penalties, etc. for example as described elsewhere herein, which may be relevant to energy from the utility grid may also be ascertained in step 2808. Additionally, in some scenarios, the utility grid may make available information indicating an amount of carbon emissions associated with grid power at a particular point in time (e.g., a time-varying power:carbon or carbon:power ratio, tonnes of CO.sub.2 per kWh), which may vary due to the utility grid receiving power from multiple sources which emit carbon at different rates (e.g., where a natural gas plant, wind farm, and solar farm are connected to the energy grid).”)
Referring to claim 9, Wenzel further teaches the system as set forth in claim 1, wherein the change in the setpoint occurs across a plurality of cycles during an extended period of relatively dirty power supply (¶ [0305], fig. 26, “At step 2610, the data from steps 2602, 2604, 2606, and 2608 is used to generate control decisions for components of the modular energy unit, in particular such that the control decisions are predicted to reduce cost and/or carbon emissions associated with serving the electrical demands on the modular energy unit.” ¶ [0306], “The optimization problem can include an objective function representing a total economic cost resulting from a selection of particular decision variables (e.g., due to a cost of purchasing electricity from the utility grid and a cost of fuel for the fuel cell 2308) plus a cost or penalty associated with carbon emissions. The cost or penalty associated with carbon emissions may be implemented by adding the cost of purchasing carbon offsets equal to the amount of carbon predicted to be emitted over the optimization period relating to the values of the decision variables being selected (e.g., to achieve net-zero emissions), or relating to a cost of carbon credits associated with the predicted emissions.”)
Referring to claim 10, Wenzel further teaches the system as set forth in claim 1, wherein the control is programmed to calculate a quantity of reduced emission based upon the adjustment of the set point (¶ [0313], fig. 27, “The predictive controller can thus reduce use of carbon-emitting energy sources to move building energy consumption toward zero carbon emissions. If carbon emissions are entirely eliminated, process 2700 can end at step 2712.” ¶ [0314], fig. 27, “If a reduced level of carbon emission remains (e.g., due to continued reliance on carbon-emitting production in the energy grid under certain conditions), the process 2700 proceeds to step 2714 where any remaining carbon emissions are automatically offset using one or more carbon capture processes. The decisions of the predictive controller and data collected thereby can be used to estimate an amount of remaining carbon emissions (e.g., in tons of CO.sub.2), which can be used to initiate and execute on a desired carbon offset program.”)
Regarding claims 11-14 and 16-20, these claims recite the method performed by the building chiller/heat pump system of claims 1-4 and 6-10 respectively; therefore, the same rationale of rejection is applicable.
Referring to claim 15, Wenzel further teaches the method as set forth in claim 14, wherein the change in the setpoint occurs across a plurality of cycles during an extended period of relatively dirty power supply (¶ [0305], fig. 26, “At step 2610, the data from steps 2602, 2604, 2606, and 2608 is used to generate control decisions for components of the modular energy unit, in particular such that the control decisions are predicted to reduce cost and/or carbon emissions associated with serving the electrical demands on the modular energy unit.” ¶ [0306], “The optimization problem can include an objective function representing a total economic cost resulting from a selection of particular decision variables (e.g., due to a cost of purchasing electricity from the utility grid and a cost of fuel for the fuel cell 2308) plus a cost or penalty associated with carbon emissions. The cost or penalty associated with carbon emissions may be implemented by adding the cost of purchasing carbon offsets equal to the amount of carbon predicted to be emitted over the optimization period relating to the values of the decision variables being selected (e.g., to achieve net-zero emissions), or relating to a cost of carbon credits associated with the predicted emissions.”)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
US 2023/0400207 (Chang) – discloses emission demand response system that modifies energy consumption by adjusting temperature setpoint.
CN 118669926 (Sui) – discloses system for indoor temperature control with heat pipe.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MONG-SHUNE CHUNG whose telephone number is (571) 270-5817. The examiner can normally be reached on M-F (9-5) EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, 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.
Information regarding the status of an application may be obtained from Patent Center and the Private Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from Patent Center or Private PAIR. Status information for unpublished applications is available through Patent Center and Private PAIR for authorized users only. Should you have questions about access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. 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.
/MONG-SHUNE CHUNG/
Primary Examiner, Art Unit 2118
Prosecution Insights