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 Objections
Claim 8 is objected to because of the following informalities:
In claim 8, “a usage scheme …” should be “the usage scheme ….” Appropriate correction is required.
In claim 8, “an event-based demand …” should be “the event-based demand ….” Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 12 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. It is unclear and thus indefinite if the claimed “evaluating a total cost savings factor that quantifies …” is a new “total cost savings factor” or if the recited features further limit the “total cost savings factor” of claim 1. Appropriate correction is required.
Claim 2 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. The claim is unclear and thus indefinite because the recited “a BESS usage cost factor …” and “a demand cost factor …” appear to be the same as those recited in claim 1. If not, then a different designation such as “second” should be used. Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-6 and 8-21 are rejected under 35 U.S.C. 101 for the reasons given below:
Claim 1 is rejected under 35 U.S.C. 101 because, while independent claim 1 falls within a statutory class of a method (i.e., claim 1 passes Step 1 of the § 101 analysis, see MPEP § 2106.03.II), under Step 2A of the § 101 analysis, claim 1 recites judicial exceptions without integrating the judicial exceptions into a practical application (i.e., fails Step 2A of the § 101 analysis). See MPEP § 2106.04. Specifically, claim 1 recites “accessing power demand data for a facility …” “determining … a new demand value based on the original demand value …,” evaluating … a total cost factor over the plurality of power demand intervals …” and “identifying… the charge-discharge profile that results in minimization of the total cost factor …” which are abstract ideas and/or mathematical concepts. These judicial exceptions are not integrated into a practical application because the claimed accessing, determine, evaluating, and identifying can be performed by observation (e.g., on a display) and/or mentally (or by using pen and paper). The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the elements-at-issue do not “improve[] the functioning of a computer or improve[] another technology or technical field” and thus they are still abstract ideas that do not integrate the judicial exceptions into a practical application. See MPEP § 2106.04(d)(1). Finally, claim 1 also fails under Step 2B of the § 101 analysis because claim 1 fails to recite any additional elements that “amount to significantly more than the judicial exception itself.” See MPEP §2106.05. Even assuming, arguendo, that the elements-at-issue are new ideas, these features are still abstract ideas, as discussed above, and thus do not amount to “significantly more.” See MPEP § 2106.05 (“a claim for a new abstract idea is still an abstract idea” quoting Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016), emphasis original).
Claims 2-3, 5-6, and 8-10, which depend on claim 1, are rejected under 35 U.S.C. 101 because they merely recite features that further define previously recited elements without integrating the identified judicial exceptions into a practical application.
Claim 4 is rejected under 35 U.S.C. 101 because claim 4 recites judicial exceptions without integrating the judicial exceptions into a practical application (i.e., fails Step 2A of the § 101 analysis). See MPEP § 2106.04. Specifically, claim 4 recites “determining … the new demand value … and evaluating the total cost factor ….,” which are abstract ideas because they can be performed mentally by a human (or by using pen and paper). Claim 4 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claimed determining and the claimed evaluating do not “improve[] the functioning of a computer or improve[] another technology or technical field” and thus they are still abstract ideas that do not integrate the judicial exceptions into a practical application. See MPEP § 2106.04(d)(1). Finally, claim 4 also fails under Step 2B of the § 101 analysis because claim 4 fails to recite any additional elements that “amount to significantly more than the judicial exception itself.” See MPEP §2106.05. Even assuming, arguendo, that the claimed determining and the claimed evaluating are new ideas, these features are still abstract ideas, as discussed above, and thus do not amount to “significantly more.” See MPEP § 2106.05 (“a claim for a new abstract idea is still an abstract idea” quoting Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016), emphasis original).
Claim 11 is rejected under 35 U.S.C. 101 by virtue of its dependency on claim 1. Although claim 11 recites “applying the charge-discharge profile to a control system that operates the BESS according to the charge-discharge profile,” these additional elements amount to no more than a recitation to implement the abstract idea on a computer and thus does not make the judicial exception patent-eligible. See MPEP § 2106.05(f) (citing Alice Corp. v. CLS Bank and stating that the additional element or combination of elements must do more than simply state the judicial exception while adding the words “apply it.”). Here, claim 11 does no more than recite “applying” the result of the abstract idea (i.e., the “charge-discharge profile”) to a control system without providing a practical application that integrates the judicial exception. Note: claim 11 can overcome the 101 rejection if rewritten to positively recite the operation on the BEES (e.g., adding a step reciting “operating the BESS by the control system according to the charge-discharge profile”).
Claim 12 is rejected under 35 U.S.C. 101 because claim 12 recites a judicial exception without integrating the judicial exception into a practical application (i.e., fails Step 2A of the § 101 analysis). See MPEP § 2106.04. Specifically, claim 12 recites “evaluating a total cost savings factor ….,” which is an abstract idea because it can be performed mentally by a human (or by using pen and paper). Claim 12 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claimed evaluating does not “improve[] the functioning of a computer or improve[] another technology or technical field” and thus it is still abstract idea that does not integrate the judicial exception into a practical application. See MPEP § 2106.04(d)(1). Finally, claim 12 also fails under Step 2B of the § 101 analysis because claim 12 fails to recite any additional elements that “amount to significantly more than the judicial exception itself.” See MPEP §2106.05. Even assuming, arguendo, that the claimed evaluating is a new idea, this feature is still abstract idea, as discussed above, and thus do not amount to “significantly more.” See MPEP § 2106.05 (“a claim for a new abstract idea is still an abstract idea” quoting Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016), emphasis original).
Claim 13 is rejected under 35 U.S.C. 101 because claim 13 recites judicial exceptions without integrating the judicial exception into a practical application (i.e., fails Step 2A of the § 101 analysis). See MPEP § 2106.04. Specifically, claim 12 recites “determining a timeframe in which the total cost savings factor is expected to exceed a total capital cost …,” which is an abstract idea because it can be performed mentally by a human (or by using pen and paper). Claim 13 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claimed determining does not “improve[] the functioning of a computer or improve[] another technology or technical field” and thus it is still abstract idea that does not integrate the judicial exception into a practical application. See MPEP § 2106.04(d)(1). Finally, claim 13 also fails under Step 2B of the § 101 analysis because claim 13 fails to recite any additional elements that “amount to significantly more than the judicial exception itself.” See MPEP §2106.05. Even assuming, arguendo, that the claimed determining is a new idea, this feature is still abstract idea, as discussed above, and thus does not amount to “significantly more.” See MPEP § 2106.05 (“a claim for a new abstract idea is still an abstract idea” quoting Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016), emphasis original).
Claim 14 is rejected under 35 U.S.C. 101 by virtue of its dependency on claim 1. Although claim 14 recites “displaying, at a display device in communication with a processor, a graphical representation representing the total cost factor,” these additional elements amount to no more than a recitation to implement the abstract idea on a computer and thus do not make the judicial exception patent-eligible. See MPEP § 2106.05(f) (Citing Alice Corp. v. CLS Bank and stating that the additional element or combination of elements must do more than simply state the judicial exception while adding the words “apply it.”). Here, claim 14 does no more than recite “displaying” the result of the abstract idea (i.e., the “total cost factor”) without providing a practical application that integrates the judicial exception.
Claim 15 is a system claim that recites features which are substantively identical to those recited in claim 1 and is therefore rejected under 35 U.S.C. 101 for the reasons given above with respect to claim 1. Although claim 15 additionally recites “a processor in communication with a memory, the memory including instructions executable by the processor,” these additional elements amount to no more than a recitation to implement the abstract idea on a computer and thus does not make the judicial exception patent-eligible. See MPEP § 2106.05(f) (Citing Alice Corp. v. CLS Bank and stating that the additional element or combination of elements must do more than simply state the judicial exception while adding the words “apply it.”). Here, claim 15 does no more than recite storing instructions corresponding to the abstract ideas without providing a practical application that integrates the judicial exception.
Claims 16-17 and 19-20, which depend on claim 15 are rejected under 35 U.S.C. 101 because they merely recite features that further define previously recited elements without integrating the identified judicial exceptions into a practical application.
Claim 18 is a system claim that recites features which are substantively identical to those recited in claim 4 and is therefore rejected under 35 U.S.C. 101 for the reasons given above with respect to claim 4.
Claim 21 is rejected under 35 U.S.C. 101 because, while independent claim 21 falls within a statutory class of a method (i.e., claim 1 passes Step 1 of the § 101 analysis, see MPEP § 2106.03.II), under Step 2A of the § 101 analysis, claim 21 recites judicial exceptions without integrating the judicial exceptions into a practical application (i.e., fails Step 2A of the § 101 analysis). See MPEP § 2106.04. Specifically, claim 1 recites “accessing power demand data for a facility …” “determining … a new demand value based on the original demand value …,” and “identifying… the charge-discharge profile of the BESS that minimizes a total cost factor …” which are abstract ideas and/or mathematical concepts. These judicial exceptions are not integrated into a practical application because the claimed accessing, determine, evaluating, and identifying can be performed by observation (e.g., on a display) and/or mentally (or by using pen and paper). The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the elements-at-issue do not “improve[] the functioning of a computer or improve[] another technology or technical field” and thus they are still abstract ideas that do not integrate the judicial exceptions into a practical application. See MPEP § 2106.04(d)(1). Finally, claim 21 also fails under Step 2B of the § 101 analysis because claim 21 fails to recite any additional elements that “amount to significantly more than the judicial exception itself.” See MPEP §2106.05. Even assuming, arguendo, that the elements-at-issue are new ideas, these features are still abstract ideas, as discussed above, and thus do not amount to “significantly more.” See MPEP § 2106.05 (“a claim for a new abstract idea is still an abstract idea” quoting Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151, 120 USPQ2d 1473, 1483 (Fed. Cir. 2016), emphasis original).
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 4-6, 8-13, 15, and 18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. Patent Application Publication No. 2020/0073342 to Lee et al. (“Lee”).
Regarding claim 1, Lee discloses:
A method (Lee discloses a method of managing energy for a building (“method”). See Lee at par. [0018].), comprising:
accessing power demand data for a facility, the power demand data representing an original demand value for each power demand interval of a plurality of power demand intervals (Lee discloses that a “High level optimizer 632 may receive load and rate predictions [(“accessing power demand data for a facility”)] from load/rate predictor 622….” See, e.g., Lee at par. [0178] and Figs. 6A and 6B. Lee also discloses that the “Load/rate predictor 622 can be configured to predict the thermal energy loads ((Î)k) of the building or campus [(“power demand data representing an original demand value”)] for each time step k (e.g., k=1 . . . n) of an optimization period [(“for each power demand interval of a plurality of power demand intervals”)].” See, e.g., Lee at par. [0143] see also par. [0258] (Lt corresponds to “original demand value”) and Fig. 10.);
determining, for a set of power demand intervals of the plurality of power demand intervals and for each of a plurality of candidate charge-discharge profiles of a Battery Energy Storage System (BESS), a new demand value based on the original demand value, the new demand value incorporating an expected discharge amount of the BESS and an expected charge amount of the BESS under the respective candidate charge-discharge profile (Lee discloses that “the optimization performed by ESS optimizer 1216 can identify charging and/or discharging amounts for ESS 1026 for multiple time steps over the period (e.g., fifteen minute time steps for a 24 hour period)” (“for a set of power demand intervals of the plurality of power demand intervals”). Lee at par. [0298]. Lee also discloses that the “amount of electricity purchased [(“new demand value”)] may be equal to the difference between the electric load of the facility eLoadi (i.e., the total amount of electricity required) [(“the original demand value”)] at time step i and the amount of power discharged from the battery asset Pbat i at time step i. Lee at par. [0186]; see also par. [0259](pt corresponds to “new demand value”) and Fig. 10. Positive values of “power discharged” indicates that the “resource is discharged from storage” and negative values indicates that the “resource is charged or stored.” Lee at par. [0183]. Thus, Lee discloses the claimed “determining … a new demand value based on the original demand value, the new demand value incorporating an expected discharge amount of the BESS and an expected charge amount of the BESS.” Lee also discloses that the “ESS optimizer 1216 can perform the optimization with discrete decisions in time intervals, multi-object optimization, linear programming (LP), dynamic programming (DP), Markov decision processes MDP, particle swamp optimization (PSO), genetic algorithm (GA), and/or grid search.” Lee at par. [0302]. At least the linear programming method of optimization discloses the claimed “plurality of candidate charge-discharge profiles” because Linear programming includes establishment of a feasible region that includes a set of values (“plurality of candidate charge-discharge profiles”) that satisfy the constraints of an optimization problem. The values in the feasible region are evaluated (e.g., using a Simplex algorithm) until an optimum value is reached. For additional information regarding linear programming, please see the Appendix with attached printouts on linear programming and feasible region from Wikipedia:
https://en.wikipedia.org/w/index.php?title=Linear_programming&oldid=1368173591, and
https://en.wikipedia.org/w/index.php?title=Feasible_region&oldid=1295712280.
Accordingly, Lee discloses the claimed “determining.”);
evaluating, for each of the plurality of candidate charge-discharge profiles, a total cost factor over the plurality of power demand intervals based on comparison between the new demand value and the original demand value for the set of power demand intervals (Lee discloses that the high level optimizer 632 includes a “[c]ost function module 902 [that] can generate a cost function or objective function [J(x)] which represents the total operating cost [(“evaluating … a total cost factor”)] of a system over a time horizon (e.g., one month, one year, one day, etc.)” (“over the plurality of power demand intervals based on comparison between the new demand value and the original demand value for the set of power demand intervals”). Lee at par. [0180]. As discussed above, Lee discloses that the “ESS optimizer 1216 can perform the optimization with discrete decisions in time intervals, multi-object optimization, linear programming (LP), dynamic programming (DP), Markov decision processes MDP, particle swamp optimization (PSO), genetic algorithm (GA), and/or grid search.” Lee at par. [0302]. Thus, Lee discloses that the ESS optimizer 1216 will evaluate the total cost function for each candidate charge-discharge profile located in the feasible region.),
the total cost factor incorporating an electricity consumption cost factor in terms of the new demand value, a BESS usage cost factor that quantifies expected degradation of the BESS over time, and a demand cost factor that quantifies an expected utility cost associated with the new demand value (Lee at pars. [0082] and [0086] (“degradation of the BESS”), pars. [0199] and [0202]-0204] (“demand cost factor”), and [0259] (“new demand value”); and
identifying, from the plurality of candidate charge-discharge profiles, the charge-discharge profile that results in minimization of the total cost factor over the plurality of power demand intervals (Lee discloses a “High level optimizer 632 [that] can be configured to optimize the utilization of a battery asset [(“charge-discharge profile”)], such as battery 108, battery 306, … [and that the] “High level optimizer 632 can allocate the battery asset at each time step (e.g., each hour) over a given horizon such that energy and demand costs are minimized …”(“minimization of the total cost factor”). Lee also discloses that the “decision variables may be sent from the ESS optimizer 1216 [of the high level optimizer 632] to charging/discharging scheduler 1218,” which stores the charging/discharging settings for use by ESS controller for controlling the energy storage system. Lee at par. [0303] and Fig. 12. Thus, based on the linear programming, ESS optimizer 1216 of the high lever optimizer 632 will identify the candidate charge-discharge profile having the optimum total cost factor.),
the charge-discharge profile including a usage scheme that defines a charge-discharge policy of the BESS and an event-based demand response policy of the BESS (Lee discloses usage schemes such as peak load contribution and load shifting. Lee at pars.[0076], [0221]-[0231]. Lee also discloses an even-based demand response (IBDR) program. Lee at pars. [0148]-[0149].).
Regarding claim 4, which depends on claim 1,
determining for the charge-discharge profile of the BESS, the new demand value for each power demand interval of the plurality of power demand intervals based on the original demand value for the power demand interval, the expected discharge amount of the BESS, and the expected charge amount of the BESS (Lee discloses that the “amount of electricity purchased [(“new demand value”)] may be equal to the difference between the electric load of the facility eLoadi (i.e., the total amount of electricity required) [(“the original demand value”)] at time step i [(“for each power demand interval of the plurality of power demand intervals”)] and the amount of power discharged from the battery asset Pbat i at time step i” (“the charge-discharge profile of the BESS”). See, e.g., Lee at par. [0186]. Positive values of “power discharged” indicates that the “resource is discharged from storage” and negative values indicates that the “resource is charged or stored” (see Lee at par. [0183]), which reads on “the new demand value incorporating an expected discharge amount of the BESS and an expected charge amount of the BESS under the charge- discharge profile.”); and
evaluating the total cost factor over the plurality of power demand intervals under the charge-discharge profile of the BESS. (Lee discloses that the high level optimizer 632 includes a “[c]ost function module 902 [that] can generate a cost function or objective function [J(x)] which represents the total operating cost [(“total cost factor”)] of a system over a time horizon (e.g., one month, one year, one day, etc.)” (“over the plurality of power demand intervals under the charge-discharge profile of the BESS”). See, e.g., Lee at par. [0180]. Thus, Lee discloses the claimed evaluation.).
Regarding claim 5, which depends on claim 4, Lee discloses:
the new demand value is determined by subtracting the expected discharge amount of the BESS under the charge-discharge profile from the original demand value for the power demand interval (Lee discloses that the “amount of electricity purchased may be equal to the difference between the electric load of the facility eLoadi (i.e., the total amount of electricity required) at time step i and the amount of power discharged from the battery asset Pbat i at time step i.” See, e.g., Lee at par. [0186]. Positive values of “power discharged” indicates that the “resource is discharged from storage” and negative values indicates that the “resource is charged or stored.” See, e.g., Lee at par. [0183]. Thus, Lee discloses “subtracting the expected discharge amount of the BESS under the charge-discharge profile from the original demand value for the power demand interval.”).
Regarding claim 6, which depends on claim 4, Lee discloses:
the new demand value is determined by adding the expected charge amount of the BESS under the charge-discharge profile to the original demand value for the power demand interval (Lee discloses that the “amount of electricity purchased may be equal to the difference between the electric load of the facility eLoadi (i.e., the total amount of electricity required) at time step i and the amount of power discharged from the battery asset Pbat i at time step i.” See, e.g., Lee at par. [0186]. Positive values of “power discharged” indicates that the “resource is discharged from storage” and negative values indicates that the “resource is charged or stored.” See, e.g., Lee at par. [0183]. Thus, Lee discloses “adding the expected charge amount of the BESS under the charge-discharge profile to the original demand value for the power demand interval.”).
Regarding claim 8, which depends on claim 1, Lee discloses:
the charge-discharge profile of the BESS including:
a set of properties of the BESS (Lee discloses that the high level optimizer 632 can include a power constraints module 904 that takes into consideration the battery capacity (“a set of properties of the BESS”) when calculating the objective function J(x). See, e.g., Lee at par. [0188].);
a usage scheme of the BESS that defines a charge-discharge policy of the BESS ( Lee discloses usage schemes such as load shifting and peak load contribution. See, e.g., Lee at pars. [0076] and [0221]-[0222]. Thus, Lee discloses the claimed usage scheme.); and
an event-based demand response policy of the BESS (Lee discloses incentive-based demand response (IBDR) programs (“event-based demand response policy of the BESS”). See, e.g., Lee at pars. [0148]-[0149].).
Regarding claim 9, which depends on claim 8, Lee discloses:
the set of properties of the BESS including one or more of: a type of the BESS; a capacity of the BESS; and a power rating of the BESS (Lee discloses that the high level optimizer 632 can include a power constraints module 904 that takes into consideration the battery capacity (“capacity of the BESS”) when calculating the objective function J(x). See, e.g., Lee at pars. [0188]-[0193].).
Regarding claim 10, which depends on claim 8, Lee discloses:
the usage scheme being one of: a peak-clipping policy where the BESS charges during intervals when the original demand value is below a charge threshold value and where the BESS discharges during intervals when the original demand value is above a discharge threshold value (Lee discloses usage schemes such as peak load contribution. See, e.g., Lee at pars. [0221]-[0231].);
a load-shifting policy where the BESS charges during off-peak usage hours and discharges during on-peak usage hours (Lee discloses usage schemes such as load shifting. See, e.g., Lee at pars. [0076] and [0222].).
Regarding claim 11, which depends on claim 1, Lee discloses:
applying the charge-discharge profile to a control system that operates the BESS according to the charge-discharge profile (Lee discloses an “[e]nergy storage controller 506 [that] can be configured to control the distribution, production, storage, and usage of resources in energy storage system 500,” including storage subplants 530 with energy storage device 533. See, e.g., Lee at pars. [0133]-[0120] and Fig. 5A; see also pars. [302]-[303] and Fig. 12. Thus, Lee discloses the claimed applying.).
Regarding claim 12, which depends on claim 1, Lee discloses:
evaluating a total cost savings factor that quantifies a total difference between costs associated with the original demand value over the plurality of power demand intervals and the total cost factor under the charge-discharge profile of the BESS over the plurality of power demand intervals (Lee discloses a planning system 700 that uses demand response optimizer 630, which can operate in a similar manner as described with reference to FIGS. 6A, “to simulate the operation of a central plant over a predetermined time period (e.g., a day, a month, a week, a year, etc.) [(“over the plurality of power demand intervals”)] for planning, budgeting, and/or design considerations … [and to] use building loads and utility rates [(“costs associated with the original demand value”)] to determine an optimal resource allocation to minimize cost [(“total cost savings factor”)] over a simulation period.” See, e.g., Lee at par. [0162] and Fig. 7.
Lee discloses that demand response optimizer 630 includes the high level optimizer 632 which in-turn includes a “[c]ost function module 902 [that] can generate a cost function or objective function [J(x)] which represents the total operating cost [(“total cost factor”)] of a system over a time horizon (e.g., one month, one year, one day, etc.).” Lee also discloses that the function J(x) includes “the total amount of each resource discharged from storage (e.g., storage subplants 530 [which includes a battery, see par. [0185]]) over the optimization horizon” (“under the charge-discharge profile of the BESS over the plurality of power demand intervals”). See, e.g., Lee at pars. [0183]-[0185]. Thus, Lee discloses the claimed evaluating.).
Regarding claim 13, which depends on claim 12, Lee discloses:
determining a timeframe in which the total cost savings factor is expected to exceed a total capital cost associated with the BESS under the charge-discharge profile of the BESS over the plurality of power demand intervals (Lee discloses the planning tool 702 can “determine the benefits of investing in a battery asset and the financial metrics associated with the investment.” See, e.g., Lee at par. [0163] and Fig. 7. Lee also discloses that “planning tool 702 [can] simulate the operation of a central plant over a predetermined time period (e.g., a day, a month, a week, a year, etc.) for planning, budgeting, and/or design considerations.” See, e.g., Lee at par. [0162]. Thus, Lee discloses the claimed determining of a timeframe.).
Regarding claim 15, Lee discloses:
A system (Lee discloses “building energy system includes an energy storage system (ESS) configured to store energy received from an energy source and provide the stored energy to one or more pieces of building equipment.” See Lee at Abstract.), comprising:
a processor in communication with a memory, the memory including instructions executable by the processor to (Lee discloses an energy storage controller 506 with a processor 608 and a memory 610. See Lee at pars. [0139]-[0140] and Fig. 6A.):
access power demand data for a facility, the power demand data representing an original demand value for each power demand interval of a plurality of power demand intervals (Please see analysis in claim 1.); and
determine, for a set of power demand intervals of the plurality of power demand intervals and for each of a plurality of candidate charge- discharge profiles of a Battery Energy Storage System (BESS), a new demand value based on the original demand value, the new demand value incorporating an expected discharge amount of the BESS and an expected charge amount of the BESS under the respective candidate charge-discharge profile (Please see analysis in claim 1.);
evaluate, for each of the plurality of candidate charge-discharge profiles, a total cost factor over the plurality of power demand intervals based on comparison between the new demand value and the original demand value for the set of power demand intervals, the total cost factor incorporating an electricity consumption cost factor in terms of the new demand value, a BESS usage cost factor that quantifies expected degradation of the BESS over time, and a demand cost factor that quantifies an expected utility cost associated with the new demand value (Please see analysis in claim 1.); and
identify, from the plurality of candidate charge-discharge profiles, the charge-discharge profile that results in minimization of the total cost factor over the plurality of power demand intervals, the charge-discharge profile including a usage scheme that defines a charge-discharge policy of the BESS and an event-based demand response policy of the BESS (Please see analysis in claim 1.).
Regarding claim 18, which depends on claim 15, Lee discloses:
the memory including instructions further executable by the processor to: determine for the charge-discharge profile of the BESS, the new demand value for each power demand interval of the plurality of power demand intervals based on the original demand value for the power demand interval, the expected discharge amount of the BESS, and the expected charge amount of the BESS: and evaluate the total cost factor over the plurality of power demand intervals under the charge-discharge profile of the BESS (Please see analysis in claim 4.).
Regarding claim 21:
A method (Lee discloses a method of managing energy for a building (“method”). See Lee at par. [0018].), comprising:
accessing power demand data for a facility, the power demand data representing an original demand value for each power demand interval of a plurality of power demand intervals (Lee discloses that a “High level optimizer 632 may receive load and rate predictions [(“accessing power demand data for a facility”)] from load/rate predictor 622….” See, e.g., Lee at par. [0178] and Figs. 6A and 6B. Lee also discloses that the “Load/rate predictor 622 can be configured to predict the thermal energy loads ((Î)k) of the building or campus [(“power demand data representing an original demand value”)] for each time step k (e.g., k=1 . . . n) of an optimization period [(“for each power demand interval of a plurality of power demand intervals”)].” See, e.g., Lee at par. [0143] see also par. [0258] (Lt corresponds to “original demand value”) and Fig. 10.);
determining, for a set of power demand intervals of the plurality of power demand intervals, a new demand value based on the original demand value and on expected charge and discharge amounts of a Battery Energy Storage System (BESS) under a charge-discharge profile of the BESS (Lee discloses that “the optimization performed by ESS optimizer 1216 can identify charging and/or discharging amounts for ESS 1026 for multiple time steps over the period (e.g., fifteen minute time steps for a 24 hour period)” (“for a set of power demand intervals of the plurality of power demand intervals”). Lee at par. [0298]. Lee also discloses that the “amount of electricity purchased [(“new demand value”)] may be equal to the difference between the electric load of the facility eLoadi (i.e., the total amount of electricity required) [(“the original demand value”)] at time step i and the amount of power discharged from the battery asset Pbat i at time step i. Lee at par. [0186]; see also par. [0259](pt corresponds to “new demand value”) and Fig. 10. Positive values of “power discharged” indicates that the “resource is discharged from storage” and negative values indicates that the “resource is charged or stored.” Lee at par. [0183]. Thus, Lee discloses the claimed “determining … a new demand value based on the original demand value and on charge and discharge amounts of a Battery Energy Storage System (BESS) under a charge-discharge profile of the BESS.”); and
identifying, based on comparison between the new demand value and the original demand value for the set of power demand intervals, the charge-discharge profile of the BESS that minimizes a total cost factor over the plurality of power demand intervals (Lee discloses that the “amount of electricity purchased [(“new demand value”)] may be equal to the difference between the electric load of the facility eLoadi (i.e., the total amount of electricity required) [(“the original demand value”)] at time step i and the amount of power discharged from the battery asset Pbat i at time step i. Lee at par. [0186]. Thus, Lee discloses the claimed “comparison between the new demand value and the original demand value for the set of power demand intervals.” Lee aldo discloses a “High level optimizer 632 [that] can be configured to optimize the utilization of a battery asset [(“charge-discharge profile”)], such as battery 108, battery 306, … [and that the] High level optimizer 632 can allocate the battery asset at each time step (e.g., each hour) over a given horizon such that energy and demand costs are minimized …”(“minimization of the total cost factor”). Lee further discloses that the “decision variables may be sent from the ESS optimizer 1216 [of the high level optimizer 632] to charging/discharging scheduler 1218,” which stores the charging/discharging settings for use by ESS controller for controlling the energy storage system. Lee at par. [0303] and Fig. 12. Thus, based on the linear programming, ESS optimizer 1216 of the high lever optimizer 632 will identify the charge-discharge profile having the optimum total cost factor (“identifying … the charge-discharge profile of the BESS that minimizes a total cost factor over the plurality of power demand intervals.”).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Lee.
Regarding claim 14, which depends on claim 1, Lee renders obvious:
displaying, at a display device in communication with a processor, a graphical representation representing the total cost factor (Lee discloses that energy storage controller 506 includes a GUI engine 614 (“processor”) for displaying “key performance indicators (KPI)” to users of a GUI (“display device”), which would be in communication with GUI engine 614. See, e.g., Lee at par. [0153] and Fig. 6A. Lee also disclose that cost function J(x) represents the “total operating cost of a system.” See Lee at pars. [0180]-[0181]. Although Lee does not explicitly disclose that the cost function J(x) is one of the KPIs, because the cost function J(x) is discussed extensively in Lee’s disclosure (see at least pars.[0180]-[0237]), it would have been obvious and one skilled in the art would have been motivated to display J(x) in order to “allow users to assess performance across one or more energy storage systems from one screen.” See, e.g., Lee at par. [0153].
Claims 2 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of U.S. Patent Application Publication No. 2023/0236560 to Lee et al. (“Lee2”).
Regarding claim 2, which depends on clam 1,Lee in view of Lee2 renders obvious:
the total cost factor incorporating:
an electricity consumption cost factor in terms of the new demand value under the charge-discharge profile of the BESS (Lee discloses that the high-level optimizer 632 includes a cost function module 902 to “generate a cost function or objective function which represents the total operating cost of a system over a time horizon (e.g., one month, one year, one day, etc.).” See Lee at par. [0180] and Fig. 9. The cost function module 902 includes a cost function J(x) whose first term “represents the total cost of all resources purchased over the optimization horizon …[such as] electricity [(“electricity consumption cost factor”)] ….” See, e.g., Lee at par. [0181].);
a BESS usage cost factor of using the BESS under the charge-discharge profile of the BESS that quantifies expected degradation of the BESS over time (Lee discloses that the costs of participation in a frequency regulating incentive “may include, for example, a monetized cost of battery degradation [(“BESS usage cost factor …that quantifies expected degradation of the BESS over time”)] as well as the energy and demand charges that will be incurred.” See, e.g., Lee at pars. [0078] and [0081]. Lee also discloses that the cost function J(x) of high level optimizer 632 can include incentive programs. See, e.g., Lee at pars. [0180]-[0181] and Fig. 9.
a demand cost factor that quantifies an expected utility cost associated with the new demand value under the charge-discharge profile of the BESS (Lee discloses that the high-level optimizer 632 includes a cost function J(x) whose “fourth term represents the demand charge [(“demand cost factor”)] associated with the maximum amount of electricity purchased from the electric utility. See, e.g., Lee at pars. [0077] and [0186]. Lee also discloses that the “first term [of J(x)] represents the cost savings resulting from the use of battery power [“the charge-discharge profile of the BESS”] to satisfy the electric demand of the facility relative to the cost which would have been incurred if the electricity were purchased from the electric utility.” See, e.g., Lee at par. [0186].); and
a demand response factor that quantifies a benefit associated with event- based demand response enrollment under the charge-discharge profile of the BESS (Lee discloses that “high level optimizer 632 … include[s] an incentive program module 912. Incentive program module 912 may modify the optimization problem to account for revenue from participating in an incentive-based demand response (IBDR) program” (“demand response factor”). See, e.g., Lee at par. [0216].),
an environmental cost factor under the charge-discharge profile of the BESS that quantifies an environmental impact of using the BESS (Lee does not explicitly disclose that the total cost factor incorporates “an environmental cost factor under the charge-discharge profile of the BESS that quantifies an environmental impact of using the BESS.” However, in the same field of endeavor, energy optimization, and thus analogous art, Lee2 discloses that the objective function, which “accounts for the cost of operating the facility 600,” can include “internalized costs of carbon emissions or other pollution associated with use of grid energy.” See, e.g., Lee2 at par. [0103]. It would have been obvious and one skilled in the art would have been motivated to include the “internalized costs of carbon emissions or other pollution associated with use of grid energy” into the objective function J(x) of Lee in order to “find the net energy trajectory that minimizes the objective function over the time period” and thus the cost of operating the facility. See, e.g., Lee2 at par. [0103]. Thus, Lee and modified by Lee2 renders obvious “an environmental cost factor under the charge-discharge profile of the BESS that quantifies an environmental impact of using the BESS.” Because Lee2 teaches to use an objective function that takes into account “carbon emissions or other pollution,” there would have been a reasonable chance of success. See MPEP § 2143.I.G.
Regarding claim 16, which depends on claim 15, Lee in view of Lee2 renders obvious:
the total cost factor incorporating: an environmental cost factor under the charge-discharge profile of the BESS that quantifies an environmental impact of using the BESS; an electricity consumption cost factor in terms of the new demand value under the charge-discharge profile of the BESS; a BESS usage cost factor of using the BESS under the charge-discharge profile of the BESS that quantifies expected degradation of the BESS over time; a demand cost factor that quantifies an expected utility cost associated with the new demand value under the charge-discharge profile of the BESS; and a demand response factor that quantifies a benefit associated with event- based demand response enrollment under the charge-discharge profile of the BESS (The features in claim 16 are the same as those recited in claim 2 and is therefore rendered obvious by Lee in view of Lee2 for the reasons given above with respect to claim 2.).
Claims 3 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of M. Sandelic, A. Sangwongwanich and F. Blaabjerg, "Incremental Degradation Estimation Method for Online Assessment of Battery Operation Cost," in IEEE Transactions on Power Electronics, vol. 37, no. 10, pp. 11497-11501, Oct. 2022, doi: 10.1109/TPEL.2022.3172499 (“Sandelic”).
Regarding claim 3, which depends on claim 2, Lee in view of Sandelic renders obvious:
the BESS usage cost factor incorporating continuous compounding over the plurality of power demand intervals (Lee discloses the use of “a battery life model to quantify and monetize battery degradation as a function of the power setpoints provided to power inverter 106.” See, e.g., Lee at par. [0082]. However, Lee does not explicitly disclose a “BESS usage cost factor “incorporating continuous compounding.”
“Continuous compounding” is not explicitly defined in the specification. However, the present specification discloses that “continuous compounding” relates modeling degradation of the battery over time. Applicant’s Specification at par. [0057]. Sandelic proposes a battery degradation cost estimation method that “determines the degradation in the incremental manner for any two successive points during the real-time operation (e.g., 5 min intervals).” See Sandelic at p. 2, Sec. III.A (col. 2). Sandelic discloses that its “proposed method overcomes the limitations of the conventional degradation methods for application in the real-time operation [and that] [i]t enables the evaluation of the true cost of battery operation, i.e., degradation cost for any chosen time interval.” See Sandelic at p. 4, Sec. IV (col. 2). Because Sandelic addresses the same problem as the claimed invention, i.e., modeling the battery degradation cost over time, Sandelic is analogous art. See MPEP § 2141.01(a). Accordingly, it would have been obvious and one skilled in the art would have been motivated to incorporate the “incremental degradation estimation method” of Sandelic into the system of Lee in order to “assess a true cost of the battery operation at all times.” See Sandelic at p. 4, Sec. IV (col. 2). Thus, Lee in view of Sandelic renders obvious a “BESS usage cost factor incorporating continuous compounding over the plurality of power demand intervals”). Because Sandelic teaches how to implement the “incremental degradation estimation method” for battery usage, there would have been a reasonable chance of success. See MPEP § 2143.I.G.
Regarding claim 17, which depends on claim 16, Lee in view of Sandelic renders obvious:
the BESS usage cost factor incorporating continuous compounding over the plurality of power demand intervals (The feature in claim 17 is the same as that recited in claim 3 and is therefore rendered obvious by Lee in view of Sandelic for the reasons given above with respect to claim 3.).
Claims 19 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Lee in view of U.S. Patent Application Publication No. 2022/0416548 to Killian et al. (“Killian”), and further in view of U.S. Patent Application Publication No. 2022/0006295 to Dimitri Torregrossa (“Torregrossa”).
Regarding claim 19, which depends on claim 15, Lee in view of Killian renders obvious:
the charge-discharge profile of the BESS including: a set of properties of the BESS including a type of the BESS, a capacity of the BESS, and a power rating of the BESS; a usage scheme of the BESS that defines a charge-discharge policy of the BESS; and an event-based demand response policy of the BESS (Lee discloses the use of “a battery life model to quantify and monetize battery degradation as a function of the power setpoints provided to power inverter 106.” See, e.g., Lee at par. [0082]. However, Lee does not explicitly disclose that a property of the BESS includes “a type of the BESS.” In a same field of endeavor, battery-based energy storage systems, Killian discloses that “[d]ifferent types of batteries age differently” and that “batteries of the same type will experience a similar aging behavior captured by the aging model.” See, e.g., Killian at pars. [0056]-[0057]. Killian also discloses that the “degradations of the batteries of the BESS can be determined … using the aging model.” See, e.g., Killian at par. [0059]. Because battery degradation can be dependent on the type of battery, it would have been obvious and one skilled in the art would have been motivated to include the type of battery as a property for the charge-discharge profile in order to “facilitat[e] accurate prediction of loss of values for multiple types of batteries.” See, e.g., Killian at par. [0057]. Thus, Lee as modified by the teachings of Killian renders obvious a “charge-discharge profile of the BESS including[] a set of properties of the BESS [that includes] a type of the BESS.” Because Killian teaches to look at the type of battery when determining degradation, there would have been a reasonable chance of success. See MPEP § 2143.I.G.
Lee in view of Killian does not explicitly disclose that the charge-discharge profile of a BESS can include “a power rating of the BESS.” However, in a same filed of endeavor, battery charge/discharge management (and thus analogous art), Torregrossa discloses C-rate (“power rating od the BESS”) “to indicate the maximum current that a battery can safely deliver on a load.” Torregrossa at par. [0009]. It would have been obvious and one skilled int e art would have been motivated to include the C-rate of a battery in order to reduce the ageing (i.e., degradation) of the battery in comparison to battery management that does not use such a strategy. Torregrossa at par. [0009]. Because Torregrossa teaches to look at the C-rate when determining ageing, there would have been a reasonable chance of success. See MPEP § 2143.I.G.
The remaining features recited in claims 19 are the same as those recited in claims 8 and 9 and are therefore rendered obvious by Lee in view of Killian for the reasons given above with respect to claims 8 and 9.).
Regarding claim 20, which depends on claim 19, Lee in view of Killian and Torregrossa renders obvious:
the usage scheme being one of: a peak-clipping policy where the BESS charges during intervals when the original demand value is below a charge threshold value and where the BESS discharges during intervals when the original demand value is above a discharge threshold value; and a load-shifting policy where the BESS charges during off-peak usage hours and discharges during on-peak usage hours (Please see analysis in claim 10.).
Response to Arguments
The objection to the specification has been withdrawn.
The 112 Rejections of claims 4-6, 9 and 18-19 have been withdrawn. However, new 112 rejections of claims 2 and 12 have been added in this Office Action.
With respect to the 101 Rejections, Applicant's arguments have been fully considered but they are not persuasive. Applicant argues the following:
The Office Action asserts that claims 1-20 recite abstract ideas and/or mathematical concepts and do not integrate any judicial exception into a practical application. For independent claim 1, the Office Action particularly characterizes "accessing power demand data" and "optimizing" as abstract and alleged mental processes. Independent claim 15 is rejected on the same rationale. The Applicant respectfully traverses these rejections.
Especially as presently amended, independent claims 1 and 15 cannot be characterized as drawn to generalized cost analysis. Rather, the claims are amended to recite a specific technological control methodology for operation of a Battery Energy Storage System in the context of facility demand management. More particularly, the amended claims now recite determining, for a set of power demand intervals and for each of a plurality of candidate charge-discharge profiles, a new demand value based on the original demand value and incorporating expected BESS discharge and charge amounts; evaluating, for each candidate profile, a total cost factor over the plurality of intervals based on comparison between the new demand value and the original demand value for the set of intervals; and identifying, from the candidate profiles, the charge- discharge profile that minimizes the total cost factor. The amended claims further recite that the selected charge-discharge profile includes a usage scheme defining a charge- discharge policy of the BESS and an event-based demand response policy of the BESS.
These limitations tie the claims to a concrete, interval-based BESS dispatch- control technique. The claimed process is directed to transforming facility demand values into new demand values using expected operation of a particular physical system, namely the BESS, and then selecting a BESS control profile based on the results of that interval-based analysis. The claims are therefore directed to a specific asserted improvement in BESS dispatch control and demand management, not to a disembodied mathematical principle. The recited steps cannot fairly be reduced to mere observation or mental analysis, because the claims recite coordinated evaluation of multiple candidate BESS charge-discharge profiles over multiple power demand intervals to determine a control profile for a physical battery energy storage system.
The Office Action also rejected dependent claims as merely further defining previously recited elements. However, the amended independent claims are clarified to provide a practical-application framework for BESS control methodology. Claims depending therefrom are now directed to further technical details of that same BESS control methodology. Thus, when considered as a whole, amended claims 1 and 15 integrate any alleged judicial exception into a practical application.
Response at pp. 12-13 (emphasis added).
Summarizing, the Applicant argues that “the claims are amended to recite a specific technological control methodology for operation of a Battery Energy Storage System in the context of facility demand management …[, that] [t]hese limitations tie the claims to a concrete, interval-based BESS dispatch- control technique …[, and that that] claims are therefore directed to a specific asserted improvement in BESS dispatch control and demand management, not to a disembodied mathematical principle.” Finally, the Applicant argues that the “recited steps cannot fairly be reduced to mere observation or mental analysis, because the claims recite coordinated evaluation of multiple candidate BESS charge-discharge profiles over multiple power demand intervals to determine a control profile for a physical battery energy storage system.” The examiner respectfully disagrees and maintains the 101 rejections.
The claims generally recite evaluating data related to demand management and then identifying a charge-discharge profiles for the BESS that has the minimum cost factor, which is an abstract idea. The claimed analysis is never integrated into a practical application. For example, the claims do not positively recite controlling the charging/discharging of a BESS using the identified charge-discharge profile. Even assuming that the claims “recite a specific technological control methodology” and “tie the claims to a concrete, interval-based BESS dispatch- control technique,” the claims still do not reduce the abstract idea into a practical application. At best, Applicant’s amendments more clearly define the abstract idea, but they do not reduce it to a practical application.
Applicant also argues that the claims are “directed to a specific asserted improvement in BESS dispatch control and demand management, not to a disembodied mathematical principle.” However, other than a conclusory statement, the Applicant provides no evidence that connects the alleged “improvement in BESS dispatch control and demand management” to improvements in the functioning of a computer or another technology or technical field. While “dispatch control” and “demand management” may use certain technologies in performing the claimed steps, the claimed steps do not improve the functioning of those technologies. At best, the claims may recite an improvement in analyzing demand data, but this alleged improvement is still an abstract idea.
Finally, the Applicant argues that the elements-at-issue are not “mere observation or mental analysis, because the claims recite coordinated evaluation of multiple candidate BESS charge-discharge profiles over multiple power demand intervals to determine a control profile for a physical battery energy storage system.” Again, the examiner respectfully disagrees. The claims do not recite a time limit (e.g., too fast for humans to perform) or a sequence of operations (e.g., steps that are performed simultaneously) that would potentially take the claimed analysis out of the realm of human capability. Accordingly, for the reasons given above and in the 101 rejection, the elements-at-issue are abstract ideas because they are mathematical concepts and/or can be performed mentally (e.g., with the aid of pen and paper). Because the abstract ideas are not integrated into a practical application and/or have not been shown to improve the functioning of a computer or another technology or technical field, the 101 rejection of claims 1-20 is maintained. Assuming support in the specification, Applicant can overcome the 101 rejection by positively reciting that the identified charge-discharge profile is used to control the charging/discharging of a BESS.
With respect to the 102/103 Rejections, Applicant has amended the independent claims and has argued that Lee does not disclose the newly added features. Specifically, Applicant argues the following:
“Lee does not disclose this candidate-profile evaluation framework. Lee determines a charging/discharging schedule based on predicted load and an optimization objective.”
“Lee does not disclose determining new demand values for each of a plurality of candidate charge-discharge profiles, evaluating each candidate profile, and then identifying a selected profile from those candidate profiles as now claimed. The Office Action's mapping of the original claims to Lee's optimization framework does not address these newly added limitations.”
“Lee likewise does not disclose the amended requirement that the identified charge-discharge profile includes a usage scheme and an event-based demand response policy in the manner now positively recited in claims 1 and 15. While Lee discusses load shifting and incentive-based demand-response concepts in different contexts, Lee's disclosure remains focused on schedule generation based on predicted load rather than on selection among multiple candidate charge-discharge profiles having the claimed profile content.”
Applicant’s Response at p. 15.
Summarizing, all of Applicant’s arguments rely on Lee allegedly not disclosing the evaluation of candidate charge-discharge profiles. However, as discussed above (e.g., see 102 rejection of claim 1), Lee discloses that the ESS optimizer can use linear programming which includes the formation of a feasible region with values that satisfy an optimization problem (“candidate charge-discharge profiles”). Accordingly, Applicant arguments have been fully considered but are not persuasive (please see analysis in claim 1).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
U.S. Patent Application Publication No. 2013/0190939 to Carl J.S. Lenox discloses a demand management system in which the power rating of the energy storage device is considered.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/B.K./Examiner, Art Unit 2116
/KENNETH M LO/Supervisory Patent Examiner, Art Unit 2116
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