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 .
Claims 1-13 are pending.
Claims 1-13 are rejected below.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claims 2-7 rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claim 2 states that the data variator can be alternatively be a parameter variator. This does not further limit the claim since the data variotr can be replaced with something else. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
Claims 10-12 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 what “ground truth data” is defined as.
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.
Claim(s) 1-13 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Sheble (U.S. PG Pub. 2016/0077507).
Sheble teaches the following:
1. A system for optimizing an energy management of a site, the system comprising: an energy optimizer adapted to determine one or more optimization goals based on an optimization algorithm[0363 - FIG. 58 lists preferred application implementation as a computer program on a single computer. The process is to get the input data, build the demand forecast as uncertainty scenario specified by the user, adjust the resource models for the initial Tree Convolution estimate of the EDDC, adjust the demand models, and perform the valuations for the availability of resources on a single path of the probability tree. A single path of the probability tree is defined by the status of each resource. As an example unit 1, unit 2 available, unit 3 available is the cheapest operating simulation as the least expensive resources are used this is shown in the tree graph of FIG. 38.]; a data variator adapted to provide at least one first energy data input and at least one second energy data input, different to the first energy data input, to the energy optimizer (fig. 58 shows the inputs); wherein the energy optimizer is adapted to receive the first and second energy data inputs from the data variator, and to determine, based the first and second energy data inputs, respective at least one first and second energy data outputs via the optimization algorithm, wherein a data sensitivity of the energy optimizer can be determined with respect to the first and second energy data inputs and the first and second energy data outputs [ 0364 The valuations are performed for these combinations and the sensitivities of the next segment impact is found. ].
2. The system according to claim 1, wherein the system comprises a parameter variator additionally or alternatively to the data variator, wherein the parameter variator is adapted to provide at least one first energy parameter input and at least one second energy parameter input, different to the first energy parameter input and, wherein the energy optimizer is adapted to: receive the first and second parameter inputs from the parameter variator, and to determine, based the first and second energy parameter inputs, respective at least one first and second energy parameter outputs via the optimization algorithm, wherein a parameter sensitivity of the energy optimizer can be determined with respect to the first and second energy parameter inputs and the first and second energy parameter outputs (the data and parameters variator seem to be doing the same things so the inputs from fig. 58 can be accomplished by either or both).
3. The system according to claim 2, wherein system comprises the data variator and the parameter variator, and wherein a combined data and parameter sensitivity of the energy optimizer can be determined with respect to combination of the first and second energy data inputs and the first and second energy data outputs, as well as the first and second energy parameter inputs and the first and second energy parameter outputs[0364].
4. The system according to claim 1, wherein the at least one first energy data input is based on historical energy data, and wherein the data variator is adapted to vary the historical energy data to create and provide the second energy data input[0368, also previous energy rates are used and can be interpreted as this].
5. The system according to claim 4, wherein the historical energy data is based on energy data of at least one energy consumer and/or at least one energy producer(fig. 58).
6. The system according to claim 2, wherein the first energy parameter input is based on an energy parameter, and wherein the parameter variator is adapted to vary the energy parameter to create and provide, based on the varied energy parameter, the second energy parameter input (fig. 58 when rates change).
7. The system according to claim 6, wherein the energy parameter is one or more of the following: an initial state-of-charge of each battery storage system; a limit/capacity of each battery storage system; a charge rate and efficiency of each battery storage system; a limit of energy that can be taken from the electrical grid (fig. 58 0339); and/or a look-ahead time of the forecasting algorithm.
8. The system according to claim 1, further comprising an explainer unit adapted to provide explanations about the sensitivity of the energy optimizer based on the energy data inputs/outputs and/or the energy parameter inputs/outputs[0053].
10. The method according to claim 9, wherein the first energy data input is formed by historical energy data, the method further comprising: determining, by the energy optimizer, a first energy data forecast based on the historical energy data[0146], providing the first energy data forecast to an optimization algorithm, determining by the optimization algorithm, a first optimization goal based on the first energy data forecast and an optimization parameter[0363], providing ground truth data to the optimization algorithm, and determining by the optimization algorithm, a second optimization goal based on the ground truth data and the optimization parameter[0364].
11. The method according to claim 10, further comprising: varying the historical energy data; providing the varied energy data to the energy optimizer; determining by the energy optimizer one or more varied energy data forecasts based on the varied energy data; providing the one or more varied energy data forecasts to the optimization algorithm; and determining by the optimization algorithm one or more varied data optimization goals based on the one or more varied energy data forecasts, wherein the optimization parameter is kept constant[0363 adjustments made].
12. The method according to claim 11, further comprising: determining at least one forecast difference between the ground truth data and each of the one or more energy data forecasts; and determining at least one optimization goal difference between the second optimization goal based on a ground truth data and each of the optimization goals based on each of the energy data forecasts (fig. 38 different tree outcomes).
13. The method according to claim 9, wherein the first energy data input is formed by historical energy data, the method further comprising: determining by the energy optimizer a constant energy data forecast based on the historical energy data[0363]; providing the constant energy data forecast to an optimization algorithm[0363-0364]; determining by the optimization algorithm a first optimization goal based on the constant energy data forecast and a optimization parameter(fig. 38); varying the optimization parameter [0363 user selections can be changed]; providing the varied optimization parameter to the energy optimizer[0363-0364]; and determining by the optimization algorithm one or more varied optimization goals based on the constant energy data forecast and the one or more varied optimization parameters(fig. 38).
Other Prior Art of Record
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Wells (U.S. Pat. 11,056,912) teaches A power flow schedule of a cluster is determined by calculating sensitivity of the net power exchange bounds.
Sayyar-Rodsari (U.S. PG Pub. 20110106277) teaches a system for optimizing and controlling production plants.
Mehta (U.S. PG Pat. 7,050,863) teaches a process control configuration system is provided for use in creating or viewing an integrated optimization and control block that implements an optimization routine and a multiple-input/multiple-output control routine.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NATHAN L LAUGHLIN whose telephone number is (571)270-1042. The examiner can normally be reached Monday-Friday 8AM-4PM.
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/NATHAN L LAUGHLIN/Primary Examiner, Art Unit 2119
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