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 .
Response to Amendment
Applicant’s amendments to the claims, filed 08/18/2025, are accepted and appreciated by the
Examiner.
Response to Arguments
Applicant’s arguments, see remarks, filed 08/18/2025, with respect to the rejection(s) of claims 1-14 under 35 U.S.C. 101 have been fully considered but they are not persuasive. The fact pattern of Example 38 and the present application are different. Even though they both correspond to a simulation the simulation in example 38 is tied to a specific device where each circuit element is at a specific location. Whereas the current application is tied to a generic electrical device and therefore measuring the electrical device can be viewed as mere data gathering as seen in MPEP 2106.05(g). Furthermore, as seen in MPEP 2106.04(a)(2) “A claim that recites a mathematical calculation, when the claim is given its broadest reasonable interpretation in light of the specification, will be considered as falling within the "mathematical concepts" grouping. A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation. There is no particular word or set of words that indicates a claim recites a mathematical calculation. That is, a claim does not have to recite the word "calculating" in order to be considered a mathematical calculation. For example, a step of "determining" a variable or number using mathematical methods or "performing" a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation.” Therefore, the claim is directed to mathematical concepts as the claim determines information by using two mathematical models.
Applicant’s arguments, see Remarks, filed 08/18/2025, with respect to the rejection of amended claim 1 under 35 U.S.C 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Feng (US 20160252401 A1) and Cheim (US 20210318391 A1) in light of claim amendments.
Claim Rejections - 35 USC § 101
Claims 1, 4-10, and 12-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 1,
the following bold limitations are considered abstract:
“A method for providing a computer simulation of an electrical device using a first mathematical model of the electrical device and a second mathematical model of the electrical device, the method comprising:
measuring the electrical device to determine a value of a thermal operating parameter of the electrical device at a starting time;
and determining a progression of a characteristic variable of the electrical device for an evaluation period comprising a plurality of evaluation times by, for each respective evaluation time:
determining, using the second mathematical model, a determined value of a determined thermal operating parameter of the electrical device at the respective evaluation time; and
determining, using the first mathematical model, a value of the characteristic variable for the respective evaluation time based on an ambient temperature of the electrical device at the respective evaluation time and the determined value of the determined thermal operating parameter of the electrical device at respective evaluation time,
wherein the first mathematical model models a dependency of a model thermal operating parameter of the electrical device based on a model ambient temperature of the electrical device and on a model electrical load factor of the electrical device, the model thermal operating parameter predicting the thermal operating parameter,
wherein the characteristic variable represents a thermal load on the electrical device, and the characteristic variable is determined for the respective evaluation time as an equivalent electrical load factor of the electrical device, the equivalent electrical load factor corresponding to a value for the model electrical load factor for which the first mathematical model, taking into account the ambient temperature at the respective evaluation time as the model ambient temperature, predicts a value for the model thermal operating parameter that corresponds to the determined value of the determined thermal operating parameter of the electrical device at the respective evaluation time, and
wherein the second mathematical model models a dependency of a second model thermal operating parameter of the electrical device based on a progression of a second model ambient temperature of the electrical device, a progression of a second model electrical load factor of the electrical device, and a starting value for the second model thermal operating parameter,
wherein the value of the thermal operating parameter determined at the starting time is used as the starting value for the second model thermal operating parameter,
wherein, for each respective evaluation time, the progression of the second model ambient temperature corresponds to a progression of the ambient temperature of the electrical device between the starting time and the respective evaluation time, and wherein, for each respective evaluation time, the progression of the second model electrical load factor of the electrical device corresponds to a progression of a determined electrical load factor of the electrical device between the starting time and the respective evaluation time.”
are directed to abstract ideas and would fall within the “Mental Process” and “Mathematical Concept” grouping of abstract ideas. Determining a progression of characteristic variables from ambient temperature and a determined value of a thermal operating parameter of an electrical device can be practically performed in the human mind using observation, evaluation, judgement, and opinion. As it requires observing data values and making judgments about the data values. According to MPEP 2106.04 “The courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 (2012) ("‘[M]ental processes and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same). Accordingly, the "mental processes" abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions.” A first mathematical model is just a well-known mathematical concept used to predict a thermal operating parameter as seen in paragraph 11. Likewise, the second mathematical model is also a well-known mathematical concept as seen in para. [0016]. Using the models to determine characteristic variables is just applying a mathematical concept to the data.
This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements –
a computer simulation of an electrical device; measuring the electrical device to determine a value of a thermal operating parameter of the electrical device at a starting time; an ambient temperature of the electrical device at the respective evaluation time.
Examiner views these limitations amount to generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h)
As such Examiner does NOT view that the claims
-Improve the functioning of a computer, or to any other technology or technical field
-Apply the judicial exception with, or by use of, a particular machine - see MPEP
2106.05(b)
-Effect a transformation or reduction of a particular article to a different state or thing -
see MPEP 2106.05(c)
-Apply or use the judicial exception in some other meaningful way beyond generally
linking the use of the judicial exception to a particular technological environment, such that the
claim as a whole is more than a drafting effort designed to monopolize the exception - see MPEP
2106.05(e) and Vanda Memo.
Moreover, Examiner views the claims to be merely generally linking the use of the judicial exception to a container of sample materials. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to
integration of the abstract idea into a practical application, the additional elements of a computer simulation of an electrical device; measuring the electrical device to determine a value of a thermal operating parameter of the electrical device at a starting time; an ambient temperature of the electrical device at the respective evaluation time amount to a generic electrical device and well-known data processed by a computer being used as a tool. Furthermore, measuring the electrical device is viewed as mere data gathering. This is considered generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h). Examiner further notes that such additional elements are viewed to be well known routine and conventional as evidenced by
Feng (US 20160252401 A1)
Gao (CN 108680801 A)
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Considering the claim as a whole, one of ordinary skill in the art would not know the practical application of the present invention since the claims do not apply or use the judicial exception in some meaningful way. As currently claimed, Examiner views that the additional elements do not apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, because the claim fails to recite clearly how the judicial exception is applied in a manner that does not monopolize the exception because the limitations an electrical device, an ambient temperature of the electrical device at the determination time and a determined value of a thermal operating parameter of the electrical device at the determination time just tie the claim to an electrical device and does not impose a meaningful limitation describing what problem is being remedied or solved.
Dependent claims 4-10 and 12-14 when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitation(s) fail(s) to establish that the claims are not directed to an abstract idea, as detailed below:
The claims are directed to making observations and manipulating the temperature, characteristic variable, thermal operating parameter, and load factor. As seen above this would represent an abstract idea. Claims 11-14 introduce a processor which is an additional element but as seen in MPEP 2106.05(f) a processor is considered mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea.
Therefore, dependent claims 4-10 and 12-14 further limit the abstract idea with an abstract idea and thus the claims are still directed to an abstract idea without significantly more.
Claim 11 is not rejected under 35 U.S.C. 101 because claim 15 includes the limitation “adjusting an actual electrical load factor of the electrical device at the respective evaluation time based on the characteristic variable” which is viewed as applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment as the electrical device is being adjusted based on the characteristic value. See MPEP 2106.05.
Claims 15-18 are not rejected under 35 U.S.C. 101 because claim 15 includes the limitation “operating the electrical device based on the progression of the predicted equivalent electrical load factor,” which is viewed as applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment as the electrical device is being controlled by the determined progression. See MPEP 2106.05.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 4, 5, 7, and 9-18 are rejected under 35 U.S.C. 103 as being unpatentable over Feng (US 20160252401 A1) and Cheim (US 20210318391 A1).
Regarding claim 1,
Feng teaches,
and determining a progression of a characteristic variable of the electrical device for an evaluation period comprising a plurality of evaluation times by, for each respective evaluation time: (Para. [0004] teaches “Using the recorded simulation currents and the recorded simulation times, a loadability function is created for determining a maximum loading level at any given time during the forecast period. The loadability function is used to operate the transformer during the forecast period.” Para. [0015] teaches “the thermal loading condition over the prediction horizon e.g., in the next 12-24 hours” (i.e. the predicted horizon/forecast period is seen as the evaluation period and any given time is seen as an evaluation time. Thermal loading condition/loadablity function is seen as characteristic variable. Fig. 1 shows that the values that are used to create the function are monitored over time and therefore a progression of the variable is taught.))
determining, using the second mathematical model, a determined value of a determined thermal operating parameter of the electrical device at the respective evaluation time; (Para. [0018] teaches “The TMPS 10 includes a dynamic thermal model 28 of the transformer 12. The dynamic thermal model 28 generally includes a top-oil temperature model and a (winding) hot-spot temperature model.”)
and determining, using the first mathematical model, a value of the characteristic variable for the respective evaluation time based on an ambient temperature of the electrical device at the respective evaluation time and the determined value of the determined thermal operating parameter of the electrical device at respective evaluation time, Para. [0029] teaches “A flow chart of the dynamic rating prediction method 50 is shown in FIG. 5.” The calculation loop 60 seen in fig. 5 is seen as the first mathematical model. It shows that both ambient temperature and top-oil values are used in step 64. Para. [0031] teaches “The maximum loadability of the transformer 12 and a substation transformer are predicted for a time period of six hours.” Where the loadability is seen as the characteristic variable.)
wherein the first mathematical model models a dependency of a model thermal operating parameter of the electrical device based on a model ambient temperature of the electrical device and on a model electrical load factor of the electrical device, the model thermal operating parameter predicting the thermal operating parameter, (i.e. The calculation loop 60 seen in fig. 5 is viewed as the first mathematical model. The load factor K is also seen in loop 60. It shows that both ambient temperature and top-oil values (operating parameter) are used in step 64.)
wherein the characteristic variable represents a thermal load on the electrical device, and the characteristic variable is determined for the respective evaluation time as an equivalent electrical load factor of the electrical device, the equivalent electrical load factor corresponding to a value for the model electrical load factor for which the first mathematical model, taking into account the ambient temperature at the respective evaluation time as the model ambient temperature, predicts a value for the model thermal operating parameter that corresponds to the determined value of the determined thermal operating parameter of the electrical device at the respective evaluation time, (Para. [0029] teaches “Once the maximum simulation time or a maximum allowed temperature is reached, the method 50 proceeds to step 66 wherein the load factor K(i) and total simulation time T.sub.sim(i) are recorded (stored) as a two-dimensional data point (K(i), T.sub.sim(i)). The method 50 then proceeds to step 68, wherein the iteration number i and load factor K are updated. More specifically, the iteration factor is increased by 1 and the load factor K is decremented by an amount, such as 0.05. Next, in step 70, a determination is made whether the calculation loop 60 should continue or stop. If K is greater than 1, the method 50 proceeds back to step 62 and a new iteration of the calculation loop 60 starts. If K is not greater than 1, the calculation loop 60 stops and the method proceeds to step 72, wherein all data points (T.sub.sim(1), K(1)), . . . (T.sub.sim (i), K(i)), . . . (T.sub.sim(N), K(N)) are collected and used to generate a power vs time curve 76.” (i.e. the loadability/loading condition is tied to a load factor as seen above. As seen in loop 60 in figure 5 ambient temperature is used in this process and every load factor is tied to a time.)
and wherein the second mathematical model models a dependency of a second model thermal operating parameter of the electrical device based on a progression of a second model ambient temperature of the electrical device, a progression of a second model electrical load factor of the electrical device, and a starting value for the second model thermal operating parameter, (Para. [0017] teaches “The dynamic thermal model 28 provides estimates of the winding hot-spot temperature and the top-oil temperature using the ambient temperature and the winding current either primary or secondary as inputs. Para. [0018] teaches “Top-oil temperature model: {dot over (θ)}. sub.top-oil(t)=f(θ.sub.top-oil(t),θ.sub.amb(t),I(t),X) Hot-spot temperature model: {dot over (θ)}.sub.hot-spot(t)=g(θ.sub.hot-spot(t),θ.sub.top-oil(t),I(t),X)” (i.e. the equations show time dependence and the second thermal operating parameter is hot spot temperature.)
wherein the value of the thermal operating parameter determined at the starting time is used as the starting value for the second model thermal operating parameter, (Para. [0004] teaches “Starting with the initial values for the top-oil temperature and the winding hot-spot temperature, updated values for the top-oil temperature and the winding hot-spot temperature for a simulation time are recursively calculated using the simulation current and a forecast of future ambient temperatures.” (i.e. initial values are viewed as starting values.)
wherein, for each respective evaluation time, the progression of the second model ambient temperature corresponds to a progression of the ambient temperature of the electrical device between the starting time and the respective evaluation time, and wherein, for each respective evaluation time, the progression of the second model electrical load factor of the electrical device corresponds to a progression of a determined electrical load factor of the electrical device between the starting time and the respective evaluation time. (Fig. 3 shows a graph of ambient temperature over time. Para. [0013] teaches “The current (real-time) and forecasted ambient temperatures are inputs to the TMPS 10. The current ambient temperature may be obtained from the online weather source 20 or from one or more temperature sensors located in the vicinity of the transformer 12. The load forecast is another input and can be obtained from a transformer load forecast application running on the substation computer 18 or from a control center or another source. The update time interval for the ambient temperature and load forecast is user configurable and may be preferably set in minutes.” (i.e. updated time interval is seen as respective evaluation time.)
Feng does not explicitly teach,
measuring the electrical device to determine a value of a thermal operating parameter of the electrical device at a starting time;
Cheim (US 20210318391 A1),
measuring the electrical device to determine a value of a thermal operating parameter of the electrical device at a starting time; (Para. [0071] teaches “Transformer related parameters, for example load on the transformer, and ambient temperature data for the transformer can be obtained by the transformer monitoring system from measurements made in the transformer/at the transformer site. Measurement of the transformer related parameters including that of moisture content, dissolved oxygen content and other parameters useful for diagnosis of the transformer/life assessment of the transformer can be made with sensors mounted in the transformer.” (i.e. the transformer is viewed as the electrical device.) Fig. 3a shows initial values of different parameters.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Feng with measuring the electrical device to determine a value of a thermal operating parameter of the electrical device at a starting time such as that of Cheim. One of ordinary skill would have been motivated to modify Feng, because Feng Para. [0004] of Cheng teaches “in acordance with the method, initial values for a top-oil temperature and a winding hot-spot temperature of the transformer are calculated using received values of the winding current and ambient temperature.” Since, the values are received they must be measured at some point. Therefore, it would be obvious to measure the values as taught in Cheim.
Regarding claim 4,
Feng further teaches,
The method as claimed in claim 1,
wherein the progression of the characteristic variable is determined as the future expected progression of the characteristic variable, starting from a current time as the starting time, over the evaluation period, (Para. [0016] teaches “Load forecasts for the transformer 12 for different time periods may be available and may be user-selectable. In this manner, if a transformer load forecast over a desired time horizon e.g., the next 12-24 hours is available, the transformer thermal loading condition in the next 12-24 hours can be evaluated, thereby providing the ability to foresee thermal overload conditions in the near future”)
wherein a prediction of the progression of the ambient temperature of the electrical device from the starting time over the evaluation period is used as the progression of the ambient temperature, (Para. [0014] teaches “The current ambient temperature used by the TMPS 10 may also be obtained from the IED 26, which, in turn, obtains it from temperature sensors associated with the IED 26 or connected to the IED 26. Alternately, the ambient temperature may be obtained from an online weather forecast source, as set forth above. The update time interval for these real-time measurements may be on the order of seconds and is user configurable. The real-time data from sensors are transmitted to the substation computer 18 through a wired or wireless communication link or may be directly provided from digital sensors.”
and wherein a prediction of the progression of the electrical load factor of the electrical device from the starting time over the evaluation period is used as the progression of the electrical load factor of the device. (Para. [0016] teaches “Load forecasts for the transformer 12 for different time periods may be available and may be user-selectable. In this manner, if a transformer load forecast over a desired time horizon e.g., the next 12-24 hours is available, the transformer thermal loading condition in the next 12-24 hours can be evaluated, thereby providing the ability to foresee thermal overload conditions in the near future”)
Regarding claim 5,
Feng does not explicitly teach,
The method as claimed in claim 1, wherein measuring the electrical device comprises directly measuring the value of the thermal operating parameter on the device, (Para. [0071] teaches “Transformer related parameters, for example load on the transformer, and ambient temperature data for the transformer can be obtained by the transformer monitoring system from measurements made in the transformer/at the transformer site. Measurement of the transformer related parameters including that of moisture content, dissolved oxygen content and other parameters useful for diagnosis of the transformer/life assessment of the transformer can be made with sensors mounted in the transformer.” (i.e. the transformer is viewed as the electrical device.) Fig. 3a shows initial values of different parameters.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Feng with measuring the electrical device to determine a value of a thermal operating parameter of the electrical device at a starting time such as that of Cheim. One of ordinary skill would have been motivated to modify Feng, because Feng Para. [0004] of Cheng teaches “in acordance with the method, initial values for a top-oil temperature and a winding hot-spot temperature of the transformer are calculated using received values of the winding current and ambient temperature.” Since, the values are received they must be measured at some point. Therefore, it would be obvious to measure the values as taught in Cheim.
Regarding claim 7,
Feng further teaches,
The method as claimed in claim 1, wherein, for the respective evaluation time, a limit characteristic variable of the electrical device is determined as that electrical load factor for which the first mathematical model, taking into account the ambient temperature of the electrical device at the respective evaluation time as the model ambient temperature, predicts a value for the thermal operating parameter of the electrical device, which corresponds to a limit value of the thermal operating parameter that must not be contravened by the operating parameter, wherein the limit value depends on an operating mode of the electrical device. (Para. [0027] teaches “Using transformer load and ambient temperature forecasts, the TMPS 10 is operable to perform a method 30 for predicting whether a thermal overload will occur in a prediction horizon of N hours. The prediction horizon may be selected by an operator through the user interface of the substation computer 18. The method 30 is schematically shown in FIG. 4. In step 32 of the method 30, transformer load (winding current) and ambient temperature forecasts for N hours are input into the dynamic thermal model 28. In step 34, the results from step 32 are analyzed to estimate top-oil and winding hot-spot temperatures for the prediction horizon (N hours). In step 36, the estimated top-oil and winding hot-spot temperatures are compared to maximum allowed values (θ.sub.top-oil.sup.max or θ.sub.hot-spot.sup.max). If the estimated top-oil temperature exceeds θ.sub.top-oil.sup.max or the estimated winding hot-spot temperature exceeds θ.sub.hot-spot.sup.max, an alarm warning an operator that the transformer 12 is expected to experience a thermal overload in the next N hours is generated in step 38. Such an alarm will permit the operator to initiate mitigation actions such as shedding non-critical loads or reconfiguring the system before a real overload happens.” (i.e. Where thermal overload is seen as the limit and load forecast is viewed as being dependent on the mode of the electrical device.)
Regarding claim 9,
Feng does not explicitly teach,
The method as claimed in claim 1, wherein prior to using the second mathematical model, the second mathematical model is selected from among a plurality of different mathematical models based on the progression of the determined electrical load factor of the electrical device.
However, Para. [0019-21] teaches three different models that all depend on a thermal load factor. Para. [0022] teaches “The accuracy of the third model is typically higher than the first and second models. All three models may be stored in the memory of the substation computer 18 and made available for use by the TMPS 10. More specifically, a user may select one of the three models for use as the dynamic thermal model 28 of the TMPS 10. Such selection may be performed through a user interface of the substation computer 18. Further, the TMPS 10 may permit a user to define its own models and store them in the memory of the substation computer 18 for later use as the dynamic thermal model 28.” Since each of the models depend on the electrical load factor in different ways it would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Feng wherein different mathematical models are used as the second mathematical model depending on a progression of an electrical load factor of the electrical device. One of ordinary skill would have been motivated to modify Feng, because the way that the factor is behaving would change the computation time and accuracy of the different models and one model would be advantageous over the others.
Regarding claim 10,
Feng further teaches,
A method for calculating grid safety in an electrical grid comprising a plurality of electrical devices, comprising the electrical device, based on a predicted progression of a load factor of the plurality of electrical devices, (Para. [0008] teaches “Fig. 3 shows a plot of the real time steady state rating of two transformers versus ambient temperature; (i.e. a predicted progression and two transformers are seen as a plurality of electrical devices.) Para. [0023] teaches “Using the conservative rating, the transformer is either underutilized when the ambient temperature is below the set value or it may be operating in an unsafe region when the ambient temperature is over the set value. In contrast to the conventional method, the TMPS 10 of the present inventions provides a real-time steady-state rating estimation using the real-time ambient temperature. In this manner, the TMPS 10 permits the transformer 12 to be more safely and optimally operated.” (i.e. safely operated is viewed as grid safety.))
wherein, for at least the electrical device of the plurality of electrical devices, the future predicted progression of the characteristic variable for the electrical device, which is determined according to the method claimed in claim 4, is used as the expected progression of the load factor of the electrical device. (Para. [0004] teaches “This procedure is repeated until the simulation current is a minimum value. Using the recorded simulation currents and the recorded simulation times, a loadability function is created for determining a maximum loading level at any given time during the forecast period. The loadability function is used to operate the transformer during the forecast period.” (i.e. Since the loadability function is used it is how the method expects the load factor to progress.)
Regarding claim 11,
Feng further teaches,
A method for managing an operation of the electrical device, the method comprising adjusting an actual electrical load factor of the electrical device at the respective evaluation time based on the characteristic variable determined for the respective evaluation time according to the method claimed in claim 1. (Para. [0030] teaches ““This procedure is repeated until the simulation current is a minimum value. Using the recorded simulation currents and the recorded simulation times, a loadability function is created for determining a maximum loading level at any given time during the forecast period. The loadability function is used to operate the transformer during the forecast period.”)
Regarding claim 12,
Feng further teaches,
A simulation system, the simulation system comprising a data processor configured to carry out the method as claimed in claim 1. (Para. [0013] teaches “Referring now to FIG. 1, there is shown an implementation of a thermal monitoring and prediction system (TMPS) 10 for an oil-immersed transformer 12 having a primary winding 14 and a secondary winding 16. The TMPS 10 is a software system that may be implemented in any layer of the control hierarchy. In one embodiment, the TMPS 10 is implemented in a substation computer 18, such as an ABB COM600. More specifically, the TMPS 10 is stored in memory of the substation computer 18 and is executed by a processor of the substation computer 18.”)
Regarding claim 13,
Feng further teaches,
A simulation system, the simulation system comprising a data processor configured to carry out the method as claimed in claim 10. (Para. [0013] teaches “Referring now to FIG. 1, there is shown an implementation of a thermal monitoring and prediction system (TMPS) 10 for an oil-immersed transformer 12 having a primary winding 14 and a secondary winding 16. The TMPS 10 is a software system that may be implemented in any layer of the control hierarchy. In one embodiment, the TMPS 10 is implemented in a substation computer 18, such as an ABB COM600. More specifically, the TMPS 10 is stored in memory of the substation computer 18 and is executed by a processor of the substation computer 18.”)
Regarding claim 14,
Feng further teaches,
A system for managing the operation of the electrical device, wherein the system comprises a data processor configured to carry out the method as claimed in claim 11. (Para. [0013] teaches “Referring now to FIG. 1, there is shown an implementation of a thermal monitoring and prediction system (TMPS) 10 for an oil-immersed transformer 12 having a primary winding 14 and a secondary winding 16. The TMPS 10 is a software system that may be implemented in any layer of the control hierarchy. In one embodiment, the TMPS 10 is implemented in a substation computer 18, such as an ABB COM600. More specifically, the TMPS 10 is stored in memory of the substation computer 18 and is executed by a processor of the substation computer 18.”)
Regarding claim 15,
Feng further teaches,
a starting value of the electrical device at a starting time, the starting value corresponding to a determined thermal operating parameter of the electrical device at the starting time; (Para. [0004] teaches “Starting with the initial values for the top-oil temperature and the winding hot-spot temperature, updated values for the top-oil temperature and the winding hot-spot temperature for a simulation time are recursively calculated using the simulation current and a forecast of future ambient temperatures.” (i.e. initial values are viewed as starting values.)
determining, for an evaluation period comprising a plurality of evaluation times from the starting time to a respective evaluation time, a progression of a predicted equivalent electrical load factor of the electrical device using a first mathematical model of the electrical device and a second mathematical model of the electrical device, the second mathematical model being different from the first mathematical model; (Para. [0004] teaches “Using the recorded simulation currents and the recorded simulation times, a loadability function is created for determining a maximum loading level at any given time during the forecast period. The loadability function is used to operate the transformer during the forecast period.” Para. [0015] teaches “the thermal loading condition over the prediction horizon e.g., in the next 12-24 hours” (i.e. the predicted horizon/forecast period is seen as the evaluation period and any given time is seen as an evaluation time. Thermal loading condition/loadablity function is seen as characteristic variable. Fig. 1 shows that the values that are used to create the function are monitored over time and therefore a progression of the variable is taught.) Para. [0018] teaches “The TMPS 10 includes a dynamic thermal model 28 of the transformer 12. The dynamic thermal model 28 generally includes a top-oil temperature model and a (winding) hot-spot temperature model.” The calculation loop 60 seen in fig. 5 is seen as the first mathematical model.))
and operating the electrical device based on the progression of the predicted equivalent electrical load factor, (Para. [0030] teaches ““This procedure is repeated until the simulation current is a minimum value. Using the recorded simulation currents and the recorded simulation times, a loadability function is created for determining a maximum loading level at any given time during the forecast period. The loadability function is used to operate the transformer during the forecast period.”)
wherein the determining of the progression of the predicted equivalent electrical load factor comprises: for the starting time: using the first mathematical model, determining the predicted equivalent electrical load factor for the respective evaluation time based on: an ambient temperature of the electrical device at the starting time; and the determined thermal operating parameter at the starting time; and for each respective evaluation time of the plurality of evaluation times after the starting time: (Figure 2 shows that ambient temperature forecast, and real-time ambient temperature are input into the system. Fig. 5 shows that it is done for each evaluation time and step 52 shows that operating parameters are obtained.)
using the second mathematical model, determining a predicted value for the thermal operating parameter of the electrical device at the respective evaluation time based on: (Para. [0018] teaches “The dynamic thermal model 28 generally includes a top-oil temperature model and a (winding) hot-spot temperature model.”)
a progression of the ambient temperature of the electrical device from the ambient temperature of the electrical device at the starting time to the ambient temperature of the electrical device at the respective evaluation time; (Para. [0017] teaches “The dynamic thermal model 28 provides estimates of the winding hot-spot temperature and the top-oil temperature using the ambient temperature and the winding current either primary or secondary as inputs.)
a progression of a determined electrical load factor of the electrical device from the starting time to the respective evaluation time; (Para. [0018] teaches “Top-oil temperature model: {dot over (θ)}. sub.top-oil(t)=f(θ.sub.top-oil(t),θ.sub.amb(t),I(t),X) Hot-spot temperature model: {dot over (θ)}.sub.hot-spot(t)=g(θ.sub.hot-spot(t),θ.sub.top-oil(t),I(t),X)” (i.e. the equations show time dependence))
and the determined thermal operating parameter at the starting time; (See step 52 on Fig. 5)
and using the first mathematical model, determining the predicted equivalent electrical load factor for the respective evaluation time based on: the ambient temperature of the electrical device at the respective evaluation time; and the predicted value for the thermal operating parameter at the respective evaluation time. (Para. [0029] teaches “Once the maximum simulation time or a maximum allowed temperature is reached, the method 50 proceeds to step 66 wherein the load factor K(i) and total simulation time T.sub.sim(i) are recorded (stored) as a two-dimensional data point (K(i), T.sub.sim(i)). The method 50 then proceeds to step 68, wherein the iteration number i and load factor K are updated. More specifically, the iteration factor is increased by 1 and the load factor K is decremented by an amount, such as 0.05. Next, in step 70, a determination is made whether the calculation loop 60 should continue or stop. If K is greater than 1, the method 50 proceeds back to step 62 and a new iteration of the calculation loop 60 starts. If K is not greater than 1, the calculation loop 60 stops and the method proceeds to step 72, wherein all data points (T.sub.sim(1), K(1)), . . . (T.sub.sim (i), K(i)), . . . (T.sub.sim(N), K(N)) are collected and used to generate a power vs time curve 76.”(i.e. the loadability/loading condition is tied to a load factor as seen above. As seen in loop 60 in figure 5 ambient temperature is used in this process and every load factor is tied to a time)
Feng does not explicitly teach,
measuring a starting value of the electrical device.
Cheim teaches,
measuring a starting value of the electrical device. (Para. [0071] teaches “Transformer related parameters, for example load on the transformer, and ambient temperature data for the transformer can be obtained by the transformer monitoring system from measurements made in the transformer/at the transformer site. Measurement of the transformer related parameters including that of moisture content, dissolved oxygen content and other parameters useful for diagnosis of the transformer/life assessment of the transformer can be made with sensors mounted in the transformer.” (i.e. the transformer is viewed as the electrical device.) Fig. 3a shows initial values of different parameters.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Feng with measuring a starting value of the electrical device such as that of Cheim. One of ordinary skill would have been motivated to modify Feng, because Feng Para. [0004] of Cheng teaches “in acordance with the method, initial values for a top-oil temperature and a winding hot-spot temperature of the transformer are calculated using received values of the winding current and ambient temperature.” Since, the values are received they must be measured at some point. Therefore, it would be obvious to measure the values as taught in Cheim.
Regarding claim 16,
Feng teaches,
The method of claim 15, wherein the first mathematical model describes a dependency of a model thermal operating parameter of the electrical device based on a model ambient temperature of the electrical device and a model electrical load factor of the electrical device at the respective evaluation time, (Fig. 2 shows that ambient temperature forecast, and real-time ambient temperature are input into the system. Fig. 5 shows that it is done for each evaluation time and step 52 shows that operating parameters are obtained.)
wherein the second mathematical model describes a dependency of second model thermal operating parameter of the electrical device based on a progression of a second model ambient temperature of the electrical device, a progression of a second model electrical load factor of the electrical device, and a starting value for the model thermal operating parameter, (Fig. 2 shows that ambient temperature forecast, and real-time ambient temperature are input into the system. It further shows load forecasts are input. Fig. further shows estimated temperatures are input into the models. It is viewed that the first and second thermal operating parameter and the first and second model ambient temperatures are the same.)
wherein the value of the determined thermal operating parameter determined at the starting time is used as the starting value for the second model thermal operating parameter, (See step 52 of fig.5)
wherein, for each respective evaluation time, the progression of the second model ambient temperature corresponds to a progression of the ambient temperature of the electrical device between the starting time and the respective evaluation time, and wherein, for each respective evaluation time, the progression of the second model electrical load factor of the electrical device corresponds to a progression of a determined electrical load factor of the electrical device between the starting time and the respective evaluation time.( Fig. 3 shows a graph of ambient temperature over time. Para. [0013] teaches “The current (real-time) and forecasted ambient temperatures are inputs to the TMPS 10. The current ambient temperature may be obtained from the online weather source 20 or from one or more temperature sensors located in the vicinity of the transformer 12. The load forecast is another input and can be obtained from a transformer load forecast application running on the substation computer 18 or from a control center or another source. The update time interval for the ambient temperature and load forecast is user configurable and may be preferably set in minutes.” (i.e. updated time interval is viewed as respective evaluation time.))
With respect to claim 17,
Feng further teaches,
The method of claim 15, wherein operating the electrical device based on the progression of the predicted equivalent electrical load factor comprises adjusting an actual load factor of the electrical device. (Para. [0030] teaches “The curve 76 may be used to control the loading (winding current) of the transformer 12. For example, the transformer 12 may be controlled so as to operate intermittently or continuously just below the curve 76 (i.e., the maximum loading level). The control may be performed by connecting and disconnecting loads to and from the transformer 12, either by an operator or automatically by a control program running on the substation computer 18 or another computer.”)
With respect to claim 18,
Feng further teaches,
The method of claim 15, wherein the electrical device is a transformer, and the thermal operating parameter is a hot spot temperature or a top oil temperature of the transformer. (Para. [0004] teaches “a method is provided for monitoring and operating an oil-filled transformer having a winding.” And “the winding hot-spot temperature, updated values for the top-oil temperature and the winding hot-spot temperature for a simulation time are recursively calculated using the simulation current and a forecast of future ambient temperatures.”)
Claims 6 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Feng (US 20160252401 A1) and Cheim (US 20210318391 A1) as applied to claim 1 and 7 above, and further in view of Gao (CN 108680801 A).
Regarding claim 6,
Feng does not explicitly teach,
The method as claimed in claim 1, wherein an equivalent electrical load factor of the electrical device, for which a difference between the thermal operating parameter determined by the first mathematical model for the determination time and the thermal operating parameter of the electrical device at the determination time falls below a predetermined limit value, is determined for a determination time as the characteristic variable for representing the thermal load on the electrical device, wherein an optimization algorithm is used to reduce the difference.
Gao teaches,
wherein an equivalent electrical load factor of the electrical device, for which a difference between the thermal operating parameter determined by the first mathematical model for the determination time and the thermal operating parameter of the electrical device at the determination time falls below a predetermined limit value, is determined for a determination time as the characteristic variable for representing the thermal load on the electrical device, wherein an optimization algorithm is used to reduce the difference. (Para(s). [0087-0090] teach “In step S405, the load difference corresponding to the overload thermal limit time is calculated based on the historical average load capacity and the current transient load capacity. “In this embodiment, the current transient load capacity is 0.8 and the thermal limit time is 780 min. Assuming that the historical average load capacity calculated according to the historical overload calculation table is 0.7, the current transient load capacity is subtracted from the historical average load capacity to obtain a load difference of -0.1. In step S406, the preset target load capacity corresponding to the overload thermal limit time is adjusted according to the load difference corresponding to the overload thermal limit time to obtain the corrected target load capacity. In this embodiment, when the load difference is -0.1, the preset target load capacity corresponding to the overload thermal limit time of 78 minutes is adjusted from 1.4 to 1.3 to obtain the corrected target load capacity.” (i.e. the corrected value is viewed as optimized to reduce the difference.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Feng wherein an equivalent electrical load factor of the electrical device, for which a difference between the thermal operating parameter determined by the first mathematical model for the determination time and the thermal operating parameter of the electrical device at the determination time falls below a predetermined limit value, is determined for a determination time as the characteristic variable for representing the thermal load on the electrical device, wherein an optimization algorithm is used to reduce the difference such as that of Gao. One of ordinary skill would have been motivated to modify Feng, because according to para. [0093] “can be seen from the above embodiments, by referring to historical load trends and using historical load capacity to correct the target load capacity, the calculated corrected thermal limit time is more accurate” Therefore, optimizing the value as taught would increase the accuracy of the method.
Regarding claim 8,
Feng does not explicitly teach,
The method as claimed in claim 7, wherein a difference between the limit characteristic variable determined for the respective evaluation time and the characteristic variable determined for the respective evaluation time is calculated as the reserve characteristic variable, the reserve characteristic variable indicating an additional load that is serviceable by the electrical device at the respective evaluation time without exceeding the limit value of the thermal operating parameter.
Gao teaches,
wherein a difference between the limit characteristic variable determined for the respective evaluation time and the characteristic variable determined for the respective evaluation time is calculated as the reserve characteristic variable, the reserve characteristic variable indicating an additional load that is serviceable by the electrical device at the respective evaluation time without exceeding the limit value of the thermal operating parameter. (Para(s). [0141-0142] “The load capacity indication difference calculation module is used to calculate the difference between the load capacity limit and the current transient load capacity, as the load capacity indication difference; The load limit warning module is used to issue a load limit warning when the load capacity warning difference is less than or equal to a preset load warning difference.” (i.e. the load capacity indication difference is viewed as the reserve characteristic variable.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Feng wherein a difference between the limit characteristic variable determined for the determination time and the characteristic variable determined for the determination time is calculated as the reserve characteristic variable such as that of Gao. One of ordinary skill would have been motivated to modify Feng, because according to para. [0005] “The disadvantage is that general transformer manufacturers leave a design margin for the design, which cannot truly reflect the actual overload capacity of the transformer, does not consider the overload capacity of the transformer components and the transient load changes of the transformer, and cannot solve the problem of calculating the transformer overload limit time in transient changes.” Therefore, the transformer may have more capacity that can be put to use.
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner
should be directed to JOSHUA L FORRISTALL whose telephone number is 703-756-4554. The examiner
can normally be reached Monday-Friday 8:30 AM- 5 PM.
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) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Catherine Rastovski can be reached on 571-270-0349. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like
assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or
571-272-1000.
/JOSHUA L FORRISTALL/Examiner, Art Unit 2863 /Catherine T. Rastovski/Supervisory Primary Examiner, Art Unit 2863
Prosecution Insights