DETAILED ACTION
This office action is in response to applicant’s communication filed 10/17/2023.
Claim(s) 1-20 have been considered.
- Claim(s) 1-20 are pending.
- Claim(s) 1-20 have been rejected as described below.
- This action is NON-FINAL.
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 .
Information Disclosure Statement
Examiner acknowledges the entry of following Information Disclosure Statement (IDS) document(s) from applicant:
The information disclosure statement(s) filed 10/17/2023 and 01/14/2025 has/have been considered by examiner.
Several reference(s) mentioned in the IDS has/have been utilized by the examiner.
Specification
The disclosure filed 10/17/2023 is objected to due to having below minor informalities:
The title of the disclosure is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
Drawings
The drawings filed 10/17/2023 are acknowledged and accepted by examiner for examination.
Claim Objections
Claim(s) 8, 15, and 19-20 is/are objected to due to having minor informalities:
Claim 8/15 in their last limitation(s) recite(s): “dispatching/dispatch one or more electrical assets …”, which should have an “and” at the beginning of the limitations as it is the last step.
In addition, claims 19 and 20 are not numbered correctly. A series of singular dependent claims is permissible in which a dependent claim refers to a preceding claim which, in turn, refers to another preceding claim.
A claim which depends from a dependent claim should not be separated by any claim which does not also depend from said dependent claim. It should be kept in mind that a dependent claim may refer to any preceding independent claim. In general, applicant's sequence will not be changed. See MPEP § 608.01(n).
Correction is required.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(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, 3-5, 8, 10, 13, 15, and 19 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Park (KR 102010147 B1 – Translation provided by Applicant via IDS).
Regarding claim 1, Park teaches:
A method of operating a microgrid system comprising: (Fig. 1 – showing the configuration of a microgrid for small and medium-sized buildings; Fig. 2 - a diagram illustrating a load tracking scheduling system.)
obtaining a microgrid dispatch schedule input that includes a schedule of required electrical energy generation for the microgrid system (0006 teaches generating a distributed energy resource (DER) operating schedule. 0012, 0032 also teach predicting the generation amount, step, etc. and creating a schedule for DER operations.) for a given time period and a schedule of electrical assets capable of meeting the schedule of required electrical energy generation; (0012 teaches prediction of energy generation and prediction of charge/discharge state, etc.; 0003, 0006, 0010 teach load forecasting. 0032-35 teach generating DER prediction operation schedules for each level classified using the predicted load data and the predicted DER data, and note the level matching the real-time load data in 0034 and comparison with real-time DER data in 0035.)
filtering the scheduled dispatch input and converting the scheduled dispatch input into power levels to meet power demands for required electrical energy generation of the dispatch schedule input for the microgrid system; (See Fig. 2, "120", ''130", "140" described in 0027-35 for load data comparison, multi-leveling and a flexible time scaling for optimization and DER control. See 0032-35 teach generating DER prediction operation schedules for each level classified using the predicted load data and the predicted DER data.)
receiving a current load level for the microgrid system based on one or more electrical loads electrically coupled to the microgrid system; (Fig. 2 & 0013 teach measured real time DER status data “20”; Fig. 2-5 & 0030 also teach real time data includes real time load data. Fig. 2 shows the actual power of the day in the load.)
comparing the schedule of required electrical energy generation to an actual required electrical energy generation for the microgrid system to determine a difference between scheduled required electrical energy generation and the actual required electrical energy generation; (Fig. 2, “110" combined with "output of "130''. "140''; 0013, 0015 along with 0035 teach the DER comparison unit 110 compares the predicted DER data with the real-time DER data, which is referred to by the DER controller prior to controlling the DERs.)
and dispatching one or more electrical assets in real time to meet a difference between the scheduled required electrical energy generation and the actual required electrical energy generation. (Fig. 2, "150", “160”, 0010-0016 along with 0032-35 teach the DER controller transmits dispatch commands to the DERs for controlling the DERs according to a DER prediction operation schedule corresponding to a level matching the real-time load data. Also, 0036-37 teach the control of the DERs according to the corresponding operating schedule is decided based on the DER data comparison.)
Regarding claim 3, Park teaches all the elements of claim 1.
Park further teaches:
wherein the schedule of required electrical energy generation and the schedule of electrical assets capable of meeting the required electrical energy generation are updated periodically. (0018 teaches, “… the time scale for rescheduling is flexibly applied by distinguishing between the case of large and small cases of real-time load variability, so that frequent rescheduling is performed when the load variability is large.”)
Regarding claim 4, Park teaches all the elements of claim 1.
Park further teaches:
wherein the one or more electrical assets include one or more of one or more gensets, one or more energy storage systems, one or more renewable energy resource assets, and a utility grid. (Fig. 1, Fig. 2, and 0023-24 teach the configuration of microgrids. For example, 0023 teaches, “As shown, microgrids for small and medium-sized buildings consist of solar generators, wind generators, cogeneration generators, ESSs, EVs, and loads.)
Regarding claim 5, Park teaches all the elements of claim 4.
Park further teaches:
wherein the one or more renewable energy resource assets include one or more of a photovoltaic asset and a wind turbine. (As above, 0023 teaches, “As shown, microgrids for small and medium-sized buildings consist of solar generators, wind generators, cogeneration generators, ESSs, EVs, and loads.)
Regarding claim 8, Park teaches:
A method of operating a microgrid system comprising: (Fig. 1 – showing the configuration of a microgrid for small and medium-sized buildings; Fig. 2 - a diagram illustrating a load tracking scheduling system.)
receiving a scheduled load signal based on a schedule of electrical load requirements for the microgrid system for a given period of time; (0006 teaches generating a distributed energy resource (DER) operating schedule, where the scheduling method includes: estimating a load; 0012 also teaches predicting the generation amount, step, etc. based on the estimated load and creating a schedule for DER operations. More specifically, see Fig. 4 (and Fig. 3) illustrate(s) a “predictive load” signal among others. 0027-28 teaches the predicted data including load data of the day predicted one day ago. In addition, 0032-35 teach generating DER prediction operation schedules for each level classified using the predicted load data and the predicted DER data, and note the level matching the real-time load data in 0034 and comparison with real-time DER data in 0035.)
receiving an expected power generation signal based on an expected power generation of one or more electrical assets electrically coupled to the microgrid system; (0006 teaches generating a distributed energy resource (DER) operating schedule. 0012-13, 0032 also teach predicting the generation amount, step, etc. and creating a schedule for DER operations. More specifically, see Fig. 4 (and Fig. 3) illustrate(s) a “predictive DER” signal among others. 0032-35 teach generating DER prediction operation schedules for each level classified using the predicted load data and the predicted DER data, and note the level matching the real-time load data in 0034 and comparison with real-time DER data in 0035.)
measuring an actual load at a measuring time that is within the given period of time and receiving an actual load signal to determine an actual load on the microgrid system; (Fig. 2 & 0013 teach measured real time DER status data “20”; Fig. 2-5 & 0030 also teach real time data includes real time load data. Fig. 2 shows the actual power of the day in the load.)
comparing the actual load signal with the scheduled load signal and the expected power generation signal; (Fig. 4 provides an example illustrating the comparison of Predictive load and real time load, along with other signals including the predictive DER signal. See below citations for further details.) developing a differential load signal based on a difference between the scheduled load signal, the expected power generation signal, and the actual load signal; (As above, Fig. 4 takes into consideration the predictive load and real time load signals along with predictive DER signal etc. for the comparison, which then is used in Fig. 5 for the load tracking-based time scaling and optimized rescheduling etc. steps. Fig. 2, “110" combined with "output of "130''. "140''; 0013, 0015 along with 0035 teach the DER comparison unit 110 compares the predicted DER data with the real-time DER data, which is referred to by the DER controller prior to controlling the DERs. More specifically, note, 0029 teaches the DER data)
dispatching one or more electrical assets to meet the differential load based on the differential load signal. (Besides above, see Fig. 2, "150", “160”, 0010-0016 along with 0032-35 teach the DER controller transmits dispatch commands to the DERs for controlling the DERs according to a DER prediction operation schedule corresponding to a level matching the real-time load data. Also, 0036-37 teach the control of the DERs according to the corresponding operating schedule is decided based on the DER data comparison.)
Regarding claim 10, Park teaches all the elements of claim 8.
Park further teaches:
wherein the expected power generation signal is based on one or more of an expected power generation of one or more renewable energy resource assets and a utility cost. (Besides 0012-13 teaching the step of predicting the generation amount based on the estimated load and the estimated generation amount of the DER, 0023 teaches, “As shown, microgrids for small and medium-sized buildings consist of solar generators, wind generators, cogeneration generators, ESSs, EVs, and loads. More specifically, 0029 teaches the DER data is data including the power generation amount of the DER…. DER includes solar generator, wind generator, … etc.)
Regarding claim 13, Park teaches all the elements of claim 8.
Park further teaches:
wherein the one or more electrical assets are dispatched in one or more groups of electrical assets. (As above, see Fig. 2, "150", “160”, 0010-0016 along with 0032-35 teach the DER controller transmits dispatch commands to the DERs for controlling the DERs according to a DER prediction operation schedule corresponding to a level matching the real-time load data. Here, under broadest reasonable interpretation of the limitation, examiner has noted that this can be interpreted as just one group with one asset.)
Regarding claim 15, Park teaches:
A controller for a microgrid system comprising: (Fig. 1 – showing the configuration of a microgrid for small and medium-sized buildings; Fig. 2 - a diagram illustrating a load tracking scheduling system.)
at least one memory storing instructions; at least one processor, operatively connected to the memory and configured to execute the instructions to: (0062 teaches computer readable recording medium can be any data storage device that can be read by a computer and can store data. For example, the computer-readable recording medium may be a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, an optical disk, a hard disk drive, or the like. In addition, the computer-readable code or program stored in the computer-readable recording medium may be transmitted through a network connected between the computers.)
receive a scheduled load signal based on a schedule of electrical load requirements for the microgrid system for a given period of time; (0006 teaches generating a distributed energy resource (DER) operating schedule, where the scheduling method includes: estimating a load; 0012 also teaches predicting the generation amount, step, etc. based on the estimated load and creating a schedule for DER operations. More specifically, see Fig. 4 (and Fig. 3) illustrate(s) a “predictive load” signal among others. 0027-28 teaches the predicted data including load data of the day predicted one day ago. In addition, 0032-35 teach generating DER prediction operation schedules for each level classified using the predicted load data and the predicted DER data, and note the level matching the real-time load data in 0034 and comparison with real-time DER data in 0035.)
receive an expected power generation signal based on an expected power generation of one or more electrical assets electrically coupled to the microgrid system; (0006 teaches generating a distributed energy resource (DER) operating schedule. 0012, 0032 also teach predicting the generation amount, step, etc. and creating a schedule for DER operations. More specifically, see Fig. 4 (and Fig. 3) illustrate(s) a “predictive DER” signal among others. 0032-35 teach generating DER prediction operation schedules for each level classified using the predicted load data and the predicted DER data, and note the level matching the real-time load data in 0034 and comparison with real-time DER data in 0035.)
measure an actual load at a measuring time that is within the given period of time and receiving an actual load signal to determine an actual load on the microgrid system; (Fig. 2 & 0013 teach measured real time DER status data “20”; Fig. 2-5 & 0030 also teach real time data includes real time load data. Fig. 2 shows the actual power of the day in the load.)
compare the actual load signal with the scheduled load signal and the expected power generation signal; (Fig. 4 provides an example illustrating the comparison of Predictive load and real time load, along with other signals including the predictive DER signal. See below citations for further details.) develop a differential load signal based on a difference between the scheduled load signal, the expected power generation signal, and the actual load signal; (As above, Fig. 4 takes into consideration the predictive load and real time load signals along with predictive DER signal etc. for the comparison, which then is used in Fig. 5 for the load tracking-based time scaling and optimized rescheduling etc. steps. Fig. 2, “110" combined with "output of "130''. "140''; 0013, 0015 along with 0035 teach the DER comparison unit 110 compares the predicted DER data with the real-time DER data, which is referred to by the DER controller prior to controlling the DERs. More specifically, note, 0029 teaches the DER data)
dispatch one or more electrical assets to meet the differential load based on the differential load signal. (Besides above, see Fig. 2, "150", “160”, 0010-0016 along with 0032-35 teach the DER controller transmits dispatch commands to the DERs for controlling the DERs according to a DER prediction operation schedule corresponding to a level matching the real-time load data. Also, 0036-37 teach the control of the DERs according to the corresponding operating schedule is decided based on the DER data comparison.)
Regarding claim 19, Park teaches all the elements of claim 15.
Park further teaches:
wherein the expected power generation signal is based on one or more of an expected power generation of one or more renewable energy resource assets and a utility cost. (Besides 0012-13 teaching the step of predicting the generation amount based on the estimated load and the estimated generation amount of the DER, 0023 teaches, “As shown, microgrids for small and medium-sized buildings consist of solar generators, wind generators, cogeneration generators, ESSs, EVs, and loads. More specifically, 0029 teaches the DER data is data including the power generation amount of the DER…. DER includes solar generator, wind generator, … etc.)
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.
Claim(s) 2, 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park (KR 102010147 B1 – Translation provided by Applicant via IDS) in view of Wells (US 11289907 B1).
Regarding claim 2, Park teaches all the elements of claim 1.
However, Park does not explicitly disclose:
wherein the one or more electrical assets are dispatched in real time based on constraints that are segmented into groups of different priorities.
Wells explicitly teaches:
wherein the one or more electrical assets are dispatched in real time based on constraints that are segmented into groups of different priorities. (Abstract, and C6, 2nd to last para, C8, para2 and C10, para3 etc. teach various exemplary constraints-based scheduling to be based on different priority groups.)
Accordingly, as Park and Wells are directed to various assets and elements’ control and scheduling management technology, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have specifically added the feature of utilizing the well-known technology of constraints-based prioritizing of dispatching/scheduling the assets, as taught by Wells to the microgrid assets scheduling and control system as taught by Park. One would have been motivated to combine these features because such a combined system/method would have enabled maximizing the benefits of demand response and enabled the curtailment to meet the optimal objective function to maximize the net benefits, etc., as evident in Wells, abstract, C10, para3, etc.
Regarding claim 9, Park teaches all the elements of claim 8.
However, Park does not explicitly disclose:
wherein the scheduled load is input by a user of the microgrid system.
Wells explicitly teaches:
wherein the scheduled load is input by a user of the microgrid system. (See Fig. 19 described in C13 last para – “FIG. 19 is a flow chart 1900 illustrating load scheduling. A load scheduling module 2022 (described in more detail in FIG. 20) receives, at 1910, user input initiating load scheduling of the plurality of electrical system loads and the generation resources.”.)
Accordingly, as Park and Wells are directed to various assets and elements’ control and scheduling management technology, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have specifically added the feature of utilizing the well-known technology of user input-based load scheduling, as taught by Wells to the microgrid assets scheduling and control system as taught by Park. One would have been motivated to combine these features because such a combined system/method would have enabled a well-known way of initiating load scheduling towards determining load scheduling characteristics, as evident in Wells, abstract, Fig. 19, C13 last para, etc.
Claim(s) 6, 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park (KR 102010147 B1 – Translation provided by Applicant via IDS) in view of Martinez (US 20220215486 A1).
Regarding claim 6, Park teaches all the elements of claim 1.
However, Park does not explicitly disclose:
wherein one or more renewable energy resource assets are dispatched based on a forecasted cloud cover, forecasted weather, and forecasted wind speed data.
Martinez explicitly teaches:
wherein one or more renewable energy resource assets are dispatched based on a forecasted cloud cover, forecasted weather, and forecasted wind speed data. (Abstract, and 0076 teach accurate forecasts are essential in any system that has renewable resources and energy storage capabilities, as the value of energy and power changes over time. 0147 teach forecasting techniques that are used for an asset manager to control distribution of power within an aggregated distributed energy resources system may include forecasting that can be done using historical data, and in others it can be done using external inputs such as weather forecast services. Note, weather forecast services provide data regarding the state of the atmosphere in a given location and comprehensive forecasts typically include temperature, precipitation, wind speed and direction, humidity, atmospheric pressure, and cloud cover.)
Accordingly, as Park and Martinez are directed to various assets and elements’ control and scheduling management technology, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have specifically added the feature of utilizing the well-known technology of weather forecast based dispatching of energy resources including renewable resources, as taught by Martinez to the microgrid assets scheduling and control system as taught by Park. One would have been motivated to combine these features because such a combined system/method would have enabled utilizing well-known technique of the art to provide accurate forecasts as one of the several ways to improve DER response, as evident in Martinez, abstract, 0075-76, 0147, etc.
Regarding claim 11, Park teaches all the elements of claim 10.
However, Park does not explicitly disclose:
wherein the expected power generation of one or more renewable energy resource assets is based on data related to one or more of average cloud cover, historical weather data, and historical wind speed data.
Martinez explicitly teaches:
wherein the expected power generation of one or more renewable energy resource assets is based on data related to one or more of average cloud cover, historical weather data, and historical wind speed data. (Abstract, and 0076 teach accurate forecasts are essential in any system that has renewable resources and energy storage capabilities, as the value of energy and power changes over time. 0147 teach forecasting techniques that are used for an asset manager to control distribution of power within an aggregated distributed energy resources system may include forecasting that can be done using historical data, and in others it can be done using external inputs such as weather forecast services. Note, weather forecast services provide data regarding the state of the atmosphere in a given location and comprehensive forecasts typically include temperature, precipitation, wind speed and direction, humidity, atmospheric pressure, and cloud cover.)
Accordingly, as Park and Martinez are directed to various assets and elements’ control and scheduling management technology, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have specifically added the feature of utilizing the well-known technology of weather forecast based dispatching of energy resources including renewable resources, as taught by Martinez to the microgrid assets scheduling and control system as taught by Park. One would have been motivated to combine these features because such a combined system/method would have enabled utilizing well-known technique of the art to provide accurate forecasts as one of the several ways to improve DER response, as evident in Martinez, abstract, 0075-76, 0147, etc.
Claim(s) 7, 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park (KR 102010147 B1 – Translation provided by Applicant via IDS) in view of Doherty (US 20190165580 A1).
Regarding claim 7, Park teaches all the elements of claim 1.
However, Park does not explicitly disclose:
wherein the dispatching of one or more electrical assets is based on one or more modes including an economics mode, a minimum emissions mode, and a maximum renewables penetration mode.
Doherty explicitly teaches:
wherein the dispatching of one or more electrical assets is based on one or more modes including an economics mode, a minimum emissions mode, and a maximum renewables penetration mode. (Abstract, and 0025 teach “and the step (c) of determining an optimal dispatch schedule comprises … (iii) generating, by the computer system, one or more dispatch schedules by applying non-linear economic optimization scheduler to the selected one or more sets of the generated one or more forecast scenarios; and (iv) averaging, by the computer system, the generated one or more dispatch schedules to produce the optimal dispatch schedule.)
Accordingly, as Park and Doherty are directed to various assets and elements’ control and scheduling management technology, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have specifically added the feature of utilizing the well-known technology of dispatching based on one or more modes such as by applying non-linear economic optimization scheduler, as taught by Doherty to the microgrid assets scheduling and control system as taught by Park. One would have been motivated to combine these features because such a combined system/method would have enabled utilizing well-known technique of the art to create optimal dispatching schedule, as evident in Doherty, abstract, 0025, etc.
Regarding claim 12, Park teaches all the elements of claim 8.
However, Park does not explicitly disclose:
wherein the dispatching of one or more electrical assets is based on one or more modes including an economics mode, a minimum emissions mode, and a maximum renewables penetration mode.
Doherty explicitly teaches:
wherein the dispatching of one or more electrical assets is based on one or more modes including an economics mode, a minimum emissions mode, and a maximum renewables penetration mode. (Abstract, and 0025 teach “and the step (c) of determining an optimal dispatch schedule comprises … (iii) generating, by the computer system, one or more dispatch schedules by applying non-linear economic optimization scheduler to the selected one or more sets of the generated one or more forecast scenarios; and (iv) averaging, by the computer system, the generated one or more dispatch schedules to produce the optimal dispatch schedule.)
Accordingly, as Park and Doherty are directed to various assets and elements’ control and scheduling management technology, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have specifically added the feature of utilizing the well-known technology of dispatching based on one or more modes such as by applying non-linear economic optimization scheduler, as taught by Doherty to the microgrid assets scheduling and control system as taught by Park. One would have been motivated to combine these features because such a combined system/method would have enabled utilizing well-known technique of the art to create optimal dispatching schedule, as evident in Doherty, abstract, 0025, etc.
Claim(s) 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park (KR 102010147 B1 – Translation provided by Applicant via IDS) in view of Sharma (US 9020649 B2).
Regarding claim 14, Park teaches all the elements of claim 8.
However, Park does not explicitly disclose:
wherein the one or more assets dispatched to meet the electrical load are grid following assets.
Sharma explicitly teaches:
wherein the one or more assets dispatched to meet the electrical load are grid following assets. (Abstract, Fig. 1A and C5 para2, and C12 para2 teach “for the grid-tied microgrids which include wind turbine and PV solar panels as generation assets and Li-Ion battery as storage device, the system is optimally designed using HOMER.RTM. with real wind speed, solar radiation, grid electricity price, and load demand data.”. Note, this aligns with the description and examples in applicant specification 0046.)
Accordingly, as Park and Sharma are directed to various assets and elements’ control and scheduling management technology, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have specifically added the feature of utilizing the well-known technology of including the grid-tied assets as part of the optimal design, as taught by Sharma to the microgrid assets scheduling and control system as taught by Park. One would have been motivated to combine these features because such a combined system/method would have enabled utilizing well-known feature of the art such as a real-time management framework for a grid-tied microgrid based on storage life and cost estimation, as evident in Sharma, abstract, Fig. 1A, C5 para2, and C12 para2, etc.
Claim(s) 16-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park (KR 102010147 B1 – Translation provided by Applicant via IDS) in view of Carr (US 20180191160 A1) in further view of Varadarajan (US 20170288413 A1).
Regarding claim 16, Park teaches all the elements of claim 15.
However, Park does not explicitly disclose:
wherein one or more energy storage systems are prioritized to be dispatched to meet the differential load based on a state of charge and a state of energy of the one or more energy storage systems.
Carr explicitly teaches:
wherein one or more energy storage systems are prioritized to be dispatched to meet the differential load based on a state of charge … of the one or more energy storage systems. (Abstract, and 0027 teach “the priority of charging and discharging the ESS have been moved depending on whether or not the energy storage state of charge (SOC) is less than or greater than 60%.”. See also the impact of exemplary conditions in table 2 and 0028.)
Accordingly, as Park and Carr are directed to various assets and elements’ control and scheduling management technology, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have specifically added the feature of utilizing the well-known technology of prioritizing based on SOC conditions, as taught by Carr to the microgrid assets scheduling and control system as taught by Park. One would have been motivated to combine these features because such a combined system/method would have enabled utilizing well-known technique of the art to include a validity check in the priority list to assist in determining whether an action can be taken, as evident in Carr, abstract, 0027, etc.
However, Park and Carr do not explicitly disclose:
[wherein one or more energy storage systems are prioritized to be dispatched to meet the differential load based on a state of charge] and a state of energy [of the one or more energy storage systems.]
Varadarajan explicitly teaches:
[wherein one or more energy storage systems are prioritized to be dispatched to meet the differential load based on a state of charge] and a state of energy [of the one or more energy storage systems.] (Abstract, Fig. 6, 0060-63 and 0068-70 teach control for optimal charge and discharge levels. More specifically, see 0069 teaches “the energy storage system provides the load requirement (300 KW), while the PV system and Diesel gen sets are shutdown, thereby prioritizing the discharge of the energy storage system to reach a preferred state-of-energy (e.g., L3 or L4).”.)
Accordingly, as Park and Varadarajan are directed to various assets and elements’ control and scheduling management technology, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have specifically added the feature of utilizing the well-known technology of prioritizing based on state-of-energy conditions, as taught by Varadarajan to the microgrid assets scheduling and control system that includes prioritization based on SOC conditions as taught by Park and Carr. One would have been motivated to combine these features because such a combined system/method would have enabled utilizing well-known technique of the art to prioritize charging and discharging of the storage system(s) based on state-of-energy conditions as additional conditions used to subsequently control the power generation of the EG system, as evident in Varadarajan, abstract, 0006, 0069, etc.
Regarding claim 17, Park, Carr, and Varadarajan teach all the elements of claim 16.
Carr and Varadarajan further teach:
wherein the energy storage systems are reduced in priority if a state of charge and state of energy of the energy storage system is below an optimal threshold. (Carr: As above, see abstract, and 0027 teach “the priority of charging and discharging the ESS have been moved depending on whether or not the energy storage state of charge (SOC) is less than or greater than 60%.”. See also the impact of exemplary conditions in table 2 and 0028. 0028 provides the example, “However, if SOC is below 60% this action is no longer valid at this action number. The system would skip it and consider the next action, shedding the Loads. This action is valid, untaken, and would result in the desired effect of decreasing the power, so it would be taken.” Varadarajan: As above, see Fig. 6, 0060-63 and 0068-70 teach control for optimal charge and discharge levels where state-of-energy is an additional condition for the prioritization-based control scheme.)
Accordingly, motivation to combine the teachings would have been dictated by the similar reasons as stated above. In addition, using these conditional validity values, the user would have ensured that the energy storage charge is conserved when less energy is available, as evident in Carr, 0028.
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park (KR 102010147 B1 – Translation provided by Applicant via IDS) in view of Carr (US 20180191160 A1) in further view of Varadarajan (US 20170288413 A1) in further view of Wells (US 11289907 B1).
Regarding claim 18, Park, Carr, and Varadarajan teach all the elements of claim 17.
While Park, Carr, and Varadarajan teach state of charge (SOC) and state-of-energy conditions-based prioritization of energy storage system(s) as part of the control actions as cited above,
Park, Carr, and Varadarajan do not explicitly disclose the specific control action in the following limitation:
wherein the controller is configured to not place the energy storage systems on the microgrid system [based on a state of charge and state of energy of the energy storage system being below a minimum threshold.]
Wells explicitly disclose:
wherein the controller is configured to not place the energy storage systems on the microgrid system [based on a state of charge and state of energy of the energy storage system being below a minimum threshold.] (C8 para2 teaches, “In some variations, the load scheduling can be performed for islanding scenario. Under islanding, the load scheduling meets the following objectives: minimizing load curtailment while ensuring maximum up time of the microgrid (battery State of Charge (SOC) included), priority or ranking of loads capable of curtailment, and the fairness factor.”)
Accordingly, as Park, Carr, Varadarajan and Wells are directed to various assets and elements’ control and scheduling management technology, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have specifically added the feature of utilizing the well-known technology of objective based conditional control of elements including energy storage system(s) for load scheduling for islanding scenario, as taught by Wells to the microgrid assets scheduling and control system that includes prioritization based on SOC and state-of-energy conditions as taught by Park, Carr, and Varadarajan. One would have been motivated to combine these features because such a combined system/method would have enabled utilizing well-known technique of the art to implement control actions for load scheduling that meets all the relevant objectives, as evident in Wells, abstract, C8 para2, etc.
Claim(s) 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park (KR 102010147 B1 – Translation provided by Applicant via IDS) in view of Carr (US 20180191160 A1) in further view of Varadarajan (US 20170288413 A1) in further view of Martinez (US 20220215486 A1).
Regarding claim 20, Park, Carr, and Varadarajan teach all the elements of claim 16.
However, Park, Carr, and Varadarajan do not explicitly disclose:
wherein the expected power generation of one or more renewable energy resource assets is based on data related to one or more of average cloud cover, historical weather data, and historical wind speed data.
Martinez explicitly teaches:
wherein the expected power generation of one or more renewable energy resource assets is based on data related to one or more of average cloud cover, historical weather data, and historical wind speed data. (Abstract, and 0076 teach accurate forecasts are essential in any system that has renewable resources and energy storage capabilities, as the value of energy and power changes over time. 0147 teach forecasting techniques that are used for an asset manager to control distribution of power within an aggregated distributed energy resources system may include forecasting that can be done using historical data, and in others it can be done using external inputs such as weather forecast services. Note, weather forecast services provide data regarding the state of the atmosphere in a given location and comprehensive forecasts typically include temperature, precipitation, wind speed and direction, humidity, atmospheric pressure, and cloud cover.)
Accordingly, as Park, Carr, Varadarajan, and Martinez are directed to various assets and elements’ control and scheduling management technology, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have specifically added the feature of utilizing the well-known technology of weather forecast based dispatching of energy resources including renewable resources, as taught by Martinez to the microgrid assets scheduling and control system as taught by Park, Carr, and Varadarajan. One would have been motivated to combine these features because such a combined system/method would have enabled utilizing well-known technique of the art to provide accurate forecasts as one of the several ways to improve DER response, as evident in Martinez, abstract, 0075-76, 0147, etc.
It is noted that any citation to specific pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. “The use of patents as references is not limited to what the patentees describe as their own inventions or to the problems with which they are concerned. They are part of the literature of the art, relevant for all they contain.” In re Heck, 699 F.2d 1331, 1332-33, 216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009,158 USPQ 275, 277 (CCPA 1968)). Further, a reference may be relied upon for all that it would have reasonably suggested to one having ordinary skill the art, including nonpreferred embodiments. Merck & Co. v. Biocraft Laboratories, 874 F.2d 804, 10 USPQ2d 1843 (Fed. Cir.), cert, denied, 493 U.S. 975 (1989). See also Upsher-Smith Labs. v. Pamlab, LLC, 412 F.3d 1319, 1323, 75 USPQ2d 1213, 1215 (Fed. Cir. 2005) (reference disclosing optional inclusion of a particular component teaches compositions that both do and do not contain that component); Celeritas Technologies Ltd. v. Rockwell International Corp., 150 F.3d 1354, 1361, 47 USPQ2d 1516, 1522-23 (Fed. Cir. 1998).
Pertinent Art(s)
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Izumi et al. (US 20220311261 A1) is related to a battery cellar that includes a storage cabinet that stores a plurality of batteries, a power converter (an AC/DC converter and a DC/DC converter) electrically connected between the plurality of batteries stored in the storage cabinet and a power system to perform a bidirectional power conversion operation, and a server that controls the power converter to charge or discharge the plurality of batteries in response to a DR request from the power system. The server, based on a level of demand determined in accordance with a rank related to a degradation degree of a battery, suppresses the charging/discharging of a battery with a higher demand rank among the plurality of batteries as compared with the charging/discharging of a battery with a lower demand rank among the plurality of batteries. … When the SOC of a used battery 9 among the used batteries 9 with a higher demand rank is within the SOC range in which the degradation progresses moderately (YES in S34), the server 20 opens the relays 213 corresponding to the used battery 9 so as to electrically disconnect the used battery 9 from the power system 5 (S35).
Conclusion
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/MARZIA T MONTY/Examiner, Art Unit 2117
/ROBERT E FENNEMA/ Supervisory Patent Examiner, Art Unit 2117
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