DETAILED ACTION
Claims 1-2, 4, 6-7, 10-11, 14, 16 and 18-28 are presented for examination. This office action is response to the submission on 1/17/2024.
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
The information disclosure statement (IDS) submitted on 1/17/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Drawings
The drawings filed on 1/17/2024 are acceptable for examination proceedings.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-2, 4, 6-7, 10-11, 14, 16, 18, 23-24 and 26-28 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Batterberry et al. (US20100138363A1).
Claim 1:
Batterberry teaches “A system for connecting an electrical appliance to an electrical grid, the system comprising: a switch module configured to electrically connect the electrical appliance and the electrical grid;” (Batterberry teaches controlling appliances 270 via smart plugs 285 in Batterberry [0039] "When using energy usage profiles 250, the energy consumer 210 responds to real-time or future forecast pricing by using a profile-based control module 265 to control attached electronics, such as, for example, appliances 270, electronic devices, hybrid-electric vehicles (HEV) 280, etc. Control of such electronics is provided either directly, in the case of “smart” electronics that include network-based control capabilities, or via “smart plugs” (285, 290, 295) between the electrical outlet and the device being controlled. It should also be noted that in various embodiments, the smart plugs (285, 290, 295) can act in direct response to pricing signals received via the smart meter 240, via the Internet or other network 260, or via the user interface 255, to turn particular devices on or off, or to adjust the energy expenditures of such devices. See Section 2.5 for a detailed discussion of “smart plugs."; Batterberry Fig. 2 teaches the appliances being connected to an energy provider i.e. an electrical grid
[AltContent: rect]
PNG
media_image1.png
851
616
media_image1.png
Greyscale
),
“and a processing system configured to: compare a current electricity price for the electrical grid to a statistical quantity representing electricity prices for the electrical grid over a period;” (Batterberry teaches that the smart grid pricer delivers future forecasted prices to smart meter 240 and that the consumer side of the smart grid pricer reacts to pricing information in Batterberry [0064] "In general, by forecasting an appropriate energy price based both on predicted future supplies and the resulting forecast demands, prices can be set at optimal levels, as discussed in Section 2.2. The Smart Grid Pricer securely delivers this customized pricing information to the consumer's premise (e.g., the “smart meter” or Smart Grid Pricer elements at the consumer's home). The consumer side of the Smart Grid Pricer then automatically reacts to the real-time pricing information to drive demand, as discussed herein."; Batterberry teaches that the consumer side of the smart grid pricer system allows a user to set a threshold for a price that allows power to be provided to an appliance and teaches a rules engine may evaluate inputs such as current and future energy pricing i.e. a statistical quantity representing electricity prices for the grid over a period to automatically control appliances in Batterberry [0054-0055] "On the consumer side of the Smart Grid Pricer system, electricity consumers make use of the Smart Grid Pricer in combination with appropriate connected energy consuming devices to automatically react to the pricing signals. In particular, in various embodiments, the consumer side of the Smart Grid Pricer includes an internet or network-based application service for consumers to define and remotely update their energy consumption preferences. Such preferences include, for example, automatically managing consumer energy usage (e.g., discretionary appliances, tolerable temperatures for heating, cooling, water heaters, etc), setting thresholds for pricing for individual appliances (e.g., allow the A/C to run when pricing drops below the threshold), electronic car consumption patterns (e.g., charge car batteries or use electricity to generate hydrogen for the car from a natural gas source or electrolysis of water), energy consumption based on the consumer's budget, etc. In other words, Smart Grid Pricer provides the energy consumer (e.g., individual homeowners, businesses, etc.) with the capability to granularly define the behavior of electronic devices, appliances, etc.Further, in controlling various devices and appliances on the consumer side, various embodiments of the Smart Grid Pricer include a “rules engine” that evaluates various inputs to automatically control appliances and other energy consuming devices. These inputs include, but are not limited to: consumer preferences; current and forecast weather; current time; historical and current energy usage; current and forecast pricing of electricity and other energy sources, such as natural gas or heating oil; tiered pricing implications (e.g., price differences for predefined amounts or blocks of energy used per month); thermal characteristics of the home or business; historical usage patterns; current and forecast occupant presence and schedules; characteristics of Heating Ventilation and Air Conditioning (HVAC) equipment; allocated budget, etc."),
“and based on the comparison, operate the switch module to control the transfer of electricity between the electrical grid and the electrical appliance.” (Batterberry teaches that if a price threshold is exceeded, the smart grid pricer may automatically turn off an air conditioner i.e. an appliance in Batterberry [0014] "A simple example of some of these concepts is an automated control for a particular consumer that will automatically turn down (or turn off) an air conditioner when the price of electricity reported to the consumer by the Smart Grid Pricer exceeds some pre-determined threshold."; Batterberry teaches that current and future predicted price may be used to control appliances e.g. based on a comparison between future and current price, the appliance may have power provided or not provided in Batterberry [0093-0094] "Clearly, there are a large number of factors that can be considered in an attempt to automatically optimize various energy usage profiles. Following is a list of a number of such factors. However, it should be understood that the following list is not intended to be an exclusive list, as it simply summarizes some of the many parameters that may be considered for optimizing energy management in the home, business, or other premise: Current and future predicted price of electricity, and the time and rate of change between them;").
Claim 2:
Batterberry teaches “The system of claim 1, wherein the processing system is configured to operate the switch module to (1) either allow or impede the transfer of electricity between the electrical grid and the electrical appliance” (Batterberry teaches that smart plugs 285 turn devices on or off i.e. allow or impede transfer of electricity between the electrical grid and the appliance in Batterberry [0039] "When using energy usage profiles 250, the energy consumer 210 responds to real-time or future forecast pricing by using a profile-based control module 265 to control attached electronics, such as, for example, appliances 270, electronic devices, hybrid-electric vehicles (HEV) 280, etc. Control of such electronics is provided either directly, in the case of “smart” electronics that include network-based control capabilities, or via “smart plugs” (285, 290, 295) between the electrical outlet and the device being controlled. It should also be noted that in various embodiments, the smart plugs (285, 290, 295) can act in direct response to pricing signals received via the smart meter 240, via the Internet or other network 260, or via the user interface 255, to turn particular devices on or off, or to adjust the energy expenditures of such devices. See Section 2.5 for a detailed discussion of “smart plugs.””), and
“and/or (2) increase or decrease the transfer of electricity between the electrical grid and the electrical appliance.” (Batterberry teaches that smart plugs 285 turn devices on or off i.e. turning the device on would increase the transfer of electricity between the electrical grid and the appliance and turning the device off would decrease it in Batterberry [0039] "When using energy usage profiles 250, the energy consumer 210 responds to real-time or future forecast pricing by using a profile-based control module 265 to control attached electronics, such as, for example, appliances 270, electronic devices, hybrid-electric vehicles (HEV) 280, etc. Control of such electronics is provided either directly, in the case of “smart” electronics that include network-based control capabilities, or via “smart plugs” (285, 290, 295) between the electrical outlet and the device being controlled. It should also be noted that in various embodiments, the smart plugs (285, 290, 295) can act in direct response to pricing signals received via the smart meter 240, via the Internet or other network 260, or via the user interface 255, to turn particular devices on or off, or to adjust the energy expenditures of such devices. See Section 2.5 for a detailed discussion of “smart plugs.”").
Claim 4:
Batterberry teaches “The system of claim 1, wherein, if the current electricity price is less than the statistical quantity, the processing system is configured to operate the switch module to allow or increase a supply of electricity by the electrical grid to the electrical appliance for powering the electrical appliance,” (Batterberry teaches when using energy usage profiles 250, smart plugs 285 may be controlled in response to pricing signals i.e. if the price is low, it will enable appliances in Batterberry [0039] "When using energy usage profiles 250, the energy consumer 210 responds to real-time or future forecast pricing by using a profile-based control module 265 to control attached electronics, such as, for example, appliances 270, electronic devices, hybrid-electric vehicles (HEV) 280, etc. Control of such electronics is provided either directly, in the case of “smart” electronics that include network-based control capabilities, or via “smart plugs” (285, 290, 295) between the electrical outlet and the device being controlled. It should also be noted that in various embodiments, the smart plugs (285, 290, 295) can act in direct response to pricing signals received via the smart meter 240, via the Internet or other network 260, or via the user interface 255, to turn particular devices on or off, or to adjust the energy expenditures of such devices. See Section 2.5 for a detailed discussion of “smart plugs.”"; Batterberry teaches that profiles trigger on/off states or settings of devices on pre-set schedules or events in Batterberry [0082] "In an ideal energy usage scenario, daily operational tasks required of the homeowner to optimize energy usage are strictly minimized and preferably eliminated. Consequently, in various embodiments, the Smart Grid Pricer provides a set of one or more standard energy “profiles” from which the user can select and customize, if desired. In general, these energy profiles allow the Smart Grid Pricer to intelligently trigger on/off states or settings of various devices (via the aforementioned “smart plugs”) based either on pre-set schedules or through events such as a determination that everyone has left the house."; Batterberry teaches that current and future predicted price of electricity may be used to optimize energy profiles in Batterberry [0092-0093] "Clearly, there are a large number of factors that can be considered in an attempt to automatically optimize various energy usage profiles. Following is a list of a number of such factors. However, it should be understood that the following list is not intended to be an exclusive list, as it simply summarizes some of the many parameters that may be considered for optimizing energy management in the home, business, or other premise: Current and future predicted price of electricity, and the time and rate of change between them;"), and
“or wherein, if the current electricity price is greater than the statistical quantity, the processing system is configured to operate the switch module to impede or reduce a supply of electricity by the electrical grid to the electrical appliance.” (Batterberry teaches when using energy usage profiles 250, smart plugs 285 may be controlled in response to pricing signals i.e. if the price is high, it will disable appliances in Batterberry [0039] "When using energy usage profiles 250, the energy consumer 210 responds to real-time or future forecast pricing by using a profile-based control module 265 to control attached electronics, such as, for example, appliances 270, electronic devices, hybrid-electric vehicles (HEV) 280, etc. Control of such electronics is provided either directly, in the case of “smart” electronics that include network-based control capabilities, or via “smart plugs” (285, 290, 295) between the electrical outlet and the device being controlled. It should also be noted that in various embodiments, the smart plugs (285, 290, 295) can act in direct response to pricing signals received via the smart meter 240, via the Internet or other network 260, or via the user interface 255, to turn particular devices on or off, or to adjust the energy expenditures of such devices. See Section 2.5 for a detailed discussion of “smart plugs.”").
Claim 6:
Batterberry teaches “The system of claim 1, wherein the statistical quantity comprises a rolling average of electricity prices for the electrical grid over the period.” (Batterberry teaches that future energy pricing is computed and includes start and end times of those prices i.e. the future energy pricing is an average for the time period in Batterberry [0051] "Note that in various embodiments, the computed energy price varies continuously over time, or is fixed for some period (e.g., seconds, minutes, or hours), depending upon current demand conditions. Consequently, in such embodiments, expiration times associated with real-time prices are reported to the consumer along with the current price. In related embodiments, future energy pricing is computed and reported to consumers by forecasting energy demand at future times based on the same or similar criteria as used for computation of real-time energy pricing. In such cases, the future prices are reported to consumers along with the start and end times of those prices. Note that such pricing may be provided to the consumer as best guess type estimates rather than fixed prices, if desired, since unknown future events (e.g., storms, power generation failures, etc.) may change the energy demand picture.").
Claim 7:
Batterberry teaches “The system of claim 6, wherein the period (1) immediately precedes or immediately follows the time in which the current electricity price applies (Batterberry teaches that future energy pricing is computed and includes start and end times of those prices i.e. the future energy pricing follows the time of the current electricity price in Batterberry [0051] "Note that in various embodiments, the computed energy price varies continuously over time, or is fixed for some period (e.g., seconds, minutes, or hours), depending upon current demand conditions. Consequently, in such embodiments, expiration times associated with real-time prices are reported to the consumer along with the current price. In related embodiments, future energy pricing is computed and reported to consumers by forecasting energy demand at future times based on the same or similar criteria as used for computation of real-time energy pricing. In such cases, the future prices are reported to consumers along with the start and end times of those prices. Note that such pricing may be provided to the consumer as best guess type estimates rather than fixed prices, if desired, since unknown future events (e.g., storms, power generation failures, etc.) may change the energy demand picture.").
Claim 10:
Batterberry teaches “The system of claim 1, wherein, to compare the current electricity price to the statistical quantity, the processing system is configured to compare a difference between the current electricity price and the statistical quantity to an index threshold.” (Batterberry teaches setting a threshold for pricing for appliances that only allow an appliance to run when pricing is below a threshold e.g. if the future energy price is higher, it may enable the appliance and disable the appliance if the future energy price is lower in Batterberry [0054] "On the consumer side of the Smart Grid Pricer system, electricity consumers make use of the Smart Grid Pricer in combination with appropriate connected energy consuming devices to automatically react to the pricing signals. In particular, in various embodiments, the consumer side of the Smart Grid Pricer includes an internet or network-based application service for consumers to define and remotely update their energy consumption preferences. Such preferences include, for example, automatically managing consumer energy usage (e.g., discretionary appliances, tolerable temperatures for heating, cooling, water heaters, etc), setting thresholds for pricing for individual appliances (e.g., allow the A/C to run when pricing drops below the threshold), electronic car consumption patterns (e.g., charge car batteries or use electricity to generate hydrogen for the car from a natural gas source or electrolysis of water), energy consumption based on the consumer's budget, etc. In other words, Smart Grid Pricer provides the energy consumer (e.g., individual homeowners, businesses, etc.) with the capability to granularly define the behavior of electronic devices, appliances, etc.").
Claim 11:
Batterberry teaches “The system of claim 1, wherein, to compare the current electricity price to the statistical quantity, the processing system is configured to: determine a price index based on the current electricity price and the statistical quantity; and compare the price index to a price index threshold.” (Batterberry teaches setting a threshold for pricing for appliances that only allow an appliance to run when pricing is below a threshold e.g. if the future energy price is higher, it may enable the appliance and disable the appliance if the future energy price is lower in Batterberry [0054] "On the consumer side of the Smart Grid Pricer system, electricity consumers make use of the Smart Grid Pricer in combination with appropriate connected energy consuming devices to automatically react to the pricing signals. In particular, in various embodiments, the consumer side of the Smart Grid Pricer includes an internet or network-based application service for consumers to define and remotely update their energy consumption preferences. Such preferences include, for example, automatically managing consumer energy usage (e.g., discretionary appliances, tolerable temperatures for heating, cooling, water heaters, etc), setting thresholds for pricing for individual appliances (e.g., allow the A/C to run when pricing drops below the threshold), electronic car consumption patterns (e.g., charge car batteries or use electricity to generate hydrogen for the car from a natural gas source or electrolysis of water), energy consumption based on the consumer's budget, etc. In other words, Smart Grid Pricer provides the energy consumer (e.g., individual homeowners, businesses, etc.) with the capability to granularly define the behavior of electronic devices, appliances, etc."; Batterberry teaches that the current and future price of electricity may be used to optimize the profile which controls the appliances in Batterberry [0092-0093] "Clearly, there are a large number of factors that can be considered in an attempt to automatically optimize various energy usage profiles. Following is a list of a number of such factors. However, it should be understood that the following list is not intended to be an exclusive list, as it simply summarizes some of the many parameters that may be considered for optimizing energy management in the home, business, or other premise: Current and future predicted price of electricity, and the time and rate of change between them;").
Claim 14:
Batterberry teaches “The system of claim 10, wherein the index threshold is (Batterberry teaches that the current and future price of electricity may be used to optimize the profile which controls the appliances i.e. it sets a dynamic threshold based on price in Batterberry [0092-0093] "Clearly, there are a large number of factors that can be considered in an attempt to automatically optimize various energy usage profiles. Following is a list of a number of such factors. However, it should be understood that the following list is not intended to be an exclusive list, as it simply summarizes some of the many parameters that may be considered for optimizing energy management in the home, business, or other premise: Current and future predicted price of electricity, and the time and rate of change between them;"), and
“and wherein the processing system is configured to set the index threshold based on an urgency for the electrical appliance to consume electricity from the electrical grid.” (Batterberry teaches assigning a priority to appliances i.e. if an appliance has a higher priority, its threshold for disabling power to the appliance may be a higher price than an appliance with a lower priority in Batterberry [0114] "For example, in the case where the consumer defines particular energy cost caps in combination with device prioritization, as the price of energy increases, the Smart Grid Pricer can perform automated operations such as, for example, ensuring that a high priority freezer maintains a particular temperature, while diming or turning off low priority lights or other devices such as air-conditioning or other appliances. Such automated operations allow the consumer side of the Smart Grid Pricer to maintain total energy usage or costs below the consumer-defined cap without requiring the consumer to interact directly with any of those devices."; Batterberry additionally teaches that a user may manually override the control of the smart grid pricer i.e. the urgency of the appliance is such that it always consumes electricity in Batterberry [0075] "Note that “smart plug” type technology may also be directly integrated into various devices rather than being connected inline between the device and the power source. In general, the optional “smart plug” component of the Smart Grid Pricer is a low energy device that does not significantly increase energy usage. Further, in various embodiments, these smart plugs include a manual override option to temporarily or permanently bypass either or both centralized control by the Smart Grid Pricer or reporting to the Smart Grid Pricer.").
Claim 16:
Batterberry teaches “The system of claim 1, wherein the statistical quantity is determined from (Batterberry teaches that future energy pricing is computed and includes start and end times of those prices in Batterberry [0051] "Note that in various embodiments, the computed energy price varies continuously over time, or is fixed for some period (e.g., seconds, minutes, or hours), depending upon current demand conditions. Consequently, in such embodiments, expiration times associated with real-time prices are reported to the consumer along with the current price. In related embodiments, future energy pricing is computed and reported to consumers by forecasting energy demand at future times based on the same or similar criteria as used for computation of real-time energy pricing. In such cases, the future prices are reported to consumers along with the start and end times of those prices. Note that such pricing may be provided to the consumer as best guess type estimates rather than fixed prices, if desired, since unknown future events (e.g., storms, power generation failures, etc.) may change the energy demand picture.").
Claim 18:
Batterberry teaches “The system of claim 16, wherein the statistical quantity is further determined from the current electricity price.” (Batterberry teaches that the current and future price of electricity may be used to optimize the profile which controls the appliances in Batterberry [0092-0093] "Clearly, there are a large number of factors that can be considered in an attempt to automatically optimize various energy usage profiles. Following is a list of a number of such factors. However, it should be understood that the following list is not intended to be an exclusive list, as it simply summarizes some of the many parameters that may be considered for optimizing energy management in the home, business, or other premise: Current and future predicted price of electricity, and the time and rate of change between them;").
Claim 23:
Batterberry teaches “The system of claim 1, wherein the electrical appliance comprises a water heater.” (Batterberry teaches controlling a water heater in Batterberry [0054] "On the consumer side of the Smart Grid Pricer system, electricity consumers make use of the Smart Grid Pricer in combination with appropriate connected energy consuming devices to automatically react to the pricing signals. In particular, in various embodiments, the consumer side of the Smart Grid Pricer includes an internet or network-based application service for consumers to define and remotely update their energy consumption preferences. Such preferences include, for example, automatically managing consumer energy usage (e.g., discretionary appliances, tolerable temperatures for heating, cooling, water heaters, etc), setting thresholds for pricing for individual appliances (e.g., allow the A/C to run when pricing drops below the threshold), electronic car consumption patterns (e.g., charge car batteries or use electricity to generate hydrogen for the car from a natural gas source or electrolysis of water), energy consumption based on the consumer's budget, etc. In other words, Smart Grid Pricer provides the energy consumer (e.g., individual homeowners, businesses, etc.) with the capability to granularly define the behavior of electronic devices, appliances, etc.").
Claim 24:
Batterberry teaches “The system of claim 23, wherein the processing system is configured to operate the switch module based on: the comparison of the current electricity price to the statistical quantity; and an urgency for the water heater to heat water.” (Batterberry teaches that current and future predicted price may be used to control appliances e.g. based on a comparison between future and current price, the appliance may have power provided or not provided in Batterberry [0093-0094] "Clearly, there are a large number of factors that can be considered in an attempt to automatically optimize various energy usage profiles. Following is a list of a number of such factors. However, it should be understood that the following list is not intended to be an exclusive list, as it simply summarizes some of the many parameters that may be considered for optimizing energy management in the home, business, or other premise: Current and future predicted price of electricity, and the time and rate of change between them;"; Batterberry teaches assigning a priority to appliances i.e. if a water heater has a higher priority, its threshold for disabling power to the appliance may be a higher price than an appliance with a lower priority in Batterberry [0114] "For example, in the case where the consumer defines particular energy cost caps in combination with device prioritization, as the price of energy increases, the Smart Grid Pricer can perform automated operations such as, for example, ensuring that a high priority freezer maintains a particular temperature, while diming or turning off low priority lights or other devices such as air-conditioning or other appliances. Such automated operations allow the consumer side of the Smart Grid Pricer to maintain total energy usage or costs below the consumer-defined cap without requiring the consumer to interact directly with any of those devices.").
Claim 26:
Batterberry teaches “The system of claim 1, wherein the electrical appliance comprises an energy storage device.” (Batterberry teaches controlling a water heater (Examiner notes that in paragraph [0065] of applicant's specification, applicant states that a water heater may be interpreted as storing energy); additionally Batterberry teaches control of charging for a car battery in Batterberry [0054] "On the consumer side of the Smart Grid Pricer system, electricity consumers make use of the Smart Grid Pricer in combination with appropriate connected energy consuming devices to automatically react to the pricing signals. In particular, in various embodiments, the consumer side of the Smart Grid Pricer includes an internet or network-based application service for consumers to define and remotely update their energy consumption preferences. Such preferences include, for example, automatically managing consumer energy usage (e.g., discretionary appliances, tolerable temperatures for heating, cooling, water heaters, etc), setting thresholds for pricing for individual appliances (e.g., allow the A/C to run when pricing drops below the threshold), electronic car consumption patterns (e.g., charge car batteries or use electricity to generate hydrogen for the car from a natural gas source or electrolysis of water), energy consumption based on the consumer's budget, etc. In other words, Smart Grid Pricer provides the energy consumer (e.g., individual homeowners, businesses, etc.) with the capability to granularly define the behavior of electronic devices, appliances, etc.").
Claim 27:
Batterberry teaches “A method for connecting an electrical appliance to an electrical grid, the method comprising: providing a switch module configured to electrically connect the electrical appliance and the electrical grid;” (Batterberry teaches controlling appliances 270 via smart plugs 285 in Batterberry [0039] "When using energy usage profiles 250, the energy consumer 210 responds to real-time or future forecast pricing by using a profile-based control module 265 to control attached electronics, such as, for example, appliances 270, electronic devices, hybrid-electric vehicles (HEV) 280, etc. Control of such electronics is provided either directly, in the case of “smart” electronics that include network-based control capabilities, or via “smart plugs” (285, 290, 295) between the electrical outlet and the device being controlled. It should also be noted that in various embodiments, the smart plugs (285, 290, 295) can act in direct response to pricing signals received via the smart meter 240, via the Internet or other network 260, or via the user interface 255, to turn particular devices on or off, or to adjust the energy expenditures of such devices. See Section 2.5 for a detailed discussion of “smart plugs."; Batterberry Fig. 2 [As shown above in claim 1] teaches the appliances being connected to an energy provider i.e. an electrical grid),
“comparing a current electricity price for the electrical grid to a statistical quantity representing electricity prices for the electrical grid over a period;” (Batterberry teaches that the smart grid pricer delivers future forecasted prices to smart meter 240 and that the consumer side of the smart grid pricer reacts to pricing information in Batterberry [0064] "In general, by forecasting an appropriate energy price based both on predicted future supplies and the resulting forecast demands, prices can be set at optimal levels, as discussed in Section 2.2. The Smart Grid Pricer securely delivers this customized pricing information to the consumer's premise (e.g., the “smart meter” or Smart Grid Pricer elements at the consumer's home). The consumer side of the Smart Grid Pricer then automatically reacts to the real-time pricing information to drive demand, as discussed herein."; Batterberry teaches that the consumer side of the smart grid pricer system allows a user to set a threshold for a price that allows power to be provided to an appliance and teaches a rules engine may evaluate inputs such as current and future energy pricing i.e. a statistical quantity representing electricity prices for the grid over a period to automatically control appliances in Batterberry [0054-0055] "On the consumer side of the Smart Grid Pricer system, electricity consumers make use of the Smart Grid Pricer in combination with appropriate connected energy consuming devices to automatically react to the pricing signals. In particular, in various embodiments, the consumer side of the Smart Grid Pricer includes an internet or network-based application service for consumers to define and remotely update their energy consumption preferences. Such preferences include, for example, automatically managing consumer energy usage (e.g., discretionary appliances, tolerable temperatures for heating, cooling, water heaters, etc), setting thresholds for pricing for individual appliances (e.g., allow the A/C to run when pricing drops below the threshold), electronic car consumption patterns (e.g., charge car batteries or use electricity to generate hydrogen for the car from a natural gas source or electrolysis of water), energy consumption based on the consumer's budget, etc. In other words, Smart Grid Pricer provides the energy consumer (e.g., individual homeowners, businesses, etc.) with the capability to granularly define the behavior of electronic devices, appliances, etc.Further, in controlling various devices and appliances on the consumer side, various embodiments of the Smart Grid Pricer include a “rules engine” that evaluates various inputs to automatically control appliances and other energy consuming devices. These inputs include, but are not limited to: consumer preferences; current and forecast weather; current time; historical and current energy usage; current and forecast pricing of electricity and other energy sources, such as natural gas or heating oil; tiered pricing implications (e.g., price differences for predefined amounts or blocks of energy used per month); thermal characteristics of the home or business; historical usage patterns; current and forecast occupant presence and schedules; characteristics of Heating Ventilation and Air Conditioning (HVAC) equipment; allocated budget, etc."),
“and based on the comparison, operating the switch module to control the transfer of electricity between the electrical grid and the electrical appliance;” (Batterberry teaches that if a price threshold is exceeded, the smart grid pricer may automatically turn off an air conditioner i.e. an appliance in Batterberry [0014] "A simple example of some of these concepts is an automated control for a particular consumer that will automatically turn down (or turn off) an air conditioner when the price of electricity reported to the consumer by the Smart Grid Pricer exceeds some pre-determined threshold."; Batterberry teaches that current and future predicted price may be used to control appliances e.g. based on a comparison between future and current price, the appliance may have power provided or not provided in Batterberry [0093-0094] "Clearly, there are a large number of factors that can be considered in an attempt to automatically optimize various energy usage profiles. Following is a list of a number of such factors. However, it should be understood that the following list is not intended to be an exclusive list, as it simply summarizes some of the many parameters that may be considered for optimizing energy management in the home, business, or other premise: Current and future predicted price of electricity, and the time and rate of change between them;"), and
“wherein the electricity price at a given time comprises the price set by an operator of the electrical grid to purchase from one or more electrical generators enough electricity to meet an expected demand for electricity from the electrical grid at the given time.” (Batterberry teaches that the smart grid pricer 100 sets energy prices to consumers on behalf of energy providers, the price being determined by estimated consumer demand in Batterberry [0027] "More specifically, as illustrated by FIG. 1, the Smart Grid Pricer 100 enables automated balancing of the supply and demand of energy supply and consumption between energy providers (110, 120) and electricity consumers (130, 140, 150). This balance is achieved through an automated market-based approach wherein the Smart Grid Pricer 100 determines, sets, and reports energy prices to the energy consumers (130, 140, 150) in real-time on behalf of the energy providers (110, 120) to drive energy demand and consumption relative to the available energy supply. In various embodiments, real-time pricing is determined by using various probabilistic models to estimate overall consumer demand as a function of factors such as energy price, time of day, region, weather, etc., to compute a price that will result in an energy demand that is closely balanced to the available supply. On the consumer side, various components of the Smart Grid Pricer automatically respond to such pricing information to optimize energy consumption in accordance with a variety of automated and/or user defined rules and preferences."; The electricity that is distributed inherently has to be generated from an electrical generator).
Claim 28:
Batterberry teaches “A switch module for electrically connecting an electrical appliance to an electrical grid,” (Batterberry teaches controlling appliances 270 via smart plugs 285 in Batterberry [0039] "When using energy usage profiles 250, the energy consumer 210 responds to real-time or future forecast pricing by using a profile-based control module 265 to control attached electronics, such as, for example, appliances 270, electronic devices, hybrid-electric vehicles (HEV) 280, etc. Control of such electronics is provided either directly, in the case of “smart” electronics that include network-based control capabilities, or via “smart plugs” (285, 290, 295) between the electrical outlet and the device being controlled. It should also be noted that in various embodiments, the smart plugs (285, 290, 295) can act in direct response to pricing signals received via the smart meter 240, via the Internet or other network 260, or via the user interface 255, to turn particular devices on or off, or to adjust the energy expenditures of such devices. See Section 2.5 for a detailed discussion of “smart plugs."; Batterberry Fig. 2 [As shown above in claim 1] teaches the appliances being connected to an energy provider i.e. an electrical grid),
“the switch module comprising a processing system configured to: compare a current electricity price for the electrical grid to a statistical quantity representing electricity prices for the electrical grid over a period;” (Batterberry teaches that the smart grid pricer delivers future forecasted prices to smart meter 240 and that the consumer side of the smart grid pricer reacts to pricing information in Batterberry [0064] "In general, by forecasting an appropriate energy price based both on predicted future supplies and the resulting forecast demands, prices can be set at optimal levels, as discussed in Section 2.2. The Smart Grid Pricer securely delivers this customized pricing information to the consumer's premise (e.g., the “smart meter” or Smart Grid Pricer elements at the consumer's home). The consumer side of the Smart Grid Pricer then automatically reacts to the real-time pricing information to drive demand, as discussed herein."; Batterberry teaches that the consumer side of the smart grid pricer system allows a user to set a threshold for a price that allows power to be provided to an appliance and teaches a rules engine may evaluate inputs such as current and future energy pricing i.e. a statistical quantity representing electricity prices for the grid over a period to automatically control appliances in Batterberry [0054-0055] "On the consumer side of the Smart Grid Pricer system, electricity consumers make use of the Smart Grid Pricer in combination with appropriate connected energy consuming devices to automatically react to the pricing signals. In particular, in various embodiments, the consumer side of the Smart Grid Pricer includes an internet or network-based application service for consumers to define and remotely update their energy consumption preferences. Such preferences include, for example, automatically managing consumer energy usage (e.g., discretionary appliances, tolerable temperatures for heating, cooling, water heaters, etc), setting thresholds for pricing for individual appliances (e.g., allow the A/C to run when pricing drops below the threshold), electronic car consumption patterns (e.g., charge car batteries or use electricity to generate hydrogen for the car from a natural gas source or electrolysis of water), energy consumption based on the consumer's budget, etc. In other words, Smart Grid Pricer provides the energy consumer (e.g., individual homeowners, businesses, etc.) with the capability to granularly define the behavior of electronic devices, appliances, etc.Further, in controlling various devices and appliances on the consumer side, various embodiments of the Smart Grid Pricer include a “rules engine” that evaluates various inputs to automatically control appliances and other energy consuming devices. These inputs include, but are not limited to: consumer preferences; current and forecast weather; current time; historical and current energy usage; current and forecast pricing of electricity and other energy sources, such as natural gas or heating oil; tiered pricing implications (e.g., price differences for predefined amounts or blocks of energy used per month); thermal characteristics of the home or business; historical usage patterns; current and forecast occupant presence and schedules; characteristics of Heating Ventilation and Air Conditioning (HVAC) equipment; allocated budget, etc."; Batterberry teaches the smart grid pricer may be implemented using a computer system in Batterberry [0117] "The Smart Grid Pricer described herein is operational within numerous types of general purpose or special purpose computing system environments or configurations. FIG. 3 illustrates a simplified example of a general-purpose computer system on which various embodiments and elements of the Smart Grid Pricer, as described herein, may be implemented. It should be noted that any boxes that are represented by broken or dashed lines in FIG. 3 represent alternate embodiments of the simplified computing device, and that any or all of these alternate embodiments, as described below, may be used in combination with other alternate embodiments that are described throughout this document."),
“and based on the comparison, operate the switch module to control the transfer of electricity between the electrical grid and the electrical appliance;” (Batterberry teaches that if a price threshold is exceeded, the smart grid pricer may automatically turn off an air conditioner i.e. an appliance in Batterberry [0014] "A simple example of some of these concepts is an automated control for a particular consumer that will automatically turn down (or turn off) an air conditioner when the price of electricity reported to the consumer by the Smart Grid Pricer exceeds some pre-determined threshold."; Batterberry teaches that current and future predicted price may be used to control appliances e.g. based on a comparison between future and current price, the appliance may have power provided or not provided in Batterberry [0093-0094] "Clearly, there are a large number of factors that can be considered in an attempt to automatically optimize various energy usage profiles. Following is a list of a number of such factors. However, it should be understood that the following list is not intended to be an exclusive list, as it simply summarizes some of the many parameters that may be considered for optimizing energy management in the home, business, or other premise: Current and future predicted price of electricity, and the time and rate of change between them;"), and
“wherein the electricity price at a given time comprises the price set by an operator of the electrical grid to purchase from one or more electrical generators enough electricity to meet an expected demand for electricity from the electrical grid at the given time.” (Batterberry teaches that the smart grid pricer 100 sets energy prices to consumers on behalf of energy providers, the price being determined by estimated consumer demand in Batterberry [0027] "More specifically, as illustrated by FIG. 1, the Smart Grid Pricer 100 enables automated balancing of the supply and demand of energy supply and consumption between energy providers (110, 120) and electricity consumers (130, 140, 150). This balance is achieved through an automated market-based approach wherein the Smart Grid Pricer 100 determines, sets, and reports energy prices to the energy consumers (130, 140, 150) in real-time on behalf of the energy providers (110, 120) to drive energy demand and consumption relative to the available energy supply. In various embodiments, real-time pricing is determined by using various probabilistic models to estimate overall consumer demand as a function of factors such as energy price, time of day, region, weather, etc., to compute a price that will result in an energy demand that is closely balanced to the available supply. On the consumer side, various components of the Smart Grid Pricer automatically respond to such pricing information to optimize energy consumption in accordance with a variety of automated and/or user defined rules and preferences."; The electricity that is distributed inherently has to be generated from an electrical generator).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 19-22 and 25 are rejected under 35 U.S.C. 103 as being unpatentable over Batterberry et al. (US20100138363A1), in view of Langton et al. (US20200406778A1).
Claim 19:
Batterberry teaches “The system of claim 1, wherein the electrical appliance is electrically connected to an auxiliary electricity source configured to supply electricity to the electrical appliance and to the electrical grid,” (Batterberry teaches consumer-based power generation 235 i.e. an auxiliary electricity source which may be used to offset energy consumption of the consumer or send the generated energy to the grid i.e. it may supply power to the appliances and grid in Batterberry [0035] "Further, in various embodiments, the energy demand forecast is also based on specific consumer data 230, such as building characteristics, energy consumption devices, local weather conditions, occupancy information, etc. In related embodiments, the energy demand forecast module 220 also considers the input of consumer-based power generation 235, such as solar or wind generated power, for example, that is used to either offset the energy consumption of that energy consumer 210, or is received into the energy grid as excess consumer generated power for use by other consumers.").
Batterberry does not appear to explicitly teach “and wherein the processing system is further configured to alter an amount of electricity supplied by the auxiliary electricity source to the electrical grid by operating the electrical appliance to control its electrical energy consumption.” However, Langton does teach this claim limitation (Langton teaches an electrical vehicle 100 including an energy store 110 which may provide power to an electrical appliance 200 which may be a water heater, and that the system server 500 may power the water heater with electricity from the grid 420 or energy store 110 in order to optimize costs in Langton [0052] "The server system 500 may, based on one or more of the characteristic profiles and boundary conditions, determine, for each of one or more operating periods Δtn, whether it is overall more desirable to power the water heater with electricity drawn from the municipal power grid 420 or from the energy store 110 of the electric vehicle. The system server 500 may, in response to the determination, control the vehicle to discharge electricity to the local power grid 300 for use by the water heater in operating at the energy usage state during the respective operating period, or may otherwise cause the vehicle not to so discharge and the water heater to draw electricity from the municipal power grid 420 instead. As discussed above, this determination may take into account one or more of: cost optimization, renewable energy optimization and carbon emissions optimization, in addition to other desirable boundary conditions that may affect the desirability of one source over another, including local electricity distribution infrastructure conditions."
[AltContent: rect]
PNG
media_image2.png
740
611
media_image2.png
Greyscale
).
Batterberry and Langton are analogous art because they are from the same field of endeavor of supplying power to appliances based on price. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having teachings of Batterberry and Langton before him/her, to modify the teachings of a Smart grid price response service of Batterberry to include the providing of power to an appliance from the grid or an energy store in order to optimize costs of Langton because adding the System for Integrating On-Premises Electric Appliances with Vehicle-To-Grid Electric Vehicles of Langton would allow for improved energy arbitrage and management as described in Langton [0038] “The system server 500 may perform various tasks based on the processing of data, information and/or commands that may have been received by the system server 500. In particular, the system server 500 may control one or more of: the electric appliance 200, the electric vehicle 100 and the local power grid 300, based on the data, information and/or commands received, so as to facilitate the improved energy arbitrage and management.”
Claim 20:
Batterberry in view of Langton teaches “The system of claim 19, wherein, if the current electricity price is lower than the statistical quantity, the processing system is configured to operate the electrical appliance to increase or allow electrical energy consumption by the electrical appliance.” (Batterberry teaches when using energy usage profiles 250, smart plugs 285 may be controlled in response to pricing signals i.e. if the price is low, it will enable appliances, increasing and allowing energy consumption in Batterberry [0039] "When using energy usage profiles 250, the energy consumer 210 responds to real-time or future forecast pricing by using a profile-based control module 265 to control attached electronics, such as, for example, appliances 270, electronic devices, hybrid-electric vehicles (HEV) 280, etc. Control of such electronics is provided either directly, in the case of “smart” electronics that include network-based control capabilities, or via “smart plugs” (285, 290, 295) between the electrical outlet and the device being controlled. It should also be noted that in various embodiments, the smart plugs (285, 290, 295) can act in direct response to pricing signals received via the smart meter 240, via the Internet or other network 260, or via the user interface 255, to turn particular devices on or off, or to adjust the energy expenditures of such devices. See Section 2.5 for a detailed discussion of “smart plugs.”"; Batterberry teaches that profiles trigger on/off states or settings of devices on pre-set schedules or events in Batterberry [0082] "In an ideal energy usage scenario, daily operational tasks required of the homeowner to optimize energy usage are strictly minimized and preferably eliminated. Consequently, in various embodiments, the Smart Grid Pricer provides a set of one or more standard energy “profiles” from which the user can select and customize, if desired. In general, these energy profiles allow the Smart Grid Pricer to intelligently trigger on/off states or settings of various devices (via the aforementioned “smart plugs”) based either on pre-set schedules or through events such as a determination that everyone has left the house."; Batterberry teaches that current and future predicted price of electricity may be used to optimize energy profiles in Batterberry [0092-0093] "Clearly, there are a large number of factors that can be considered in an attempt to automatically optimize various energy usage profiles. Following is a list of a number of such factors. However, it should be understood that the following list is not intended to be an exclusive list, as it simply summarizes some of the many parameters that may be considered for optimizing energy management in the home, business, or other premise: Current and future predicted price of electricity, and the time and rate of change between them;").
Claim 21:
Batterberry in view of Langton teaches “The system of claim 19, wherein, if the current electricity price is greater than the statistical quantity, the processing system is configured to operate the electrical appliance to reduce or stop electrical energy consumption by the electrical appliance.” (Batterberry teaches when using energy usage profiles 250, smart plugs 285 may be controlled in response to pricing signals i.e. if the price is high, it will disable appliances, reducing and stopping energy consumption in Batterberry [0039] "When using energy usage profiles 250, the energy consumer 210 responds to real-time or future forecast pricing by using a profile-based control module 265 to control attached electronics, such as, for example, appliances 270, electronic devices, hybrid-electric vehicles (HEV) 280, etc. Control of such electronics is provided either directly, in the case of “smart” electronics that include network-based control capabilities, or via “smart plugs” (285, 290, 295) between the electrical outlet and the device being controlled. It should also be noted that in various embodiments, the smart plugs (285, 290, 295) can act in direct response to pricing signals received via the smart meter 240, via the Internet or other network 260, or via the user interface 255, to turn particular devices on or off, or to adjust the energy expenditures of such devices. See Section 2.5 for a detailed discussion of “smart plugs.”").
Claim 22:
Batterberry in view of Langton teaches “The system of claim 19, wherein the processing system is further configured to: receive auxiliary supply data indicative of an amount of electricity supplied by the auxiliary electricity source to the electrical appliance; and operate the switch module to control an amount of electricity supplied by the electrical grid to the electrical appliance based on the auxiliary supply data.” (Langton teaches local grid 300 may allocate electricity to appliances, which would create data indicative of the amount of electricity supplied in Langton [0033-0034] "The system server 500 may receive and transmit data, information and/or commands to and from the electric appliance 200 and/or the electric vehicle 100. In some embodiments, the local power grid 300 may be a smart local power grid 300 in which the allocation and supply of electricity within the local power grid 300 to on-premises appliances is controlled by a central control unit 302, which may be a standard processor, such as a central processing unit (CPU), or may be a dedicated processor, such as an application-specific integrated circuit (ASIC) or a field programmable gate array (FPGA). The central control unit 302 may be coupled to a local memory 304, which may be hardware capable of storing information accessible by the central control unit 302, such as a ROM, RAM, hard-drive, CD-ROM, DVD, write-capable, read-only, etc. The local memory 304 may further store a set of instructions included in software that can be implemented by the central control unit 302 to perform the various tasks, either individually or in connection with other components of the local power grid 300, in accordance with the principles discussed herein."; Langton teaches an electrical vehicle 100 including an energy store 110 which may provide power to an electrical appliance 200 which may be a water heater, and that the system server 500 may power the water heater with electricity from the grid 420 or energy store 110 in order based on local distribution conditions i.e. it controls the amount of electricity supplied by the grid to the appliance based on auxiliary supply data in Langton [0052] "The server system 500 may, based on one or more of the characteristic profiles and boundary conditions, determine, for each of one or more operating periods Δtn, whether it is overall more desirable to power the water heater with electricity drawn from the municipal power grid 420 or from the energy store 110 of the electric vehicle. The system server 500 may, in response to the determination, control the vehicle to discharge electricity to the local power grid 300 for use by the water heater in operating at the energy usage state during the respective operating period, or may otherwise cause the vehicle not to so discharge and the water heater to draw electricity from the municipal power grid 420 instead. As discussed above, this determination may take into account one or more of: cost optimization, renewable energy optimization and carbon emissions optimization, in addition to other desirable boundary conditions that may affect the desirability of one source over another, including local electricity distribution infrastructure conditions.").
Claim 25:
Batterberry in view of Langton teaches “The system of claim 24, wherein the urgency depends on the temperature of water stored in the water heater,” (Langton teaches the server 500 determines a temperature minimum profile i.e. if the water temperature is below the minimum, it will enable heating in Langton [0051] "The system server 500 may determine a temperature minimum profile, which correlates minimum temperatures of the stored water in the water heater (or air in the HVAC) that are sufficient for anticipated uses of the water heater (or HVAC), for each point-in-time over the time period. The temperature minimum profile may be determined based on the utility related data, the appliance related data, and/or the vehicle related data."),
“and wherein the processing system is further configured to: receive temperature data indicative of the temperature of water stored in the water heater;” (Langton teaches heating water to the minimum temperature, which would require receiving data indicative of the water temperature in Langton [0055] "The determination of one or more operating periods Δtn may be subject to one or more constraints based on one or more of the characteristic profiles. The determination may be constrained to ensure that the state-of-charge of the vehicle energy store during an operating period is sufficient to operate the water heater to heat water at least to the minimum temperature corresponding to the operating period. The determination may be constrained to ensure that the state-of-charge of the vehicle energy store after discharging to the local power grid 300 is at or above the corresponding minimum state-of-charge. The determination may be constrained by preferred energy performances of the water heater and/or the electric vehicle 100 over the operating periods."), and
“and based on the temperature data, operate the switch module to control the transfer of electricity between the electrical grid and the water heater.” (Langton teaches providing power to an electrical appliance 200 which may be a water heater, and that the system server 500 may power the water heater with electricity from the grid 420 based on characteristic profiles which may include the temperature minimum profile in Langton [0051-0052] "The system server 500 may determine a temperature minimum profile, which correlates minimum temperatures of the stored water in the water heater (or air in the HVAC) that are sufficient for anticipated uses of the water heater (or HVAC), for each point-in-time over the time period. The temperature minimum profile may be determined based on the utility related data, the appliance related data, and/or the vehicle related data. The server system 500 may, based on one or more of the characteristic profiles and boundary conditions, determine, for each of one or more operating periods Δtn, whether it is overall more desirable to power the water heater with electricity drawn from the municipal power grid 420 or from the energy store 110 of the electric vehicle. The system server 500 may, in response to the determination, control the vehicle to discharge electricity to the local power grid 300 for use by the water heater in operating at the energy usage state during the respective operating period, or may otherwise cause the vehicle not to so discharge and the water heater to draw electricity from the municipal power grid 420 instead. As discussed above, this determination may take into account one or more of: cost optimization, renewable energy optimization and carbon emissions optimization, in addition to other desirable boundary conditions that may affect the desirability of one source over another, including local electricity distribution infrastructure conditions.").
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Tinio et al. (US20200387981A1) teaches a stored energy dispatch system with a static price threshold to determine whether to discharge a battery in Tinio [0038-0039] "In one example, the stored energy dispatch system 136 will run on a set, yet dynamic charge schedule. The novel algorithm will run simultaneously and will activate a discharge during the normal charge schedule when: 1. The real-time-price (RTP) is greater than an absolute price threshold, that is: RTP>$xx then discharge the energy storage devices until the RTP falls below the thresh-hold or the energy storage devices run out of charge. This captures any instantaneous price fluctuation."
Yun et al. (KR20110091307A) teaches a smart outlet that receives an electricity price and compares it to a reference in order to determine whether to power the appliance in Yun [0045-0046] "At this time, the standard electricity price that serves as the price basis in the relative electricity price display method means the price of electricity without any discount or surcharge. When displaying the current electricity price using the relative electricity price display method, it is preferable to receive not only the current electricity price but also the standard electricity price information that serves as the basis when receiving the electricity price from the electricity price information providing device (20) through the price information communication unit (11). Alternatively, it may be possible to sample the electricity price received from the Price Information and Communication Department (11) at predetermined intervals (e.g., at 1-hour intervals for 24 hours) for a predetermined period of time, obtain the average of the sampled electricity prices, and use this as the standard electricity price."; Yun teaches that an outlet may stop providing power when price is higher than average or only provide power when it is lower than average in Yun [0079-0080] "When the central control unit (16) is implemented using a microcontroller, the smart grid outlet according to the present invention is controlled by software built into the microcontroller, so there is an advantage in that detailed functions can be easily changed, adjusted, or set as needed. For example, there may be a situation where power should be cut off only when the electricity price is more than 10% higher than the average price using a smart grid outlet according to the present invention, on the other hand, there may be a situation where power should be used only when the electricity price is more than 10% lower than the average price, and there may also be a situation where power should be supplied at all times regardless of the current electricity price. This has the advantage of being able to meet various needs without having to redesign or change the hardware itself, by simply replacing, changing, or setting the software embedded in the microcontroller to suit the situation and needs."
Biehl et al. (DE102011054199A1) teaches a heating device that may switch between an electricity transmitted from a distribution device to a locally provided heating source based on price in Biehl [0021] "According to an advantageous further development of the heating device, the switching device can include a switching enable unit that enables or prevents switching depending on heating device enable parameters, in particular heat energy demand, available fuel quantity, fuel costs or similar. The switching release unit can, for example, release a switchover if an electricity price transmitted by the distribution device for generating a unit of heat energy is lower than a heating fuel price of a locally available heating fuel, such as oil, pellets or wood. Since the price of locally available heating fuel depends on a purchase date in the past, it may be more advantageous for individual heating devices to switch over based on a distributed control signal only when the electricity price has dropped accordingly."
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Zachary A Cain whose telephone number is (571)272-4503. The examiner can normally be reached Mon-Fri 7:00-3:30 CST.
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, Kenneth M Lo can be reached at (571) 272-9774. 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.
/Z.A.C./Examiner, Art Unit 2116
/KENNETH M LO/Supervisory Patent Examiner, Art Unit 2116