DETAILED ACTION
Claims 1-30 (filed 07/23/2026) have been considered in this action. Claims 1-2, 5, 7, 10, 12-14, 17, 19, 24 and 27-28 have been amended. Claims 3-4, 6, 8-9, 11, 15-16, 18, 20-21, and 29 have been canceled. Claims 22-23 and 25-26 have been presented in the same format as previously presented. Claim 30 is newly filed.
Response to Arguments
Applicant’s arguments, see page 13 paragraph 3, filed 07/23/2026, with respect to interpretation of claims under 35 U.S.C. 112(f) have been fully considered and are persuasive. The interpretation of the claims under 35 U.S.C. 112(f) has been withdrawn due to the recitation of proper structure.
Applicant’s arguments, see page 15 paragraph 3, filed 07/23/2026, with respect to rejection of claims 6 and 18 under 35 U.S.C. 112(b) have been fully considered and are persuasive. The rejection of claims 6 and 18 under 35 U.S.C. 112(b) has been withdrawn.
Applicant’s arguments, see page 16 paragraph 1, filed 07/23/2026, with respect to rejection of claims 27-28 under 35 U.S.C. 101 have been fully considered and are persuasive. The rejection of claims 27-28 under 35 U.S.C. 101 has been withdrawn.
Applicant's arguments, see page 16 paragraph 3, filed 07/23/2026 have been fully considered but they are not persuasive.
Applicant has argued that “nothing in Ryuji appears to disclose or suggest that, after recalculation of the optimal power plan, the sum of the calorifiers over a predetermined period must be greater than or equal to a sum of the power usage amounts of the calorifiers according to the simulations performed by the supply-demand planning device”. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., recalculation of the optimal plan) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). The claim only has one single determination of an operation schedule, there is no “recalculation of the optimal power plan”
Based upon the BRI of the claim, the wherein clause of “wherein a sum of the power usage amounts of the heat storage device over a predetermined period is greater than or equal to a sum of the power usage amounts of the heat storage device according to the load prediction” is a circular statement, as the sum of power usage amounts of the heat storage device are always equal to the sum of the power usage amounts of the heat storage device. There is no further clarifying in the claim that the two uses of “sum of the power usage amounts of the heat storage device” are not one and the same, as there is no clarifying statement as to where the source of these data are, nor how they relate to one another. For example, while the first of the “sum of the power usage amounts of the heat storage device” relates to a particular predetermined period, while the second “sum of the power usage amounts of the heat storage device” relates to the load predictions, there is nothing in the claim that disallows a reasonable interpretation of these sums being one and the same. Is the second “sum of the power usage amounts of the heat storage device” for the same predetermined period? What is the source of the first “sum of the power usage amounts of the heat storage device” such that it doesn’t come from the load predictions? The claim is vague and unspecific in how it is performing this wherein clause, such that under the BRI, the examiner considers this claim statement to be circular and self-evident in that a sum of things is equal to the same sum of things, as this is a mathematical law of the universe. In other words, the claim fails to distinguish the relationship between these sums, such that under the BRI, they are considered one and the same.
Secondly, based upon the BRI, the claim only requires that after a power usage amount in a tight time zone is determined, a power usage amount in the tight time zone is reduced to equal or less than a threshold. This is inherently being performed by Ryuji during the process of “[0085] As explained above, the hot water tank temperature control devices 22 can be made to recalculate the heating plan after setting the power price, to a maximum value, of a time period where the planned demand is greater than the optimal demand if such time period exists. Since the heating plan is recalculated to minimize the electric power cost for heating by the hot water tank temperature control devices 22, the heating plan is expected to be corrected to reduce the consumed power of time periods having the raised power price. In this way, the power demand can be brought close to the optimal supply-demand plan” wherein the threshold is the old planned demand value determined via the simulation and thus because the raising of price reduces the demand (i.e. lower power usage by some calorifiers) the sum after the raising of prices will be less than the threshold that was the old demand, because some calorifiers are having their demand reduced. This is in line with what is claimed in how when a tight time zone is determined (i.e. planned demand is greater than planned supply) the price is raised to recalculate an optimal plan that lowers the demand (i.e. reduced power is supplied to the calorifiers). In other words, claim 1 is not specific enough in the process steps it is claiming to overcome the prior art.
Accordingly, the examiner maintains their rejection of the amended claim 1 under 35 U.S.C. 103. See below for a mapping of the amended claim language.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-2, 5, 7, 10, 12-14, 17, 19, 22-23 and 30 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 recites “the communications interface is further configured to… control an operation of the heat storage device based on the operation schedule”. Claim 10 recites “a communications interface configured to…and control an operation of the heat storage device based on the operation schedule”. The written disclosure does not recite nor explain how a communications interface has the capability to control a heat storage device. Based upon the BRI, PHOSITA would understand that a communications interface does not have the capability to control a heat storage device. Accordingly, claims 1 and 10, and all their dependents are rejected under 35 U.S.C. 112(a).
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-2, 5, 7, 10, 12-14, 17, 19 and 22-23 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites “the communications interface is further configured to… control an operation of the heat storage device based on the operation schedule”. Claim 10 recites “a communications interface configured to…and control an operation of the heat storage device based on the operation schedule”. It is unclear how a communications interface is capable of performing the acts of controlling a heat storage device. The specification fails to explain how a communications interface is capable of providing such functionality, and thus the claim is considered unclear and indefinite. Accordingly, claims 1 and 10, and all their dependents are rejected under 35 U.S.C. 112(b).
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.
Claim(s) 1-2, 7, 10, 12-14, 19, 24-28 are rejected under 35 U.S.C. 103 as being unpatentable over Ryuji (US 20130138468, hereinafter Ryuji) in view of Arnold (US 20130327313, hereinafter Arnold).
In regard to Claim 1, Ryuji teaches “A heat storage system control device comprising: a microcomputer having a processor, memory and a communications interface, wherein the communications interface is configured to acquire power supply and demand information from a power control instruction device;” ([0042] The hot water tank temperature control devices 22 are computers provided for each calorifier of the power demander. The hot water tank temperature control devices 22 may be, for example, control boards built in the calorifiers or may be personal computers and PDAs that connect to the calorifiers. [0039] The economical load distribution adjusting device 10 is connected to the water level planning devices 21, the hot water tank temperature control devices 22 and the supply-demand planning device 23 via the communication network 24. The communication network 24 is, for example, the Internet or a LAN (Local Area Network) and is built with a public telephone network, the Ethernet (registered trademark), a wireless communication network or the like; [0040] And the supply-demand planning device 23 calculates the unit cost for power generation (hereinafter "unit power generation cost"), and further calculates the power generation expenses by multiplying the total output by the unit power generation cost and tabulating the result for 24 hours. Thereafter the supply-demand planning device 23 calculates the hydroelectric output that minimizes the power generation expenses (hereinafter "optimal output"), thermal output that minimizes the power generation expenses, output besides those by hydraulic power and thermal power that minimizes the power generation expenses, demand of water heaters that minimizes the power generation expenses (hereinafter "optimal demand"), electrical power consumed by other loads and the like. [0042] The hot water tank temperature control devices 22 are also provided hourly power prices for calculating the optimal heating plan according to the provided power price; wherein the network is used for receiving and transmitting data) “the processor is configured to determine an operation schedule of a heat storage device based on the power supply and demand information” ([0042] the method disclosed in PTL 2 can be used in the optimal heating plan by the hot water tank temperature control devices 22. As the limiting conditions associated to heating in calorifier type tanks, there are for example, the minimum amount of power that can be carried to the calorifier type tanks (hereinafter "minimum carried current") or maximum amount thereof (hereinafter "maximum carried current"). The hot water tank temperature control devices 22 are also provided hourly power prices for calculating the optimal heating plan according to the provided power price. Additionally, the hot water tank temperature control devices 22 also calculate the hourly hot-water demand in the optimal heating plan (hereinafter "planned demand"). The hot water tank temperature control devices 22 are computers provided for each calorifier of the power demander; wherein the optimal heating plan is an operation schedule for the hot water tanks) “wherein determining the operational schedule comprises: performing a load prediction for the heat storage device from at least an operation history of the heat storage device and operation setting information of a user” ([0040] The supply-demand planning device 23 performs simulations on amount of electrical power generated by hydroelectric power generation (hereinafter "hydroelectric output"), amount of electrical power generated by thermal power generation (hereinafter "thermal output"), amount of electrical power consumed by the calorifier (hereinafter "demand of water heaters") and amount of electrical power consumed by loads other than calorifiers)) “comparing a load prediction of the heat storage device with the power supply and demand information, determining a tight time zone in which a power supply is tight in the power supply and demand information, and comparing a power supply amount of the load prediction with a predetermined threshold” ([0043] The economical load distribution adjusting device 10 makes adjustments so that the water level planning of the reservoir and the heat planning of the calorifiers are performed to agree as much as possible with the optimal supply-demand plan calculated by the supply-demand planning device 23... if there is a time period when the planned demand that the hot water tank temperature control devices 22 have planned is greater than the optimal demand in the optimal supply-demand plan, the economical load distribution adjusting device 10 raises the power price of that time period and makes the hot water tank temperature control devices 22 recalculate the heating plan; wherein there is a comparison between planned and optimal demand to determine when they are greater) “and determining, when a power usage amount of the heat storage device in a tight time zone in the load prediction is greater than or less than the predetermining threshold and determining, the operation schedule so that a power usage amount of the heat storage device in the tight time zone is reduced to equal to or less than a threshold” ([0010] In order to solve the above-described problem, the electric power demand plan adjusting device according to present invention may have the price adjusting unit set a predetermined maximum value to the power price for the unit time at which the planned value of the amount of demand exceeds the optimal value of the amount of demand. [0040] The supply-demand planning device 23 creates a plan (hereinafter "optimal supply-demand plan") for output and power demand so that the cost for generating electricity is minimized during a predetermined period (24 hours in the present embodiment). [0042] The hot water tank temperature control devices 22 (corresponding to the "demand planning device") plans the heating of the hot water stored in the calorifier type tank so that the electric power cost for heating is minimized while satisfying the various limiting conditions (hereinafter "optimal heating plan"). For example, the method disclosed in PTL 2 can be used in the optimal heating plan by the hot water tank temperature control devices 22. As the limiting conditions associated to heating in calorifier type tanks, there are for example, the minimum amount of power that can be carried to the calorifier type tanks (hereinafter "minimum carried current") or maximum amount thereof (hereinafter "maximum carried current"). The hot water tank temperature control devices 22 are also provided hourly power prices for calculating the optimal heating plan according to the provided power price. [0085] As explained above, the hot water tank temperature control devices 22 can be made to recalculate the heating plan after setting the power price, to a maximum value, of a time period where the planned demand is greater than the optimal demand if such time period exists. Since the heating plan is recalculated to minimize the electric power cost for heating by the hot water tank temperature control devices 22, the heating plan is expected to be corrected to reduce the consumed power of time periods having the raised power price. In this way, the power demand can be brought close to the optimal supply-demand plan; wherein when planned demand is greater than optimal demand is a tight time zone in which its greater than a predetermined threshold (zero) for which the schedule is recalculated on the basis of new pricing information that reduces the demand to below its previous amount) “wherein a sum of the power usage amount of the heat storage device over a predetermined period is greater than or equal to a sum of the power usage amounts of the heat storage device according to the load prediction;” ([0050] the power price adjusting unit 114 adjusts the power price for the time period during which the total amount of planned demand acquired from the hot water tank temperature control devices 22 exceeds the optimal demand included in the optimal supply-demand plan so to become higher than the current power price, and sends the optimal plan request including the adjusted power price to the hot water tank temperature control devices 22 for recalculation thereby. [0072] , the economical load distribution adjusting device 10 sums up the planned demand corresponding to each calorifier for each time to set in the hourly total column 651 of the demand list 72. Furthermore, the economical load distribution adjusting device 10 creates a limiting conditions list 73 that stores limiting conditions of each time for each calorifier and sets the limiting conditions as the initial values (S522). FIG. 17 is a table showing an example of the limiting conditions list 73. Note that in the present embodiment, the limiting conditions assume only the minimum carried current and the maximum carried current. Additionally, the initial values of the limiting conditions for all the calorifiers take the same value) “and the communication interface is further configured to transmit the operation schedule to the power control instruction device;” ([0049] The optimal demand acquiring unit 113 acquires the hourly planned demand in the optimal heating plan calculated by the hot water tank temperature control devices 22. In the present embodiment, the optimal demand acquiring unit 113 sends the optimal plan request including the hourly optimal power price acquired from the supply-demand planning device 23 to the hot water tank temperature control devices 22. The hot water tank temperature control devices 22 calculate the optimal heating plan according to the optimal plan request, makes a response indicating the hourly planned demand in the optimal heating plan to the economical load distribution adjusting device 10 to be received by the optimal demand acquiring unit 113) “and control an operation of the heat storage device based on the operation” ([0042] The hot water tank temperature control devices 22 (corresponding to the "demand planning device") plans the heating of the hot water stored in the calorifier type tank so that the electric power cost for heating is minimized while satisfying the various limiting conditions (hereinafter "optimal heating plan"). For example, the method disclosed in PTL 2 can be used in the optimal heating plan by the hot water tank temperature control devices 22...The hot water tank temperature control devices 22 are also provided hourly power prices for calculating the optimal heating plan according to the provided power price. Additionally, the hot water tank temperature control devices 22 also calculate the hourly hot-water demand in the optimal heating plan (hereinafter "planned demand"). The hot water tank temperature control devices 22 are computers provided for each calorifier of the power demander. The hot water tank temperature control devices 22 may be, for example, control boards built in the calorifiers or may be personal computers and PDAs that connect to the calorifiers; wherein the control device 22 is a heat storage device control unit; [0043] if there is a time period when the planned demand that the hot water tank temperature control devices 22 have planned is greater than the optimal demand in the optimal supply-demand plan, the economical load distribution adjusting device 10 raises the power price of that time period and makes the hot water tank temperature control devices 22 recalculate the heating plan. Since the heating plan is calculated to minimize the consumed electric power cost at the hot water tank temperature control devices 22, the heating plan is expected to be corrected so that the electrical power consumed during the time period with increased power price is cut down. In this way, the electric power demand can be brought close to the optimal supply-demand plan; wherein the planned demand is executed by the control device, even after correction of price)
Ryuji fails to teach “performing a load prediction for the heat storage device from at least an operation history of the heat storage device and operation setting information of a user”. While Ryuji discloses that load predictions for heat storage devices are done via simulation, the particulars of using operation history and operation setting information of a user is not discussed.
Arnold teaches “perform a load prediction for the heat storage device from at least an operation history of the heat storage device and operation setting information of a user” ([0007] At least one source of data related to a consumption of hot water from the high-efficiency water heating system is provided and software running on the processor analyzes the data and calculates a predicted demand for the hot water based upon the data, then controls the operation of the at least one source of heat responsive to the predicted demand. [0039] In the neural network 430 implementation, each input is considered with a weighing factor. For example, last week's usage history has a high weighing factor, the week before usage history has a lower weighing factor, and the external weather (e.g. cloudy, raining) has even a lower weighing factor. As the neural network system 430 continues to predict hot water demand, hot water usage (e.g. flow rates) is measured and fed back into the neural network 430 and the neural network 430 makes adjustments. For example, if, over time, the neural network 430 recognizes that hot water demand is 10% higher on cloudy days, the neural network 430 will increase the weight given to external weather. [0034] Schedule data 33 is also optionally considered by the analysis algorithms 30 to predict when demand will occur. For example, in a dormitory, by knowing the schedule of students, the analysis algorithms 30 control the heater(s) 120/122 and valves 130/132/134 based upon the schedule data 33 such that, knowing that lights out starts at 10:00 PM and classes start at 8:00 AM, the analysis algorithms 30 predict very low hot water usage after 10:00 PM when the students are asleep, high hot water usage prior to 8:00 AM when students are waking and taking showers, and low hot water usage when students are in class after 8:00 AM, etc. In another example, by knowing the schedule data 33 for people in a home, the analysis algorithms 30 make similar predictions; [0036] Another optional source of data to the analysis algorithms 30 is external data 36. External data includes any data feed that has information regarding the future demand for hot water. This data includes, but is not limited to, weather predictions, data from an almanac (e.g. sunrise and sunset times), local news information, school information, lunch menus, school events, local events, etc. For example, if the dormitory dinner menu includes cold sandwiches, there is likely to be a higher demand for hot water that evening then if the menu includes hot soup. If the forecast for tomorrow is rain and sleet, depending on the users, such weather will change demand. For example, some hot water users will forego showering/bathing until they return from classes so as to not be as cold walking to classes. Other events will affect hot water consumption. For example, if Friday night is Prom Night, then extra hot water will be needed between, say, 5:00 PM and 7:00 PM for prom goers to shower/bathe; wherein the schedule data or external data are operational setting information of a user).
It would have been obvious to a person having ordinary skill in the art before the effective file date of the claimed invention to have modified the system for adjusting a water heater schedule during periods of tight demand that are recognized as times when prices are high determined from comparisons of load predictions to received power supply and demand information, with the use of a load prediction which comes about from historical information and operational settings of users as taught by Arnold, because it can be considered taking one form of load prediction (simulation) and replacing it with another (history and user operational settings) in a known way that achieves predictable results. Furthermore, it can be considered that Arnold’s methods of load prediction take into consideration the historical uses of hot water and other factors in a user’s schedule or information that affects how the operation of settings for the water heater change on the basis of user’s activities, thus affording the improvement of better predicting how the water heater usage is impacted by a user’s past behavior and their planned activities. By combining these elements, it can be considered taking the known method of load prediction that uses historical data and user operational settings, and using it in place of the simulation-based load predictions of Ryuji in a known way that achieves predictable results.
In regards to Claim 2, the combination of Ryuji and Arnold teaches the heat storage system control device as incorporated by claim 1 above. Ryuji further teaches “The heat storage system control device of claim 1, wherein the communications interface is configured to transmit an amount of power to be consumed in the operation schedule determined by the processor to the power control instruction device” ([0049] The optimal demand acquiring unit 113 acquires the hourly planned demand in the optimal heating plan calculated by the hot water tank temperature control devices 22. In the present embodiment, the optimal demand acquiring unit 113 sends the optimal plan request including the hourly optimal power price acquired from the supply-demand planning device 23 to the hot water tank temperature control devices 22. The hot water tank temperature control devices 22 calculate the optimal heating plan according to the optimal plan request, makes a response indicating the hourly planned demand in the optimal heating plan to the economical load distribution adjusting device 10 to be received by the optimal demand acquiring unit 113).
In regards to Claim 7, the combination of Ryuji and Arnold teaches the heat storage system control device as incorporated by claim 1 above. Ryuji further teaches “The heat storage system control device of claim 1, wherein the processor is further configured to classify re-acquired power supply and demand information newly acquired from the power control instruction device by communications interface after the communications interface transmits the operation schedule to the power control instruction device, into a high tightness time zone in which a degree of power supply tightness is high and another time zone” ([0050] the power price adjusting unit 114 adjusts the power price for the time period during which the total amount of planned demand acquired from the hot water tank temperature control devices 22 exceeds the optimal demand included in the optimal supply-demand plan so to become higher than the current power price, and sends the optimal plan request including the adjusted power price to the hot water tank temperature control devices 22 for recalculation thereby. [0084] FIG. 22 shows diagrams explaining the power price adjustment processes shown in aforementioned FIG. 16. (a1) shows a graph indicating the optimal power price calculated by the supply-demand planning device 23, (a2) shows a line graph of the optimal demand and a stacked bar chart of the planned demand calculated by each of the hot water tank temperature control devices 22 according to the optimal power price. In the example shown in FIG. 22, the total planned demand exceeds the optimal demand between 5 o'clock and 8 o'clock. When the power price of the calorifiers 4 and 5 are raised at 7 o'clock at which the total planned demand exceeds the optimal demand (b1), the hot water tank temperature control devices 22 controlling the calorifiers 4 and 5 are expected to reduce the demand for time at which the power price is raised and to increase the demand at other times to minimize the electric power cost associated with consumed power. In the example of (b2), heating by calorifier 5 planned at 7 o'clock is shifted to 4 o'clock. The power prices for calorifiers 4 and 5 are raised at also 8 o'clock (c1) and hereby the hot water tank temperature control devices 22 of the calorifiers 4 and 5 shift the heating planned at 8 o'clock to 3 o'clock in order to minimize the electric power cost. The power prices for calorifiers 4 and 5 are raised at also 5 o'clock (d1) and the heating planned at 5 o'clock is shifted to 2 o'clock (d2), and the power prices for calorifiers 4 and 5 are raised at also 6 o'clock (e1) and the heating planned at 6 o'clock is shifted to 1 o'clock (e2). In this way, heating plans are laid at (e2) by each of the hot water tank temperature control devices 22 in conditions approximately agreeing with the optimal output) “and change the operation schedule transmitted to the power control instruction device so that a power usage amount of the heat storage device in the high tightness time zone is reduced and a power usage amount of the heat storage device in the another time zone is increased” ([0043] if there is a time period when the planned demand that the hot water tank temperature control devices 22 have planned is greater than the optimal demand in the optimal supply-demand plan, the economical load distribution adjusting device 10 raises the power price of that time period and makes the hot water tank temperature control devices 22 recalculate the heating plan. Since the heating plan is calculated to minimize the consumed electric power cost at the hot water tank temperature control devices 22, the heating plan is expected to be corrected so that the electrical power consumed during the time period with increased power price is cut down. In this way, the electric power demand can be brought close to the optimal supply-demand plan. [0084] When the power price of the calorifiers 4 and 5 are raised at 7 o'clock at which the total planned demand exceeds the optimal demand (b1), the hot water tank temperature control devices 22 controlling the calorifiers 4 and 5 are expected to reduce the demand for time at which the power price is raised and to increase the demand at other times to minimize the electric power cost associated with consumed power. In the example of (b2), heating by calorifier 5 planned at 7 o'clock is shifted to 4 o'clock. The power prices for calorifiers 4 and 5 are raised at also 8 o'clock (c1) and hereby the hot water tank temperature control devices 22 of the calorifiers 4 and 5 shift the heating planned at 8 o'clock to 3 o'clock in order to minimize the electric power cost. The power prices for calorifiers 4 and 5 are raised at also 5 o'clock (d1) and the heating planned at 5 o'clock is shifted to 2 o'clock (d2), and the power prices for calorifiers 4 and 5 are raised at also 6 o'clock (e1) and the heating planned at 6 o'clock is shifted to 1 o'clock (e2). In this way, heating plans are laid at (e2) by each of the hot water tank temperature control devices 22 in conditions approximately agreeing with the optimal output; wherein shifting from high demand to lower demand is shifting power from tight time zone to another time zone).
In regards to Claim 10, Ryuji teaches “A heat storage system for controlling a heat storage device based on power supply and demand information, the heat storage system comprising: a heat storage system microcomputer configured to control the heat storage device” ([0042] The hot water tank temperature control devices 22 (corresponding to the "demand planning device") plans the heating of the hot water stored in the calorifier type tank so that the electric power cost for heating is minimized while satisfying the various limiting conditions (hereinafter "optimal heating plan"). For example, the method disclosed in PTL 2 can be used in the optimal heating plan by the hot water tank temperature control devices 22...The hot water tank temperature control devices 22 are also provided hourly power prices for calculating the optimal heating plan according to the provided power price. Additionally, the hot water tank temperature control devices 22 also calculate the hourly hot-water demand in the optimal heating plan (hereinafter "planned demand"). The hot water tank temperature control devices 22 are computers provided for each calorifier of the power demander. The hot water tank temperature control devices 22 may be, for example, control boards built in the calorifiers or may be personal computers and PDAs that connect to the calorifiers; wherein the computer is a microcomputer;) “and a power control instruction server configured to provide power supply and demand information to the heat storage system control device” ([0045] FIG. 2 is a diagram showing the hardware configuration of the economical load distribution adjusting device 10. The economical load distribution adjusting device 10 includes a CPU 101, a memory 102, a storage device 103, a communication interface 104, an input device 105 and an output device 106. [0039] The economical load distribution adjusting device 10 is connected to the water level planning devices 21, the hot water tank temperature control devices 22 and the supply-demand planning device 23 via the communication network 24. The communication network 24 is, for example, the Internet or a LAN (Local Area Network) and is built with a public telephone network, the Ethernet (registered trademark), a wireless communication network or the like; [0042] The hot water tank temperature control devices 22 are also provided hourly power prices for calculating the optimal heating plan according to the provided power price; wherein the functionality of the economical load distribution adjusting device and the supply-demand planning device is a power control instruction device) “the power control instruction server is configured to generate the power supply and demand information” ([0046] FIG. 3 is a diagram showing the software configuration of the economical load distribution adjusting device 10. The economical load distribution adjusting device 10 includes function units of an optimal supply-demand plan acquiring unit 111, an optimal output acquiring unit 112, an optimal demand acquiring unit 113 and a power price adjusting unit 114. Note that, the above functions are implemented by the CPU 101 included in the economical load distribution adjusting device 10 reading programs stored in the storage device 103 to the memory 102 and executing the same. [0047] The optimal supply-demand plan acquiring unit 111 acquires an optimal supply-demand plan calculated by the supply-demand planning device 23. In the present embodiment, the optimal supply-demand plan acquiring unit 111 sends a command instructing to perform an optimization calculation (hereafter "optimal plan request") to the supply-demand planning device 23, the supply-demand planning device 23 calculates an optimal supply-demand plan in accordance with the optimal plan request, makes a response indicating the optimal power price, optimal demand and optimal output to the economical load distribution adjusting device 10 to be received by the optimal supply-demand plan acquiring unit 111) “the heat storage system control microcomputer includes a processor configured to determine an operation schedule of the heat storage device based on the power supply and demand information;” ([0042] the method disclosed in PTL 2 can be used in the optimal heating plan by the hot water tank temperature control devices 22. As the limiting conditions associated to heating in calorifier type tanks, there are for example, the minimum amount of power that can be carried to the calorifier type tanks (hereinafter "minimum carried current") or maximum amount thereof (hereinafter "maximum carried current"). The hot water tank temperature control devices 22 are also provided hourly power prices for calculating the optimal heating plan according to the provided power price. Additionally, the hot water tank temperature control devices 22 also calculate the hourly hot-water demand in the optimal heating plan (hereinafter "planned demand"). The hot water tank temperature control devices 22 are computers provided for each calorifier of the power demander; wherein the optimal heating plan is an operation schedule for the hot water tanks) “wherein determining the operation schedule comprises: performing a load prediction for the heat storage device from at least an operation history of the heat storage device and operation setting information of a user” ([0040] The supply-demand planning device 23 performs simulations on amount of electrical power generated by hydroelectric power generation (hereinafter "hydroelectric output"), amount of electrical power generated by thermal power generation (hereinafter "thermal output"), amount of electrical power consumed by the calorifier (hereinafter "demand of water heaters") and amount of electrical power consumed by loads other than calorifiers)) “comparing a load prediction of the heat storage device with the power supply and demand information, determining a tight time zone in which a power supply is tight in the power supply and demand information, comparing a power supply amount of the load prediction with a predetermined threshold” ([0043] The economical load distribution adjusting device 10 makes adjustments so that the water level planning of the reservoir and the heat planning of the calorifiers are performed to agree as much as possible with the optimal supply-demand plan calculated by the supply-demand planning device 23... if there is a time period when the planned demand that the hot water tank temperature control devices 22 have planned is greater than the optimal demand in the optimal supply-demand plan, the economical load distribution adjusting device 10 raises the power price of that time period and makes the hot water tank temperature control devices 22 recalculate the heating plan; wherein there is a comparison between planned and optimal demand to determine when they are greater) “and determining, when the power usage amount of the heat storage device in a tight time zone in the load prediction is greater than or less than a predetermining threshold and determining, the operation schedule so that a power usage amount of the heat storage device in the tight time zone is reduced to equal to or less than a threshold” ([0010] In order to solve the above-described problem, the electric power demand plan adjusting device according to present invention may have the price adjusting unit set a predetermined maximum value to the power price for the unit time at which the planned value of the amount of demand exceeds the optimal value of the amount of demand. [0040] The supply-demand planning device 23 creates a plan (hereinafter "optimal supply-demand plan") for output and power demand so that the cost for generating electricity is minimized during a predetermined period (24 hours in the present embodiment). [0042] The hot water tank temperature control devices 22 (corresponding to the "demand planning device") plans the heating of the hot water stored in the calorifier type tank so that the electric power cost for heating is minimized while satisfying the various limiting conditions (hereinafter "optimal heating plan"). For example, the method disclosed in PTL 2 can be used in the optimal heating plan by the hot water tank temperature control devices 22. As the limiting conditions associated to heating in calorifier type tanks, there are for example, the minimum amount of power that can be carried to the calorifier type tanks (hereinafter "minimum carried current") or maximum amount thereof (hereinafter "maximum carried current"). The hot water tank temperature control devices 22 are also provided hourly power prices for calculating the optimal heating plan according to the provided power price. [0085] As explained above, the hot water tank temperature control devices 22 can be made to recalculate the heating plan after setting the power price, to a maximum value, of a time period where the planned demand is greater than the optimal demand if such time period exists. Since the heating plan is recalculated to minimize the electric power cost for heating by the hot water tank temperature control devices 22, the heating plan is expected to be corrected to reduce the consumed power of time periods having the raised power price. In this way, the power demand can be brought close to the optimal supply-demand plan; wherein when planned demand is greater than optimal demand is a tight time zone in which its greater than a predetermined threshold (zero) for which the schedule is recalculated on the basis of new pricing information that reduces the demand to below its previous amount) “wherein a sum of the power usage amount of the heat storage device over a predetermined period is greater than or equal to a sum of the power usage amounts of the heat storage device according to the load prediction;” ([0050] the power price adjusting unit 114 adjusts the power price for the time period during which the total amount of planned demand acquired from the hot water tank temperature control devices 22 exceeds the optimal demand included in the optimal supply-demand plan so to become higher than the current power price, and sends the optimal plan request including the adjusted power price to the hot water tank temperature control devices 22 for recalculation thereby. [0072] , the economical load distribution adjusting device 10 sums up the planned demand corresponding to each calorifier for each time to set in the hourly total column 651 of the demand list 72. Furthermore, the economical load distribution adjusting device 10 creates a limiting conditions list 73 that stores limiting conditions of each time for each calorifier and sets the limiting conditions as the initial values (S522). FIG. 17 is a table showing an example of the limiting conditions list 73. Note that in the present embodiment, the limiting conditions assume only the minimum carried current and the maximum carried current. Additionally, the initial values of the limiting conditions for all the calorifiers take the same value) “and a communication configured to acquire the supply and demand information from the power control instruction server and transmit the operation schedule determined by the processor to the power control instruction server” ([0049] The optimal demand acquiring unit 113 acquires the hourly planned demand in the optimal heating plan calculated by the hot water tank temperature control devices 22. In the present embodiment, the optimal demand acquiring unit 113 sends the optimal plan request including the hourly optimal power price acquired from the supply-demand planning device 23 to the hot water tank temperature control devices 22. The hot water tank temperature control devices 22 calculate the optimal heating plan according to the optimal plan request, makes a response indicating the hourly planned demand in the optimal heating plan to the economical load distribution adjusting device 10 to be received by the optimal demand acquiring unit 113) “and control an operation of the heat storage device based on the operation schedule” ([0042] The hot water tank temperature control devices 22 (corresponding to the "demand planning device") plans the heating of the hot water stored in the calorifier type tank so that the electric power cost for heating is minimized while satisfying the various limiting conditions (hereinafter "optimal heating plan"). For example, the method disclosed in PTL 2 can be used in the optimal heating plan by the hot water tank temperature control devices 22...The hot water tank temperature control devices 22 are also provided hourly power prices for calculating the optimal heating plan according to the provided power price. Additionally, the hot water tank temperature control devices 22 also calculate the hourly hot-water demand in the optimal heating plan (hereinafter "planned demand"). The hot water tank temperature control devices 22 are computers provided for each calorifier of the power demander. The hot water tank temperature control devices 22 may be, for example, control boards built in the calorifiers or may be personal computers and PDAs that connect to the calorifiers; wherein the control device 22 is a heat storage device control unit; [0043] if there is a time period when the planned demand that the hot water tank temperature control devices 22 have planned is greater than the optimal demand in the optimal supply-demand plan, the economical load distribution adjusting device 10 raises the power price of that time period and makes the hot water tank temperature control devices 22 recalculate the heating plan. Since the heating plan is calculated to minimize the consumed electric power cost at the hot water tank temperature control devices 22, the heating plan is expected to be corrected so that the electrical power consumed during the time period with increased power price is cut down. In this way, the electric power demand can be brought close to the optimal supply-demand plan; wherein the planned demand is executed by the control device, even after correction of price)
Ryuji fails to teach “performing a load prediction for the heat storage device from at least an operation history of the heat storage device and operation setting information of a user”. While Ryuji discloses that load predictions for heat storage devices are done via simulation, the particulars of using operation history and operation setting information of a user is not discussed.
Arnold teaches “perform a load prediction for the heat storage device from at least an operation history of the heat storage device and operation setting information of a user” ([0007] At least one source of data related to a consumption of hot water from the high-efficiency water heating system is provided and software running on the processor analyzes the data and calculates a predicted demand for the hot water based upon the data, then controls the operation of the at least one source of heat responsive to the predicted demand. [0039] In the neural network 430 implementation, each input is considered with a weighing factor. For example, last week's usage history has a high weighing factor, the week before usage history has a lower weighing factor, and the external weather (e.g. cloudy, raining) has even a lower weighing factor. As the neural network system 430 continues to predict hot water demand, hot water usage (e.g. flow rates) is measured and fed back into the neural network 430 and the neural network 430 makes adjustments. For example, if, over time, the neural network 430 recognizes that hot water demand is 10% higher on cloudy days, the neural network 430 will increase the weight given to external weather. [0034] Schedule data 33 is also optionally considered by the analysis algorithms 30 to predict when demand will occur. For example, in a dormitory, by knowing the schedule of students, the analysis algorithms 30 control the heater(s) 120/122 and valves 130/132/134 based upon the schedule data 33 such that, knowing that lights out starts at 10:00 PM and classes start at 8:00 AM, the analysis algorithms 30 predict very low hot water usage after 10:00 PM when the students are asleep, high hot water usage prior to 8:00 AM when students are waking and taking showers, and low hot water usage when students are in class after 8:00 AM, etc. In another example, by knowing the schedule data 33 for people in a home, the analysis algorithms 30 make similar predictions; [0036] Another optional source of data to the analysis algorithms 30 is external data 36. External data includes any data feed that has information regarding the future demand for hot water. This data includes, but is not limited to, weather predictions, data from an almanac (e.g. sunrise and sunset times), local news information, school information, lunch menus, school events, local events, etc. For example, if the dormitory dinner menu includes cold sandwiches, there is likely to be a higher demand for hot water that evening then if the menu includes hot soup. If the forecast for tomorrow is rain and sleet, depending on the users, such weather will change demand. For example, some hot water users will forego showering/bathing until they return from classes so as to not be as cold walking to classes. Other events will affect hot water consumption. For example, if Friday night is Prom Night, then extra hot water will be needed between, say, 5:00 PM and 7:00 PM for prom goers to shower/bathe; wherein the schedule data or external data are operational setting information of a user).
It would have been obvious to a person having ordinary skill in the art before the effective file date of the claimed invention to have modified the system for adjusting a water heater schedule during periods of tight demand that are recognized as times when prices are high determined from comparisons of load predictions to received power supply and demand information, with the use of a load prediction which comes about from historical information and operational settings of users as taught by Arnold, because it can be considered taking one form of load prediction (simulation) and replacing it with another (history and user operational settings) in a known way that achieves predictable results. Furthermore, it can be considered that Arnold’s methods of load prediction take into consideration the historical uses of hot water and other factors in a user’s schedule or information that affects how the operation of settings for the water heater change on the basis of user’s activities, thus affording the improvement of better predicting how the water heater usage is impacted by a user’s past behavior and their planned activities. By combining these elements, it can be considered taking the known method of load prediction that uses historical data and user operational settings, and using it in place of the simulation-based load predictions of Ryuji in a known way that achieves predictable results.
In regards to Claim 12, the combination of Ryuji and Arnold teaches the heat storage system as incorporated by claim 10 above. Ryuji further teaches “The heat storage system of claim 10, wherein the communications interface is configured to transmit an amount of power to be consumed in the operation schedule determined by the processor to the power control instruction server” ([0049] The optimal demand acquiring unit 113 acquires the hourly planned demand in the optimal heating plan calculated by the hot water tank temperature control devices 22. In the present embodiment, the optimal demand acquiring unit 113 sends the optimal plan request including the hourly optimal power price acquired from the supply-demand planning device 23 to the hot water tank temperature control devices 22. The hot water tank temperature control devices 22 calculate the optimal heating plan according to the optimal plan request, makes a response indicating the hourly planned demand in the optimal heating plan to the economical load distribution adjusting device 10 to be received by the optimal demand acquiring unit 113).
In regards to Claim 13, the combination of Ryuji and Arnold teaches the heat storage system as incorporated by claim 10 above. Ryuji further teaches “The heat storage system of claim 10, wherein the power control instruction server is configured to transmit, as the power supply and demand information, information on an electricity rate per unit of electric energy for each time zone to the heat storage device control system control microcomputer” ([0040] The supply-demand planning device 23 increases or decreases the hourly amount of electric power demand, hydroelectric output and thermal output according to facts such as for example, hourly power price for a unit amount of electrical power at the electric power exchange or expenses for starting up the generator for thermal power generation (start-up cost)...in the present embodiment, the unit power generation cost is assumed to be the power price, however, profit may be added to the unit power generation cost to be set as the power price. The supply-demand planning device 23 is, for example, a personal computer or a workstation, a mobile phone unit, PDA (Personal Digital Assistant) and the like. Further, the supply-demand planning device 23 and the later-described economical load distribution adjusting device 10 may be implemented by a single computer. [0043] The economical load distribution adjusting device 10 makes adjustments so that the water level planning of the reservoir and the heat planning of the calorifiers are performed to agree as much as possible with the optimal supply-demand plan calculated by the supply-demand planning device 23. If there is a time period when the total amount of planned output that the water level planning devices 21 have planned are greater than the optimal output in the optimal supply-demand plan, the economical load distribution adjusting device 10 reduces the power price of that time period and makes the water level planning devices 21 recalculate the water level plan. Since the water level planning devices 21 plans the water level to maximize the selling price of power, the plan is expected to be corrected so that the output during the time period with the reduced power price is cut down. In this way, the output can be brought close to the optimal supply-demand plan. Further, if there is a time period when the planned demand that the hot water tank temperature control devices 22 have planned is greater than the optimal demand in the optimal supply-demand plan, the economical load distribution adjusting device 10 raises the power price of that time period and makes the hot water tank temperature control devices 22 recalculate the heating plan).
In regards to Claim 14, the combination of Ryuji and Arnold teaches the heat storage system as incorporated by claim 10 above. Ryuji further teaches “The heat storage system of claim 13, wherein the power control instruction server is configured to set a high electricity rate for a time zone in which a power supply is tight” ([0043] The economical load distribution adjusting device 10 makes adjustments so that the water level planning of the reservoir and the heat planning of the calorifiers are performed to agree as much as possible with the optimal supply-demand plan calculated by the supply-demand planning device 23. If there is a time period when the total amount of planned output that the water level planning devices 21 have planned are greater than the optimal output in the optimal supply-demand plan, the economical load distribution adjusting device 10 reduces the power price of that time period and makes the water level planning devices 21 recalculate the water level plan. Since the water level planning devices 21 plans the water level to maximize the selling price of power, the plan is expected to be corrected so that the output during the time period with the reduced power price is cut down. In this way, the output can be brought close to the optimal supply-demand plan. Further, if there is a time period when the planned demand that the hot water tank temperature control devices 22 have planned is greater than the optimal demand in the optimal supply-demand plan, the economical load distribution adjusting device 10 raises the power price of that time period and makes the hot water tank temperature control devices 22 recalculate the heating plan. Since the heating plan is calculated to minimize the consumed electric power cost at the hot water tank temperature control devices 22, the heating plan is expected to be corrected so that the electrical power consumed during the time period with increased power price is cut down. In this way, the electric power demand can be brought close to the optimal supply-demand plan; wherein the output of the water level planning device is a power supply).
In regards to Claim 19, the combination of Ryuji and Arnold teaches the heat storage system as incorporated by claim 10 above. Ryuji further teaches “The heat storage system of claim 10, wherein the processor is configured to classify re-acquired power supply and demand information newly acquired from the power control instruction device server by the communications interface after the communications interface transmits the operation schedule to the power control instruction server, into a high tightness time zone in which a degree of power supply tightness is high and another time zone,” ([0050] the power price adjusting unit 114 adjusts the power price for the time period during which the total amount of planned demand acquired from the hot water tank temperature control devices 22 exceeds the optimal demand included in the optimal supply-demand plan so to become higher than the current power price, and sends the optimal plan request including the adjusted power price to the hot water tank temperature control devices 22 for recalculation thereby. [0084] FIG. 22 shows diagrams explaining the power price adjustment processes shown in aforementioned FIG. 16. (a1) shows a graph indicating the optimal power price calculated by the supply-demand planning device 23, (a2) shows a line graph of the optimal demand and a stacked bar chart of the planned demand calculated by each of the hot water tank temperature control devices 22 according to the optimal power price. In the example shown in FIG. 22, the total planned demand exceeds the optimal demand between 5 o'clock and 8 o'clock. When the power price of the calorifiers 4 and 5 are raised at 7 o'clock at which the total planned demand exceeds the optimal demand (b1), the hot water tank temperature control devices 22 controlling the calorifiers 4 and 5 are expected to reduce the demand for time at which the power price is raised and to increase the demand at other times to minimize the electric power cost associated with consumed power. In the example of (b2), heating by calorifier 5 planned at 7 o'clock is shifted to 4 o'clock. The power prices for calorifiers 4 and 5 are raised at also 8 o'clock (c1) and hereby the hot water tank temperature control devices 22 of the calorifiers 4 and 5 shift the heating planned at 8 o'clock to 3 o'clock in order to minimize the electric power cost. The power prices for calorifiers 4 and 5 are raised at also 5 o'clock (d1) and the heating planned at 5 o'clock is shifted to 2 o'clock (d2), and the power prices for calorifiers 4 and 5 are raised at also 6 o'clock (e1) and the heating planned at 6 o'clock is shifted to 1 o'clock (e2). In this way, heating plans are laid at (e2) by each of the hot water tank temperature control devices 22 in conditions approximately agreeing with the optimal output) “change the operation schedule transmitted to the power control instruction server so that a power usage amount of the heat storage device in the high tightness time zone is reduced and a power usage amount of the heat storage device in the another time zone is increased” ([0043] if there is a time period when the planned demand that the hot water tank temperature control devices 22 have planned is greater than the optimal demand in the optimal supply-demand plan, the economical load distribution adjusting device 10 raises the power price of that time period and makes the hot water tank temperature control devices 22 recalculate the heating plan. Since the heating plan is calculated to minimize the consumed electric power cost at the hot water tank temperature control devices 22, the heating plan is expected to be corrected so that the electrical power consumed during the time period with increased power price is cut down. In this way, the electric power demand can be brought close to the optimal supply-demand plan. [0084] When the power price of the calorifiers 4 and 5 are raised at 7 o'clock at which the total planned demand exceeds the optimal demand (b1), the hot water tank temperature control devices 22 controlling the calorifiers 4 and 5 are expected to reduce the demand for time at which the power price is raised and to increase the demand at other times to minimize the electric power cost associated with consumed power. In the example of (b2), heating by calorifier 5 planned at 7 o'clock is shifted to 4 o'clock. The power prices for calorifiers 4 and 5 are raised at also 8 o'clock (c1) and hereby the hot water tank temperature control devices 22 of the calorifiers 4 and 5 shift the heating planned at 8 o'clock to 3 o'clock in order to minimize the electric power cost. The power prices for calorifiers 4 and 5 are raised at also 5 o'clock (d1) and the heating planned at 5 o'clock is shifted to 2 o'clock (d2), and the power prices for calorifiers 4 and 5 are raised at also 6 o'clock (e1) and the heating planned at 6 o'clock is shifted to 1 o'clock (e2). In this way, heating plans are laid at (e2) by each of the hot water tank temperature control devices 22 in conditions approximately agreeing with the optimal output; wherein demand is shifted from d1 to d2, thus from tight to other time zone).
In regards to Claim 24, Ryuji teaches “A heat storage system control method for controlling an operation of a heat storage device based on power supply and demand information, the heat storage system control method comprising: performing load prediction for the heat storage device from at least an operation history of the heat storage device and operation setting information of a user” ([0040] The supply-demand planning device 23 performs simulations on amount of electrical power generated by hydroelectric power generation (hereinafter "hydroelectric output"), amount of electrical power generated by thermal power generation (hereinafter "thermal output"), amount of electrical power consumed by the calorifier (hereinafter "demand of water heaters") and amount of electrical power consumed by loads other than calorifiers) “determining a tight time zone in which a power supply is tight” ([0010] In order to solve the above-described problem, the electric power demand plan adjusting device according to present invention may have the price adjusting unit set a predetermined maximum value to the power price for the unit time at which the planned value of the amount of demand exceeds the optimal value of the amount of demand. [0085] As explained above, the hot water tank temperature control devices 22 can be made to recalculate the heating plan after setting the power price, to a maximum value, of a time period where the planned demand is greater than the optimal demand if such time period exists. Since the heating plan is recalculated to minimize the electric power cost for heating by the hot water tank temperature control devices 22, the heating plan is expected to be corrected to reduce the consumed power of time periods having the raised power price. In this way, the power demand can be brought close to the optimal supply-demand plan; wherein when planned demand is greater than optimal demand is a tight time zone in which its greater than a predetermined threshold (zero)) “and determining an operation schedule of the heat storage device based on the power supply and demand information so that a power usage amount of the heat storage device in the tight time zone is reduced to equal to or less than a threshold when a power usage amount of the heat storage device in a high tightness time zone is greater or less than a predetermined threshold” ([0043] if there is a time period when the planned demand that the hot water tank temperature control devices 22 have planned is greater than the optimal demand in the optimal supply-demand plan, the economical load distribution adjusting device 10 raises the power price of that time period and makes the hot water tank temperature control devices 22 recalculate the heating plan. Since the heating plan is calculated to minimize the consumed electric power cost at the hot water tank temperature control devices 22, the heating plan is expected to be corrected so that the electrical power consumed during the time period with increased power price is cut down; [0081] The economical load distribution adjusting device 10 performs the following processes for variable i starting from 1 and ending with k. The economical load distribution adjusting device 10 reads t (i) from the time table in order of demand 74 for the n.sup.th and preceding calorifiers, acquires the demand in the demand list 72 corresponding to t (i) o'clock (S535). The economical load distribution adjusting device 10 sets the acquired demand to both the minimum carried current and the maximum carried current of the limiting conditions list 73 corresponding to t (i) o'clock for the n.sup.th and preceding calorifiers (S536). In this way, the carried current at t (i) o'clock is prevented from being varied for the first to n.sup.th power plants. And therefore, the demand at t (i) o'clock can be prevented from varying when the hot water tank temperature control devices 22 recalculate the optimal heating plan; [0085] As explained above, the hot water tank temperature control devices 22 can be made to recalculate the heating plan after setting the power price, to a maximum value, of a time period where the planned demand is greater than the optimal demand if such time period exists. Since the heating plan is recalculated to minimize the electric power cost for heating by the hot water tank temperature control devices 22, the heating plan is expected to be corrected to reduce the consumed power of time periods having the raised power price. In this way, the power demand can be brought close to the optimal supply-demand plan; wherein the minimum and maximum carried current is a threshold value for adjusting heat storage device) “wherein a sum of the power usage amount of the heat storage device over a predetermined period is greater than or equal to a sum of the power usage amounts of the heat storage device according to the load prediction;” ([0050] the power price adjusting unit 114 adjusts the power price for the time period during which the total amount of planned demand acquired from the hot water tank temperature control devices 22 exceeds the optimal demand included in the optimal supply-demand plan so to become higher than the current power price, and sends the optimal plan request including the adjusted power price to the hot water tank temperature control devices 22 for recalculation thereby. [0072] , the economical load distribution adjusting device 10 sums up the planned demand corresponding to each calorifier for each time to set in the hourly total column 651 of the demand list 72. Furthermore, the economical load distribution adjusting device 10 creates a limiting conditions list 73 that stores limiting conditions of each time for each calorifier and sets the limiting conditions as the initial values (S522). FIG. 17 is a table showing an example of the limiting conditions list 73. Note that in the present embodiment, the limiting conditions assume only the minimum carried current and the maximum carried current. Additionally, the initial values of the limiting conditions for all the calorifiers take the same value [0085] the hot water tank temperature control devices 22 can be made to recalculate the heating plan after setting the power price, to a maximum value, of a time period where the planned demand is greater than the optimal demand if such time period exists. Since the heating plan is recalculated to minimize the electric power cost for heating by the hot water tank temperature control devices 22, the heating plan is expected to be corrected to reduce the consumed power of time periods having the raised power price. In this way, the power demand can be brought close to the optimal supply-demand plan.) “and controlling the heat storage device based on the operation schedule” ([0042] The hot water tank temperature control devices 22 (corresponding to the "demand planning device") plans the heating of the hot water stored in the calorifier type tank so that the electric power cost for heating is minimized while satisfying the various limiting conditions (hereinafter "optimal heating plan"). For example, the method disclosed in PTL 2 can be used in the optimal heating plan by the hot water tank temperature control devices 22...The hot water tank temperature control devices 22 are also provided hourly power prices for calculating the optimal heating plan according to the provided power price. Additionally, the hot water tank temperature control devices 22 also calculate the hourly hot-water demand in the optimal heating plan (hereinafter "planned demand"). The hot water tank temperature control devices 22 are computers provided for each calorifier of the power demander. The hot water tank temperature control devices 22 may be, for example, control boards built in the calorifiers or may be personal computers and PDAs that connect to the calorifiers; wherein the control device 22 is a heat storage device control unit; [0043] if there is a time period when the planned demand that the hot water tank temperature control devices 22 have planned is greater than the optimal demand in the optimal supply-demand plan, the economical load distribution adjusting device 10 raises the power price of that time period and makes the hot water tank temperature control devices 22 recalculate the heating plan. Since the heating plan is calculated to minimize the consumed electric power cost at the hot water tank temperature control devices 22, the heating plan is expected to be corrected so that the electrical power consumed during the time period with increased power price is cut down. In this way, the electric power demand can be brought close to the optimal supply-demand plan; wherein the planned demand is executed by the control device, even after correction of price).
Ryuji fails to teach “performing load prediction for the heat storage device from at least an operation history of the heat storage device and operation setting information of a user”. While Ryuji discloses that load predictions for heat storage devices are done via simulation, the particulars of using operation history and operation setting information of a user is not discussed.
Arnold teaches “perform a load prediction for the heat storage device from at least an operation history of the heat storage device and operation setting information of a user” ([0007] At least one source of data related to a consumption of hot water from the high-efficiency water heating system is provided and software running on the processor analyzes the data and calculates a predicted demand for the hot water based upon the data, then controls the operation of the at least one source of heat responsive to the predicted demand. [0039] In the neural network 430 implementation, each input is considered with a weighing factor. For example, last week's usage history has a high weighing factor, the week before usage history has a lower weighing factor, and the external weather (e.g. cloudy, raining) has even a lower weighing factor. As the neural network system 430 continues to predict hot water demand, hot water usage (e.g. flow rates) is measured and fed back into the neural network 430 and the neural network 430 makes adjustments. For example, if, over time, the neural network 430 recognizes that hot water demand is 10% higher on cloudy days, the neural network 430 will increase the weight given to external weather. [0034] Schedule data 33 is also optionally considered by the analysis algorithms 30 to predict when demand will occur. For example, in a dormitory, by knowing the schedule of students, the analysis algorithms 30 control the heater(s) 120/122 and valves 130/132/134 based upon the schedule data 33 such that, knowing that lights out starts at 10:00 PM and classes start at 8:00 AM, the analysis algorithms 30 predict very low hot water usage after 10:00 PM when the students are asleep, high hot water usage prior to 8:00 AM when students are waking and taking showers, and low hot water usage when students are in class after 8:00 AM, etc. In another example, by knowing the schedule data 33 for people in a home, the analysis algorithms 30 make similar predictions; [0036] Another optional source of data to the analysis algorithms 30 is external data 36. External data includes any data feed that has information regarding the future demand for hot water. This data includes, but is not limited to, weather predictions, data from an almanac (e.g. sunrise and sunset times), local news information, school information, lunch menus, school events, local events, etc. For example, if the dormitory dinner menu includes cold sandwiches, there is likely to be a higher demand for hot water that evening then if the menu includes hot soup. If the forecast for tomorrow is rain and sleet, depending on the users, such weather will change demand. For example, some hot water users will forego showering/bathing until they return from classes so as to not be as cold walking to classes. Other events will affect hot water consumption. For example, if Friday night is Prom Night, then extra hot water will be needed between, say, 5:00 PM and 7:00 PM for prom goers to shower/bathe; wherein the schedule data or external data are operational setting information of a user).
It would have been obvious to a person having ordinary skill in the art before the effective file date of the claimed invention to have modified the system for adjusting a water heater schedule during periods of tight demand that are recognized as times when prices are high determined from comparisons of load predictions to received power supply and demand information, with the use of a load prediction which comes about from historical information and operational settings of users as taught by Arnold, because it can be considered taking one form of load prediction (simulation) and replacing it with another (history and user operational settings) in a known way that achieves predictable results. Furthermore, it can be considered that Arnold’s methods of load prediction take into consideration the historical uses of hot water and other factors in a user’s schedule or information that affects how the operation of settings for the water heater change on the basis of user’s activities, thus affording the improvement of better predicting how the water heater usage is impacted by a user’s past behavior and their planned activities. By combining these elements, it can be considered taking the known method of load prediction that uses historical data and user operational settings, and using it in place of the simulation-based load predictions of Ryuji in a known way that achieves predictable results.
In regards to Claim 25, the combination of Ryuji and Arnold teaches the heat storage control method as incorporated by claim 24 above. Ryuji further teaches “The heat storage system control method of claim 24, further comprising: transmitting the operation schedule also to a power control instruction device” ([0049] The optimal demand acquiring unit 113 acquires the hourly planned demand in the optimal heating plan calculated by the hot water tank temperature control devices 22. In the present embodiment, the optimal demand acquiring unit 113 sends the optimal plan request including the hourly optimal power price acquired from the supply-demand planning device 23 to the hot water tank temperature control devices 22. The hot water tank temperature control devices 22 calculate the optimal heating plan according to the optimal plan request, makes a response indicating the hourly planned demand in the optimal heating plan to the economical load distribution adjusting device 10 to be received by the optimal demand acquiring unit 113) “wherein the power control instruction device performs a supply and demand adjustment after receiving the operation schedule, and generates re-acquired power supply and demand information” ([0050] The power price adjusting unit 114 makes the water level planning devices 21 recalculate so that the hydroelectric outputs acquired from the water level planning devices 21 agree as much as possible with the optimal supply-demand plan. The power price adjusting unit 114 also makes the hot water tank temperature control devices 22 recalculate so that the water heater demand acquired from the hot water tank temperature control devices 22 agrees as much as possible with the optimal supply-demand plan. In the present embodiment, the power price adjusting unit 114 adjusts the power price of the time period during which the total amount of planned output acquired from the water level planning devices 21 exceeds the optimal output included in the optimal supply-demand plan so to become lower than the current power price, and sends the optimal plan request including the adjusted power price to the water level planning devices 21 for recalculation thereby. Further, the power price adjusting unit 114 adjusts the power price for the time period during which the total amount of planned demand acquired from the hot water tank temperature control devices 22 exceeds the optimal demand included in the optimal supply-demand plan so to become higher than the current power price, and sends the optimal plan request including the adjusted power price to the hot water tank temperature control devices 22 for recalculation thereby).
In regards to Claim 26, the combination of Ryuji and Arnold teaches the heat storage control method as incorporated by claim 24 above. Ryuji further teaches “The heat storage system control method of claim 25, wherein after the transmitting, the operation schedule is changed based on the re-acquired power supply and demand information from the power control instruction device” ([0050] The power price adjusting unit 114 makes the water level planning devices 21 recalculate so that the hydroelectric outputs acquired from the water level planning devices 21 agree as much as possible with the optimal supply-demand plan. The power price adjusting unit 114 also makes the hot water tank temperature control devices 22 recalculate so that the water heater demand acquired from the hot water tank temperature control devices 22 agrees as much as possible with the optimal supply-demand plan. In the present embodiment, the power price adjusting unit 114 adjusts the power price of the time period during which the total amount of planned output acquired from the water level planning devices 21 exceeds the optimal output included in the optimal supply-demand plan so to become lower than the current power price, and sends the optimal plan request including the adjusted power price to the water level planning devices 21 for recalculation thereby. Further, the power price adjusting unit 114 adjusts the power price for the time period during which the total amount of planned demand acquired from the hot water tank temperature control devices 22 exceeds the optimal demand included in the optimal supply-demand plan so to become higher than the current power price, and sends the optimal plan request including the adjusted power price to the hot water tank temperature control devices 22 for recalculation thereby; wherein the recalculation of the planned demand is a schedule change based on a newly received price/supply-demand information).
In regards to Claim 27, Ryuji teaches “A non-transitory computer readable medium storing a control program for causing a computer to function as a heat storage system control device configured to control an operation of a heat storage device, the control program comprising: a program instruction for causing a computer to function as a receiving unit configured to receive power supply and demand information from a power control instruction device” ([0042] The hot water tank temperature control devices 22 are computers provided for each calorifier of the power demander. The hot water tank temperature control devices 22 may be, for example, control boards built in the calorifiers or may be personal computers and PDAs that connect to the calorifiers; wherein computers are well-known to execute software; [0039] The economical load distribution adjusting device 10 is connected to the water level planning devices 21, the hot water tank temperature control devices 22 and the supply-demand planning device 23 via the communication network 24. The communication network 24 is, for example, the Internet or a LAN (Local Area Network) and is built with a public telephone network, the Ethernet (registered trademark), a wireless communication network or the like; [0040] And the supply-demand planning device 23 calculates the unit cost for power generation (hereinafter "unit power generation cost"), and further calculates the power generation expenses by multiplying the total output by the unit power generation cost and tabulating the result for 24 hours. Thereafter the supply-demand planning device 23 calculates the hydroelectric output that minimizes the power generation expenses (hereinafter "optimal output"), thermal output that minimizes the power generation expenses, output besides those by hydraulic power and thermal power that minimizes the power generation expenses, demand of water heaters that minimizes the power generation expenses (hereinafter "optimal demand"), electrical power consumed by other loads and the like [0042] The hot water tank temperature control devices 22 are also provided hourly power prices for calculating the optimal heating plan according to the provided power price) “as a load prediction unit configured to perform a load prediction for the heat storage device from at least an operation history of the heat storage device and operation setting information of a user” ([0040] The supply-demand planning device 23 performs simulations on amount of electrical power generated by hydroelectric power generation (hereinafter "hydroelectric output"), amount of electrical power generated by thermal power generation (hereinafter "thermal output"), amount of electrical power consumed by the calorifier (hereinafter "demand of water heaters") and amount of electrical power consumed by loads other than calorifiers) “as a comparison unit configured to compare the load prediction with the power supply and demand information” ([0043] The economical load distribution adjusting device 10 makes adjustments so that the water level planning of the reservoir and the heat planning of the calorifiers are performed to agree as much as possible with the optimal supply-demand plan calculated by the supply-demand planning device 23... if there is a time period when the planned demand that the hot water tank temperature control devices 22 have planned is greater than the optimal demand in the optimal supply-demand plan, the economical load distribution adjusting device 10 raises the power price of that time period and makes the hot water tank temperature control devices 22 recalculate the heating plan; wherein there is a comparison between planned and optimal demand) “as an operation schedule determination unit configured to determine a tight time zone in which a power supply is tight from the power supply and demand information, and determine an operation schedule so that a power usage amount in the tight time zone is reduced to equal to or less than a threshold when a power usage amount of the load prediction in a high tightness time zone is greater or less than a predetermined threshold” (([0043] if there is a time period when the planned demand that the hot water tank temperature control devices 22 have planned is greater than the optimal demand in the optimal supply-demand plan, the economical load distribution adjusting device 10 raises the power price of that time period and makes the hot water tank temperature control devices 22 recalculate the heating plan. Since the heating plan is calculated to minimize the consumed electric power cost at the hot water tank temperature control devices 22, the heating plan is expected to be corrected so that the electrical power consumed during the time period with increased power price is cut down; [0081] The economical load distribution adjusting device 10 performs the following processes for variable i starting from 1 and ending with k. The economical load distribution adjusting device 10 reads t (i) from the time table in order of demand 74 for the n.sup.th and preceding calorifiers, acquires the demand in the demand list 72 corresponding to t (i) o'clock (S535). The economical load distribution adjusting device 10 sets the acquired demand to both the minimum carried current and the maximum carried current of the limiting conditions list 73 corresponding to t (i) o'clock for the n.sup.th and preceding calorifiers (S536). In this way, the carried current at t (i) o'clock is prevented from being varied for the first to n.sup.th power plants. And therefore, the demand at t (i) o'clock can be prevented from varying when the hot water tank temperature control devices 22 recalculate the optimal heating plan; [0085] As explained above, the hot water tank temperature control devices 22 can be made to recalculate the heating plan after setting the power price, to a maximum value, of a time period where the planned demand is greater than the optimal demand if such time period exists. Since the heating plan is recalculated to minimize the electric power cost for heating by the hot water tank temperature control devices 22, the heating plan is expected to be corrected to reduce the consumed power of time periods having the raised power price. In this way, the power demand can be brought close to the optimal supply-demand plan; wherein the minimum and maximum carried current is a threshold value for adjusting heat storage device) “wherein a sum of the power usage amount of the heat storage device over a predetermined period is greater than or equal to a sum of the power usage amounts of the heat storage device according to the load prediction;” ([0050] the power price adjusting unit 114 adjusts the power price for the time period during which the total amount of planned demand acquired from the hot water tank temperature control devices 22 exceeds the optimal demand included in the optimal supply-demand plan so to become higher than the current power price, and sends the optimal plan request including the adjusted power price to the hot water tank temperature control devices 22 for recalculation thereby. [0072] , the economical load distribution adjusting device 10 sums up the planned demand corresponding to each calorifier for each time to set in the hourly total column 651 of the demand list 72. Furthermore, the economical load distribution adjusting device 10 creates a limiting conditions list 73 that stores limiting conditions of each time for each calorifier and sets the limiting conditions as the initial values (S522). FIG. 17 is a table showing an example of the limiting conditions list 73. Note that in the present embodiment, the limiting conditions assume only the minimum carried current and the maximum carried current. Additionally, the initial values of the limiting conditions for all the calorifiers take the same value [0085] the hot water tank temperature control devices 22 can be made to recalculate the heating plan after setting the power price, to a maximum value, of a time period where the planned demand is greater than the optimal demand if such time period exists. Since the heating plan is recalculated to minimize the electric power cost for heating by the hot water tank temperature control devices 22, the heating plan is expected to be corrected to reduce the consumed power of time periods having the raised power price. In this way, the power demand can be brought close to the optimal supply-demand plan.) “and as a transmission unit configured to transmit the operation schedule to the power control instruction device and the heat storage device” ([0049] The optimal demand acquiring unit 113 acquires the hourly planned demand in the optimal heating plan calculated by the hot water tank temperature control devices 22. In the present embodiment, the optimal demand acquiring unit 113 sends the optimal plan request including the hourly optimal power price acquired from the supply-demand planning device 23 to the hot water tank temperature control devices 22. The hot water tank temperature control devices 22 calculate the optimal heating plan according to the optimal plan request, makes a response indicating the hourly planned demand in the optimal heating plan to the economical load distribution adjusting device 10 to be received by the optimal demand acquiring unit 113.).
Ryuji fails to teach “performing load prediction for the heat storage device from at least an operation history of the heat storage device and operation setting information of a user”. While Ryuji discloses that load predictions for heat storage devices are done via simulation, the particulars of using operation history and operation setting information of a user is not discussed.
Arnold teaches “perform a load prediction for the heat storage device from at least an operation history of the heat storage device and operation setting information of a user” ([0007] At least one source of data related to a consumption of hot water from the high-efficiency water heating system is provided and software running on the processor analyzes the data and calculates a predicted demand for the hot water based upon the data, then controls the operation of the at least one source of heat responsive to the predicted demand. [0039] In the neural network 430 implementation, each input is considered with a weighing factor. For example, last week's usage history has a high weighing factor, the week before usage history has a lower weighing factor, and the external weather (e.g. cloudy, raining) has even a lower weighing factor. As the neural network system 430 continues to predict hot water demand, hot water usage (e.g. flow rates) is measured and fed back into the neural network 430 and the neural network 430 makes adjustments. For example, if, over time, the neural network 430 recognizes that hot water demand is 10% higher on cloudy days, the neural network 430 will increase the weight given to external weather. [0034] Schedule data 33 is also optionally considered by the analysis algorithms 30 to predict when demand will occur. For example, in a dormitory, by knowing the schedule of students, the analysis algorithms 30 control the heater(s) 120/122 and valves 130/132/134 based upon the schedule data 33 such that, knowing that lights out starts at 10:00 PM and classes start at 8:00 AM, the analysis algorithms 30 predict very low hot water usage after 10:00 PM when the students are asleep, high hot water usage prior to 8:00 AM when students are waking and taking showers, and low hot water usage when students are in class after 8:00 AM, etc. In another example, by knowing the schedule data 33 for people in a home, the analysis algorithms 30 make similar predictions; [0036] Another optional source of data to the analysis algorithms 30 is external data 36. External data includes any data feed that has information regarding the future demand for hot water. This data includes, but is not limited to, weather predictions, data from an almanac (e.g. sunrise and sunset times), local news information, school information, lunch menus, school events, local events, etc. For example, if the dormitory dinner menu includes cold sandwiches, there is likely to be a higher demand for hot water that evening then if the menu includes hot soup. If the forecast for tomorrow is rain and sleet, depending on the users, such weather will change demand. For example, some hot water users will forego showering/bathing until they return from classes so as to not be as cold walking to classes. Other events will affect hot water consumption. For example, if Friday night is Prom Night, then extra hot water will be needed between, say, 5:00 PM and 7:00 PM for prom goers to shower/bathe; wherein the schedule data or external data are operational setting information of a user).
It would have been obvious to a person having ordinary skill in the art before the effective file date of the claimed invention to have modified the system for adjusting a water heater schedule during periods of tight demand that are recognized as times when prices are high determined from comparisons of load predictions to received power supply and demand information, with the use of a load prediction which comes about from historical information and operational settings of users as taught by Arnold, because it can be considered taking one form of load prediction (simulation) and replacing it with another (history and user operational settings) in a known way that achieves predictable results. Furthermore, it can be considered that Arnold’s methods of load prediction take into consideration the historical uses of hot water and other factors in a user’s schedule or information that affects how the operation of settings for the water heater change on the basis of user’s activities, thus affording the improvement of better predicting how the water heater usage is impacted by a user’s past behavior and their planned activities. By combining these elements, it can be considered taking the known method of load prediction that uses historical data and user operational settings, and using it in place of the simulation-based load predictions of Ryuji in a known way that achieves predictable results.
In regards to Claim 28, the combination of Ryuji and Arnold teaches the method as incorporated by claim 27 above. Ryuji further teaches “The non-transitory computer readable medium of claim 27, the control program further comprising: a program instruction for causing the computer to function as a re-receiving unit configured to receive re-acquired power supply and demand information, which is power supply and demand information in which a supply and a demand have been adjusted, from the power control instruction device after the transmission of the operation schedule and as an operation schedule change unit configured to change the operation schedule of the heat storage device based on the re-acquired power supply and demand information.” ([0049] The optimal demand acquiring unit 113 acquires the hourly planned demand in the optimal heating plan calculated by the hot water tank temperature control devices 22. In the present embodiment, the optimal demand acquiring unit 113 sends the optimal plan request including the hourly optimal power price acquired from the supply-demand planning device 23 to the hot water tank temperature control devices 22. The hot water tank temperature control devices 22 calculate the optimal heating plan according to the optimal plan request, makes a response indicating the hourly planned demand in the optimal heating plan to the economical load distribution adjusting device 10 to be received by the optimal demand acquiring unit 113. [0050] The power price adjusting unit 114 makes the water level planning devices 21 recalculate so that the hydroelectric outputs acquired from the water level planning devices 21 agree as much as possible with the optimal supply-demand plan. The power price adjusting unit 114 also makes the hot water tank temperature control devices 22 recalculate so that the water heater demand acquired from the hot water tank temperature control devices 22 agrees as much as possible with the optimal supply-demand plan. In the present embodiment, the power price adjusting unit 114 adjusts the power price of the time period during which the total amount of planned output acquired from the water level planning devices 21 exceeds the optimal output included in the optimal supply-demand plan so to become lower than the current power price, and sends the optimal plan request including the adjusted power price to the water level planning devices 21 for recalculation thereby. Further, the power price adjusting unit 114 adjusts the power price for the time period during which the total amount of planned demand acquired from the hot water tank temperature control devices 22 exceeds the optimal demand included in the optimal supply-demand plan so to become higher than the current power price, and sends the optimal plan request including the adjusted power price to the hot water tank temperature control devices 22 for recalculation thereby; wherein each price change iteration causes recalculation of the planned demand of the water heater).
In regards to Claim 30, the combination of Ryuji and Arnold teaches the heat storage system control device as incorporated by claim 1 above. Ryuji further teaches “The heat storage system control device of claim 1, wherein the predetermined period is one day” ([0040] The supply-demand planning device 23 creates a plan (hereinafter "optimal supply-demand plan") for output and power demand so that the cost for generating electricity is minimized during a predetermined period (24 hours in the present embodiment)).
Claims 5 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Ryuji and Arnold as applied to claims 1 and 10 above, and further in view of Eustis (US 20170227299, hereinafter Eustis).
In regards to Claim 5, the combination of Ryuji and Arnold teaches the heat storage system control device as incorporated by claim 1 above.
Ryuji further teaches “The heat storage system control device of claim 1…. determine the operation schedule so that a power usage amount of the heat storage device in the off-peak time zone is increased to equal to or greater than a threshold” ([0042] The hot water tank temperature control devices 22 (corresponding to the "demand planning device") plans the heating of the hot water stored in the calorifier type tank so that the electric power cost for heating is minimized while satisfying the various limiting conditions (hereinafter "optimal heating plan"). For example, the method disclosed in PTL 2 can be used in the optimal heating plan by the hot water tank temperature control devices 22. As the limiting conditions associated to heating in calorifier type tanks, there are for example, the minimum amount of power that can be carried to the calorifier type tanks (hereinafter "minimum carried current") or maximum amount thereof (hereinafter "maximum carried current"). The hot water tank temperature control devices 22 are also provided hourly power prices for calculating the optimal heating plan according to the provided power price. Additionally, the hot water tank temperature control devices 22 also calculate the hourly hot-water demand in the optimal heating plan (hereinafter "planned demand"). [0043] Since the heating plan is calculated to minimize the consumed electric power cost at the hot water tank temperature control devices 22, the heating plan is expected to be corrected so that the electrical power consumed during the time period with increased power price is cut down. In this way, the electric power demand can be brought close to the optimal supply-demand plan; [0085] [0085] As explained above, the hot water tank temperature control devices 22 can be made to recalculate the heating plan after setting the power price, to a maximum value, of a time period where the planned demand is greater than the optimal demand if such time period exists. Since the heating plan is recalculated to minimize the electric power cost for heating by the hot water tank temperature control devices 22, the heating plan is expected to be corrected to reduce the consumed power of time periods having the raised power price. In this way, the power demand can be brought close to the optimal supply-demand plan; wherein the periods with increased power price is a peak, and thus by shifting them to time periods with lower prices it is shifted to off-peak (i.e. not peak price)).
The combination of Ryuji and Arnold fail to teach “wherein the processor is further configured to determine an off-peak time zone in which a power demand is small in the power supply and demand information”.
Eustis teaches “wherein the processor is further configured to determine an off-peak time zone in which a power demand is small in the power supply and demand information” ([0002] This disclosure relates to a method to mitigate peak electric demand and to effectively store excess energy generated by variable power sources at user premises for later use. This disclosure also relates to a unique energy storage system at user premises. [0010] Electricity is often billed to a customer by a utility at different rates (e.g. at a peak rate or rates during high electricity demand times and at one or more lower rates during low or off-peak demand times, such as at night). [0011] Power forecasts from grid coupled power plants and other sources such as wind farms and solar generating facilities are conventional and are available for use in determining which sources are to be coupled to the electricity grid and the capacity at which such sources are to operate. Actual operations can deviate from the forecasts (e.g. the wind blows harder or lasts longer than forecasted by a weather forecast, or there is more solar energy to a solar generation facility than expected from a weather forecast). Also, electricity demand can vary from the forecasted demand. The system heat pumps can be operated as a cushion to store more energy (e.g. operate at a higher power level in the case of a variable speed system heat pump, or for a longer time) to increase demand in the event the power generation is higher than expected or demand is lower than expected. Conversely, if power generation is lower than forecast or demand is higher than forecast, the system heat pumps can be operated at a lower power level, or for less time (such as not being operated) with energy stored in the thermal storage reservoir being used for heating and/or cooling the premises to reduce the demand on the grid; wherein the periods where power demand is smaller than forecast are the off-peak periods for shifting load to).
It would have been obvious to a person having ordinary skill in the art before the effective file date of the claimed invention to have modified the system which shifts power utilized by a water heater from time periods with high prices to those with low prices that correspond with off-peak periods, with the determination of off-peak periods from supply and demand information as taught by Eustis because both Ryuji and Eustis have the same effect of their invention of wanting to reduce the cost of energy by shifting energy away from time periods where price is a maximum, and thus it would be obvious to determine off-peak or low demand areas of the time periods on the basis of demand information as taught by Eustis. By incorporating such features of Eustis it would gain the stated benefit of Eustis, namely “[0003] The thermal storage in this system can be used to reduce consumption of electricity for heating and cooling at times of peak system demand.”. By combining these elements, it can be considered taking the known method of determining peak and off-peak times from demand information as taught by Eustis, and incorporating those features into Ryuji in a known way that achieves predictable results.
In regards to Claim 17, the combination of Ryuji and Arnold teaches the heat storage system as incorporated by claim 10 above.
Ryuji further teaches “The heat storage system of claim 10 wherein the processor is further configured to…. determine the operation schedule so that a power usage amount of the heat storage device in the off-peak time zone is increased to equal to or greater than a threshold” ([0042] The hot water tank temperature control devices 22 (corresponding to the "demand planning device") plans the heating of the hot water stored in the calorifier type tank so that the electric power cost for heating is minimized while satisfying the various limiting conditions (hereinafter "optimal heating plan"). For example, the method disclosed in PTL 2 can be used in the optimal heating plan by the hot water tank temperature control devices 22. As the limiting conditions associated to heating in calorifier type tanks, there are for example, the minimum amount of power that can be carried to the calorifier type tanks (hereinafter "minimum carried current") or maximum amount thereof (hereinafter "maximum carried current"). The hot water tank temperature control devices 22 are also provided hourly power prices for calculating the optimal heating plan according to the provided power price. Additionally, the hot water tank temperature control devices 22 also calculate the hourly hot-water demand in the optimal heating plan (hereinafter "planned demand"). [0043] Since the heating plan is calculated to minimize the consumed electric power cost at the hot water tank temperature control devices 22, the heating plan is expected to be corrected so that the electrical power consumed during the time period with increased power price is cut down. In this way, the electric power demand can be brought close to the optimal supply-demand plan; [0085] [0085] As explained above, the hot water tank temperature control devices 22 can be made to recalculate the heating plan after setting the power price, to a maximum value, of a time period where the planned demand is greater than the optimal demand if such time period exists. Since the heating plan is recalculated to minimize the electric power cost for heating by the hot water tank temperature control devices 22, the heating plan is expected to be corrected to reduce the consumed power of time periods having the raised power price. In this way, the power demand can be brought close to the optimal supply-demand plan; wherein the periods with increased power price is a peak, and thus by shifting them to time periods with lower prices it is shifted to off-peak (i.e. not peak price)).
The combination of Ryuji and Arnold fail to teach “determine an off-peak time zone in which a power demand is small in the power supply and demand information”.
Eustis teaches “determine an off-peak time zone in which a power demand is small in the power supply and demand information” ([0002] This disclosure relates to a method to mitigate peak electric demand and to effectively store excess energy generated by variable power sources at user premises for later use. This disclosure also relates to a unique energy storage system at user premises. [0010] Electricity is often billed to a customer by a utility at different rates (e.g. at a peak rate or rates during high electricity demand times and at one or more lower rates during low or off-peak demand times, such as at night). [0011] Power forecasts from grid coupled power plants and other sources such as wind farms and solar generating facilities are conventional and are available for use in determining which sources are to be coupled to the electricity grid and the capacity at which such sources are to operate. Actual operations can deviate from the forecasts (e.g. the wind blows harder or lasts longer than forecasted by a weather forecast, or there is more solar energy to a solar generation facility than expected from a weather forecast). Also, electricity demand can vary from the forecasted demand. The system heat pumps can be operated as a cushion to store more energy (e.g. operate at a higher power level in the case of a variable speed system heat pump, or for a longer time) to increase demand in the event the power generation is higher than expected or demand is lower than expected. Conversely, if power generation is lower than forecast or demand is higher than forecast, the system heat pumps can be operated at a lower power level, or for less time (such as not being operated) with energy stored in the thermal storage reservoir being used for heating and/or cooling the premises to reduce the demand on the grid; wherein the periods where power demand is smaller than forecast are the off-peak periods for shifting load to).
It would have been obvious to a person having ordinary skill in the art before the effective file date of the claimed invention to have modified the system which shifts power utilized by a water heater from time periods with high prices to those with low prices that correspond with off-peak periods, with the determination of off-peak periods from supply and demand information as taught by Eustis because both Ryuji and Eustis have the same effect of their invention of wanting to reduce the cost of energy by shifting energy away from time periods where price is a maximum, and thus it would be obvious to determine off-peak or low demand areas of the time periods on the basis of demand information as taught by Eustis. By incorporating such features of Eustis it would gain the stated benefit of Eustis, namely “[0003] The thermal storage in this system can be used to reduce consumption of electricity for heating and cooling at times of peak system demand.”. By combining these elements, it can be considered taking the known method of determining peak and off-peak times from demand information as taught by Eustis, and incorporating those features into Ryuji in a known way that achieves predictable results.
Claims 22-23 are rejected under 35 U.S.C. 103 as being unpatentable over Ryuji and Arnold as applied to claim10 above, and further in view of Flohr (US 20140105584, hereinafter Flohr).
In regards to Claim 22, the combination of Ryuji and Arnold teaches the heat storage system as incorporated by claim 10 above.
Ryuji further teaches “The heat storage system of claim 10, wherein the heat storage device includes a plurality of heat storage devices” ([0039] a plurality of hot water tank temperature control devices 22… The hot water tank temperature control devices 22 are computers provided for each calorifier of the power demander; wherein it is implied that there are a plurality of calorifiers/heat storage devices).
The combination of Ryuji and Arnold fail to teach “and at least some of the plurality of heat storage devices are operated with a different operation schedule”.
Flohr teaches “and at least some of the plurality of heat storage devices are operated with a different operation schedule” ([0311] FIG. 46 is a schematic illustration of water heaters organized into banks A-L where each of the banks includes a group of water heaters that are assigned nominal time slots for activation in some embodiments according to the invention. According to FIG. 46, each of the banks A-L includes a respective group (shown horizontally in FIG. 46) which are each assigned a time interval during which those groups of water heaters may be activated. For example, as shown in FIG. 46, the group 4605 in bank A is nominally scheduled for activation for a three minute time interval, such as 7:00 AM to 7:03 AM. [0312] As further illustrated in FIG. 46, each of the other banks B-L also includes an analogous group of water heaters organized for activation during the same time intervals, if needed. For example, group 4620 included in Bank G is also configured for activation during the same time interval assigned to group 4605. It will be further understood that the remaining groups in banks B-F and H-L are available for activation during the same time interval but nominally remain disabled unless needed. [0313] As further shown in FIG. 46, bank B includes a group 4610 and bank H includes an analogous group 4625, both of which are scheduled for activation during a second three minute time interval, such as 7:03 AM to 7:06 AM. Still further, bank C includes a group 4615 and group I includes a group 4631 both of which are scheduled for activation in a third three minute time interval, such as 7:06 AM to 7:09 AM. As finally shown in FIG. 46, the final three minute time slot shown in FIG. 46 is organized to activate the water heaters in group 4610 in bank B and the group 4625 in bank H in the same way as described above with respect to the second time interval; wherein the water heaters in different banks are operated with different schedules).
It would have been obvious to a person having ordinary skill in the art before the effective file date of the claimed invention to have modified the system that determines an operating plan/schedule for a plurality of water heaters as taught by Ryuji, to include the feature of having a different plan/schedule be determined for at least some of the water heaters as taught by Flohr, because they would gain the stated benefit of Flohr, namely “[0314] In operation, the substantially deterministic loads provided by the staggered activation of different groups of water heaters in different time intervals can allow for a substantially deterministic amount of load provided by the water heaters on the grid. Still furthermore, the groups of water heaters shown in FIG. 46 that are deactivated during those same time intervals are available for activation in the event that an additional load is called for to address imbalance. Likewise, the groups of water heaters that are scheduled for activation during the pre-assigned time slot can be deactivated to address an imbalance where loads should be removed from the grid by disabling water heaters”. In other words, by using the banks of water heaters at different schedules, it affords the improvement of improved balance between supply and demand. By incorporating these features, it can be considered taking the known methods of operating banks of water heaters at different time periods in a schedule, and incorporating these features into Ryuji in a known way that achieves predictable results.
In regards to Claim 23, the combination of Ryuji and Arnold teaches the heat storage system as incorporated by claim 10 above.
Ryuji further teaches “The heat storage system of claim 10, wherein the heat storage device includes a plurality of heat storage devices” ([0039] a plurality of hot water tank temperature control devices 22… The hot water tank temperature control devices 22 are computers provided for each calorifier of the power demander; wherein it is implied that there are a plurality of calorifiers/heat storage devices).
The combination of Ryuji and Arnold fail to teach “and the plurality of heat storage devices are operated with a same operation schedule”
Flohr teaches “the plurality of heat storage devices are operated with a same operation schedule” ([0311] FIG. 46 is a schematic illustration of water heaters organized into banks A-L where each of the banks includes a group of water heaters that are assigned nominal time slots for activation in some embodiments according to the invention. According to FIG. 46, each of the banks A-L includes a respective group (shown horizontally in FIG. 46) which are each assigned a time interval during which those groups of water heaters may be activated. For example, as shown in FIG. 46, the group 4605 in bank A is nominally scheduled for activation for a three minute time interval, such as 7:00 AM to 7:03 AM. [0312] As further illustrated in FIG. 46, each of the other banks B-L also includes an analogous group of water heaters organized for activation during the same time intervals, if needed. For example, group 4620 included in Bank G is also configured for activation during the same time interval assigned to group 4605. It will be further understood that the remaining groups in banks B-F and H-L are available for activation during the same time interval but nominally remain disabled unless needed. [0313] As further shown in FIG. 46, bank B includes a group 4610 and bank H includes an analogous group 4625, both of which are scheduled for activation during a second three minute time interval, such as 7:03 AM to 7:06 AM. Still further, bank C includes a group 4615 and group I includes a group 4631 both of which are scheduled for activation in a third three minute time interval, such as 7:06 AM to 7:09 AM. As finally shown in FIG. 46, the final three minute time slot shown in FIG. 46 is organized to activate the water heaters in group 4610 in bank B and the group 4625 in bank H in the same way as described above with respect to the second time interval; wherein the water heaters in the same banks are operated with the same schedules).
It would have been obvious to a person having ordinary skill in the art before the effective file date of the claimed invention to have modified the system that determines an operating plan/schedule for a plurality of water heaters as taught by Ryuji, to include the feature of having a same plan/schedule be determined for at least some of the water heaters as taught by Flohr, because they would gain the stated benefit of Flohr, namely “[0314] In operation, the substantially deterministic loads provided by the staggered activation of different groups of water heaters in different time intervals can allow for a substantially deterministic amount of load provided by the water heaters on the grid. Still furthermore, the groups of water heaters shown in FIG. 46 that are deactivated during those same time intervals are available for activation in the event that an additional load is called for to address imbalance. Likewise, the groups of water heaters that are scheduled for activation during the pre-assigned time slot can be deactivated to address an imbalance where loads should be removed from the grid by disabling water heaters”. In other words, by using the banks of water heaters at the same schedules, it affords the improvement of improved balance between supply and demand because the amount being shifted is an aggregate of those water heaters in the bank. By incorporating these features, it can be considered taking the known methods of operating banks of water heaters at the same time periods in a schedule, and incorporating these features into Ryuji in a known way that achieves predictable results.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JONATHAN M SKRZYCKI whose telephone number is (571)272-0933. The examiner can normally be reached M-Th 7:30-3:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ken 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.
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/JONATHAN MICHAEL SKRZYCKI/ Examiner, Art Unit 2116
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