JP5221762B2 - Water heater - Google Patents

Abstract

According to one embodiment, a hot water supply apparatus calculates a value representing an ordinary index for the hot water usage of each hot water destination, determines hot water supply whose value is less than a threshold as hot water supply of low ordinary, and determines hot water supply whose value is not less than the threshold as hot water supply of high ordinary. The apparatus also calculates a first boiling-up amount for the hot water supply determined as the hot water supply of low ordinary, and calculates a second boiling-up amount for the hot water supply determined as the hot water supply of high ordinary.

Description

  The present invention relates to a hot water supply apparatus that sets a boiling amount in response to daily activities.

  The storage-type water heater boils hot water at midnight and covers the use of hot water the next day. At this time, if the tank is full, the energy for boiling unused hot water is wasted. In order to reduce this, there is a technique for determining the amount of hot water for the next day by taking statistics on the daily hot water usage. However, with this technique, energy corresponding to the amount of remaining hot water is wasted on days when hot water usage is low.

  There is a technique for performing additional boiling up to a threshold when the amount of remaining hot water falls below the threshold. In this technique, since the amount of hot water corresponding to the threshold always remains, energy corresponding to that amount is wasted. Moreover, the completion of additional boiling may not be in time for the start of hot water supply use, and there is a possibility that hot water runs out.

  For example, Patent Document 1 below describes a technique for performing additional boiling by determining an abnormal increase in power consumption.

JP 2006-250471 A

  The technique of the above cited reference 1 does not calculate whether additional hot water is generated for each hot water type, and does not perform additional boiling.

  On the other hand, the present invention performs additional boiling when a different hot water supply occurs for each type of hot water supply, and for hot water that is normally used, for example, boiling at midnight reduces the total amount of hot water and saves energy. It aims at providing the hot-water supply apparatus which can implement | achieve.

  A hot water supply apparatus according to an aspect of the present invention is installed in different places, and a plurality of human sensors that react to the presence of a nearby person, a hot water supply sensor that measures the amount of hot water used, and the human sensor responded A classification device for determining a hot water supply type corresponding to a consumer's behavior estimated based on an installation location, and classifying the hot water use amount into a hot water use amount for each hot water supply type, and a hot water use amount for each hot water supply type Calculating a value indicating the degree of normality, determining that the hot water supply whose value is lower than the threshold is hot water supply having low normality, and determining that the hot water supply having the value equal to or higher than the threshold is hot water supply having high normality A first boiling point is calculated for the hot water supply determined to be a hot water supply having a low normality, and a second boiling point for the hot water supply determined to be a hot water supply having a high normality. A second calculating device for calculating the upper amount; Characterized by comprising a heating-up apparatus for performing the first Niejo amount and said second boiling above amount of boiling above, the.

  According to the present invention, when a different hot water supply is generated for each hot water type, additional boiling is performed.For hot water that is normally used, for example, by boiling at midnight, the total amount of boiling water is reduced to save energy. A hot water supply apparatus to be realized can be provided.

It is a block diagram which shows the hot water supply apparatus which concerns on one Embodiment. It is a figure which shows the hardware structural example. It is a flowchart which shows the specific process sequence of action estimation. It is a figure which shows an action record table. It is a flowchart which shows the specific process sequence of hot water supply classification determination. It is a figure which shows a hot-water supply table. It is a figure which shows the data of a learning object day. It is a flowchart which shows the specific process sequence of a usual degree calculation phase. It is a figure which shows the hot-water supply table showing a usual degree and usual property. It is a flowchart which shows the specific process sequence of late-night boiling-up amount calculation. It is a graph which shows the example of the time change of the amount of hot water supplies. It is a graph which shows the comparative example which concerns on embodiment of this invention.

  As shown in FIG. 1, a hot water supply apparatus according to an embodiment includes a human sensor 100, a hot water supply amount sensor 200, a hot water supply classification apparatus 300, a hot water supply ordinary degree calculation apparatus (hereinafter referred to as “first calculation apparatus”) 400a to 400a. 400c, a boiling amount calculation device (hereinafter referred to as "second calculation device") 500, and a boiling device 600. A plurality of first calculation devices 400a to 400c are provided corresponding to different hot water supply types.

  In this embodiment, there are three types of hot water supply, for example, bath, kitchen, and other hot water supply. That is, 400a is a first calculation device for a bath, 400b is a first calculation device for a kitchen, and 400c is a first calculation device for other hot water supply. These types of hot water supply are associated with the living environment, specifically, the living behavior of a consumer who uses hot water in a residence.

  Other hot water supplies may be further finely classified according to living behavior (life pattern). In this case, a corresponding first calculation device may be added. Although this embodiment is directed to a hot water supply device (residential hot water supply device) installed in a human living environment, the hot water supply device for other uses, such as a commercial hot water supply device, an industrial water heater, and an industrial overheat. The present invention can also be applied to a container or the like.

  In FIG. 1, hot water supply classification apparatus 300 includes behavior estimation unit 310 and hot water supply type determination unit 320. As an input to the hot water supply classification apparatus 300, the human sensor 100 is connected to the behavior estimation unit 310, and the hot water supply amount sensor 200 is connected to the hot water supply type determination unit 320. As an output from the hot water supply classification device 300, the hot water supply type determination unit 320 is connected to the plurality of first calculation devices 400a to 400c. The human sensor 100 responds to the presence of a nearby person, for example, and outputs the number of reactions in a certain time. A plurality of human sensors 100 are installed in different places so that the living behavior associated with each of the plurality of hot water supply types can be detected. For example, in the present embodiment, it is assumed that the human sensor 100 is provided in each of a bath and a kitchen in a residence.

  The hot water supply amount sensor 200 is a sensor that measures the amount of hot water supply used.

  The behavior estimation unit 310 of the hot water supply classification apparatus 300 performs behavior estimation based on the installation location where the human sensor 100 has reacted. Specifically, if the number of reactions of human sensor 100 corresponding to the hot water supply type is larger than a threshold value, it is estimated that there is an action corresponding to the hot water supply type. Such behavior information associated with one of the plurality of hot water supply types is sent to the hot water supply type determination unit 320 of the hot water supply classification apparatus 300. The hot water supply type determination unit 320 determines the hot water supply type from the behavior information obtained from the behavior estimation unit 310, obtains the hot water use amount for each hot water supply type from the measured hot water supply amount output by the hot water supply amount sensor 200, and corresponds to the hot water supply type. The data is sent to the first calculation devices 400a to 400c.

  As described above, the hot water supply classification apparatus 300 determines the hot water supply type corresponding to the consumer's behavior estimated based on the reaction of the human sensor 100 that reacts to the presence of a person, and is measured by the hot water supply amount sensor 200. It is comprised so that hot water supply usage may be classified into hot water usage for each hot water supply type.

  Although it has been described above that a plurality of first calculation devices are provided corresponding to hot water supply types, a specific configuration thereof will be described by taking the first calculation device 400a for a bath as an example. The configuration and operation of the first calculation device 400b for kitchen and the other first calculation device 400c for hot water supply are the same as those of the first calculation device 400a for bath except that the type of hot water supply is different.

  The first calculation device 400a for a bath is a value that represents the degree of normality for the amount of hot water used for a bath (in other words, the degree of whether or not this amount of hot water used can be regarded as an amount normally used). , That is, normal degree) is calculated using a standard hot water supply model, hot water whose value falls below the threshold value is determined as hot water having low normality, and hot water whose value is equal to or higher than the threshold value is hot water supply with high normality Is determined.

  Hot water supply with low normality is subject to additional boiling. For this reason, the additional boiling amount calculation unit 510 of the second calculation device 500 calculates the first boiling amount to be additionally boiled as the additional boiling amount for the hot water supply having low ordinaryity.

  On the other hand, a hot water supply having high normality is not a target for additional boiling, and is heated at, for example, midnight. For this reason, the midnight boiling-up amount calculation unit 520 of the second calculation device 500 is, for example, the second based on the integrated value of the hot water supply amount having a high normality in a certain period (for example, one day) (the final value of the normal hot water supply integrated amount). The boiling amount is calculated as the midnight boiling amount.

  More specifically, the first calculation device 400a for bath stores a hot water supply amount that stores a calculation unit 410 that calculates the normal temperature of hot water supply, and a hot water supply table that indicates the amount of hot water used for each hot water supply type (in this case, bath). Database (DB) 420 and the ratio of the number of days that the accumulated amount of each hot water use amount reaches a specific amount within a predetermined period, the average of the arrival times when the specific amount is reached, and the standard deviation of the arrival times A creation unit 430 that creates a standard hot water supply model to be represented based on a hot water supply table for a learning target period, a standard hot water supply model database (DB) 440 that stores the standard hot water supply model, and a threshold value for determining the level of normality (presence / absence) And a threshold value setting unit 460 for setting according to the input from the input device 450.

  The calculation unit 410 stores a value obtained by multiplying a probability based on a cumulative distribution function at a specific time in a normal distribution of the average and standard deviation represented by the standard hot water supply model, and a storage unit 411 that stores a normal integrated amount of hot water usage. The probability calculation unit 412 that calculates the ordinary degree, and the hot water supply in which the calculated ordinary degree value is lower than the threshold set by the threshold setting unit 460 are determined to be hot water supplies that have low ordinaryity, and the normal degree value is A threshold value determination unit 413 that determines that the hot water supply that is equal to or higher than the threshold value is hot water supply that is usually high in nature.

  The additional boiling amount calculation unit 510 and the midnight boiling amount calculation unit 520 of the second calculation device 500 are connected to the boiling device 600. The boiling device 600 performs boiling (boiling) of the additional boiling amount instructed from the additional boiling amount calculation unit 510. In addition, the boiling device 600 performs boiling at the midnight boiling amount instructed from the midnight boiling amount calculation unit 520 at midnight. In other words, hot water supply with high normality is heated at midnight to cover hot water supply with high normality the next day.

  In the system configuration of the hot water supply apparatus shown in FIG. 1, the hot water supply classification apparatus 300, the first calculation apparatuses 400 a to 400 c, and the second calculation apparatus 500 may be realized as a program executed by the computer 700. The hardware configuration of this embodiment in this case is shown in FIG. The computer 700 includes, for example, an input interface (IF) 710, a CPU 730, a memory 740, a hard disk 750, and an output interface (IF) 760, which are connected to a bus 720. The input device 450, the human sensor 100, and the hot water supply sensor 200 shown in FIG. 1 are connected to the input interface (IF) 710 of the computer 700, and the boiling device 600 shown in FIG. Connected to. The hard disk 750 of the computer 700 is an example of a recording medium for storing the program. The program is read from the hard disk 750 to the memory 740 via the bus 720 and executed by the CPU 730. The hot water supply classification device 300, the first calculation devices 400a to 400c, and the second calculation device 500 may be realized as a plurality of programs that are executed by different computers.

  Hereinafter, detailed configurations and operations of the hot water supply classification device 300, the first calculation device 400a, and the second calculation device 500 will be described.

  A specific processing procedure of behavior estimation in the hot water supply classification apparatus 300 is shown in the flowchart of FIG.

  (Step S1) The behavior estimation unit 310 records the number of reactions for d minutes of the human sensor 100 in the bath and kitchen in the behavior record table shown in FIG. Here, the time interval d for measuring the number of reactions of the human sensor 100 is, for example, 10 minutes.

  (Step S2) Next, for each time, the behavior estimation unit 310 sets the value of the number of reactions of the human sensor 100 for the bath and the value of the number of reactions of the human sensor 100 for the kitchen in the behavior record table for the bath behavior. It compares with the threshold value b_thr and the threshold value d_thr of a kitchen action. If these threshold values are exceeded, it is considered that a bathing action or a kitchen action has been performed during d minutes, and 1 is recorded in the bathing action or kitchen action in the action recording table. If the threshold is not exceeded, 0 is recorded. Note that the values of the bath action threshold value b_thr and the kitchen action threshold value d_thr are, for example, 5 [times].

  By repeating the steps S1 and S2, the behavior of the consumer is estimated and recorded for each time.

  The specific processing procedure of hot water supply type determination in the hot water supply classification apparatus 300 is shown in the flowchart of FIG.

  (Step S1) The amount of hot water used at each time is recorded in the hot water table shown in FIG.

  (Step S2) The action record table is referred for each time. If the bath action is 1 in the action record table, the value of the hot water usage is entered in the bath hot water column at the same time in the hot water table. If the kitchen action is 1, enter the amount of hot water used in the kitchen hot water column. If not, enter the amount of hot water used in the other hot water column. For example, if the bath action and the kitchen action are both 1, the usage amount of the hot water supply is prorated and entered in the bath hot water supply and the kitchen hot water supply, respectively.

  By repeating the above steps S1 and S2, time series data of the amount of hot water used for each hot water type can be created based on the measured values of hot water supply for the bath and kitchen. The use time series data is sent to the corresponding first calculation device 400a for bath, first calculation device 400b for kitchen, and other first calculation device 400c for hot water supply according to the type of hot water supply.

  A specific processing procedure of the first calculation device 400a will be described. This processing procedure is roughly divided into a learning phase for creating a standard hot water supply model and a phase for calculating the usual degree of hot water usage measurement. The learning phase is performed using data on the learning target day for bath hot water, kitchen hot water, and other hot water. The normality calculation phase is performed on the data for the normality calculation target date. In addition, when setting it as the structure using the standard hot water supply model prepared beforehand, a learning phase may be abbreviate | omitted and it is good also as a structure which is not provided with the preparation part 430 of a standard hot water supply model.

  Moreover, about a learning phase, it is preferable to update the created standard hot water supply model suitably by repeating this regularly or with an appropriate timing.

  A specific processing procedure of the learning phase in the first calculation device 400a will be described.

  As shown in FIG. 6, the hot water supply amount DB 420 describes the hot water use amount for each time. The standard hot water supply model creation unit 430 determines the ratio tr [s] of the number of days that the accumulated hot water usage amount on the learning target day has reached a specific amount (s liters), and the specific amount for a plurality of learning target data. Each arrival time is obtained, and the average tm [s] and standard deviation ts [s] of the arrival times are calculated.

  Here, the value of the specific amount s is, for example, a multiple of 10 that is greater than or equal to 0, and the value of s is increased until the arrival time ratio tr [s] becomes 0. Assuming that a set of values that s can take is S, a ratio tr [S] of arrival days, an average tm [S] of arrival times, and a standard deviation ts [S] are used as a standard hot water supply model. This is stored in the standard hot water supply model DB 440.

  FIG. 7 shows the learning target date data used for creating the standard hot water supply model. Assume that a standard hot water supply model is created using data for three days from DAY1 to DAY3. DAY1 represents a pattern that used 10 liters by 12:00 and was not used thereafter. DAY2 represents a pattern that used 20 liters by 12:00 and was not used thereafter. DAY3 represents a pattern that used 20 liters by 24:00 and was not used thereafter.

  Assuming that the set S is {10, 20}, the time of each day when it reaches 10 liters is {12, 6, 12}, so the average tm [10] of the arrival times is 10:00 and the standard deviation ts [10] is 3.46. Further, since 10 liters of hot water is used every day, the ratio tr [10] of the arrival days is 1. Since the time of each day reaching 20 liters is {φ, 12, 24}, the average arrival time tm [20] is 18:00 and the standard deviation ts [20] is 8.48. Since the day when it reaches 20 liters is only two days, the average tr [20] of the arrival times is 2/3.

  Next, before describing the normality calculation phase, setting of a threshold value for determining normality will be described.

  A consumer who is a user can input the desired degree of energy saving using the input device 450. There are three levels of energy saving, for example, “strong”, “medium”, and “weak”. The threshold value setting unit 460 sets one of the first threshold value, the second threshold value, and the third threshold value as a threshold value for determining normality according to the input degree of energy saving. Here, the magnitude relationship between the first to third thresholds is as follows: first threshold <second threshold <third threshold.

  A specific processing procedure of the normality calculation phase in the first calculation device 400a will be described with reference to the flowchart of FIG.

  (Step S1) Calculation unit 410 initializes normal integrated hot water supply amount n stored in normal hot water supply integrated amount storage unit 411 to zero. The time variable t is set to the start time 0:00. Let p_thr be a threshold for determining normality. The amount of hot water used at time t is m (t).

  (Step S <b> 2) The calculation unit 410 substitutes the value of the variable n + m (t) for the variable n ′. When tm [n ′] and ts [n ′] do not exist in the standard hot water supply model, the time is advanced until n ′ exceeds the value existing in the standard hot water supply model, and m (t) is accumulated. This integrated value is stored in the normal hot water supply integrated amount storage unit 411.

(Step S3) The probability calculation unit 412 of the calculation unit 410 sets the value p representing the usual degree to p = 1/2 (1 + erf {(t−tm [n ′]) / {ts [n ′] * sqrt (2)). }) * Tr [n ′] (formula)
Calculate from

  In the right side of the above formula, the part of “1/2 (1 + erf {(t−tm [n ′]) / {ts [n ′] * sqrt (2)})” is the standard tm [n ′]. This represents a cumulative distribution function at time t when a normal distribution with a deviation of ts [n ′] is given. The calculated value represents whether the arrival time of the hot water supply reaches n ′ at time t, whether the arrival time is earlier or later than the average, and is a value ranging from 0 to 1. For example, the probability calculation unit 412 returns 0.5 when the arrival time is the same as the average, returns 0.15 when ts [n ′] is earlier than the average, and returns 0 when 2 * ts [n ′] is earlier. .025 is returned.

  Here, the value of 0.025 means that when assuming a standard hot water supply model with an average arrival time tm [n ′] and standard deviation ts [n ′], tm [n ′] − 2 * ts [ n ′] means that the probability that the accumulated hot water supply amount reaches n ′ at a time before n ′] is 2.5% or less. It can be said that such a hot water supply is a hot water supply having a low ordinaryity.

  In the above equation, tr [n ′] is a value based on the standard hot water supply model. The normality value p is obtained by multiplying the ratio tr [n '] of the arrival days reaching n' as a weight.

  For example, if there are only 20 days out of 30 days when n ′ is reached, a standard hot water supply model representing the average and standard deviation of arrival times reaching n ′ for 20 days is created and calculated from that model. The probability is multiplied by 20/30.

  (Step S4) The threshold value determination unit 413 of the calculation unit 410 substitutes the value of the variable n ′ for the variable n if the usual degree p> = the threshold value p_thr.

  (Step S5) The calculation unit 410 advances the time t by one time (here, 10 minutes).

  (Step S6) If the time t does not exceed the final time 24:00, the calculation unit 410 returns to step S2, and otherwise ends the processing.

  By the above process, the normality value and the normality level (presence / absence) value can be added to the hot water supply usage amount for each hot water supply type at each time. These values are inserted into the hot water supply table of the hot water supply amount DB 420 as shown in FIG. In the hot water supply table, the normality is set to 1 for the amount of hot water used in which the normality p is determined to be equal to or greater than the threshold p_thr in step S4, and it is determined that the normality p is smaller than the threshold p_thr. For things, the normality is set to zero. Hot water supply with normality of 0, that is, low normality, is subject to additional boiling. For such hot water use with low ordinaryity, the hot water use amount is sent to the additional boiling point calculation unit 510 of the second calculation device 500. The additional boiling calculation unit 510 receives this data, sets it as the additional boiling amount, and sends it to the boiling apparatus 600. The boiling device 600 performs an additional boiling amount of water and stores it in a tank (not shown) of the hot water supply device.

  A specific processing procedure of the midnight boiling amount calculation unit 520 in the second calculation device 500 will be described with reference to the flowchart of FIG.

  The midnight boiling calculation unit 520 of the second calculation device 500 obtains, for example, 30 days of hot water usage history from the hot water supply DB 420 and calculates the midnight boiling amount using the history.

  (Step S1) The midnight boiling-up calculating unit 520 acquires the final value of the normal hot water supply integrated amount calculated at the time of calculating the usual degree for the calculation date of the midnight boiling amount.

  (Step S2) The midnight boiling-up calculating unit 520 calculates the average and standard deviation of the final values obtained in Step S1, and sets the average + 2 * standard deviation as the midnight boiling amount. In order to reduce the possibility of running out of hot water, the standard deviation coefficient may be increased.

  An example of the temporal change in the amount of hot water when the normality of hot water is determined according to this embodiment is shown in FIG. The figure (a) has shown the time change of the hot water supply amount [lit; liter] of hot water supply with high usual property of one day. FIG. 5B shows the change over time in the amount of hot water supply of the hot water supply that is usually less common on the same day. On this day, hot water supply with low ordinaryity continues from around 11:00 to around 16:00, and according to the present embodiment, these portions are additionally boiled up.

  FIG. 12 shows a comparative example between boiling water corresponding to the tank full (no control) using actual housing data and without applying the present invention (with cooperative control). There are days that are reversed for about three days, but on average, energy saving of 4.4 [KWh] is achieved per day.

  According to the embodiment of the present invention described above, additional hot water is raised when hot water different from usual occurs for each hot water type, and for hot water used normally, for example, by boiling in the middle of the night A hot water supply apparatus that reduces the amount and realizes energy saving can be provided.

  Note that the present invention is not limited to the above-described embodiment as it is, and can be embodied by modifying the constituent elements without departing from the scope of the invention in the implementation stage. In addition, various inventions can be formed by appropriately combining a plurality of components disclosed in the embodiment. For example, some components may be deleted from all the components shown in the embodiment. Furthermore, constituent elements over different embodiments may be appropriately combined.

100: Human sensor;
200 ... Hot water supply sensor;
300 ... Hot water supply classification device;
310 ... action estimation unit;
320 ... Hot water supply type determination unit;
400a-400c ... Hot water supply ordinary degree calculation device (first calculation device);
410 ... calculation part;
420 ... Hot water supply amount database (DB);
430 ... creating section;
440 ... Standard hot water supply model database (DB);
450 ... input device;
460 ... threshold setting unit;
500 ... boiling amount calculation device (second calculation device);
510 ... Additional boiling amount calculation unit;
520: Late night boiling amount calculation unit;
600 ... Boiling device

Claims (2)

Multiple human sensors installed in different locations and reacting to the presence of nearby people,
A hot water supply sensor for measuring the amount of hot water used,
A classification device that determines a hot water supply type corresponding to a consumer's behavior estimated based on an installation location where the human sensor has reacted, and classifies the hot water use amount into the hot water use amount for each hot water type,
A value indicating the degree of normality is calculated for the amount of hot water used for each hot water supply type, hot water whose value is lower than the threshold value is determined to be hot water having low normality, and hot water whose value is equal to or greater than the threshold value. A first calculation device for determining that the hot water supply is usually high;
A second boiling amount is calculated for the hot water supply determined to be the hot water supply having the low normality, and a second boiling amount is calculated for the hot water supply determined to be the hot water supply having the high normality. A calculation device;
A elevating device for elevating the first elevating amount and the second elevating amount;
A hot water supply apparatus comprising: The first calculation means includes
A storage unit for storing an integrated amount of hot water use for each hot water supply type;
A database that stores a standard hot water supply model that represents a ratio of each number of days that the accumulated amount has reached a specific amount within a predetermined period, an average of arrival times that have reached the specific amount, and a standard deviation of the arrival times;
A probability calculator that calculates a value obtained by multiplying the probability based on a cumulative distribution function at a specific time in the normal distribution of the average and standard deviation by the ratio as a value representing the degree of normality;
The hot water supply apparatus according to claim 1, comprising:

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