JP2011043984A - Living situation estimation method and system for electric power consumer resident, and living situation estimating program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To automatically set an activity current threshold and a value k necessary for estimation to values suitable for an electric power consumer thereof. <P>SOLUTION: A total load current is measured about a plurality of days, a data group is obtained by the use of a measurement value (A) of the total load current which is decided so that the total load current is measured at a home day of the electric power consumer to set the data group as a value determining data group (B, C), k% values are calculated by k assumption values by the use of a plurality of preset the assumption values about the value determining data group are arranged in a descending order, and graphed (D, E), graphs by the k assumption values are compared in a preset area CA (F), one graph is selected based on a graph shape, the k assumption value corresponding to the selected graph is set as the value k (G), and the k% value of a second position preset to the selected graph is set as the activity current threshold (E). <P>COPYRIGHT: (C)2011,JPO&INPIT

Description

  The present invention relates to a living situation estimation method and system for a consumer of electric power consumers and a living situation estimation program. More specifically, the present invention relates to a method and system for estimating a living situation such as the safety, presence / absence, sleeping / non-sleeping of a resident by a non-intrusive method that does not enter the home of a power consumer, and living It relates to a situation estimation program.

  As a conventional system for estimating the living situation of a resident, for example, there is a living situation estimating system (Patent Document 1). In this living situation estimation system, the total power consumption is measured at regular time intervals Δt by a power meter installed near the service line of the power consumer, and the absolute value of the difference from the total power consumption of the previous measurement is obtained. The target data. And about the data group which consists of several target data obtained in the past fixed time width, arrange | position target data in descending order, and use the preset value k, "The number of the said target data more than the value is. The k% value that is “k% with respect to the total number of data in the data group” is calculated. The calculation of the k% value is performed every fixed calculation time step Δt ′. Then, the calculated k% value is compared with a preset threshold value, and if k% value ≧ threshold value, it is determined that there is an intentional operation of the electric device by a resident in the power consumer. When k% value <threshold, it is determined that there is no intentional operation of the electric device by the resident in the power consumer.

  Appropriate values are set in advance as the value k and the threshold value.

  According to this living situation estimation system, information on a specific electric device arranged in the electric power consumer is required without providing an additional function or device in the electric device itself arranged in the electric power consumer. It is possible to determine whether or not an occupant intentionally operates an electric device, that is, whether the occupant uses the electric device due to an indoor activity. It is possible to estimate the living situation such as whether the resident is active or not, and further the living situation including whether the resident is living healthy. Therefore, it is possible to reduce the maintenance cost of the system, and it is possible to promote the spread of the system and to improve the living safety of, for example, the elderly living alone or the household only for the elderly.

Japanese Patent No. 4172709

  However, in the living situation estimation system of Patent Document 1, it is necessary for the administrator to set the value k and the threshold to values suitable for the power consumer while visually confirming the measurement data, and automatic setting is difficult. .

  The present invention does not provide an additional function or device in the electrical equipment itself disposed in the power consumer, and does not require information on the specific electrical equipment disposed in the power consumer, The living situation of the resident can be estimated, and the value k and the threshold value for discriminating the presence or absence of the intentional operation of the electric equipment by the resident are automatically set to values suitable for the electric power consumer. It is an object to provide a living situation estimation method and system that can be set.

  In order to achieve this object, the invention according to claim 1 measures the total load current by the electric equipment arranged in the electric power consumer at every constant time interval Δt, and changes the total load current at every constant time interval Δt. Is obtained as target data, and a value k is used for a data group consisting of a plurality of target data obtained in the past constant time width T for each constant calculation time step Δt ′, Calculate the k% value, which is the value that the above target data count is k% with respect to the total number of data in the data group, and based on whether the k% value is greater than or equal to the active current threshold. A life situation estimation method for estimating the presence or absence of a resident's intentional operation on an electrical device, measuring the total load current for multiple days, and determining the total load that is determined to be measured on the home days of electricity consumers Find the data group using the measured current value In addition to the fixed data group, for the value determining data group, k% values are calculated for each k hypothesized value using a plurality of k assumed values set in advance, arranged in descending order, and graphed for each k hypothesized value. Comparison is made in a predetermined region, one graph is selected based on the graph shape, k assumed value corresponding to the selected graph is set as a value k, and k% value at the second position set in advance for the selected graph is This is the active current threshold.

  The time fluctuation of the total load current due to the electrical equipment installed in the power consumer is caused by the intentional operation of the resident on the electrical equipment, as well as the state transition such as on / off such as a refrigerator. Are caused by the operation of electrical equipment that automatically repeats. Therefore, the total load current is measured at regular time intervals, the absolute value of the change in the total load current at each regular time interval is obtained as the target data, and within the past regular time width for each regular calculation time step. The k% value is calculated for the data group consisting of the absolute values of the change in the total load current obtained in (1). Here, the k% value is defined as a value in which the number of target data in the data group that is equal to or greater than that value is k% with respect to the total number of data in the data group. When the value of k is appropriately selected, the k% value reflects the change in the total load current of the electrical equipment due to the resident's intentional operation, and changes state such as on / off like a refrigerator. This eliminates the influence of the change in the total load current due to the operation of the electrical equipment that automatically repeats the above.

  Therefore, when the time change of the k% value is observed, for example, when the k% value is large, it can be estimated that the resident's intentional operation on the electric device has been performed. From this, it can be estimated that the resident is at home and is active. On the other hand, in a time zone where the k% value is small, it can be estimated that the resident's intentional operation on the electric device is not performed, and the resident is absent or is sleeping. In addition, when the length of time when the k% value is small is unusual, for example, when the resident's activity cannot be confirmed for more than a whole day, the resident is bedridden or the resident falls down in the house The possibility of an emergency is also conceivable. As described above, according to the present invention, it is possible to estimate the living situation of the electricity consumer resident, for example, whether he / she is at home / not at home or sleeping / not sleeping or even if the resident is living normally. .

  In the present invention, an active current threshold value is provided to determine the magnitude of the k% value, and this active current threshold value is automatically acquired. The automatic acquisition of the active current threshold is performed as follows. First, measure the total load current for the power consumer for multiple days, collect the measurement data, and extract the data judged to be measured from the collected measurement data on the home day of the power consumer To do. Here, the extraction of data determined to be measured on the day at home is, for example, if there are measurement data for X days, the measurement data for one day is totaled for each day, and the total load current amount for one day is calculated. The measurement is performed by extracting the measurement data for Z days in order from the day with the largest total daily load current.

  Then, a data group (value determination data group) is obtained in the same manner as the above estimation is performed using the extracted data, and a k% value is calculated using a preset k assumption value. Here, a plurality of k assumed values are used. The calculated k% values are arranged in descending order according to k assumed values and graphed, and the graph shapes of the comparison areas set in advance are compared. Then, one graph is selected based on the graph shape, the k assumed value corresponding to the selected graph is set as the value k, and the k% value at the second position set in advance for the selected graph is obtained. Let the value be the active current threshold. Here, in the selection of the graph based on the graph shape, the difference between the maximum value and the minimum value of the k% value in the preset region is large and the number of large values is small, and the preset k% of the first position. A graph whose value is equal to or greater than a preset minimum current value is selected.

  Using the k and the active current threshold value obtained in this manner, the magnitude of the k% value is determined, and the presence or absence of an intentional operation of the electric device by the resident is determined. If the k% value is larger than the active current threshold, it is considered that the occupant is intentionally operating the electrical equipment, that is, the electrical equipment is used for indoor activities, and the resident is at home. And it can be estimated that it is active. On the other hand, if the k% value is less than the active current threshold value, it is considered that the occupant is not operating the electrical device intentionally, that is, the indoor device is not used for indoor activities, and the resident is absent or goes to sleep. It can be estimated that it is inside.

  Furthermore, the time when the k% value based on the total load current of the power consumer is continuously above the active current threshold, that is, the time during which the activity is continued, or the time when it is continuously below, ie, the activity is stopped. If the time is far from the expected time from the normal life pattern, there may be an emergency such as the resident being bedridden or the resident falling indoors Is also possible.

  According to a second aspect of the present invention, there is provided a measuring means for measuring a total load current by an electric device disposed in an electric power consumer at a constant time interval Δt, and a fixed time interval based on a measured value obtained from the measuring means. An absolute value of a change in total load current for each Δt is obtained as target data, and a value k is obtained for a data group composed of a plurality of target data obtained in the past constant time width T for each constant calculation time step Δt ′. And calculating means for calculating a k% value that is “the number of the target data that is equal to or greater than that value is k% of the total number of data in the data group”, and k% of the active current threshold An estimation system for estimating the presence or absence of a resident's intentional operation with respect to electrical equipment in a power consumer based on whether the value is large or not, comprising: Measured at home A plurality of days of total load current measurement values, a plurality of preset k assumption values, a preset graph comparison area, a first position in a preset graph comparison area, and a preset minimum A data unit is obtained by using a current value, a storage unit that stores a preset second position, and a measured value of the total load current stored in the storage unit to obtain a data group for value determination. For the data group for determination, k% values are calculated for each k hypothesized value using a plurality of k hypothesized values stored in the storage means, arranged in descending order, and graphs for each k hypothesized value are stored in the storage means. The selected graph is stored in the storage means, and the value k determining means for selecting the k assumed value corresponding to the selected graph as the value k. K% value of the second position In which and a threshold determination unit that the dynamic current threshold. Therefore, it is possible to estimate the presence or absence of a resident's intentional operation on the electrical equipment, and the living situation of the electricity consumer resident, for example, whether he / she is living at home / not at home or sleeping / not sleeping, and whether the resident is living normally. , Can be estimated.

  According to a third aspect of the present invention, there is provided a notification system for transmitting the presence / absence of a resident's intentional operation to an external information processing apparatus. The information processing device displays information indicating the time change of the k% value, etc., so that the manager or owner of the information processing device can understand the life situation of the resident of the electric power consumer, for example, at home / not at home or at bed / no sleep. It is possible to estimate whether the occupant is in good health at bedtime.

  Furthermore, the life situation estimation program according to claim 4 is based on at least a measurement value based on a measurement value for each time interval Δt of the total load current by the electric equipment arranged in the power consumer stored in advance in the storage means. The absolute value of the change in the total load current for each interval Δt is obtained as target data, and for each calculation time step Δt ′ previously stored in the storage means, in the past time width T stored in advance in the storage means With respect to the obtained data group composed of a plurality of target data, using the value k, a k% value that is a value “the number of target data equal to or greater than that value is k% with respect to the total number of data in the data group”. Calculating means, estimating means for estimating presence / absence of a resident's intentional operation on the electric equipment in the electric power consumer based on whether or not the k% value is larger than the active current threshold, and storing means in advance Remembered total load Among the measured values for each flow time interval Δt, a data group is obtained by using data for a plurality of days determined to be measured on the home day of the power consumer, and is used as a value determining data group. For a data group, a plurality of k assumption values stored in advance in the storage means are used to calculate k% values for each k assumption value, arranged in descending order, and are graphed, and a graph for each k assumption value is stored in the storage means in advance. A comparison area of the graphs selected, one graph is selected based on the graph shape, and a value k determining means for setting the k assumed value corresponding to the selected graph to a value k; This is for causing the computer to function as a threshold value determining means using the k% value at the second position as the active current threshold value.

  In other words, the computer and the life situation estimation program realize the calculation means, the estimation means, the value k determination means, and the threshold value determination means of the life situation estimation system.

  According to the life situation estimation method and system and the life situation estimation program of a power consumer resident according to the present invention, an advanced information processing function and a communication function such as a wireless communication device are added to or built in the electrical equipment itself in the power consumer. Without being able to estimate the presence or absence of intentional operation of the resident on the electric equipment with a non-intrusive method and simple configuration that does not enter the home of the electric power consumer, It is possible to estimate whether the resident is living normally at home or away from home or sleeping or not sleeping. Furthermore, in the present invention, the electrical equipment itself installed in the power consumer does not communicate with the information processing apparatus outside the power consumer, and the power demand is transmitted in a non-intrusive manner that does not enter the household of the power consumer. Since the living situation of the resident can be estimated, it can be configured so that the resident is not conscious of being monitored by a third party as much as possible.

  Further, in the present invention, the total load current of the power consumer is measured for a plurality of days, data that is determined to be measured at home is extracted, and the value k is calculated using the extracted data. Since the active current threshold value is set, the value k and the active current threshold value can be set according to the load pattern of the electric power consumer, and can be set automatically. Therefore, it is not necessary for the administrator to perform the work and experience of setting the measurement data by visual observation, etc. For example, even when a large number of power consumers are to be estimated simultaneously, It is possible to quickly set an appropriate value k and an active current threshold for each power consumer. Moreover, although the load pattern of a power consumer changes according to a seasonal change etc., since the value k and the active current threshold can be automatically set, the value k and the activity are changed according to the change of the load pattern. It is easy to update the current threshold. Further, when the administrator sets the value k and the active current threshold, the setting value may vary depending on the subjectivity of the administrator. However, by automating the setting of the value k and the active current threshold, the subjectivity of the administrator The value k and the active current threshold can always be set on a constant basis. In addition, when setting the value k and the active current threshold value, the value k and the active current threshold value become values according to the most recent load pattern of the power consumer by using the latest measurement data. Can be estimated.

It is a flowchart explaining an example of embodiment of the living condition estimation method of this invention. It is a block diagram which shows an example of embodiment of the living condition estimation system of this invention. It is a block diagram which shows the structural example of the living condition estimation system of this embodiment. The procedure for setting the value k and the active current threshold D is conceptually shown, (A) is a conceptual diagram showing the measured value of the total load current, and (B) is the target data obtained based on the measured value of the total load current. (C) is a conceptual diagram showing a value determining data group made up of a plurality of target data obtained within a time width T, and (D) is a list of target data in the value determining data group in descending order. (E) is a graph in which k% values are calculated for each k assumed value and arranged in descending order, (F) is a graph in which the graphs obtained for each k assumed value are superimposed, (G) is a value k and activity It is a conceptual diagram which shows a mode that a current threshold value is determined. It is a figure which expands and shows the comparison area | region of the graph of each k assumption value. It is a conceptual diagram which shows an example of the time change of the total load current of an electric power consumer. It is a conceptual diagram which shows an example of the time change of the calculated k% value. It is a conceptual diagram which shows the other example of the time change of the calculated k% value. It is a figure which shows the relationship between presence / absence and the total load current amount of 1 day. It is a figure which shows the time transition of k% value (estimated index value) of a certain household, and shows the example of one day in autumn. It is a figure which shows the time transition of k% value (estimated index value) of a certain household, and shows the example of one day in winter. It is a figure which shows the example which rearranged k% value (estimated index value) in descending order. It is a figure for demonstrating the conditions 1 which select a graph, and is a schematic diagram of the example which rearranged k% value (estimated index value).

  Hereinafter, the configuration of the present invention will be described in detail based on the best mode shown in the drawings.

  FIG. 1 to FIG. 4 show an embodiment of a method and system for estimating a living situation of a power consumer resident according to the present invention. In the present embodiment, a case where the present invention is applied to the power consumer 2 shown in FIG. 2 will be described.

  The indoor wiring circuit 17 in the electric power consumer 2 of the present embodiment includes, as the electrical equipment 3, a living room lighting equipment 3e including a television receiver 3a, a refrigerator 3b, an inverter air conditioner 3c, a fluorescent lamp 3d, an incandescent lamp, and an incandescent lamp. A toilet lighting device 3f made of a lamp is connected. The indoor wiring circuit 17 is connected to an electric power system such as an electric power company through electric wires installed on the lead-in wire 4 and the utility pole 5. In addition, the electric equipment 3 connected to the indoor wiring circuit 17 in the electric power consumer 2 is not limited to what was illustrated in this embodiment.

  As shown in FIG. 1, the method for estimating the living situation of a power consumer resident according to the present invention comprises a parameter setting step (steps S <b> 1 to S <b> 2 in FIG. 1) and an estimation step (steps S <b> 3 to S <b> 7 in FIG. 1). Yes. The parameter setting process is performed, for example, as necessary. The total load current is measured for a plurality of days, and the measured value of the total load current that is determined to be measured on the home day of the power consumer (FIG. 4). (A)) is used to obtain a data group to be a value determination data group (FIGS. 4B and 4C), and the value determination data group is arranged in descending order for each data group and is graphed (FIG. 4 ( D)), using a plurality of preset k assumption values, k% values are extracted from the respective graphs for each k assumption value, and further arranged in descending order (FIG. 4 (E)), for each k assumption value. The graphs are compared in a preset area CA (FIG. 4 (F)), one graph is selected based on the graph shape, k assumed value corresponding to the selected graph is set as the value k, and the selected graph K at the set second position (Y in FIG. 4E) And the value activities current threshold (D in FIG. 4 (E)) is (step S2 in FIG. 1, FIG. 4 (G)) as. Here, in the selection of the graph based on the graph shape, the difference between the maximum value and the minimum value of the k% value in the preset area CA is large and the number of large values is small, and the first in the preset area CA is small. A graph is selected in which the k% value at the position (m5 in FIG. 4F) is equal to or greater than the preset minimum current value (U in FIG. 4F).

  Further, in the estimation step, the total load current by the electric equipment 3 disposed in the electric power consumer 2 is measured at regular time intervals Δt (step S3 in FIG. 1), and the total load current at regular time intervals Δt. The absolute value of the change is obtained as target data (step S4), and the value k is used for a data group composed of a plurality of target data obtained in the past constant time width T for each constant calculation time step Δt ′. K% value is calculated (step S5), and based on whether or not the k% value is equal to or greater than the active current threshold value D, the presence or absence of a resident's intentional operation on the electric equipment 3 in the power consumer 2 is estimated. (Step S6). And in this embodiment, based on the presence or absence of a resident's intentional operation with respect to the electric equipment 3 in the electric power consumer 2, the living situation of the electric power consumer resident, for example, home / non-home or sleeping / non-sleeping Is to estimate whether the resident is living well (step S7).

  Here, the k% value is defined as a value in which the number of target data in the data group that is equal to or greater than that value is k% with respect to the total data number of the data group.

  The living situation estimation method is realized as a living situation estimation system of the present invention. In this embodiment, a case where the living situation estimation system 1 estimates the living situation of a resident of the power consumer 2 using the living situation estimation method will be described as an example.

  As shown in FIGS. 2 and 3, for example, the living situation estimation system 1 of the present embodiment is a measuring unit that measures the total load current due to the electrical equipment 3 disposed in the power consumer 2 at regular time intervals Δt. 10 and the absolute value of the total load current change for each constant time interval Δt based on the measurement value obtained from the measuring means 10 as target data, and the past constant time width T for each constant calculation time increment Δt ′. Electric power demand based on calculation means 11 for calculating a k% value using a value k and whether or not the k% value is larger than the active current threshold D for a data group consisting of a plurality of target data obtained in And estimation means 12 for estimating the presence or absence of a resident's intentional operation on the electrical equipment 3 in the house 2.

  In addition, the living situation estimation system 1 of the present embodiment includes the measurement value obtained from the measurement unit 10, the calculation result of the calculation unit 11, and the total load current for a plurality of days determined to have been measured on the home day of the power consumer 2. Measured values, a plurality of pre-set k assumption values, graph comparison area CA and positions m1, m2, m3, and m4, first position m5 in graph comparison area CA, minimum current value U, and second position Y For example, a storage device 13 (storage means) such as a RAM (Random Access Memory) or a hard disk for recording a time interval Δt, a calculation time step Δt ′, a time width T, etc., and a total load current stored in the storage device 13 Using the measured values, a value determination data group is obtained, and for the value determination data group, k% values are calculated for each k assumption value using a plurality of k assumption values stored in the storage device 13 and arranged in descending order. Graph and k assumption Each graph is compared in the comparison area CA of the graph stored in the storage device 13, one graph is selected based on the graph shape, and the value k is determined with the k assumed value corresponding to the selected graph as the value k. Means 16 and threshold value determination means 15 that uses the k% value of the second position Y stored in the storage device 13 for the selected graph as the active current threshold value D.

  This living situation estimation system 1 can also be realized by executing the living situation estimation program of the present invention on a computer. That is, the computing means 11 and the estimating means 12 include at least one arithmetic processing unit such as a CPU and MPU, an interface that inputs and outputs data, a computer that includes a memory that stores programs and data, and a life situation estimation program. , Threshold value determining means 15 and value k determining means 16 are realized. That is, the arithmetic processing unit realizes the arithmetic means 11, the estimation means 12, the threshold value determination means 15, and the value k determination means 16 by using a control program such as an OS, a life situation estimation program, and necessary data stored in the memory. is doing. Further, an output device such as a CRT display or a printer may be connected to the computer.

  In carrying out the living situation estimation by the living situation estimation system 1, first, the value k determining means 16 determines whether or not the setting of the value k and the active current threshold D is necessary (S1). The value k determination means 16 starts the estimation of the living situation when a predetermined period such as one day, several days, several months, etc. has elapsed since the previous setting of the value k and the active current threshold D. When it is executed, it is determined that the value k and the active current threshold D need to be set, and the process proceeds to step S2 where the value k and the active current threshold D are set. On the other hand, the value k determining means 16 determines that the setting of the value k and the active current threshold D is unnecessary, for example, immediately after the previous setting, and proceeds from step S1 to step S3. The storage device 13 stores the previous value k and the setting date and time of the active current threshold D, and the value k determining means 16 reads the setting date and time stored in the storage device 13 to know the previous setting date and time. it can. In addition, this time is the first implementation of the living situation estimation, and when the value k and the active current threshold D are not set, a blank symbol is stored as the set date.

  In step S2 of the parameter setting step, the value k determining unit 16 sets the value k, and the threshold determining unit 15 automatically sets the active current threshold D. Here, the storage device 13 stores measurement data on the total load current of the power consumer 2 in advance. That is, the total load current measured by the measuring means 10 is supplied to and stored in the storage device 13.

  In the storage device 13, for example, data for the most recent tens of days or months are stored as the total load current. The value k determining unit 16 extracts data determined to be measured on the day at home from the stored data. For example, if data for X days is stored in the storage device 13, the data for one day is totaled for each day to obtain the total load current amount for one day, and the one with the larger total load current amount for one day To extract data for Z days. This is because, among the past X days, the number of days that were completely absent is less than (XZ) days, in other words, at least the number of days that the resident has intentionally operated the electrical equipment. It is assumed that there are Z days. Z is determined from such a viewpoint and is stored in the storage device 13 in advance. For example, the X day is 30 days and the Z day is 7 days.

  For example, if the measurement of the total load current by the measuring means 10 is performed at 1 minute intervals (time interval Δt = 1 minute), the storage device 13 stores 1 (pieces) × 60 (minutes) as data for one day. X24 (time) = 1440 data (measured value of total load current) is stored, and (1440 × X) data is stored as data for X days. Then, the value k determining means 16 sums the measured values for each day to calculate the total load current amount for one day, and extracts data for Z days from the one with the larger total daily load current amount. Thereby, (1440 × Z) pieces of data for Z days are extracted as data determined to be measured on the day when the electric power consumer 2 is at home. The extracted data is stored in the storage device 13.

Based on the extracted data for Z days, the value k determining means 16 performs the same processing as steps S4 and S5 described later to obtain a data group for value determination. For example, the measured value of the total load current measured at a certain measurement time t is Da (t), and the total load current measured at the measurement time (t−Δt) immediately before the measurement time t is Da (t− Assuming that Δt), the absolute value ΔDa (t) of the total load current change at a constant time interval Δt is expressed by Equation 1. The value k determining means 16 obtains the absolute value ΔDa (t) of the total load current change for each time interval Δt and sets it as target data (FIGS. 4A and 4B). In FIG. 4A, data Da (t) for each time interval Δt is described as d1, d2,..., And in FIG. 4B, the absolute value (target data) ΔDa (t) for each time interval Δt is shown. .DELTA.d1, .DELTA.d2,...
<Equation 1>
ΔDa (t) = | Da (t) −Da (t−Δt) |

  Next, the value k determination means 16 obtains a data group for value determination consisting of a plurality of target data obtained in the past fixed time width T for every fixed calculation time step Δt ′ (FIG. 4 (C )). Now, since there are n (= T / Δt) target data from the time (t−T) retroactive to the past by the time width T from the time t, there are n target data. A data group for value determination consisting of the target data is sequentially obtained for each calculation time step Δt ′.

  Next, the value k determining means 16 reads the k assumed value set in advance and stored in the storage device 13, performs the same processing as that of step S5 described later, and uses the k assumed value to obtain k%. Calculate the value. The k assumed value corresponds to a value k, which will be described later, and is a representative value of the value k that is used for convenience to obtain an appropriate value k. In the present embodiment, values of 5, 10, 25, and 50 are set in advance as k assumed values. However, the k assumed value is not limited to these values, and other values may be used. Further, the number of k assumed values is not limited to four, but may be two or three, or may be five or more.

  Next, the value k determining unit 16 arranges the target data included in the value determining data group in descending order (FIG. 4D), and obtains the k% value using the k assumed value. That is, of the target data arranged in descending order, the “n × k / 100” -th target data from the larger one is set as the k% value. For example, if there are 100 (n = 100) target data in one value determining data group, and the k hypothesized value is 5, among the target data arranged in descending order, the fifth ( = 100 × 5 ÷ 100) If the value of the target data is k% and the k assumption value is 10, the 10th target (= 100 × 10 ÷ 100) from the largest direction among the target data arranged in descending order The data value is the k% value. The same applies when the k assumed value is 25 or 50. Here, when the value of “n × k / 100” does not become an integer, the value of “n × k / 100” is rounded up and used. However, it is not necessarily limited to rounding up, and may be rounded down or rounded off.

  Next, the value k determining unit 16 arranges the k% values obtained as described above in descending order for each k hypothesized value and graphs them (FIG. 4E). The k% value is obtained for all the data for Z days, but this graphing is performed for all the Z days by k assumed values. Then, the respective graphs are compared in the area CA set in advance and stored in the storage device 13 (FIG. 4F). Here, since the graph usually shows a shape as shown in the figure, the comparison area CA is determined so that a portion that curves (changes) greatly can be compared. In the present embodiment, the comparison area CA is from the position m1 to the position m4 when the k% values are arranged in descending order (FIG. 5).

  The value k determining means 16 selects one graph based on the graph shape. Here, in the selection of the graph based on the graph shape, the difference between the maximum value and the minimum value of the k% value in the preset region is large and the number of large values is small, and the preset k% of the first position. A graph whose value is equal to or greater than a preset minimum current value is selected. In this embodiment, selection is performed using the following two conditions. That is, the difference between the maximum value and the minimum value of the graph in the comparison area CA is large and the number of large values is small (Condition 1), and the preset k% value of the first position m5 in the comparison area CA is preset. The graph of the minimum current value U or higher (condition 2) is selected. Then, an assumed k value corresponding to the selected graph is set as a value k (FIG. 4G).

In the present embodiment, Formula 2 is adopted as Condition 1, and the value k determination unit 16 selects a graph in which N ^k of Formula 2 is the largest. Here, the selection of the graph will be described with reference to FIG. FIG. 5 is an enlarged view of the comparison area CA, that is, the position m1 to the position m4. In the present embodiment, the positions m2 and m3 are provided in the comparison area CA. For example, (m1−m2) = (m2−m3) = (m3−m4), that is, at equal intervals. Positions m1, m2, m3 and m4 are set. However, it is not always necessary to set the positions m1, m2, m3, and m4 at equal intervals. If the magnitude relationship is position m1 <position m2 <position m3 <position m4, the positions may not be equally spaced. A position suitable for the determination of condition 1 may be used. In FIG. 5, the shape of the graph is changed from that of FIG. 4 in order to make the concept of graph selection easy to understand.
<Equation 2>
N ^k = (k% value of m1−k% value of m4) ÷ {(k% value of m2 + k% value of m3) ÷ 2}

In condition 1, the larger the difference between the k% value at position m1 and the k% value at position 4, the better, and the smaller the k% value at position m2 and the k% value at position m3, the better. This is expressed by Equation 2 as an expression. If the value of N ^k in Expression 2 is large, it can be said that the difference between the maximum value and the minimum value of the graph is large and the number of large values is small in the comparison area CA. Here, it is assumed that the values of N ^k are graph (1): 0.42, graph (2): 0.62, graph (3): 1.04, graph (4): 5.6. In 1, the value k determining means 16 selects the graph (4) having the largest value of N ^k .

Further, in the present embodiment, Formula 3 is adopted as the condition 2, and the value k determining unit 16 determines whether or not the graph selected by the condition 1 satisfies the condition 2, and if the condition is satisfied, selects the graph. If the condition is not satisfied, the condition other than the currently selected graph that satisfies the condition 1 and condition 2 is selected again. Here, the first position m5 is set in advance in the comparison area CA.
<Equation 3>
K% value of first position m5 ≧ U

In the graph (4) selected under the condition 1, if the k% value at the first position m5 (hereinafter, the k% value is appropriately referred to as an estimated index value) is U or more, the value k determining means 16 displays the graph (4 ) Keep the selection. On the other hand, if the k% value at the first position m5 of the graph (4) is less than U, the value k determining means 16 reselects the graph (3) having the second largest value of N ^k in the condition 1. . Then, the value k determining means 16 applies the graph (3) to the condition 2 and maintains the selection of the graph (3) if the k% value at the first position m5 is greater than or equal to U, and k% at the first position m5. If the value is less than U, the process returns to Condition 1 to reselect the graph.

  In the present embodiment, position m1: 2% from the largest in descending order, position m2: 5% position, position m3: 7% position, position m4: 10% position, first position m5: 5% position, U = 0.5A. However, it is not limited to these.

  The value k determining means 16 sets the k assumed value corresponding to the graph selected in this way as the value k (FIG. 4G). In FIG. 4G, the value k determining means 16 selects a graph with an assumed k value of 10, and sets the value k to 10. Then, the value k determining unit 16 stores the obtained value k in the storage device 13.

  Next, the threshold value determination means 15 obtains a preset k% value of the second position Y for the graph selected by the value k determination means 16 and sets it as the active current threshold value D (FIG. 4E). Then, the threshold value determination unit 15 stores the obtained active current threshold value D in the storage device 13 and also stores the value k and the date and time when the active current threshold value D is obtained in the storage device 13.

  In the present embodiment, the second position Y is 5. However, the present invention is not limited to this.

  Next, the estimation process will be described. In step S <b> 3, the measuring unit 10 measures the total load current by the electric device 3 disposed in the power consumer 2. Here, the measuring means 10 measures the total load current due to the electric equipment 3 disposed in the power consumer 2, that is, the load current of the power consumer 2 as a whole. In this embodiment, an ammeter is used.

  The measuring means 10 is installed in the vicinity of the service entrance of the service line 4 of the power consumer 2. By adopting such a configuration, the living situation estimation method and system according to the present invention uses the total load current by the plurality of electrical devices 3 connected to the indoor wiring circuit 17 in the power consumer 2, that is, A method and a system that do not use information on a specific electrical device 3 disposed in the power consumer 2 can be used.

  The total load current Da (t) at time t of the power consumer 2 measured and output by the measuring means 10 is recorded in the storage device 13.

Next, the calculating means 11 calculates | requires absolute value (DELTA) Da (t) of a total load current change based on the total load current Da (t) obtained by the process of step S3. Now, let Da (t) be the total load current measured at a certain measurement time t, and let Da (t-Δt) be the total load current measured at the measurement time (t−Δt) immediately before the measurement time t. Then, the absolute value ΔDa (t) of the total load current change at a constant time interval Δt is expressed by Equation 4.
<Equation 4>
ΔDa (t) = | Da (t) −Da (t−Δt) |

  Next, the calculation means 11 calculates | requires k% value as follows (S5). In other words, it is assumed that there are n ΔDa from the time (t−T) retroactive to the past by the time width T from the time t to the time t. In this case, n = T / Δt. These n ΔDa are arranged in descending order, that is, in descending order, and the “n × k / 100” -th ΔDa from the larger one is set as a k% value (estimated index value). Here, when the value of “n × k / 100” does not become an integer, the value of “n × k / 100” is rounded up and used. However, it is not limited to rounding up, and the decimal part may be rounded down or rounded off. In this embodiment, Δt = Δt ′ = 1 minute and T = 30 minutes. However, it is not restricted to these values.

  The k% value is a reference value for selecting the upper k% ΔDa from n ΔDa obtained between time (t−T) and time t, and is equal to or greater than the k% value of n ΔDa. ΔDa is expressed as “n × k / 100”. When k is appropriately selected, the k% value reflects the change in the total load current of the electrical equipment 3 due to the intentional operation of the resident in the electric power consumer 2, and the resident's value like the refrigerator 3b. The influence of the change in the total load current due to the operation of the electrical device 3 that automatically repeats the state transition such as on / off regardless of the operation is eliminated. In the present invention, since the value k automatically set in step S2 is used, the k% value is determined by the operation of the electric device 3 that automatically repeats the state transition such as on / off regardless of the resident's operation. The influence of the change in the total load current can be eliminated. The calculating means 11 stores the obtained k% value in the storage device 13.

  The relationship between the influence of the change in the total load current due to the operation of the electric device 3 that automatically repeats the state transition such as on / off regardless of the resident's operation and the value k will be described with reference to FIGS.

  For example, FIG. 6 shows a concept of the time change of the total load current of the power consumer 2 actually measured with the measurement time interval Δt as 1 minute. The fluctuation of the total load current, which is periodically turned on and off as indicated by the symbol J in the figure, is due to the operation of the refrigerator 3b. Based on the time change of the total load current Da (t) shown in FIG. 6, the time width T was set to 30 minutes, the calculation time increment Δt ′ was set to 1 minute, and the time change of the k% value was obtained. This is shown in FIGS. FIG. 7 shows the case where k = 25, and FIG. 8 shows the case where k = 50.

  Both FIG. 7 and FIG. 8 exclude the uneven and relatively low fluctuation of the total load current due to the operation of the refrigerator 3b seen in FIG. In FIG. 8, as the value of k is larger, the result of reflecting the portion where the change in the total load current is smaller than that in FIG. In addition, at times such as 7:00 to 9:00 or 18:00 to 22:00, the resident is generally at home, and the frequency of using the electrical equipment 3 for cooking, washing, entertainment, etc. is considered high. The k% value is large. Therefore, for example, by setting k to about 25 to 50, the influence of the change in the total load current due to the operation of the electric device 3 that automatically repeats the state transition such as on / off can be excluded from the k% value. The change in the total load current of the electric device 3 due to the intentional operation can be reflected in the k% value in a deep color.

  Therefore, when the time change of the k% value is observed and the k% value is large as shown by the symbol M in FIGS. 7 and 8, for example, the resident's intentional operation on the electric equipment 3 is performed. Can be estimated. From this, it can be estimated that the resident is at home and is active. On the other hand, it can be estimated that the resident's intentional operation with respect to the electric device 3 is not performed in the time zone where the k% value is small, and the resident is absent or is sleeping. In addition, when the length of time when the k% value is small is unusual, for example, when the resident's activity cannot be confirmed for more than a whole day, the resident is bedridden or the resident falls down in the house The possibility of an emergency is also conceivable. As described above, according to the method of estimating the living situation of the electricity consumer resident of the present invention, the living situation of the resident, for example, whether or not the resident is living normally at home / not at home or sleeping / not sleeping, Can be estimated.

  In this embodiment, the estimation means 12 estimates the presence or absence of the intentional operation of the electric equipment 3 by the resident in the electric power consumer 2 using the k% value obtained by the process of step S5 (S6). Specifically, the estimation means 12 compares the k% value recorded in the storage device 13 with the value of the active current threshold D.

  The active current threshold value D is a threshold value for determining whether or not the resident has intentionally operated the electric device 3 in the electric power consumer 2, and is calculated by executing step S <b> 2 and recorded in the storage device 13. Has been.

  Then, when the k% value changes from a value equal to or less than the active current threshold D to a value greater than the active current threshold D, the estimation unit 12 performs an intentional operation of the electric device 3 by a resident in the power consumer 2. Judge that started.

  On the other hand, when the k% value changes from a value larger than the active current threshold D to a value less than or equal to the active current integrated value D, the estimating means 12 intentionally operates the electric device 3 by a resident in the power consumer 2. Is determined to have ended.

  Furthermore, in this embodiment, the estimation means 12 estimates the living situation of the resident of the power consumer 2 based on the estimation result of the presence / absence of the intentional operation of the electric device 3 by the resident obtained by the process of step S6. Perform (S7).

  In the process of step S6, the estimation means 12 determines that the resident is at home and is active when it is estimated that the intentional operation of the electric device 3 by the resident is started. Activity start information is output as information representing

  On the other hand, if the estimation means 12 estimates that the resident's intentional operation of the electrical device 3 has been completed in the process of step S6, the resident is at home but is not active or is absent or is sleeping. The activity end information is output as information representing the estimation result.

  Further, the estimation means 12 outputs, for example, an estimation result that the resident is absent when the time has elapsed since outputting the activity end information in the daytime, or outputs the activity end information at night. When a predetermined time elapses, the resident outputs an estimation result indicating that he is sleeping.

  Here, the living situation estimation system 1 of the present embodiment further includes notification means 14 for transmitting the activity start information and the activity end information output by the estimation means 12 to an external information processing apparatus, and these are output by the estimation means 12. This information is used to confirm the safety of residents living in the electric power consumer 2.

  In this case, the living situation estimation method and system described above can be used as a resident safety confirmation method and system. Hereinafter, the resident of the electric power consumer 2 that is the target of the safety confirmation system is referred to as a target person.

  According to this safety confirmation system, it becomes possible for the subject's family, the doctor in charge, etc. to remotely confirm whether or not the subject is living healthy. Contribute. Therefore, this safety confirmation system is particularly useful when it is installed in, for example, an elderly person living alone, a household with a disabled person, or a household only for the elderly.

  As an external information processing apparatus, for example, a computer 20 (hereinafter referred to as a safety information management means 20) operated by a business operator (hereinafter referred to as a safety confirmation business operator) who performs safety confirmation of the subject person, or An information terminal 21 such as a personal computer or a telephone set or a cellular phone owned by the subject's family or a doctor in charge is used.

  In addition, communication technologies such as a wired or wireless communication line and a communication protocol are used for communication between the notification unit 14, the safety information management unit 20, and the information terminal 21. The notification unit 14, the safety information management unit 20, and the information terminal 21 are mounted with hardware and software that enable communication using the employed communication line and communication technology.

  The safety information management means 20 and the information terminal 21 use the arithmetic functions provided by them to calculate the time from the time when the activity end information was last received until the current time passed without receiving the activity start information (hereinafter referred to as the activity stoppage). (Referred to as time) and the calculated activity stop time is compared with a predetermined activity stop reference time.

  The activity stop reference time is appropriately set in consideration of the life pattern of the subject. Specifically, for example, it is normal that intentional operation of an electrical device is not performed during sleep of about 8 hours a day, so that the activity stop reference time is between 9 hours and 12 hours. It can be set. Or, if it is a long time to go out during the day as the subject's life pattern, or if it is normal that intentional operation of electrical equipment is not frequently performed as the subject's lifestyle, consider these circumstances Thus, it is conceivable that the activity stop reference time is set between 12 hours and 24 hours.

  In addition, the safety information management means 20 and the information terminal 21 have a time (hereinafter, referred to as the time from the time when the activity start information was last received until the current time passed without receiving the activity end information, by a calculation function or the like provided therein. (Referred to as activity duration) and the calculated activity duration is compared with a predetermined activity duration reference time.

  The activity continuation reference time is appropriately set in consideration of the life pattern of the subject. Specifically, for example, when it is normal that the electrical activity during indoor activities of about 16 hours a day is continuously used as the lifestyle of the subject, the activity continuation reference time is taken into consideration It may be set between 16 hours and 20 hours.

  And the safety information management means 20 and the information terminal 21 are output devices such as speakers and displays provided when the activity stop time is equal to or greater than the activity stop reference time or when the activity continuation time is equal to or greater than the activity continuation reference time. Warning information such as a warning sound and warning message is automatically output to the safety confirmation operator, the target person's family, the doctor in charge, etc.

  Then, the safety confirmation operator who received the warning information, the subject's family, the doctor in charge, etc., determined that there may be an emergency such as the subject being bedridden or falling indoors. For example, a safety confirmation operator or the subject's family member or doctor in charge makes a telephone call to the subject person to confirm the safety, or a safety confirmation operator makes a phone call to the subject's family member or doctor in charge, etc. Measures are taken such as requesting the safety confirmation of the subject person. This makes it possible to prevent the situation from becoming worse without anybody knowing that an emergency has occurred in a single person living alone or a household only for the elderly, etc. Life safety is ensured.

  According to this safety confirmation method and system, there is no need to provide an additional function or device in the electrical equipment 3 itself disposed in the power consumer 2, and a specific facility disposed in the power consumer 2. Without requiring information on the electrical device 3, it is possible to determine whether the electrical device 3 is intentionally operated by the resident, that is, whether or not the electrical device 3 is used in an indoor activity. It is possible to estimate whether or not you are living. Therefore, the maintenance cost of the safety confirmation system can be reduced, and the spread of the system can be promoted to improve the living safety of, for example, the elderly living alone or the household only for the elderly. Further, in the present invention, since the health of the resident is estimated without using the information of the specific electric equipment 3 arranged in the electric power consumer 2, it is monitored by a third party or It is possible to prevent an unpleasant sensation such as a resident having a consciousness that the life mode is known. Therefore, the spread of the system can be promoted, and for example, the living safety of a single person living alone or a household only for the elderly can be improved.

  In the present invention, the total load current of the power consumer 2 is measured for a plurality of days, data that is determined to be measured at home is extracted, and the value k and activity are extracted using the extracted data. Since the current threshold value D is obtained, the value k and the active current threshold value D can be set to values according to the load pattern of the electric power consumer 2 and can be automatically set. Therefore, it is not necessary for the administrator to set the value k and the active current threshold value D by visually observing the measurement data, and it is not necessary to perform an operation that requires experience. For example, a large number of power consumers 2 are simultaneously estimated. Even in the case, an appropriate value k and active current threshold D can be quickly set for each electric power consumer 2.

  Moreover, although the load pattern of the electric power consumer 2 changes according to a seasonal change etc., since the value k and the active current threshold value D can be automatically set in the present invention, the load pattern changes according to the change of the load pattern. Thus, it is easy to update the value k and the active current threshold D to appropriate values.

  Further, when the administrator sets the value k and the active current threshold D, the setting value may vary depending on the subjectivity of the administrator. In the present invention, however, the setting of the value k and the active current threshold D is automated. Therefore, there is no room for human subjectivity to enter the value k and the active current threshold value D, and the active current threshold value D can always be set on a constant basis.

  Moreover, when setting the value k and the active current threshold D, the value k and the active current threshold D become values according to the latest load pattern of the power consumer 2 by using the latest measurement data, and the power consumer 2 can be estimated according to the current situation. However, the data to be used is not necessarily strictly measured data. As long as the load pattern of the electric power consumer 2 can be reflected in the value k and the active current threshold D to the extent necessary for the estimation, data after a certain period of time may be used.

  The above-described embodiment is an example of a preferred embodiment of the present invention, but is not limited thereto, and various modifications can be made without departing from the gist of the present invention.

  For example, in the above-described embodiment, the operation detection information output from the estimation unit 12 is transmitted to the safety information management unit 20 or the information terminal 21 that is an external information processing apparatus by the notification unit 14. The information indicating the result of the determination up to the safety determination may be transmitted to the safety information management unit 20 or the information terminal 21 by the notification unit 14. In this case, for example, the estimation unit 12 records the above-described operation detection information in the storage device 13. The estimation means 12 calculates the time from the last recording of the operation detection information to the present time, compares the calculated time length with a predetermined determination reference time (for example, 24 hours), When the length of time during which detection information is not recorded is equal to or greater than the reference time, it is determined that there is a possibility of an emergency such as the subject being bedridden or the subject falling down in the house. , Output alarm information. The notification means 14 transmits this warning information to the safety information management means 20 or the information terminal 21.

In the above description, Formula 2 is employed as Condition 1, but Formula 5 may be employed instead of Formula 2. That is, in Equation 2, “the average of the k% value of m2 and the k% value of m3” is used as the denominator, but “the sum of all the k% values from m1 to m4” is used in the denominator as in Equation 5. Integration value) ”may be used.
Here, V k _^m: is the upper m% of values of the estimated index values rearranged in descending order for each k. For example, when Δt = 1 minute, Z = 7 days, m1 = 2%, m4 = 10%, the value that comes to the denominator is 806 (≈806.4 = 1440 × 7 × (10−2) ÷ 100). It will calculate the sum of the individual degree of numerical value V ^k _m.

  Even when Formula 5 is adopted as the condition 1, as in the case where Formula 2 is adopted, a graph with a large difference between the maximum value and the minimum value of the graph and a small number of large values is selected in the comparison area CA. Can do.

Further, in the denominator of Equation 5, instead of the sum of all the V ^k _m, it may be total to pick so not biased only in a partial area of the comparison region CA some of them.

  Further, in the above description, the calculation means 11, the estimation means 12, the storage device 13, the value k determination means 16, and the threshold value determination means 15 are provided in addition to the measurement means 10 on the power consumer 2 side. For example, the measuring unit 10 is installed on the power consumer 2 side, and the computing unit 11, the estimating unit 12, the storage device 13, the value k determining unit 16, and the threshold determining unit 15 are installed on the manager side. May be.

  Furthermore, the life situation estimation method and system for the power consumer resident of the present invention are not necessarily limited to those used as a resident safety confirmation method and system. For example, the information on the life pattern of the electricity consumer resident estimated by the present invention at home / not at home or sleeping / non-sleeping is used for learning of an electric device such as an air conditioner, and the electric device is based on the learning. In addition, it may be possible to perform driving suitable for the lifestyle pattern of the resident of the customer.

  In the above-described embodiment, n ΔDa obtained from time (t−T) to time t are arranged in descending order, and the “n × k / 100” -th ΔDa from the largest is set to k%. When the value “n × k / 100” is not an integer, the value “n × k / 100” is rounded up and used. However, the calculation method of the k% value is not necessarily limited to the above example. . For example, when the value of “n × k / 100” is not an integer, the value of ΔDa in the ranks before and after “n × k / 100” is used to interpolate between the previous and subsequent ΔDa by interpolation. Further, a value corresponding to “n × k / 100” may be calculated, and the calculated value may be set as a k% value. The same applies to the k% value for determining the value k and the active current threshold D.

  Experiments were performed to confirm that the value k and the active current threshold D can be automatically set according to the present invention, and that the automatically set value k and the active current threshold D are appropriate. The experiment was performed using the total load current data actually measured, and compared with the previous verification tests. In the verification tests conducted in the past, the value k and the active current threshold D set by the manager while visually examining the data were used.

The experimental flow is shown below.
(1) Extracting home Z (= 7) days from past X (= 14) data (2) Value used for watching (estimating) using data for Z days extracted in (1) k is determined (3) Using the data for Z days extracted in (1), the active current threshold D used for watching is determined for the value k determined in (2). (4) Every household Repeat (1) to (3) every time

  In (1), the date used for the determination of the parameters (value k and active current threshold D) is extracted. A Z day with a large total daily load current (unit: Ah) is extracted from the X day closest to the day. FIG. 9 is a distribution of the total amount of load current per day for each household presence / absence situation. It can be seen that the total load current of the day is smaller on the day absent all day than on the day at home. By extracting the Z day from the past X days and updating the data every day, the change of the load pattern is followed, and the value k and the active current threshold D are set by eliminating the influence of the absence until the Z day. be able to.

  In (2), the value k used for watching is determined. 10 and 11 show the total load current of a certain household and the time transition of the estimated index value (k% value) when the value k is 5, 10, 25, and 50%. FIG. 10 shows an example of a day in autumn, and FIG. 11 shows an example of a day in winter. For the operation in the demonstration test, the value k = 25% and the active current threshold D = 0.3 [A] are used on the day of FIG. 10, from 10 am to 10:30 am and from 6:30 pm It was determined that the active current threshold D was exceeded around 7 o'clock. However, when the day shown in FIG. 11 is watched with the same parameter, the estimated index value continuously becomes a large value in response to the operation of the heating equipment, and thus it becomes impossible to grasp the resident's main equipment operation. It was. For operation in the demonstration test, the value k = 5% and the active current threshold D = 5 [A] were used on the day of FIG. As a result, the estimated index value takes a large value in response to a main operation other than the heating device, and does not exceed the threshold value when only the heating device is operated. Thus, it was found that even in the same household, the load pattern changes when the electric equipment used changes according to the season, and it becomes difficult to monitor with the same value k.

  As described above, the estimated index value is greatly responsive to changes in current due to the occupants' main electrical equipment operation, and depends on equipment that operates automatically, such as refrigerators and warm water toilet seats, and equipment that operates for a long time. It is desirable not to react to current changes. That is, it is desirable that the estimated index value has a large relative fluctuation range and does not continue to take a large value for a long time. Therefore, it is considered that the estimated index values for the values of k are rearranged in descending order for the Z day extracted in (1).

FIG. 12 shows an example of the result of rearranging the estimated index values in descending order. When the value k is appropriately selected, the estimated index value responds only to the resident's independent operation, so the proportion of time that the estimated index value takes a large value is small, and the estimated index value rapidly Decrease. When responding to a current pattern other than the main operation, the ratio of the time for which the estimated index value takes a large value is large, and takes a shape close to horizontal when the estimated index value is large. That is, when the value of the upper m% of the value rearranged estimated index values in descending order for each k and V ^k _m, in order relative fluctuation range does not take a larger and larger value for a long time is 13 Of the four curves shown in (4), it is preferable that the shape is as shown in (4). That is, it is _preferable that V ^k _m1 is sufficiently larger than V ^k _{m4 and} that V ^k _m2 and V ^k _m3 positioned therebetween are relatively small. In a curve having such characteristics, the evaluation index N ^k defined by Equation 6 is large.

Therefore, N ^k is calculated for each of k = 5, 10, 25, and 50%, and the largest one is set as k used for watching the day (Condition 1). However, even when the shape of the relative curve is ideal, if the estimated index value is too small, it may not be suitable for watching, so m5 [%] (first position) and U [A] Are set in advance so that V ^k _m5 ≧ U is satisfied (condition 2). It is used to watch over (estimate) k that satisfies these two conditions.

  In (3), the active current threshold D used for watching is determined. The active current threshold value D is the value of Y [%] (second position) from the top by rearranging the estimated index values for the value k determined in (2) in descending order for the Z day extracted in (1). For example, in the case of Y = 5%, an average of 1.2 hours (= 24 hours × 0.05) exceeds the active current threshold D for the extracted day.

  By automatically calculating (1) to (3) for each household every day and using the obtained parameters (value k and active current threshold D), it is possible to perform appropriate watching.

  Table 1 shows the estimated results of monitoring when the parameters actually used for watching are used (in the case of a verification test using the living situation estimation method of Patent Document 1) and when the parameters set according to the present invention are used. Indicates. However, here, data of X ≧ 7 days or more (from the 8th day after the start of measurement) is used, and m1 = 2%, m2 = 5%, m3 = 7%, m4 = 10%, m5 = Y = 5% case and m5 = Y = 10% case were calculated.

  It can be seen that even when the parameters set according to the present invention are used, almost the same estimation results are obtained as when the manually set parameters are used (in the case of the demonstration test). Even if at home, if the electricity is not used much, the estimated index value does not reach the active current threshold D, and the estimation result is absent.

  Table 2 also shows the number of days that did not exceed the active current threshold D, the number of days that exceeded the threshold for less than 6 hours, and the number of days that exceeded 6 hours or more. Compared with the estimation result when the manually set parameters are used (in the case of the demonstration test), the number of days that exceeded the threshold for 6 hours or more is smaller in the result of the automatic setting of the present invention. This is because in the automatic setting, the threshold value becomes an appropriate size following the change or addition of the electric equipment used.

  From the above, by using the parameters automatically set by the present invention (value k and active current threshold D), it is possible to obtain the same estimation result as the case where the administrator manually sets (in the case of the demonstration test), And it has confirmed that the automatic setting by this invention can track the change of the load pattern of an electric power consumer.

DESCRIPTION OF SYMBOLS 1 Living condition estimation system 2 Electric power consumer 3 Electric equipment 10 Measuring means 11 Calculation means 12 Estimation means 14 Notification means 15 Threshold value determination means 16 Value k determination means 20 Safety information management means (external information processing apparatus)
21 Information terminal (external information processing device)

Claims (4)

  Measure the total load current by the electric equipment arranged in the electric power consumer at every fixed time interval Δt, obtain the absolute value of the total load current change at each fixed time interval Δt as target data, and have a fixed calculation time For each step Δt ′, a value k is used for a data group composed of a plurality of the target data obtained in the past fixed time span T, and “the number of the target data that is equal to or greater than the value is K% value that is “k% with respect to the total number of data” is calculated, and the resident's intention for the electrical equipment in the power consumer is based on whether the k% value is equal to or greater than the active current threshold. A life situation estimation method for estimating presence / absence of an operation, wherein the measurement of the total load current is performed for a plurality of days, and the measurement value of the total load current determined to be measured on a home day of the power consumer is used. To obtain the data group and The k% value is calculated for each k hypothesis value using a plurality of preset k assumption values and arranged in descending order for the data group for value determination, and is graphed for each k hypothesis value. The graphs are compared in a preset region, one graph is selected based on the graph shape, the k assumed value corresponding to the selected graph is set as the value k, and a second preset for the selected graph is used. A method for estimating a living situation of a resident of an electric power consumer, wherein a k% value of a position is set as the active current threshold.   A measuring means for measuring a total load current by an electric device arranged in a power consumer at a constant time interval Δt, and a change in the total load current at the constant time interval Δt based on a measurement value obtained from the measuring means. An absolute value is obtained as target data, and a value k is used for a data group consisting of a plurality of the target data obtained in the past constant time width T for each constant calculation time step Δt ′. The calculation means for calculating the k% value, which is a value in which the number of the target data becomes k% with respect to the total number of data in the data group, and whether the k% value is larger than the active current threshold value An estimation means for estimating presence / absence of a resident's intentional operation with respect to the electric equipment in the electric power consumer based on the life-time estimation system of the electric power consumer resident, Determined to have been measured A plurality of days of the total load current measurement value, a plurality of preset k assumption values, a preset graph comparison area, and a first position in the preset graph comparison area A storage unit storing a minimum current value and a preset second position; a data group for determining a value by obtaining the data group using a measured value of the total load current stored in the storage unit; In addition, for the value determination data group, the k% values are calculated for each of the k assumption values using the plurality of k assumption values stored in the storage unit, arranged in descending order, and graphed. A value-by-value graph is compared in the comparison area of the graph stored in the storage means, one graph is selected based on the graph shape, and the k assumed value corresponding to the selected graph is set as the value k k determination means and the selection Living conditions estimation system electric power consumer resident, characterized in that it comprises a threshold value determining means for the k% value of the second position stored in the storage means for rough and the activities current threshold.   The living condition estimation system for a power consumer resident according to claim 2, further comprising notification means for transmitting the presence / absence of the resident's intentional operation to an external information processing apparatus.   At least the absolute value of the change in the total load current for each time interval Δt based on the measurement value for each time interval Δt of the total load current by the electrical equipment disposed in the power consumer stored in advance in the storage means And a data group composed of a plurality of the target data obtained in the past time width T stored in advance in the storage unit for each calculation time increment Δt ′ previously stored in the storage unit , A calculation means for calculating a k% value that is a value that “the number of the target data that is equal to or greater than the value is k% with respect to the total number of data in the data group” using the value k; Estimating means for estimating presence / absence of a resident's intentional operation on the electric equipment in the electric power consumer based on whether or not the k% value is larger than a threshold; and the total stored in the storage means in advance Load current time interval Among the measured values for each t, the data group is obtained using a plurality of days determined to have been measured on the day when the electric power consumer is at home and is used as a value determining data group, and the value determining data For a group, the k% values are calculated for each k hypothesized value using a plurality of k hypothesized values stored in advance in the storage means, arranged in descending order, and graphs for each k hypothesized value are plotted in the storage means. A value k determining means for comparing in a comparison area of a graph stored in advance, selecting one graph based on a graph shape, and setting the k assumed value corresponding to the selected graph as the value k; A program for estimating a living situation for causing a computer to function as a threshold value determining unit using the k% value of the second position stored in advance in the storage unit for the selection graph as the active current threshold value.