JP6127769B2 - Information processing apparatus, information processing method, information processing system, and information processing program - Google Patents

Description

  The present invention relates to an information processing apparatus, an information processing method, an information processing system, and an information processing program.

  In recent years, a demand response (DR) is known as a method for suppressing the peak power of a consumer device on the power provider side. DR is a method of monitoring the demand in the power grid on the power provider side and suppressing the power consumption of the consumer's equipment according to the demand. As a suppression method, there are a method of increasing a power charge in a peak time zone, a method of reducing demand by paying compensation for a power demand reduced by a customer, and the like.

  In DR, a smart outlet capable of measuring the power consumption of a connected device is used as a measuring instrument for estimating the power consumption on the customer side, for example. A smart outlet is a device including a power tap and a power sensor, and the power sensor can measure the power consumption of the device connected to the outlet.

Japanese Patent Laid-Open No. 5-233011 Japanese Patent Laid-Open No. 2004-280618 JP 2005-258530 A JP 2008-310659 A JP 2010-225133 A JP 2011-172419 A International Publication No. 2011/021378

  In order to realize effective DR, it is preferable that the amount of power demand can be predicted as accurately as possible. However, for example, if a power sensor is connected to each device in order to estimate the power consumption of each device, the facility scale increases, which may be disadvantageous in terms of cost. Therefore, it is preferable that the power consumption of each device can be estimated with a simple equipment configuration.

  An object of one aspect of the present invention is to provide an information processing apparatus, an information processing method, an information processing system, and an information processing program capable of estimating the power consumption of each device with a simple equipment configuration.

  According to an aspect of the invention, from each of a plurality of devices, an operation information acquisition unit that acquires information on an operation state including information on a state of an external power supply and information on a power reception state, and the one of the plurality of devices When it is determined that the correlation does not decrease for a combination of devices having a correlation with the operating state, the power receiving state of at least one device among the devices corresponding to the combination is the power receiving state of another device. An information processing apparatus is provided that includes a correlation control unit that performs control differently and a power calculation unit that calculates power consumption of each of the plurality of devices using the information on the operating state.

  According to one embodiment, it is possible to provide an information processing apparatus, an information processing method, an information processing system, and an information processing program capable of estimating the power consumption of each device with a simple equipment configuration.

FIG. 1 is a diagram illustrating an example of an information processing system. FIG. 2 is a flowchart illustrating an example of processing executed by the information processing apparatus. FIG. 3 is a diagram illustrating an example of initial setting information regarding measurement timing. FIG. 4 is an example of a table showing power consumption using the operating state of the device and the power supply source as parameters. FIG. 5 is a flowchart illustrating an example of a method for controlling charging of the battery of the device in S103. FIG. 6 is a sequence diagram according to an example of a method for controlling charging of the battery of the device in S103. FIG. 7 is a diagram illustrating an example of a case where there is a correlation in operating state between different devices. FIG. 8 is a diagram illustrating an example of a temporal change in total power consumption by a plurality of devices. FIG. 9 is a flowchart illustrating an example of processing for evaluating the correlation between devices and controlling the power reception state in S104. FIG. 10 is a diagram illustrating an example of a correlation value calculation method in S302. FIG. 11 is a diagram illustrating an example of a method for calculating the VIF in S302. FIG. 12 is a flowchart illustrating an example of processing for determining whether or not to control the operating state in S304. FIG. 13 is a diagram for explaining the processing of S401. FIG. 14 is a diagram illustrating definitions of terms used for explaining the process of S403. FIG. 15 is a diagram illustrating an example of a change in the operating state of the device when the difference in state change time is greater than half of the measurement time interval. FIG. 16 is a diagram illustrating an example of a change in the operating state of the device when the difference in state change time is smaller than half of the measurement time interval. FIG. 17 is a diagram for explaining the state appearance frequency. FIG. 18 is a flowchart illustrating an example of processing for determining an operating state control method in S307. FIG. 19 is a diagram illustrating an example of information on the CPU usage rate and the remaining battery level. FIG. 20 is a diagram illustrating an example of processing for switching the power receiving state of the selected device to battery driving in S308. FIG. 21 is a diagram illustrating an example of information on the remaining battery capacity of each device at each measurement timing. FIG. 22 is a diagram illustrating an example of a correlation value calculation method in S506. FIG. 23 is a diagram illustrating an example of a correlation value calculation result in S506. FIG. 24 is a flowchart illustrating an example of a method for calculating power consumption for each device. FIG. 25 is a diagram illustrating an example of total power consumption and operation status data for each device at each measurement timing. FIG. 26 is a diagram illustrating an example of a matrix y indicating total power information and a matrix A ′ indicating operation information obtained from the data in FIG. 25. Figure 27 is a ^T 'transposed matrix A' matrix A shown in FIG. 26. FIG. 28 is a diagram illustrating a result of calculating a matrix (A ′ ^T × A ′). Figure 29 is a diagram illustrating a matrix (A ^'T × A') inverse matrix of (A ^'T × ^A') result of calculating the ^-1. FIG. 30 is a diagram illustrating a result of calculating a matrix (A ′ ^T × y). FIG. 31 is a diagram illustrating a result of calculating the matrix X ″. FIG. 32 is a diagram showing the estimated power consumption of each device obtained from FIG. FIG. 33 is an example of a table showing the estimated power consumption in each operating state of the device 3a and the device 3b. FIG. 34 is a flowchart illustrating an example of evaluation of accuracy of estimated power consumption. FIG. 35 is a sequence diagram illustrating an example of evaluation of accuracy of estimated power consumption. FIG. 36 is a flowchart (No. 1) showing a modification of S304. FIG. 37 is a flowchart (No. 2) showing a modification of S304.

  Hereinafter, embodiments of the present invention will be described in detail with reference to FIGS.

  FIG. 1 is a diagram illustrating an example of an information processing system. As illustrated in FIG. 1, the information processing system includes an information processing device 1, a distribution board 2, a device 3, and a device 4. The information processing apparatus 1 is connected to the distribution board 2 and the device 3 so that they can communicate with each other. The distribution board 2 is electrically connected to the devices 3 and 4.

  Hereinafter, the function of each unit constituting the information processing system will be described.

  The information processing apparatus 1 is a management apparatus for controlling power supplied to the device 3 by DR, which is owned by an electric power company, for example, a server. The information processing apparatus 1 includes an initial setting unit 5, an input device 6, a storage unit 7, an operation state monitoring unit 8, a power supply state control unit 9, an operation information acquisition unit 10, a correlation determination unit 11, The control target selection unit 12, the correlation control unit 13, the power information acquisition unit 14, the power calculation unit 15, the estimation evaluation unit 16, the control execution determination unit 17, and the output device 18 are provided.

  The initial setting unit 5 includes identification information for identifying each of the plurality of devices 3 to be controlled, and the total power consumption indicating the total value of the power consumed by the device 3 and the device 4 for each system. Initial setting information including timing (measurement timing) for measuring total power information as information is received via the input device 6.

  The input device 6 is, for example, a keyboard or a mouse. The initial setting unit 5 stores the initial setting information received via the input device 6 in the storage unit 7.

  The storage unit 7 is used as a database (DB; Data Base) for storing various information. The storage unit 7 can store information for identifying the control target device 3 received by the initial setting unit 5 from the input device 6. The storage unit 7 can also store operation information received from each device 3 by the operation state monitoring unit 8 or the operation information acquisition unit 10.

  In addition, the storage unit 7 is a total indicating the operation information of each device 3 acquired by the operation information acquisition unit 10 and the total value for each system of power consumed by the device 3 and the device 4 acquired by the power information acquisition unit 14. The total power information, which is power consumption information, can be stored in association with each other. The storage unit 7 can also store power consumption information calculated by the power calculation unit 15. The storage unit 7 can also store threshold values used for various determination processes executed in the information processing apparatus 1.

  The storage unit 7 is a storage device such as a semiconductor memory such as a ROM (Read Only Memory) or a flash memory, or an HDD (Hard Disk Drive). Note that a plurality of storage units 7 may be provided for each type of information to be stored, or may be configured as the same storage unit.

  The operating state monitoring unit 8 monitors the operating state of the device 3. Specifically, the operating state monitoring unit 8 acquires, in real time, information from each device 3 including the fact that the power state of the device 3 has changed from on to off or from off to on, and the time at which the change event occurred. To do.

  The power supply state control unit 9 controls on / off of charging of the battery of the device 3 based on the operation information of the device 3 acquired by the operation state monitoring unit 8. Specifically, the power supply state control unit 9 changes the power supply state from on to off when it is detected that there is a device whose power supply state has changed from on to off from among the plurality of devices 3. Control so that the battery of the power supply of the device is not charged. On the other hand, when it is detected that there is a device whose power state has changed from off to on, control is performed so that the battery of the device whose power state has changed from off to on is charged. Details of the control method will be described later.

  The operation information acquisition unit 10 acquires, as operation information, for example, operation information in which power source state information of each device is associated with power reception state (power reception state) information of each device in real time. Here, the power status information of each device is, for example, information indicating whether each device is powered on, off, or in standby. The information on the power reception status of each device is, for example, whether each device is receiving power from an alternating current (AC) power source but is not being charged to the battery, or is receiving power from the AC power source and to the battery. Is information indicating whether the battery is being charged or is not receiving power from the AC power source and is consuming (or discharging) the battery power. The standby state is a state in which the supply of power to other devices in the device is turned off while maintaining the supply of power to some devices, for example, the memory from the AC power supply or the battery of the device.

  Further, the operation information acquisition unit 10 acquires the CPU usage rate and the remaining battery information from each device. Here, the CPU usage rate is a rate at which the program being executed on the computer occupies the processing time of the CPU. The information on the remaining battery level is the ratio of the remaining battery level at the time of acquisition to the fully charged state of the battery, and is information expressed in units of%, for example.

  In the following description, “AC” indicates a power reception state in which power is received from an AC power source but is not charged, and “AC + charge” indicates that a power reception state in which power is received from the AC power source and the battery is also charged is AC The power receiving state in which the device 3 is driven by the battery without receiving power from the power source or charging the battery is denoted as “battery”.

  For example, an operating state in which power is being received from an AC power source but charging is not being performed and the AC power source of the device 3 is on is denoted as “AC / ON”. In the “AC / ON” state, the device 3 is operated by an AC power source. Further, an operating state in which power is being received from the AC power source but charging is not performed and the AC power source of the device 3 is off is denoted as “AC / OFF”. An operating state in which power is being received from an AC power source but charging is not being performed and the device 3 is in a standby state is referred to as “AC / standby”.

  Further, an operating state in which power is received from the AC power source and the battery is being charged and the AC power source is turned on is referred to as “AC + charge / ON”. Further, an operating state in which the battery is charged from the AC power supply and the battery is being charged and the AC power supply is turned off is denoted as “AC + charge / OFF”. Further, an operating state in which power is received from the AC power source and the battery is being charged and the AC power source is in a standby state is referred to as “AC + charging / standby”.

  The correlation determination unit 11 operates in each device 3 based on information in which the power state information of each device 3 acquired by the operation information acquisition unit 10 is associated with the power reception state information of each device. It is determined whether or not there is a combination of the devices 3 having a correlation in the state.

  The control target selection unit 12 determines a method for controlling the power reception state when there is a combination of the devices 3 having a correlation in the operation state based on the determination result of the presence or absence of the correlation by the correlation determination unit 11. The device 3 to be controlled is selected.

  The correlation control unit 13 has a combination of devices 3 having correlation, and when the operation state of each device corresponding to the combination is the same, each of the combinations corresponding to the combination having the correlation of the operation state Control for changing the power reception state of at least one device of the device 3 to be different from the power reception state of other devices is executed. By this control, the information processing apparatus 1 can reduce the correlation of the operating state. A method for changing the power reception state will be described later.

  The power information acquisition unit 14 acquires total power information from the distribution board 2 and stores the acquired total power information in the storage unit 7.

  The power calculation unit 15 calculates the power consumption of each device based on the total power information acquired by the power information acquisition unit 14 and the operation information acquired by the operation information acquisition unit 10, and calculates the calculated power consumption value. Store in the storage unit 7.

  The estimation evaluation unit 16 calculates the accuracy of the estimated power consumption value of each device calculated by the power calculation unit 15 and evaluates whether or not a predetermined criterion is satisfied. The accuracy evaluation method will be described later.

  The control execution determination unit 17 indicates an index value indicating whether or not a difference in operating state between the two devices 3 corresponding to the combination occurs for a combination of devices having a correlation with the operating state among the plurality of devices 3. To get. Further, the control execution determination unit 17 determines whether or not to perform control for switching the power reception state of the two devices 3 based on the acquired index value.

  The output device 18 can output the processing result by the information processing device 1. The output device 18 is a display device such as a liquid crystal display, a plasma display, or an organic EL display.

  Initial setting unit 5, operation state monitoring unit 8, power supply state control unit 9, operation information acquisition unit 10, correlation determination unit 11, control target selection unit 12, correlation control unit 13, power information acquisition unit 14, power calculation unit 15, the estimation evaluation part 16, and the control execution determination part 17 are realizable by processors, such as CPU (Central Processing Unit) and MPU (Micro-Processing Unit), for example. More specifically, it can be realized by, for example, reading an information processing program stored in a storage medium such as a semiconductor memory or HDD into a processor such as a CPU or MPU and executing each process of the information processing program.

  The distribution board 2 is a power meter having a communication function, for example, a smart meter. The distribution board 2 can communicate with the information processing apparatus 1 and control the power consumption of the device 3 via the input / output IF 20 that is an input / output interface. The device 3 is a device that is owned by a consumer and that is a power consumption control target, and includes a battery that is charged with at least part of the supplied power supplied from the AC power supply. The device 3 is an information processing terminal such as a personal computer (PC). In FIG. 1, each of the devices 3 a, 3 b, 3 c and 3 d is electrically connected to the distribution board 2 as an example of the device 3.

  Each device 3 is provided with a power control client 30. The power control client 30 is an input / output interface of the device 3 used when communicating with the information processing apparatus 1. The power control client 30 transmits the operation information to the operation state monitoring unit 8 and the operation information acquisition unit 10 of the information processing device 1 in real time. For example, when an event in which the operation state of the device 3 changes occurs, the power control client 30 can notify the changed time together with the changed operation information.

  Further, the power control client 30 performs control so that the power of the device 3 is turned on or off based on the control signal received from the power supply state control unit 5 of the information processing apparatus 1. In the example of FIG. 1, as an example of the power control client 30, the device 3a includes a power control client 30a, the device 3b includes a power control client 30b, the device 3c includes a power control client 30c, and the device 3d includes a power control client 30d. Each is provided.

  The device 4 is a device that is owned by a consumer but is not an object of power consumption control, and is an information processing device such as a server or a printer. In FIG. 1, as an example of the device 4, a device 4 a and a device 4 b are electrically connected to the distribution board 2.

  Next, the operation of the information processing system in the embodiment of the present invention will be described.

  FIG. 2 is a flowchart illustrating an example of processing executed by the information processing apparatus 1.

  First, the initial setting unit 5 sets a device to be controlled and information related to the measurement timing of total power information (S101).

FIG. 3 is a diagram illustrating an example of initial setting information regarding measurement timing. As shown in FIG. 3, for example, "2011 9:00" as the measurement starting time _{t s,} "2011 14:00" as the measurement end time _{t e,} "15 as the measurement time interval Δt “Min”, “21 times” as the number of data measurements n _max , and “10 [piece / one operation state]” can be set as the number of data for correlation evaluation. Each parameter will be described later.

  The initial setting unit 5 stores the identification information of each device received via the input device 6 and the information related to the measurement timing of the total power consumption received from the operating state monitoring unit 8 in the storage unit 7. By storing the acquired information in the storage unit 7, the process of S101 is completed.

  Subsequently, the distribution board 2 starts measuring the total power information indicating the total power consumption of each device 3, and the operating state monitoring unit 8 and the operating information acquiring unit 10 start acquiring operating information ( S102). Specifically, first, the power information acquisition unit 14 notifies the distribution board 2 of each information of the measurement start time, the measurement start time, and the measurement time interval set by the initial setting unit 5. Then, the distribution board 2 starts measuring the total power information at the measurement start time notified from the power information acquisition unit 14 and measures the total power information at every measurement time interval.

  On the other hand, the operation information acquisition unit 10 notifies each device 3 of the information of the measurement start time and the measurement start time. Then, the power control client 30 of each device 3 transmits the respective operation information to the operation state monitoring unit 8 and the operation information acquisition unit 10 in real time. Thereby, the information processing apparatus 1 can collect total power information and operation information.

  Subsequently, the operation state monitoring unit 8 monitors the operation state of the device 3, and the power supply state control unit 9 charges the battery of the device 3 based on the operation information of the device 3 acquired by the operation state monitoring unit 8. Is turned on / off (S103). In parallel with S103, the correlation determination unit 11 evaluates the correlation between different devices 3, and the correlation control unit 13 controls the power receiving state of the device 3 based on the evaluation result (S104). S104 is a process executed by the thread process with S103.

  First, the background of the process of S103 will be described.

  FIG. 4 is an example of a table showing power consumption using the operating state and the power receiving state of the device as parameters. The relationship between the on / off control method for charging the battery of the device 3 and the multiple regression analysis used as means for estimating the power consumption of each device will be described with reference to FIG.

  FIG. 4A is an example of a table indicating power consumption when the device does not have a charging function and a standby function. As shown in FIG. 4A, the power state of the device is only one of two states (ON or OFF), and the power receiving state of the device is only “AC”. The device consumes power of the power value Wac as power consumption only when “AC / ON”. On the other hand, since the power is not supplied to the device when “AC / OFF”, the power consumed by the device is zero. Therefore, there is only one explanatory variable (Wac) to be estimated. That is, if Wac becomes clear, it is possible to estimate the power consumption in each operating state of the device.

  FIG. 4B shows the power consumption of a device that has a charging function and a standby function, and can charge the battery not only when the device is turned on or on standby, but also when the device is turned off. It is an example of the table which shows. As shown in FIG. 4B, when the power receiving state of the device is “AC + charge”, the device can be in any one of the operating states of on, standby, and off.

  When “AC / ON” is selected, power is supplied from the AC power supply, and the device consumes Wac power. Even in the “AC / standby” mode, power is supplied from the AC power source, so that the device consumes Wstb power.

  In the case of “AC + charge / ON”, since the power Wch for charging the battery is supplied in addition to the power for operating the device from the AC power supply, the device consumes the power of Wac + Wch. Similarly, in the case of “AC + charge / standby”, in addition to supplying power for operation from the AC power supply, power Wch is also supplied, so that the device consumes Wstb + Wch power. On the other hand, when “AC + charge / OFF”, Wac is not supplied, so the device consumes only Wch power.

  “Battery” is a case where the power path between the outlet and the AC power source is interrupted, and the device is operated by the battery or the AC power source. In the case of the “battery”, since no new power is supplied, the power consumption of the device is zero regardless of the operating state of the power source.

  When the power receiving state of the device is “AC + charge”, Wch is included in the power consumption value regardless of the operating state of the device. Therefore, the power consumption values in each operating state are correlated with each other. If this correlation exists, when multiple regression analysis is performed to estimate the power consumption of each device, a problem that the analysis result shows an abnormal value (called a multi-collinearity problem) occurs. This may cause a problem that it is difficult to accurately calculate and estimate the power consumption.

  On the other hand, according to one embodiment of the present invention, when estimating the power consumption of each device, among the devices connected to the distribution board 2, the device whose power is changed from on to off. The battery is controlled not to be charged. FIG. 4C is an example of a table indicating power consumption when control is performed so that the battery is not charged when the power state of the device is off. As shown in FIG. 4C, when the power receiving state of the device is “AC + charge”, if the control is performed so that the battery is not charged when the power state of the device is off, power consumption occurs. Are in four states: “AC / ON”, “AC / Standby”, “AC + Charge / ON”, and “AC + Charge / Standby”.

  Therefore, Wch can be derived by obtaining the difference (Wac + Wch) −Wac between the power consumption value Wac at “AC / ON” and the power consumption value Wac + Wch at “AC + charge / ON”. Alternatively, Wch can be derived by obtaining a difference (Wstb + Wch) −Wstb between the power consumption value Wstb at the time of “AC / standby” and the power consumption value Wstb + Wch at the time of “AC + charge / standby”.

  As described above, when the device whose power is changed from on to off is controlled so as not to charge the battery, the operation state of the device when the power receiving state of the device is “AC + charge” is three states (on, The number of explanatory variables can be reduced by one because the number of states is reduced from standby to off) to two states (on and standby). As a result, the correlation between the operating states of the devices can be reduced as compared with the case where one explanatory variable is not reduced, and the power consumption can be estimated more accurately while avoiding the occurrence of the multicollinearity problem. Can do.

  Next, a method for monitoring the operating state of the device and controlling the power receiving state executed in S103 will be described with reference to FIGS.

  FIG. 5 is a flowchart illustrating an example of a method for controlling charging of the battery of each device 3 in S103. FIG. 6 is a sequence diagram according to an example of a method for controlling charging of the battery of each device 3 in S103.

  First, as illustrated in FIG. 6A, the operation state monitoring unit 8 of the information processing apparatus 1 requests the power control client 30 of each device 3 to notify when a change in the power supply state is detected. When the power control client 30 of each device 3 accepts the notification, the power control client 30 returns a signal indicating acceptance to the operating state monitoring unit 8.

  Subsequently, as illustrated in FIG. 5, the operation state monitoring unit 8 monitors the operation state of each device 3 by thread processing and monitors the reception signal from each device 3. It is determined whether there is a device 3 that has been turned off (S201). When it is determined that there is a device 3 whose power has been changed from on to off (Yes in S201), the process proceeds to S202, and as illustrated in FIG. A command to stop charging the battery is transmitted to the device 3a of the device 3 whose power source has changed from on to off, and control is performed so as not to supply power (charge) to the battery. On the other hand, if it is determined that there is no device 3 whose power has been changed from on to off (No in S201), the process proceeds to S203, and the operating state monitoring unit 8 determines whether there is a device 3 whose power has been changed from off to on. Determine if.

  When it is determined that there is a device 3 whose power has been changed from off to on (Yes in S203), as illustrated in (c) of FIG. Then, a command to start charging the battery is transmitted to the device 3a that has been determined that the power supply has changed from off to on, and control is performed to charge the battery (S204). On the other hand, when it is determined that there is no device 3 whose power has been changed from off to on (No in S203), the process returns to S201.

  After executing the processing of S202 or S204, the operating state monitoring unit 8 determines whether it is time to end monitoring (S205). The operating state monitoring unit 8 can determine whether or not it is time to end monitoring based on, for example, information on the measurement end time set by the initial setting unit in S101.

  When it is determined that it is time to end the monitoring (Yes at S205), the operating state monitoring unit 8 ends the monitoring and proceeds to S105. When the monitoring is completed, the battery is charged when the power of the device changes from on to off. On the other hand, when it is determined that it is not the time to end the monitoring (No at S205), the process returns to S201.

  According to FIG. 5 and FIG. 6, it is determined whether or not there is a device 3 whose power is changed from on to off, and when there is no device 3 whose power is changed from on to off, the power is turned off. Processing is performed to determine whether there is a device 3 that has turned on. That is, since the process for determining whether or not there is a device 3 whose power has been changed from on to off is prioritized, the battery is not charged after the power is changed from on to off. The time lag until the control is started can be shortened. If the time lag can be shortened, the time lag from when the power source is turned off until the battery is stopped can be shortened, so that the accuracy of estimated power consumption of each device can be improved. If the time lag from when the power is turned off to when the charging of the battery stops is negligible, the process of S203 can be executed after the process of S203 is executed.

  As described above, in the process of S103, the operating state of the device can be monitored and charging of the battery can be controlled.

  Next, the process of S104 will be described.

  In S <b> 104, the correlation determination unit 11 evaluates the correlation between the devices 3. When there is a combination of the devices 3 having the correlation, the correlation control unit 13 makes the power reception state of at least one of the devices 3 different from the power reception states of the other devices in order to reduce the correlation. Control. Hereinafter, problems in the case where there is a correlation in the operating state between different devices 3 will be described with reference to FIGS. 7 and 8.

  FIG. 7 is a diagram illustrating an example of a case where there is a correlation in operating state between different devices 3. FIG. 7 shows the operating states of the devices 3a, 3b, and 3c at times t1, t2, t3, t4, and t5, and the time elapses in the order of t1, t2, t3, t4, and t5. . First, referring to the device 3a and the device 3b, as shown in FIG. 7, at the times t1, t2, and t4, the operating states of the devices 3a and 3b are both “AC / ON”, and the operating states are the same. I understand that. From this, it can be determined that there is a correlation in the operating state between the device 3a and the device 3b. On the other hand, the device 3c is not in the same operating state as the other devices 3a and 3b at any time. From this, it can determine with the apparatus 3c not having a correlation in an operation state between the other apparatuses 3a and 3b.

  The operating status of different devices 3 is, for example, the rule that the PC is set to standby during the company's lunch break, or the custom of turning off the PC at night and charging the PC during the morning. In some cases, there is a possibility that the same operating state will occur. Alternatively, even when a plurality of PCs are used in a data transfer operation or the like, the plurality of PCs may be in the same operating state.

FIG. 8 is a diagram illustrating an example of a temporal change in total power consumption by a plurality of devices. In both FIG. 8A and FIG. 8B, the horizontal axis indicates time, and the vertical axis indicates the total power consumption of the device 3a and the device 3b. As shown in FIG. 8A, between 12:00 and 12:15, the operating state of the device 3a is AC / ON, and the operating state of the device 3b is “AC / OFF”. That is, the operating states are different from each other. Therefore, from 12:00 if the total power consumption _{X A} is revealed between 12:15, it is possible to estimate the power consumption when the AC / ON of devices 3a and _{X A.} Further, between 12:15 and 12:30, the operating state of the device 3a is “AC / OFF”, and the operating state of the device 3b is “AC / ON”. That is, since the different operating conditions during this time with each other, 12: if 15 revealed total consumption power X _B between 12:30 power consumption when the "AC / ON" of the device 3b X _B can be estimated.

On the other hand, as shown in FIG. 8B, between 12:00 and 12:15, the operating state of the device 3a is “AC / ON”, and the operating state of the device 3b is “AC / ON”. That is, the operating state is the same. For this reason, even if the total power consumption X _C between 12:00 and 12:15 becomes clear, it may be difficult to estimate the power consumption of the devices 3a and 3b by separating X _C. There is.

  As described above, when the operating states are the same between different devices, even when explanatory variables with different devices have a correlation, when multiple regression analysis for estimating the power consumption of each device is performed, multiple sharing is performed. A linearity problem may occur, and it may be difficult to accurately calculate and estimate the power consumption of each device. For this reason, in order to accurately calculate and estimate the power consumption of each device, it is preferable to suppress the same operating state between different devices and reduce the correlation.

  Next, a control method for reducing the correlation between devices executed in S104 will be described with reference to FIGS.

  FIG. 9 is a flowchart illustrating an example of processing for evaluating the correlation between devices and controlling the power reception state in S104.

  After starting the measurement of total power information and the acquisition of operation information in S102, if the number of accumulated data reaches the number of correlation evaluation data set in S101, the correlation determination unit 11 will The acquired data is read from the storage unit 7 as the storage destination (S301).

  Subsequently, the correlation determination unit 11 uses the read data to combine an arbitrary operating state of one device and an arbitrary operating state of the other device, and obtains a correlation value for each combination pattern. Calculate (S302).

  Here, an example of a correlation value calculation method will be described.

  FIG. 10 is a diagram illustrating an example of a correlation value calculation method in S302. FIG. 10A is a table showing the data on the operating state of each device at each acquisition timing. Each data indicates the operation status of each device at each acquisition timing of the devices 3a, 3b, and 3c shown in FIG. The vertical axis of the table represents the time at which the data was acquired, and the acquisition timing becomes new as it goes down. The data shown in FIG. 10 is an example of data acquired according to the initial setting information shown in FIG. The number of data used for calculating the correlation value is 10 per operating state as shown in the preset number of correlation evaluation data in FIG.

A ₁₁ , A ₁₂ , A ₁₃ and A ₁₄ are parameters indicating the operating state of the device 3a. In the item A ₁₁ , “1” is displayed when the device 3 a is in the “AC / ON” state, and “0” is displayed when the device 3 a is not in the “AC / ON” state. In the item of A _12, "1" is displayed when device 3a is in a state of "AC / Standby", "0" is displayed if it is not in a state of "AC / Standby". In the item of A ₁₃ , “1” is displayed when the device 3 a is in the “AC + charge / ON” state, and “0” is displayed when the device 3 a is not in the “AC + charge / ON” state. In the item of A _14, "1" is displayed when device 3a is in a state of "AC + Charging / Standby", "0" is displayed if it is not in a state of "AC + Charging / Standby".

A ₂₁ , A ₂₂ , A ₂₃ and A ₂₄ are parameters indicating the operating state of the device 3b. In the item A ₂₁ , “1” is displayed when the device 3 b is in the “AC / ON” state, and “0” is displayed when the device 3 b is not in the “AC / ON” state. In the item A ₂₂ , “1” is displayed when the device 3 b is in the “AC / standby” state, and “0” is displayed when the device 3 b is not in the “AC / standby” state. In the item of A ₂₃ , “1” is displayed when the device 3b is in the “AC + charge / ON” state, and “0” is displayed when the device 3b is not in the “AC + charge / ON” state. In the item A ₂₄ , “1” is displayed when the device 3 b is in the “AC + charge / standby” state, and “0” is displayed when the device 3 b is not in the “AC + charge / standby” state.

A ₃₁ , A ₃₂ , A ₃₃ and A ₃₄ are parameters indicating the operating state of the device 3c. In the item A ₃₁ , “1” is displayed when the device 3 c is in the “AC / ON” state, and “0” is displayed when the device 3 c is not in the “AC / ON” state. In the item A ₃₂ , “1” is displayed when the device 3 c is in the “AC / standby” state, and “0” is displayed when the device 3 c is not in the “AC / standby” state. In the item A ₃₃ , “1” is displayed when the device 3 c is in the “AC + charge / ON” state, and “0” is displayed when the device 3 c is not in the “AC + charge / ON” state. In the item A ₃₄ , “1” is displayed when the device 3 c is in the “AC + charge / standby” state, and “0” is displayed when the device 3 c is not in the “AC + charge / standby” state.

As an index representing the correlation value, for example, a variance expansion factor (hereinafter referred to as VIF) can be used. VIF can be calculated by, for example, the following equations (1) and (2).
Formula (1);

Formula (2);
FIG. 11 is a diagram illustrating an example of a method for calculating the VIF in S302. The upper table of FIG. 11 _(a), operation status of each acquisition timing of the _{A 11 a 11,1, a 11,2,} ···, a 11,10, and health of each acquisition timing of _{A 22} a _{22,1, a} 22,2, ···, it shows the data obtained by extracting _{a 22, 10} from FIG. 10 (a). According to FIG. 11A, the value of T in equation (1) is T = 10.

First, an average value of each operating status of _{A 11} and _{A 22} using the data shown on the upper side of FIG. 11 (a). Mean values for each operating status of A _11, as shown in the lower side of the table of FIG. 11 (a),
Formula (3);
Is calculated. The average value of each operating state of the A _22, as shown in the lower side of the table of FIG. 11 (a),
Formula (4);
Is calculated.
Subsequently, the _numerator of correlation coefficient R ₁₁ , ₂₂ is calculated. Using FIG. 11 (a), formula (3) and formula (4), as shown in FIG. 11 (b), the molecules of R _{11 and 22} are
Formula (5);
Is calculated.
Subsequently, the denominators of correlation coefficients R _{11 and 22} are calculated. Using the data of FIG. 11 (b), as shown in FIG. 11 (c), the denominators of R _{11 and 22} are
Formula (6);
Is calculated.
Therefore, the correlation coefficients R ₁₁ and ₂₂ of A ₁₁ and A ₂₂ are _expressed by using the equations (5) and (6):
Formula (7);

And VIF is calculated using equation (7):
Formula (8);
Is calculated.

  By calculating the VIF in all combinations between the parameters indicating the operation information of the devices 3a, 3b, and 3c by the above method, for example, data illustrated in FIG. 10B can be obtained. The VIF can be calculated as described above.

Returning to FIG. 9, after calculating the correlation value in S <b> 302, the correlation determination unit 11 determines whether there is a combination of operating states in which the correlation value exceeds the threshold (S <b> 303). For example, when the threshold value of VIF is set to VIF = 10 and FIG. 10B is referred, the value of VIF in the combination of A ₁₁ and A ₂₁ indicates positive infinity (INF), which exceeds the threshold value. . Therefore, the correlation determination unit 11 determines that there is a combination whose correlation value exceeds the threshold value. In addition, when there are a plurality of combinations of operation information whose correlation values exceed the threshold value, all corresponding devices can be set as control target candidates. Further, the threshold value of VIF can be set as appropriate according to the number of devices connected to the distribution board 2.

  When it is determined that there is no combination of operating states in which the correlation value exceeds the threshold (No in S303), the process proceeds to S310. The process of S310 will be described later. On the other hand, if it is determined that there is a combination of operating states in which the correlation value exceeds the threshold (Yes in S303), the control execution determination unit 17 determines whether to perform switching control for each combination of operating states in which the correlation value exceeds the threshold. Is determined (S304). Hereinafter, the process of S304 will be described with reference to FIG.

  FIG. 12 is a flowchart illustrating an example of processing for determining whether or not to control the operating state in S304. First, the process of S401 will be described.

FIG. 13 is a diagram for explaining the processing of S401. The horizontal axis in FIG. 13 indicates time. The two bands in FIG. 13A show an example of the time change of the operating state of the device 3a and the device 3b. Of the operating states, A ₁₁ and A ₂₁ are shown as being determined to have high correlation. A plurality of dotted scales extending in a direction perpendicular to the direction in which the two bands extend along the time axis are measurement timings. The leftmost measurement timing indicates the current time, and the leftmost measurement timing indicates the measurement end time. That is, at the time of the current time, the time zone between the current time and the measurement end time is the remaining measurement time.

  FIG. 13B shows the relationship between the remaining number of measurements plotted at each measurement timing and the time. As shown in FIG. 13B, the remaining number of measurements decreases with the passage of time and becomes zero at the measurement end time.

  FIG. 13C shows the relationship between an index indicating the possibility of a difference and time. As shown in FIG. 13C, the possibility that a difference in operating state occurs decreases with the passage of time. When the current time approaches the measurement end time after a lapse of time, the remaining number of times of measurement is reduced, so that the possibility that a difference in operating state appears at the measurement timing is reduced.

  Therefore, a threshold value (one-dot chain line) is set at a time close to the measurement end time, and it is considered that there is no possibility of a difference in operating state in the time zone from the threshold value to the measurement end time. Then, when the current time is within this time zone, the control execution determination unit 17 does not suppress switching control of the operating state of the device. Since the data measurement period is limited, if the time expires before the difference in the operating state appears, the opportunity to perform the switching control of the operating state is missed, and the correlation cannot be reduced. According to the above-described method, it is possible to forcibly control the switching of the operating state at the end of the measurement period in which the possibility that the correlation is eliminated, so that the above-described problem can be solved.

Therefore, the control execution determination unit 17 determines whether or not the remaining number of measurement times is smaller than the threshold value using a preset threshold value for the remaining number of measurement times (S401). The remaining number of measurements is the remaining number of measurements at the time of determination in S401, and can be calculated by subtracting the number of times already measured from the data measurement number n _max of the initial setting information. For example, when the number of data measurements is 21 and the process of S401 is performed when the operation state of the two devices 3 indicates the same operation state for the fourth time after the measurement is started, with reference to FIG. The number of times of measurement can be calculated as 21-4 = 17 [times]. On the other hand, the threshold value can be set, for example, based on the longest time during which a correlated operating state (for example, A ₁₁ and A ₂₁ ) did not appear.

  When the remaining number of times of measurement is less than the predetermined threshold value (Yes at S401), it is determined that there is a low possibility that the operating state is different, and it is determined that the operating state switching control is performed (S407). On the other hand, when the remaining number of measurements is equal to or greater than the predetermined threshold (No in S401), the control execution determination unit 17 has a sufficient number of remaining measurements, and there is a possibility that a difference in operating state having a correlation will occur. Judge that Then, the process proceeds to the process of calculating the probability that the difference in the operating state does not occur after S402. For example, if the remaining number of measurements is 17 and the predetermined threshold is set to 5 times, since 17 times ≧ 5 times, it is determined that S401 is negative.

  In S402, the control execution determination unit 17 selects one from combinations of operating states having correlation.

  Subsequently, the control execution determination unit 17 calculates a state change time difference rate from the past state change time and the measurement time interval for the selected combination of operating states (S403). Hereinafter, the process of S403 will be described.

FIG. 14 is a diagram illustrating definitions of terms used for explaining the process of S403. The horizontal axis in FIG. 14 indicates time, and two bands indicate examples of time changes in the operating states of the devices 3a and 3b. A plurality of dotted scales extending in a direction perpendicular to the direction in which the two bands extend along the time axis are measurement timings. Of Health, and health A ₁₁ of device 3a, and the operating state A ₂₁ of the device 3b shows the determined combination to have a high correlation. As shown in FIG. 14, even when the operating states A ₁₁ and A ₂₁ have high correlation, the time at which the operating state A ₁₁ or A ₂₁ changes from a certain operating state is not always the same, Often different. Hereinafter, a time at which a certain operating state changes to a highly correlated operating state is referred to as a “state change time”, and a time difference between the two state change times is referred to as a “state change time difference”. In addition, the measurement timing interval is referred to as “measurement time interval”.

FIG. 15 is a diagram illustrating an example of a change in the operating state of the device when the difference in state change time is greater than half of the measurement time interval. Three dotted lines in the figure indicate measurement timings T1, T2, and T3. If the difference between the state change time is greater than half the measurement time interval, as shown in FIG. 15 (a), the measurement timing of the A ₁₁ and A ₂₁ are correlated (in synchronization) is only T3, T2 in equipment 3b since the state of running is a _22, not correlated. FIG. 15B shows an example in which the difference in state change time is the same as in FIG. 15A and the state change time is different. The same applies to the case of FIG. 15B. Measurement timing and A ₁₁ and _{A 21} are correlated (in synchronization) is only T3, it does not correlate at T2.

  FIG. 16 is a diagram illustrating an example of a change in the operating state of the device when the difference in state change time is smaller than half of the measurement time interval. Three dotted lines in FIG. 16 indicate measurement timings T1, T2, and T3.

If the difference between the state change time is less than half the measurement time interval, as shown in FIG. 16 (a), are correlated with A ₁₁ and A ₂₁ also in T2 well T3. FIG. 16B is an example in which the difference in state change time is the same as in FIG. 16A and the state change time is different. Even if 16 of (b), in the T2 and _T3, and _{A 11} and _{A 21} are correlated.

  As can be seen from FIG. 15 and FIG. 16, the possibility that a difference between two operating states having a correlation in the measurement timing will increase as the difference in state change time increases.

  Therefore, the ratio of the difference in state change time to the measurement time interval is defined as “state change time difference rate”. The state change time difference rate corresponds to the probability that a difference in operating state occurs at one measurement timing. The control execution determination unit 17 uses the state change time difference rate as an index for predicting the possibility that a difference in operating state appears at the measurement timing.

Assuming that the state change time difference rate is d, the control execution determination unit 17 can calculate d using the following equation (9).
Formula (9);
d = (average difference in state change time) / (measurement time interval)
Here, the average of the difference in state change time indicates the average of the time difference when the change in the operating state of the two devices occurs two or more times. Moreover, the value of the measurement time interval set in S101 can be used as the measurement time interval. For example, if the average difference in state change time is 3 minutes and the measurement time interval is 15 minutes, d can be calculated as d = 3/15 = 0.2.

  As described above, the process of S402 is executed.

  Returning to FIG. 12, after the process of S403, the control execution determination unit 17 calculates the state appearance frequency from the past measurement count and the appearance count of the operating state having the correlation (S404).

FIG. 17 is a diagram for explaining the state appearance frequency. The way of viewing the table shown in FIG. 17 is substantially the same as that shown in FIGS. The state appearance frequency is a ratio of the frequency at which at least one state of a combination of operating states having a correlation with the number of measurement timings appears. If the state appearance frequency is f, f can be calculated using the following equation (10).
Formula (10);
f = (number of appearances of operating state having correlation) / (number of past measurements)
Here, the number of occurrences of Health with correlation is, for example, the number of times that at least one state is detected in the A ₁₁ or A ₂₁ in the measurement timing. The number of appearances of the operating state having correlation and the number of past measurements may be measured and accumulated before the time point of determination in S404. In the example of FIG. 17 (a), the past measurement count was 10 times, of which the number of times the at least one state is the appearance of A ₁₁ or A ₂₁ is 6 times. Therefore, f = 6/10 = 0.6 is calculated. Meanwhile, in the example of FIG. 17 (b), the past measurement count was 10 times, of which the number of times the at least one state is the appearance of A ₁₁ or A ₂₁ is 2 times. Therefore, f = 2/10 = 0.2 is calculated.

Subsequently, the control execution determination unit 17 calculates a probability that no difference appears based on the state change time difference rate, the state appearance frequency, and the remaining measurement time (S405). If the probability that no difference appears is p, p can be calculated using the following equation (11).
Formula (11);
p = (1-d) ^ (f × number of remaining measurements)
Here, “^” is a power, and “f × number of remaining measurements” indicates a predicted value of the number of times that a correlated operating state appears at the remaining measurement timing until the measurement end time. For example, if the remaining measurement count is 17, and d = 0.2 and f = 0.25, p is p = (1−0.2)） (0.25 × 17) ≈0.39. Can be calculated. Note that the method for calculating p is not limited to the method described above, and other methods may be used. p is an example of an index value.

  Subsequently, the control execution determination unit 17 determines whether or not the probability that the difference in operating state does not appear is equal to or greater than a predetermined threshold (S406). When it is determined that the probability that the difference in the operating state does not appear is equal to or greater than the predetermined threshold (Yes in S406), the control execution determination unit 17 determines to perform the switching control of the operating state (S407). Thereafter, the process proceeds to S409. On the other hand, when it is determined that the probability that the difference in the operating state does not appear is not equal to or greater than the predetermined threshold (No in S406), the control execution determination unit 17 determines not to perform the operation state switching control (S408). Thereafter, the process proceeds to S409.

  In step S409, the control execution determination unit 17 determines whether all combinations for performing switching control have been selected. If it is determined that all the combinations for performing the switching control have been selected (Yes at S409), the process proceeds to S305. On the other hand, when it is not determined that all combinations to be controlled are selected (No at S409), the process returns to S402, and the processes after S402 are executed again.

  As described above, the process of S304 is executed.

  If the device 3 is frequently controlled to switch the power receiving state, the convenience of the user of the device 3 may be reduced and the psychological burden of the user may be increased. For this reason, it is desirable for the user of the device 3 that the frequency of the switching control is as low as possible. The burden on the user can be reduced to some extent by reducing the frequency of switching control. However, since the frequency at which the operating state changes varies depending on the standby setting conditions and usage conditions of the devices, even if the switching control frequency is lowered uniformly for all devices, the correlation may not be sufficiently eliminated.

  Therefore, according to the process of S304, whether or not the correlation of the operating state is likely to be eliminated by the measurement end time can be estimated using the probability that the difference in the operating state does not appear. Then, when it is determined that the probability that the correlation is not eliminated is relatively high, the switching control is executed on the corresponding device 3. As a result, it is possible to reduce the number of times of switching control by an optimum method for each device 3, so that the correlation can be sufficiently eliminated, and the burden on the user can be reduced.

  Further, according to the above-described method, it is determined whether or not the operation state switching control is performed based on the absolute value of the probability that the difference in the operation state does not appear. For this reason, it is possible to perform switching control without exception for combinations of operating states that are estimated to require switching control.

  Returning to FIG. 9, after the process of S304, the control target selection unit 12 determines whether it is determined to control at least one of the combinations of operating states having correlation as a result of the process of S304. (S305). If it is determined that at least one of the combinations of operating states having the correlation is to be controlled (Yes in S305), the process proceeds to S306. On the other hand, if there is no combination determined to be controlled as a result of the process of S304 (No in S305), the process proceeds to S310.

  In S306, the control target selection unit 12 selects one from the combinations determined to be controlled. After the process of S306, the control target selection unit 12 determines an operating state control method (S307). Hereinafter, the process of determining the operating state control method will be described with reference to FIG.

  FIG. 18 is a flowchart illustrating an example of processing for determining an operating state control method in S307.

First, the operation information acquisition unit 10 acquires information on the CPU usage rate and the remaining battery level from each correlated device (S501). In the example shown in FIG. _10, since the combination of _{A 11} and _{A 21} are _extracted, and equipment 3a and _{A 21} corresponding device 3b the control object candidate corresponding to _{A 11.} The operation information acquisition unit 10 acquires information on the CPU usage rate and the remaining battery level of the devices 3a and 3b. Specifically, the operation information acquisition unit 10 transmits a signal requesting information on the CPU usage rate and the remaining battery level to the power control client 30a of the device 3a and the power control client 30b of the device 3b. The power control client 30 a and the power control client 30 b that have received the signal transmit a response signal including information on the CPU usage rate and the remaining battery level to the operation information acquisition unit 10. The operation information acquisition unit 10 that has received the response signal stores the acquired information in the storage unit 7.

Subsequently, the correlation determination unit 11 determines whether or not the remaining battery level is equal to or greater than the predetermined threshold C _L1 and the CPU usage rate satisfies the predetermined threshold U _h or less (S502). The correlation determination unit 11 reads out information on the CPU usage rate and the remaining battery level of the devices 3a and 3b, the threshold value C _L1 and the threshold value U _h used as the determination criteria, from the storage unit 7, and satisfies the above conditions. Determine if.

When it is determined that the remaining battery level is equal to or greater than the predetermined threshold value C _L1 and the CPU usage rate satisfies the predetermined threshold value U _h (Yes in S502), any one of the correlated devices is selected and driven by the battery. The method of switching to is determined as a control method (S503). The battery drive means that the power receiving state of the device is set to the “battery” state shown in FIG. 4B or 4C.

  The operation state control method is determined as described above.

  Returning to FIG. 9, the control target selection unit 12 selects a device to be controlled, and the correlation control unit 13 starts control to switch the power receiving state of the selected device to battery drive (S308). When switching to battery driving, if the battery level of the device is not sufficient, the battery may run out in a short time after switching. There is also known a device that changes the CPU operating clock frequency depending on the type of power source, for example, an external power source (AC power source) using a commercial power source as an example or a battery built in the device. Therefore, when switching to battery driving when the usage rate of the CPU of the device is high, the processing performance of the CPU may be degraded. Therefore, in S307, the control target selection unit 12 selects a device to be switched to battery driving based on the remaining battery level and CPU usage rate of each device. Specifically, for example, the remaining battery levels of devices having correlation are compared, and the device having the largest remaining battery level is selected as a target to be switched to battery driving. When there are a plurality of devices having the largest remaining battery capacity, the CPU usage rates of the devices are compared, and the device with the lowest CPU usage rate is selected as a target to be switched to battery driving.

  Next, processing from S502 of FIG. 18 through S503 to S307 will be described using a specific example with reference to FIG. 19 and FIG.

  FIG. 19 is a diagram illustrating an example of information on the CPU usage rate and the remaining battery level. FIG. 19 shows the remaining battery capacity and CPU usage rate of the devices 3a, 3b, and 3c.

In S502 of FIG. 18, when the threshold value C _L1 is set to 50% and the threshold value U _h is set to 50%, the remaining battery level of the device 3a is equal to or higher than the predetermined threshold value C _L1 and the CPU usage rate is equal to or lower than the predetermined threshold value U _h. Satisfy the condition of For this reason, it is determined as S502 affirmative in S502, and the control target selection unit 12 selects any one of the correlated devices and determines a method of switching to battery driving as a control method (S503). Thereafter, the process proceeds to S308 in FIG.

  In S308, first, the remaining battery levels are compared. When comparing the remaining battery levels with reference to FIG. 19, it can be seen that the devices with the largest remaining battery amount are the devices 3a and 3b (both are 80%). Next, when the CPU usage rates of the device 3a and the device 3c are compared, the CPU usage rate of the device 3a is 20%, whereas the remaining battery capacity of the device 3c is 60%. That is, it can be seen that the CPU usage rate is higher in the device 3c than in the device 3a. For this reason, the control target selection unit 12 selects the device 3a having a lower CPU usage rate as a target to be switched to battery driving. And the correlation control part 13 performs the process which switches a power receiving state to battery drive about the selected apparatus 3a.

  In this way, by selecting the device that switches to battery driving based on the remaining battery level of each device, it is possible to select the device that is least likely to cause the battery to run out. Can be suppressed. In addition, by selecting a device that switches to battery-powered operation based on the CPU usage rate of each device, it is possible to select a device that is least likely to cause a decrease in performance. Can be suppressed.

FIG. 20 is a diagram illustrating an example of processing for switching the power receiving state of the selected device to battery driving in S308. In S304 of FIG. 9, based on the data in FIG. 10, _{A 11} and _{A 21} are extracted as a combination of the correlation value exceeds the threshold value. In S307 of FIG. 9, the device 3a is selected as a target for executing the process of switching the power receiving state to battery driving based on the data of FIG. Therefore, the correlation controller 13, as shown in FIG. 19 (a), the acquisition timing of the 11 th, the operating state of the devices 3a and equipment 3b are both "AC / ON", _i.e., the _{A 11} and _{A 21} When both the operating states are “1”, a process of switching the operating state of the device 3a to battery driving is executed. Then, as illustrated in FIG. 19B, the operating state of A ₁₁ changes from “1” to “0”, which is different from the operating state “1” of A ₂₁ . Therefore, it is possible within the scope of the data group Health related A ₁₁ and A ₂₁ were obtained from acquisition timing 1st to 11th, lowering both correlation.

Note that, at the eleventh acquisition timing, when the operating states of A ₁₁ and A ₂₁ are different, the correlation control unit 13 may not perform the process of switching the operating state of the device 3a to battery driving. In this case, the correlation control unit 13 returns to S302 again through S309 without performing the switching process, and executes the processes after the 12th acquisition timing. Then, after the twelfth acquisition timing, when the operating states of the selected devices having the correlation are both “1”, a process of switching the operating state of any of the devices to battery driving is executed. That's fine.

Returning to FIG. 18, when it is determined that the remaining battery level is equal to or greater than the predetermined threshold C _L1 and the CPU usage rate does not satisfy the predetermined threshold U _h or less (No in S502), the control target selection unit 12 determines the correlation. It is determined whether or not the total remaining battery level of each device having a value is equal to or greater than a predetermined threshold value C _L2 (S504).

In S504, if the total remaining battery capacity is judged to be a predetermined threshold value C _L2 above (S504: Yes), the control target selection unit 12 selects the largest device battery remaining amount for each acquisition timing, the battery A method of switching to driving is determined as a control method (S505). Thereafter, the process proceeds to S308 in FIG.

  Next, the processing from S502 through S505 to S307 will be described using a specific example with reference to FIG.

  FIG. 21 is a diagram illustrating an example of information on the remaining battery capacity of each device at each measurement timing. FIG. 21 shows the remaining battery levels of the device 3a, the device 3b, and the device 3c for each of acquisition timing times t1, t2, and t3. It is assumed that the elapsed time is in the order of t1, t2, and t3.

When the threshold value C _L1 used for the determination in S502 is set to 50%, the remaining battery level of all the devices is less than 50% at time t1, and does not reach the predetermined threshold value C _L1 . For this reason, it is determined that S502 is negative in S502, and the process proceeds to S504.

If the threshold value _{C L2} used for the determination of S504 is set to 100%, calculating the sum of the remaining battery capacity of each device at the time t1, it is calculated to be 40% + 35% + 30% = 105%. Therefore, in S504, it is determined that S504 is affirmative, and the process proceeds to S505.

  In step S <b> 505, the control target selection unit 12 selects a device having the largest remaining battery capacity and determines a method of executing a process of switching to battery driving at each acquisition timing as a control method. After the process of S505, the process proceeds to S307 in FIG.

  In S307, for each acquisition timing, a device with the largest remaining battery capacity is selected for each acquisition timing, and a process of switching to battery driving is executed.

  First, referring to FIG. 21, comparing the remaining battery level of each device at time t1, it can be seen that the remaining battery level of the device 3a is the largest. Therefore, the control target selection unit 12 selects the device 3a as a target to be switched to battery driving. And the correlation control part 13 performs the process which switches a power receiving state to battery drive about the selected apparatus 3a.

  Subsequently, at time t2, which is the acquisition timing after time t1, when the remaining battery levels of the respective devices are compared, it can be seen that the remaining battery level of the device 3b is the largest. Therefore, the control target selection unit 12 selects the device 3b as a target to be switched to battery driving. And the correlation control part 13 performs the process which switches an electric power receiving state to battery drive about the selected apparatus 3b.

  Subsequently, at time t3, which is the acquisition timing after time t2, when the remaining battery levels of the devices are compared, it can be seen that the remaining battery level of the device 3c is the largest. Therefore, the control target selection unit 12 selects the device 3c as a target to be switched to battery driving. And the correlation control part 13 performs the process which switches a power receiving state to battery control about the selected apparatus 3c. Switching to battery control is performed, for example, by switching when the operating states of the devices determined to have correlation with each other match, and by waiting when the operating states do not match.

  Thus, at each acquisition timing, it is most likely that the battery will run out by selecting the device with the most remaining battery level based on the updated information on the remaining battery level and executing the process of switching to battery driving. Since a low device can be selected based on the latest information, the above-described problems can be suppressed.

  If the operating state of the selected device is different from the operating states of other correlated devices, the process of switching the operating state of the device to battery driving is not performed. In this case, the correlation control unit 13 can select a device having the second largest battery remaining amount and perform a switching process. Alternatively, a method of skipping the switching process at the acquisition timing and reselecting a device having the largest remaining battery capacity at the next acquisition timing can be adopted.

Returning to FIG. 18, when it is determined in S504 that the total remaining amount of the battery does not satisfy the predetermined threshold value C _L2 (No in S504), the correlation determination unit 11 determines whether the battery is charged until the next acquisition timing. Correlation values with all operating states of the device are calculated (S506). Note that the device for which the correlation value is calculated is a device corresponding to the combination of operating states determined in S303 of FIG. 9 that the correlation value exceeds the threshold value.

  When it is determined in S504 that the total remaining battery level of each device does not satisfy the predetermined threshold, it is predicted that the remaining battery level of each device is not sufficient. If the device driving method is switched to battery driving in a state where the remaining battery level is not sufficient, as described above, the battery may run out in a short time after switching.

  Therefore, in this embodiment, after charging until the next acquisition timing to increase the remaining battery level of the device, a process of switching to battery driving is executed. However, there is a possibility that the charging causes a correlation between the operating states of the other devices and causes a new multicollinearity problem. For this reason, in consideration of the operation state assumed at the next acquisition timing, the correlation with other devices is evaluated, and a device having the smallest correlation is selected.

  FIG. 22 is a diagram illustrating an example of a correlation value calculation method in S506. The way of viewing the table shown in FIG. 22 is substantially the same as FIG. FIG. 22 assumes a case where the device 3a is charged from the 10th acquisition timing to the 11th acquisition timing which is the next acquisition timing. In this case, the operating state of the device 3a at the eleventh acquisition timing is “AC + charge / ON”. Therefore, as shown in FIG. 22A, “1” is displayed in the column of the eleventh acquisition timing of the operating state “AC + charge / ON” of the device 3a.

  On the other hand, the devices 3b and 3c can take a value of “1” or “0” in all operating states at the next acquisition timing. FIG. 22B shows the operation information of the devices 3b and 3c when the operation states of the devices 3b and 3c at the eleventh acquisition timing are “1”. FIG. 22C illustrates the operation information of the devices 3b and 3c when the operation states of the devices 3b and 3c at the eleventh acquisition timing are “0”.

In S506, correlation determining section 11 calculates the operation information A ₁₃ of the apparatus 3a, considering data that can be taken at the next acquisition timing, device 3b, the combination of the operation information of 16 types of 3c correlation . Specifically, the operation information _{A 13} of device 3a shown in FIG. 22 (a), the operation information _A 21 of the device 3b and equipment 3c shown in FIG. _{22 (b), A 22,} A 23, A 24, A 31 , A ₃₂ , A ₃₃ , and A ₃₄ are calculated. Further, the operation information _{A 13} of device 3a shown in FIG. 22 (a), and _{A 21, A 22, A 23} , A 24, A 31, A 32, A 33, A 34 shown in FIG. 22 (c) A correlation value is calculated.

Similarly, the correlation determination unit 11 includes the operation information A ₂₃ related to “AC + charging / ON” of the device 3b and 16 types of operation information of the devices 3a and 3c in consideration of data that can be taken at the next acquisition timing. Correlation is calculated for each combination. In addition, the correlation determination unit 11 includes the operation information A ₃₃ related to “AC + charging / ON” of the device 3c and the 16 types of operation information of the devices 3a and 3b in consideration of data that can be taken at the next acquisition timing. The correlation is calculated for the combination.

FIG. 23 is a diagram illustrating an example of the calculation result of the correlation value in S506. Items A ₁₃ , A _23, and A _{33 in} each column are parameters indicating operation information of devices that are charged before the next acquisition timing. Items A ₁₁ , A ₁₂ ,..., A _{34 in} each row are parameters indicating operation information of devices other than the devices that are charged before the next acquisition timing. FIG. 23A shows a case where it is assumed that the operating state at the next acquisition timing of other devices other than the device to be charged is “1”. FIG. 23B shows a case where it is assumed that the operating state at the next acquisition timing of other devices other than the device to be charged is “0”.

Referring to FIGS. 23A and 23B, when the device 3a is charged through all the data (A ₁₃ ), the largest correlation value is indicated by A ₂₂ of the device 3b in FIG. This is the case of combination (VIF = 2.909). When the device 3b is charged (A ₂₃ ), the largest correlation value is obtained when the device 3b is combined with A ₁₂ of the device 3a in FIG. 23A (VIF = 2.455). When the device 3c is charged (A ₃₃ ), the largest correlation value is obtained when the device 3c is combined with A ₂₃ of the device 3b in FIG. 23A (VIF = 1.454).

Returning to FIG. 18, after the processing of S506, the correlation determination unit 11 determines whether there is a device in which all the correlation values are within the predetermined threshold _Vth based on the calculated calculation result of the correlation values. (S507). When the value of V _{th is} , for example, V _th = 10, and referring to FIGS. 23A and 23B, since all correlation values are 10 or less, it can be seen that the determination formula of S507 is satisfied. . As described above, when there is a device in which all the correlation values fall below the predetermined threshold _Vth (Yes in S507), the control target selection unit 12 selects the device having the smallest correlation value, and performs battery driving after charging the battery. The switching method is determined as the control method (S508). After the process of S508, the process proceeds to S308 in FIG.

On the other hand, when there is no device in which all the correlation values are equal to or smaller than the predetermined threshold _Vth (No in S507), the correlation determination unit 11 waits for a predetermined time (S509). Then, it returns to S501 again and performs the process after S501.

  In S308 of FIG. 9, a device having the smallest correlation value is selected, and a process of switching to battery driving after battery charging is executed. First, referring to FIGS. 23A and 23B, the control target selection unit 12 charges the device 3b with the largest correlation value (VIF = 2.909) shown when the device 3a is charged. In this case, the largest correlation value (VIF = 2.455) is compared with the largest correlation value (VIF = 1.454) when the device 3c is charged. And the apparatus 3c with the smallest correlation value is selected as charging object. Subsequently, the correlation control unit 13 performs processing for switching the power receiving state to battery driving after charging the selected device 3b until the next acquisition timing.

  In this way, when the total remaining battery capacity of each device does not satisfy the predetermined threshold, the correlation with other devices when a certain device is charged until the next acquisition timing is evaluated, and based on the evaluation result Select the device to charge. Then, after charging the selected device for a predetermined time, the power receiving state is changed. As a result, it is possible to select a device that is unlikely to cause multiple collinearity even if it is charged, so that the power consumption of each device can be estimated more accurately regardless of the remaining battery level of each device. Moreover, since it charges before switching to battery drive, possibility that a battery will run out in a short time after switching can be reduced.

  After executing the processing of S308, the correlation control unit 13 determines whether or not all combinations whose correlation values exceed the threshold are selected (S309). If it is determined that not all combinations have been selected (No at S309), the process returns to S306, and the processes after S306 are executed again.

  On the other hand, when it is determined that all combinations have been selected (Yes in S309), the operating state monitoring unit 8 determines whether it is time to end monitoring (S310). Similarly to the process of S205, the operating state monitoring unit 8 can determine whether or not it is time to end monitoring based on, for example, information on the measurement end time set by the initial setting unit in S101.

  When it is determined that it is time to end the monitoring (Yes in S310), the process proceeds to S105 in FIG. On the other hand, when it is determined that it is not the time to end the monitoring (No in S310), the process returns to S302, and the processes after S302 are executed again.

  As described above, the correlation between devices can be evaluated and the power receiving state can be controlled in S104 of FIG.

  According to the embodiment of the present invention, by selecting any one of the devices having correlation with each other and switching the selected device to battery driving, the power consumption of the device switched to battery driving can be reduced to zero. it can. Thereby, since the correlation between apparatuses can be reduced, the multicollinearity which becomes a problem when estimating the power consumption of an apparatus by regression analysis can be suppressed, and the estimation accuracy can be improved.

  When the processes of S103 and S104 in FIG. 2 are finished, the distribution board 2 finishes measuring the total power information indicating the total power consumption of each device 3, and the operating state monitoring unit 8 and the operating information acquisition unit 10 The operation information acquisition ends (S105).

  Subsequently, the power calculation unit 15 calculates the estimated power consumption for each device 3 using the acquired total power information and operation information (S106). The estimated power consumption for each device 3 will be described with reference to the example of FIG. 22B, for example. The acquisition timing used from the first time used by the correlation determination unit 11 to determine the presence / absence of the correlation between the operating states of the devices 3 The second operation acquired after the 11th acquisition timing under the control of the power reception state by the correlation control unit 13 after acquiring the information on the first operation state and the information on the first operation state up to the first time It is calculated based on the state information. Hereinafter, the process of S106 will be described.

  FIG. 24 is a flowchart illustrating an example of a method for calculating power consumption for each device. First, the power calculation unit 15 reads the total power information y and the operation information A ′ of each device 3 stored in the storage unit 7 (S901).

The total power information y is time series data of the total power value measured by the distribution board 2 at each measurement timing, and the matrix y
Formula (12);

Can be represented by The row of the matrix y represents the total power value at each time of the measurement timing, and indicates that the time when the data of the total power value is acquired is newer as the row number increases. That is, in Expression (12), y ₁ is the value of total power acquired first, and y _t is the value of total power acquired last. Each element of the matrix y is used as an objective variable when performing multiple regression analysis described later.

The operation information A ′ is time-series data of the operation information of each device 3, and the matrix A ′ in Expression (13).
Formula (13);

Can be represented by Each element of the matrix A ′ is used as an explanatory variable when performing multiple regression analysis described later.

Here, the column of the matrix A ′ represents the difference in the operating state of the devices 3 and 4. For example, in the first column (a _{1,1 to} a _{Z, 1} ), the device 3a is in the “AC / ON” state, in the second column, the device 3a is in the “AC / standby” state, and in the third column, The device 3a is in the “AC + charge / ON” state, and the rightmost column indicates a state in which any of the devices 4 is operating. The values assigned to the elements of the matrix A ′ indicate in time series whether or not the device 3 or the device 4 is in the operating state. That is, “1” is substituted when the operation state is set, and “0” is substituted when the operation state is not set. The total power information y and the operation information A ′ of each device are acquired at the same acquisition timing. For this reason, the matrix y and the matrix A ′ have a correspondence relationship between the same row numbers.

  Subsequently, the power calculation unit 15 calculates a matrix X ″ satisfying y = A ′ × X ′ = A ′ × X ″ + E based on the read total power information y and operation information A ′ (S902). Hereinafter, a method for calculating the matrix X ″ will be described.

First, the power consumption of each device 3 that is an estimation target by the multiple regression analysis in the present embodiment can be represented by a matrix X ′ shown in the following equation (14).
Formula (14);

Here, x ₁ , x ₂ ,... X _M are the power consumption of each device 3, and Z is the total power consumption of the device 4.

From Expressions (12) to (14), the relationship between the total power consumption, the operating state, and the power consumption of each device is a form in which a multiple regression equation is represented by a matrix y = A ′ × X ′, that is, Expression (15) ;
Can be expressed as
In S606 following S605, multiple regression analysis by the least square method is performed, and X ′ that minimizes the sum of squares of the rows of (y−A ′ × X ′) is calculated from Equation (15).

  Here, a method for calculating the matrix X ′ will be described using an example of data of total power information y and operation information A ′.

  FIG. 25 is a diagram illustrating an example of the total power amount and the operation status data for each device at each acquisition timing. FIG. 25 shows the total power consumption at each acquisition timing and the operation for each device when the devices to be controlled are set as the devices 3a and 3b and the devices not to be controlled are 4a and 4b among the devices shown in FIG. Shows status data. November 1, 2011, 9:00 is the first acquisition timing, and the interval between the acquisition timings is 15 min. The number of acquired data is 21 for each parameter indicating operation information. The unit of the total electric energy is W (watt).

A _1a , A _1b , A _1c and A _1d are parameters indicating the operation information of the device 3a. In the item A _1a , “1” is displayed when the device 3a is in the “AC / ON” state, and “0” is displayed when the device 3a is not in the “AC / ON” state. In the item A _1b , “1” is displayed when the device 3a is in the “AC / standby” state, and “0” is displayed when the device 3a is not in the “AC / standby” state. In the item of A _1c , “1” is displayed when the device 3a is in the “AC + charge / ON” state, and “0” is displayed when the device 3a is not in the “AC + charge / ON” state. In the item A _1d , “1” is displayed when the device 3a is in the “AC + charge / standby” state, and “0” is displayed when the device 3a is not in the “AC + charge / standby” state.

A _2a , A _2b , A _2c and A _2d are parameters indicating operation information of the device 3b. In the item A _2a , “1” is displayed when the device 3b is in the “AC / ON” state, and “0” is displayed when the device 3b is not in the “AC / ON” state. In the item A _2b , “1” is displayed when the device 3b is in the “AC / standby” state, and “0” is displayed when the device 3b is not in the “AC / standby” state. In the item A _2c , “1” is displayed when the device 3b is in the “AC + charge / ON” state, and “0” is displayed when the device 3b is not in the “AC + charge / ON” state. In the item A _2d , “1” is displayed when the device 3b is in the “AC + charge / standby” state, and “0” is displayed when the device 3b is not in the “AC + charge / standby” state.

Also, items _{A z} represents the operating state of the device 4a, 4b. In FIG. 25, the devices 4a and 4b are collectively referred to as the device 4. The devices 4 a and 4 b are devices that are not controlled by the DR, and do not have the power control client 30. In the example shown in FIG. 26, the device 4a, assuming that 4b are both running, "1" is substituted in all the acquisition timing in the item of A _z.

In the item of A _z, equipment 4a, one of the power devices 4b is "1" is displayed when the state of ON, "0" is displayed if it is off.

FIG. 26 is a diagram illustrating an example of a matrix y indicating total power information and a matrix A ′ indicating operation information obtained from the data in FIG. 25. As shown in FIG. 26, a matrix y of 21 rows and 1 column and a matrix A ′ of 21 rows and 9 columns can be obtained from the data of FIG.
In the multiple regression analysis, if the expression y = A ′ × X ′ is expressed in a form including a matrix E indicating an error,
Formula (16);
y = A ′ × X ′ = A ′ × X ″ + E
It can be expressed as. Here, X ″ is a matrix composed of values having no error.

According to Expression (16), A ′ × X ″ represents y more accurately as the value of each element constituting the matrix E indicating the error is smaller. "Is preferable. If the absolute value of E indicating the size of the matrix E indicating the error is squared,
Formula (17);
And the sum of squares of each element e1, e2, e3,. Therefore, it is preferable to obtain X ″ that minimizes the sum of squares. The sum of squares of Expression (17) can be expressed as E × E ^T using the transposed matrix E ^T of the matrix E. X ″ that minimizes E × E ^T is
Formula (18);
X ″ = (A ′ ^T × A ′) ⁻¹ × (A ′ ^T × y)
Can be expressed as That is, the ^T 'transposed matrix A' A, is the inverse matrix of the matrix (A ^'T × A') and calculates the ^{(A 'T × A')} -1, and the calculated transposed matrix A ^'T, X ″ can be calculated by substituting (A ′ ^T × A ′) ⁻¹ and y into Equation (18).

Figure 27 is a ^T 'transposed matrix A' matrix A shown in FIG. 26. As shown in FIG. 27, a 9 × 21 transposed matrix A ′ ^T can be obtained from the matrix A ′.

Subsequently, A ′ ^T × A ′ is calculated from the matrix A ′ of FIG. 26 and the transposed matrix A ′ ^{T of} FIG.

FIG. 28 is a diagram illustrating a result of calculating a matrix (A ′ ^T × A ′). As shown in FIG. 28, a matrix of 9 rows and 9 columns (A ′ ^T × A ′) is calculated from the matrix A ′ of FIG. 26 and the transposed matrix A′T of FIG.

Subsequently, the inverse matrix from the matrix of FIG. ^{28 (A 'T × A'} ) (A 'T × A') to calculate a ^-1. Figure 29 is a diagram illustrating a matrix (A ^'T × A') inverse matrix of (A ^'T × ^A') result of calculating the ^-1. As shown in FIG. 29, as an inverse matrix ^{(A 'T × A')} -1 of the matrix ^{(A 'T × A')} , it is possible to obtain a matrix of 9 rows and 9 columns.

Subsequently, a matrix (A ′ ^T × y) is calculated from the matrix y shown in FIG. 27 and the matrix A ′ ^T shown in FIG. FIG. 30 is a diagram illustrating a result of calculating a matrix (A ′ ^T × y). As shown in FIG. 30, a matrix of 9 rows and 1 column can be obtained as a matrix (A ′ ^T × y).

Subsequently, by substituting the inverse matrix (A ′ ^T × A ′) ⁻¹ shown in FIG. 29 and the matrix (A ′ ^T × y) shown in FIG. 30 into the equation (18), the matrix X ″ is calculated. FIG. 31 is a diagram illustrating a result of calculating the matrix X ″. As shown in FIG. 31, a matrix of 9 rows and 1 column can be obtained as a matrix X ″. Each element of the matrix X ″ indicates the estimated power consumption for each operating state.

  FIG. 32 is a diagram showing the estimated power consumption of each device obtained from FIG. Each numerical value in FIG. 32 represents each element of the matrix X ″ shown in FIG. 32 with three significant digits.

Referring to FIG. 4C, X _1a and X _2a correspond to the power consumption value Wac when “AC / ON”. X _1b and X _2b correspond to the power consumption value Wstb at the time of “AC / standby”. X _1c and X _2c correspond to the power consumption value Wac + Wch at the time of “AC + charge / ON”. X _1d and X _2d correspond to the power consumption value Wstb + Wch at the time of “AC + charge / standby”.

  Thus, by deriving the matrix X ″, the estimated power consumption in the above four operating states can be calculated for each device.

  Returning to FIG. 24, after calculating the matrix X ″, the power consumption in the state of “AC + charge / OFF” is calculated (S903). In step S <b> 902, the estimated power consumption is calculated under the operating environment excluding the “AC + charge / OFF” state by controlling the device whose power source has changed from on to off so as not to charge the battery. Went. Therefore, in S903, the power consumption in the excluded “AC + charge / OFF” state is calculated based on the result of calculating the estimated power consumption.

Referring to FIG. 4C, the power consumption Wch in the “AC + charge / OFF” state is, for example, (1): the power consumption value Wac when “AC / ON” and “AC + charge / ON”. A method of deriving an estimated value of Wch by obtaining a difference (Wac + Wch) −Wac from a power consumption value Wac + Wch of (1) or (2): a power consumption value Wstb at the time of “AC / standby” and “AC + charge / standby” ”Can be calculated by a method of deriving an estimated value of Wch by obtaining a difference (Wstb + Wch) −Wstb from the power consumption value Wstb + Wch.

Since the calculated values of Wac, Wstb, Wac + Wch, and Wstb + Wch each include an error, Wch obtained by the method (1) and Wch obtained by the method (2) are not necessarily the same. It is not always the same value. Therefore, for example, it can be calculated by a method of deriving an estimated value of Wch by obtaining an average value of Wch obtained by the method (3) :( 1) and Wch obtained by the method (2). According to the method of (3), a more accurate estimated value is derived regardless of the magnitude of the error of Wch obtained by the method of (1) and the magnitude of error of Wch obtained by the method of (2). It becomes possible to do.

  FIG. 33 is an example of a table showing the estimated power consumption in each operating state of the device 3a and the device 3b. FIG. 33 is obtained by substituting calculated values for each item in the table shown in FIG. Fig.33 (a) has shown the estimated power consumption in each operation state of the apparatus 3a, and FIG.33 (b) has shown the estimated power consumption in each operation state of the apparatus 3b. Note that the power consumption in the state of “AC + charge / OFF” in FIGS. 33A and 33B is calculated using the method (3).

  As described above, the process of S106 can be executed.

  Returning to FIG. 2 again, after executing the processing of S106, the estimation evaluation unit 16 evaluates the current time based on the information indicating the timing for performing the accuracy evaluation of the estimated power consumption stored in the storage unit 7. It is determined whether or not it is time to perform (S107). The interval for evaluating the accuracy of the estimated power consumption is preferably larger than the interval for calculating the power consumption for each device, and may be, for example, 2 to 3 hours or every other day.

  When it is determined that the current time is not the timing for evaluating the accuracy of the estimated power consumption (No in S107), the estimated evaluation unit 16 maintains the standby state until a predetermined time elapses, and after the predetermined time elapses. S107 is executed again.

  On the other hand, when it is determined that the current time is the timing for evaluating the accuracy of the estimated power consumption (Yes in S107), the estimation evaluating unit 16 calculates the accuracy of the estimated power consumption (S108).

  As described above, since the estimated power consumption calculated in S106 is calculated by regression calculation, the calculated value includes an error. Therefore, the estimation accuracy of the estimated power consumption can be improved by controlling the error while periodically comparing the estimated power consumption value with the actual power consumption value.

  Hereinafter, an example of a method for evaluating the accuracy of estimated power consumption will be described with reference to FIGS. 35 and 36.

  FIG. 34 is a flowchart illustrating an example of evaluation of accuracy of estimated power consumption. FIG. 35 is a sequence diagram illustrating an example of evaluation of accuracy of estimated power consumption.

  First, as illustrated in FIG. 34, the information processing apparatus 1 stops the control of charging the battery (S701). The reason why the control of the charging of the battery is stopped is to make it possible to acquire the actual power consumption value when “AC + charging / OFF” is performed in a later process. As shown in FIG. 36, in S701, the operating state monitoring unit 8 of the information processing apparatus 1 cancels the notification when the power supply state changes, and the power control client 30a of the device 3a and the power control client 30b of the device 3b. To request. The power control clients 30a and 30b return a response indicating that the request is accepted.

  Subsequently, the power information acquisition unit 14 acquires power consumption information from the distribution board 2 (S702). Specifically, as illustrated in FIG. 35, the power information acquisition unit 14 of the information processing device 1 transmits a signal requesting total power information to the distribution board 2. The distribution board 2 that has received the signal requesting the total power information transmits the total power information to the power information acquisition unit 14. The power information acquisition unit 14 that has received the total power information transmits the acquired information to the estimation evaluation unit 16.

  Thereafter, the operation information acquisition unit 10 acquires the operation information of each device and stores it in the storage unit 7 (S703). Specifically, as illustrated in FIG. 35, the operation information acquisition unit 10 of the information processing device 1 transmits a signal requesting each operation information to the devices 3a and 3b. The devices 3 a and 3 b that have received the signal requesting the operation information of each device transmit the operation information of each device to the operation information acquisition unit 10. The operation information acquisition unit 10 that has received the operation information of each device stores the acquired information in the storage unit 7.

  Subsequently, the estimated evaluation unit 16 acquires estimated power consumption information corresponding to the operation information from the storage unit 7 (S704). The storage unit 7 stores the estimated power consumption value for each device calculated in S105 in advance. As illustrated in FIG. 35, the estimation evaluation unit 16 of the information processing device 1 extracts the estimated power consumption information of each device corresponding to the operation information acquired in S703 from the storage unit 7, and the estimation evaluation unit 16 Send.

  Thereafter, the estimation evaluation unit 16 calculates the difference between the total value of the estimated power consumption and the total power consumption (S705). Specifically, the estimated evaluation unit 16 calculates the total value by summing the estimated power consumption values of the devices extracted from the storage unit 7 in S704. Then, the estimation evaluation unit 16 calculates a difference between the total value and the value of the total power consumption acquired in S702. This difference corresponds to the accuracy of the estimated power consumption.

  Here, returning to FIG. 2 again, the estimation evaluation unit 16 determines whether or not the accuracy of the calculated estimated power consumption satisfies the standard (S109).

  In S109, as shown in FIG. 34, the estimation / evaluation unit 16 calculates a difference in S705, and then determines whether or not the difference value is equal to or smaller than a predetermined threshold (S706). The predetermined threshold value can be appropriately set according to the accuracy level desired by the electric power company. When it is determined that the difference is equal to or smaller than the predetermined threshold (Yes in S706), the estimation evaluation unit 16 waits until the next evaluation timing is reached (S707), and ends the process. On the other hand, when it is determined that the difference is larger than the predetermined threshold (No in S706), the process proceeds to S708, and the control of the power receiving state and the calculation of the estimated power consumption are executed again. Therefore, as shown in FIG. Returning to step S102, the processes after S102 are repeated.

As described above, the accuracy of the estimated power consumption can be evaluated.
(Modification)
Next, a modified example of the method of determining the combination of operating states for executing the operating state switching control in the process of S304 will be described. Note that the information processing system for realizing the modification can use the configuration of the information processing system illustrated in FIG. 1 and FIG.

  In the method shown in FIG. 12, it is determined whether or not the operation state switching control is performed by comparing the probability that the difference in the operation state is not filed with a predetermined threshold value. On the other hand, the modified example is characterized in that it is determined whether or not the operation state switching control is to be performed based on the relative rank assigned according to the probability that the difference in the operation state does not appear.

  36 and 37 are flowcharts showing a modification of S304. Since the process from the start of the process until the determination in S401 is negative in S401 and the process up to S405 is the same as the process described with reference to FIG.

  After the process of S405, the control execution determination unit 17 determines whether or not all combinations have been selected. If it is determined that not all combinations have been determined (No in S801), the process returns to S402, and the processes after S402 are executed again. On the other hand, when it is determined that all the combinations have been selected (Yes in S801), the control execution determination unit 17 assigns a relative rank to each of all the combinations for which the probability that the difference in the operation state does not appear (S802). . For example, after calculating the probability that no difference appears for all combinations, the control execution determination unit 17 gives the first rank as the relative rank to the combination having the highest probability in the set of all combinations. Then, relative ranks of second and subsequent ranks are assigned to the other combinations in the set in descending order of probability. After the processing in S802, the process proceeds to S803 in FIG.

  On the other hand, after it is determined that S401 is affirmative in the process of S401 after the process is started and control is determined in S407, the process proceeds to S305.

  In S803 of FIG. 37, the control execution determination unit 17 selects one from combinations of operating states having correlation (S402).

  Subsequently, the control execution determination unit 17 determines whether the relative rank of the selected combination is higher than a predetermined rank (S804). When it is determined that the relative rank of the selected combination is higher than the predetermined rank (Yes in S804), the control execution determination unit 17 determines that control is performed on the selected combination of operating states (S805). ). Thereafter, the process proceeds to S807. On the other hand, when it is determined that the relative rank of the selected combination is equal to or lower than the predetermined rank (No in S804), the control execution determination unit 17 determines that control is not performed on the selected combination of operating states ( S807). Thereafter, the process proceeds to S807.

  In step S807, the control execution determination unit 17 determines whether all combinations have been selected. When it is determined that all combinations have been selected (Yes at S807), the process proceeds to S305. On the other hand, if it is not determined that all combinations to be controlled have been selected (No at S807), the process returns to S802, and the processes after S802 are executed again.

  As described above, the process of S304 is executed.

  According to the above-described method, since the number of combinations of operating states for which switching control is performed is determined in advance, whether or not to perform control does not depend on the absolute value of the probability that no difference in operating states will appear. For this reason, the amount of reduction in the number of switching times can always be kept constant.

The preferred embodiments of the present invention have been described in detail above, but the present invention is not limited to specific embodiments, and various modifications and changes can be made. For example, in S304, it is determined whether or not the operation state switching control is to be performed by comparing the probability that the operation state difference does not appear with a predetermined threshold. By comparing with a predetermined threshold value, it is also possible to determine whether or not to perform operation state switching control. For example, in the present embodiment, VIF is used as an index representing a correlation value. However, for example, the correlation coefficient R _ij shown in Expression (1) can also be used as an index representing a correlation value. Alternatively, (1-R _ij ² ), which is the denominator component of VIF (referred to as tolerance) shown in Expression (2), can also be used as an index representing the correlation value.

1: Information processing device 2: Distribution board 3: Device 4: Device 5: Initial setting unit 6: Input device 7: Storage unit 8: Operation state monitoring unit 9: Power supply state control unit 10: Operation information acquisition unit 11: Correlation Sex determination unit 12: control target selection unit 13: correlation control unit 14: power information acquisition unit 15: power calculation unit 16: estimation evaluation unit 17: control execution determination unit 18: output device 20: input / output IF
30: Power control client

Claims (9)

An operation information acquisition unit that acquires operation state information including information on the state of the external power supply and information on the power reception state from each of the plurality of devices;
For a combination of devices having a correlation with the operating state among the plurality of devices, when it is determined that the correlation does not decrease, the power receiving state of at least one device among the devices corresponding to the combination is determined. A correlation control unit that controls the power receiving state differently from other devices;
A power calculator that calculates power consumption of each of the plurality of devices using the information on the operating state;
An information processing apparatus comprising:   For a combination of devices having a correlation with the operating state among the plurality of devices, an index value indicating whether or not the correlation is reduced is obtained, and each of the combinations corresponding to the combination based on the index value The information processing apparatus according to claim 1, further comprising a control execution determination unit that determines whether to control a power reception state of at least one of the devices.   The control execution determination unit determines whether or not to control a power reception state of at least one device among devices corresponding to the combination by comparing the index value with a predetermined index value. The information processing apparatus according to claim 2.   The control execution determination unit determines whether to control the power reception state of at least one device among the devices corresponding to the combination by comparing the relative rank given according to the index value and a predetermined relative rank. The information processing apparatus according to claim 2, wherein the information processing apparatus determines. The index value is the remaining number of times of measurement of power information including a total value of power consumption of each of the plurality of devices at a time corresponding to the information on the operating state ,
The control execution determination unit determines whether to control a power receiving state of at least one device among the devices corresponding to the combination by comparing the remaining number of times of measurement with a predetermined number of times of measurement. The information processing apparatus according to any one of claims 2 to 4. The index value is a probability that a change in the operating state in which the correlation is reduced does not occur ,
Information before Symbol Health includes information of the time when the operating state changes to a different state,
The control execution determination unit calculates a time difference between the times when the operation state has a correlation with respect to a combination of devices having a correlation with the operation state, and is specified by the time difference and the time included in the operation state information. 5. The probability is calculated based on a ratio to a time interval in which a total value of power consumption of each of the plurality of devices is measured. 5. Information processing device. An information processing method of an information processing apparatus for calculating power consumption of each of a plurality of devices,
From each of a plurality of devices, obtain information on the operating state including information on the state of the external power supply and information on the power receiving state,
For a combination of devices having a correlation with the operating state among the plurality of devices, when it is determined that the correlation does not decrease, the power receiving state of at least one device among the devices corresponding to the combination is determined. , Change it to be different from the power reception status of other devices,
Using the operating state information, calculate the power consumption of each of the plurality of devices,
An information processing method characterized by the above. Distribution board,
A plurality of devices electrically connected to the distribution board;
An operation information acquisition unit that acquires operation state information including information on the state of the external power supply and information on the power reception state from each of the plurality of devices;
For a combination of devices having a correlation with the operating state among the plurality of devices, when it is determined that the correlation does not decrease, the power receiving state of at least one device among the devices corresponding to the combination is determined. A correlation control unit that changes to be different from the power reception state of other devices,
A power calculator that calculates power consumption of each of the plurality of devices using the information on the operating state;
An information processing system comprising: An information processing program executed by an information processing device that calculates the power consumption of each of a plurality of devices,
From each of the plurality of devices, obtain information on the operating state including information on the state of the external power supply and information on the power receiving state,
For a combination of devices having a correlation with the operating state among the plurality of devices, when it is determined that the correlation does not decrease, the power receiving state of at least one device among the devices corresponding to the combination is determined. , Change it to be different from the power reception status of other devices,
Using the operating state information, calculate the power consumption of each of the plurality of devices,
An information processing program that executes processing.