JP5834832B2 - Power control support program, power control support device, and power control support method - Google Patents

Description

  The present invention relates to a power control support program, a power control support device, and a power control support method.

  In recent years, efforts have been made to suppress the peak of power load. By suppressing the peak of the power load, the power supply side can easily supply power stably, and the cost for excessive power generation equipment can be suppressed. In addition, a power storage device is prepared on the power demand side, and the peak value of power supplied from a commercial power source is suppressed by discharging from the power storage device during a time period when the power load increases.

  As a related prior art, for example, there is a control method for controlling power supplied from a commercial power source in accordance with a change in demand power (hereinafter, “Prior Art 1”). The prior art 1 calculates the degree of divergence between the actual demand power and the predicted demand power in the most recent unit period using the actual demand power transition data and the demand power prediction data. Then, according to the related art 1, the correction amount of the leveling target value, which is the target value of the maximum power supplied from the commercial power source, is calculated according to the calculated degree of deviation, and the power of the leveling target value corrected by the correction amount is calculated. The power feeding device is controlled so as to be supplied from commercial power.

JP 2011-229238 A

  However, according to the prior art, there is still a problem that it is difficult to suppress the peak of the power load. For example, according to the above-described prior art 1, when the variation of the power usage status for each time zone increases, it becomes difficult to predict the demand power, and it becomes difficult to suppress the peak of the power load.

  An object of the present invention is to provide a power control support program, a power control support device, and a power control support method that can calculate the discharge amount of a storage battery according to the degree of power consumption of a power consumption source as predicted. To do.

  In order to solve the above-described problems and achieve the object, according to one aspect of the present invention, predicted power consumption for each measurement period based on power consumption of a power consumption source in the same time zone of a plurality of different measurement periods; Obtaining the predicted power consumption accuracy for each measurement period in which the power consumption of the power consumption source in the control target period becomes the predicted power consumption, and any one of the predicted power consumption for each of the acquired measurement periods It is determined whether the power is larger than the target value of the maximum power in the time zone supplied from the commercial power source. If the determined predicted power consumption is larger than the target value, the determined predicted power consumption and the target value The amount of discharge to the power consumption source in the time zone of the control target period of the storage battery that charges and discharges electricity is calculated based on the difference between and the accuracy of the determined predicted power consumption. Wherein the power control assistance program that outputs the discharge amount of the source of power consumption in the serial time period, the power control assistance device and power control support method is proposed.

  According to one aspect of the present invention, there is an effect that it is possible to calculate the discharge amount of the storage battery according to the degree to which the power consumption of the power consumption source becomes as predicted.

FIG. 1 is an explanatory diagram of an example of the power control support method according to the embodiment. FIG. 2 is an explanatory diagram showing a system configuration example of the power control support system 200. FIG. 3 is a block diagram illustrating a hardware configuration example of the power control support apparatus 101. FIG. 4 is an explanatory diagram showing an example of the contents stored in the result data table 400. FIG. 5 is an explanatory diagram showing an example of the stored contents of the predicted power consumption table 500. FIG. 6 is an explanatory diagram showing an example of the stored contents of the probability table 600. FIG. 7 is a block diagram illustrating a functional configuration of the power control support apparatus 101. FIG. 8 is an explanatory diagram illustrating an example of classification of performance data. FIG. 9 is an explanatory diagram showing a transition example of the stored contents of the control plan table 900. FIG. 10 is an explanatory diagram showing an example of concentration of the discharge amount Bout (t) of the storage battery 102. FIG. 11 is an explanatory diagram showing a transition example of the stored contents of the power storage amount table. FIG. 12 is an explanatory diagram showing an example of the stored contents of the control plan table 900 when the target value is changed. FIG. 13 is an explanatory diagram showing an example of the stored contents of the stored electricity amount table 1100 when the target value is changed. FIG. 14 is an explanatory diagram of a specific example of the control plan table. FIG. 15 is an explanatory diagram illustrating an example of a charge / discharge control result of the storage battery 102. FIG. 16 is a flowchart illustrating an example of a power control support processing procedure of the power control support apparatus 101. FIG. 17 is a flowchart illustrating an example of a specific processing procedure of predicted power consumption calculation processing. FIG. 18 is a flowchart (part 1) illustrating an example of a specific process procedure of the control plan creation process. FIG. 19 is a flowchart (part 2) illustrating an example of a specific process procedure of the control plan creation process. FIG. 20 is a flowchart (part 1) illustrating an example of a control plan evaluation process procedure of the power control support apparatus 101. FIG. 21 is a flowchart (part 2) illustrating an example of a control plan evaluation process procedure of the power control support apparatus 101.

  Exemplary embodiments of a power control support program, a power control support device, and a power control support method according to the present invention will be explained below in detail with reference to the accompanying drawings.

(One embodiment of power control support method)
FIG. 1 is an explanatory diagram of an example of the power control support method according to the embodiment. In FIG. 1, a power control support apparatus 101 is a computer that supports control of charging / discharging of the storage battery 102 with respect to a power consumption source. Here, the power consumption source is one or more control target devices to be power controlled.

  The control target device is, for example, a notebook PC (Personal Computer), an electric vehicle, or a UPS (Uninterruptable Power Supply). That is, the power consumption source is a set of control target devices provided in, for example, a home, an office, a building, or a factory. A set of control target devices may be a power consumption source in units of cities, regions, power plants, power companies, and the like.

  The storage battery 102 is a device that charges and discharges electricity. The storage battery 102 may be, for example, a storage battery included in each of the control target devices, or may be a storage battery that charges and discharges electricity with respect to a plurality of control target devices. Furthermore, you may decide to handle what gathered the storage battery which each of control object apparatus has as the storage battery 102. FIG.

  In FIG. 1, graphs 110 and 120 are shown in a coordinate system including a horizontal axis representing time and a vertical axis representing power consumption. The unit of power consumption is [Wh]. Here, the graphs 110 and 120 represent the predicted power consumption of the power consumption source in each time zone from 9:00 to 17:00. The graphs 110 and 120 are the prediction curves 1 and 2 created based on the actual data representing the actual power consumption of the power consumption source in each time zone of a plurality of different measurement periods.

  The graphs 110 and 120 are each given a certain degree of accuracy representing the probability that the power consumption of the power consumption source in each time zone will change according to the predicted power consumption. Specifically, a probability “60 [%]” that the power consumption of the power consumption source changes according to the predicted power consumption in each time zone represented by the graph 110 is assigned to the graph 110. In addition, the graph 120 is given a probability “40 [%]” that the power consumption of the power consumption source changes according to the predicted power consumption of each time period represented by the graph 120.

  By performing discharge from the storage battery 102 to the power consumption source during the time period when the power load increases, the peak of the power load supplied from the commercial power source can be suppressed. The commercial power source is a facility that supplies power received from an electric power company or the like to a power consumption source or the storage battery 102.

  However, as shown in the graphs 110 and 120, when the measurement period of the actual data is different, the power usage state is different, and the variation of the power consumption for each time zone of the power consumption source may increase. For example, the graph 110 has a peak predicted power consumption in the 10 o'clock time zone, while the graph 120 has a peak predicted power consumption in the 15 o'clock time zone.

  That is, it may be difficult to make a highly accurate demand prediction in consideration of various factors that cause a large variation in power consumption of power consumption sources. In addition, it is not efficient to perform a plurality of predictions according to a factor that causes a large variation in power consumption of the power consumption source, and to continue discharging in all time periods when the power consumption of the power consumption source is high.

  Therefore, in the present embodiment, the power control support apparatus 101 uses a plurality of prediction curves with certainty representing the degree to which the power consumption of the power consumption source is as predicted, and the time during which the predicted power consumption is higher than the target value. The amount of discharge of the storage battery 102 in the band is determined according to the accuracy. Thereby, the control plan which suppresses the peak of electric power load is drawn up, reducing the risk when the prediction of power consumption comes off.

  Hereinafter, an example of the power control support process of the power control support apparatus 101 will be described.

  (1) The power control support apparatus 101 acquires the predicted power consumption for each measurement period based on the power consumption of the power consumption source in the same time zone of a plurality of different measurement periods. Further, the power control support apparatus 101 acquires the accuracy of the predicted power consumption for each measurement period in which the power consumption of the power consumption source in the control target period becomes the predicted power consumption.

  Here, the same time zone is one of a plurality of time zones included in the measurement period. Moreover, a control object period is a period which controls charging / discharging of the storage battery 102 with respect to an electric power consumption source. Here, as an example of the same time zone, a time zone of 10:00 will be described as an example.

  In this case, the power control support apparatus 101 acquires the predicted power consumption “15 [Wh], 12 [Wh]” for each of the graphs 110 and 120 in the 10 o'clock time zone. In addition, the power control support apparatus 101 acquires probabilities “60 [%] and 40 [%]” for each of the graphs 110 and 120 in which the power consumption of the power consumption source in the control target period becomes the predicted power consumption.

  (2) The power control support apparatus 101 determines whether any predicted power consumption of the acquired predicted power consumption for each measurement period is larger than a target value of the maximum power in the time zone supplied from the commercial power source. judge. The target value of the maximum power in each time zone supplied from the commercial power source is set in advance, for example.

  Here, the target value of the maximum power in each time zone supplied from the commercial power source is “10 [Wh]”. In this case, the power control support apparatus 101 determines that the predicted power consumption “15 [Wh], 12 [Wh]” for each of the graphs 110 and 120 in the 10:00 time zone is larger than the target value.

  (3) When any predicted power consumption is larger than the target value, the power control support apparatus 101 calculates the amount of discharge to the power consumption source in the time period of the control target period of the storage battery 102. Specifically, for example, the power control support apparatus 101 uses the power consumption based on the difference between the predicted power consumption that is larger than the target value and the target value and the probability that the power consumption of the power consumption source becomes the predicted power consumption. Calculate the amount of discharge to the source.

  More specifically, for example, the power control support apparatus 101 sets the difference “5 [Wh]” between the predicted power consumption “15 [Wh]” and the target value “10 [Wh]” of the graph 110 that is larger than the target value. calculate. Then, the power control support apparatus 101 multiplies the calculated difference “5 [Wh]” by the probability “0.6 = 60 [%]” of the graph 110 to thereby discharge the amount “3 [Wh] to the power consumption source. ]] Is calculated.

  Further, the power control support apparatus 101 calculates the difference “2 [Wh]” between the predicted power consumption “12 [Wh]” and the target value “10 [Wh]” of the graph 120 that is larger than the target value. Then, the power control support apparatus 101 multiplies the calculated difference “2 [Wh]” by the probability “0.4 = 40 [%]” of the graph 120, thereby generating a discharge amount “0.8” to the power consumption source. [Wh] "is calculated.

  Then, the power control support apparatus 101 adds the calculated discharge amount “3 [Wh]” to the power consumption source and the discharge amount “0.8 [Wh]” to 10 o'clock in the control target period of the storage battery 102. The amount of discharge to the power consumption source in the time zone is calculated. Here, the amount of discharge to the power consumption source in the 10 o'clock time zone of the control target period is “3.8 [Wh]”.

  (4) The power control support apparatus 101 outputs the calculated discharge amount to the power consumption source in the time zone. In the example described above, the power control support apparatus 101 outputs information indicating the discharge amount “3.8 [Wh]” to the power consumption source in the 10 o'clock time zone of the control target period.

  Thus, according to the power control support apparatus 101, the discharge amount of the storage battery 102 in the time zone in which the power consumption of the power consumption source is predicted to be higher than the target value can be calculated. As a result, it becomes possible to make a control plan for charging / discharging the storage battery 102 based on the calculated discharge amount of the storage battery 102 in the time zone, reducing the power consumption of the power consumption source in the time zone, The load peak can be suppressed.

  Further, according to the power control support apparatus 101, the storage battery 102 is discharged using a plurality of prediction curves with probabilities (for example, prediction curves 1 and 2) representing the degree to which the actual power consumption of the power consumption source is as predicted. The amount can be calculated. As a result, even when the peak time zones of a plurality of prediction curves vary, the amount of discharge of the storage battery 102 can be allocated according to the probability of each prediction curve, and the electric power can be reduced while reducing the risk when the prediction is lost. The load peak can be suppressed.

(System configuration example of power control support system 200)
Next, a system configuration of the power control support system 200 according to the embodiment will be described. FIG. 2 is an explanatory diagram showing a system configuration example of the power control support system 200. In FIG. 2, the power control support system 200 includes a power control support device 101 and a plurality of control target devices 201.

  In the power control support system 200, the power control support device 101 and the control target device 201 are connected via a wired or wireless network 210 so that they can communicate with each other. The network 210 is, for example, a local area network (LAN), a wide area network (WAN), or the Internet.

  Here, the power control support apparatus 101 supports the charge / discharge control of the battery 202 with respect to the control target apparatus 201. The control target device 201 is a power consumption source that consumes power. The control target device 201 includes a battery 202 that charges and discharges electricity. The control target device 201 is, for example, a notebook PC used by employees such as offices, buildings, and factories.

  The commercial power supply 203 is a facility that supplies power received from a power supply side such as an electric power company to the control target device 201 and the storage battery 102. The storage battery 102 corresponds to, for example, a collection of batteries 202 included in each control target device 201. However, the storage battery 102 may be a power storage device that charges and discharges electricity to and from the plurality of control target devices 201.

  In addition, the power control support apparatus 101 collects information indicating the power consumption of each control target apparatus 201. Specifically, for example, the power control support apparatus 101 acquires performance data representing the power consumption of each control target apparatus 201 for each preset time slot periodically or irregularly from each control target apparatus 201. In addition, the power control support apparatus 101 acquires performance data representing the power consumption of all the control target devices 201 from a distribution board (not shown) that supplies power from the commercial power supply 203 to each control target device 201. Also good.

  In addition, the power control support apparatus 101 collects information on the battery 202 included in each control target apparatus 201. The information of the battery 202 includes, for example, the remaining power storage capacity, the maximum storage capacity, the maximum discharge amount per unit time, the maximum charge amount per unit time, and the like. Specifically, for example, the power control support apparatus 101 acquires information on the battery 202 from the control target apparatus 201 regularly or irregularly.

(Hardware configuration example of power control support apparatus 101)
FIG. 3 is a block diagram illustrating a hardware configuration example of the power control support apparatus 101. In FIG. 3, a power control support apparatus 101 includes a CPU (Central Processing Unit) 301, a ROM (Read-Only Memory) 302, a RAM (Random Access Memory) 303, a magnetic disk drive 304, a magnetic disk 305, An optical disk drive 306, an optical disk 307, an interface (I / F) 308, a display 309, a keyboard 310, and a mouse 311 are included. Each component is connected by a bus 300.

  Here, the CPU 301 governs overall control of the power control support apparatus 101. The ROM 302 stores a program such as a boot program. The RAM 303 is used as a work area for the CPU 301. The magnetic disk drive 304 controls the reading / writing of the data with respect to the magnetic disk 305 according to control of CPU301. The magnetic disk 305 stores data written under the control of the magnetic disk drive 304.

  The optical disk drive 306 controls the reading / writing of the data with respect to the optical disk 307 according to control of CPU301. The optical disk 307 stores data written under the control of the optical disk drive 306, and causes the computer to read data stored on the optical disk 307.

  The display 309 displays data such as a document, an image, and function information as well as a cursor, an icon, or a tool box. As this display 309, for example, a CRT, a TFT liquid crystal display, a plasma display, or the like can be adopted.

  The I / F 308 is connected to the network 210 through a communication line, and is connected to other devices via the network 210. The I / F 308 controls an internal interface with the network 210 and controls input / output of data from other devices. For example, a modem or a LAN adapter may be employed as the I / F 308.

  The keyboard 310 includes keys for inputting characters, numbers, various instructions, and the like, and inputs data. Moreover, a touch panel type input pad or a numeric keypad may be used. The mouse 311 performs cursor movement, range selection, window movement, size change, and the like. A trackball or a joystick may be used as long as they have the same function as a pointing device.

  2 can be realized by a hardware configuration similar to that of the power control support apparatus 101 described above. The power control support apparatus 101 may not include, for example, the optical disk drive 306, the optical disk 307, the display 309, the keyboard 310, and the mouse 311 among the components described above.

(Stored contents of the result data table 400)
Next, a performance data table 400 that stores performance data representing the power consumption of the power consumption source in each time zone in a plurality of different measurement periods will be described with reference to FIG. The record data table 400 is realized by a storage device such as the RAM 303, the magnetic disk 305, and the optical disk 307 shown in FIG.

  FIG. 4 is an explanatory diagram showing an example of the contents stored in the result data table 400. In FIG. 4, the record data table 400 stores record data 400-1 to 400-6 representing the power consumption of the power consumption source in each time zone for each of the dates 1 to 6. The power consumption source is, for example, the plurality of control target devices 201 illustrated in FIG. The unit of power consumption is [Wh].

  Here, Date 1 to Date 5 are a plurality of different measurement periods in which the power consumption of the power consumption source is measured. Date 6 is a control target period for controlling charging / discharging of the storage battery 102 with respect to the power consumption source. The time represents a time zone of one hour unit in one day. For example, time 1 represents a time zone of 1 o'clock of the day, that is, 1:00 to 1:59.

  Taking the actual data 400-1 as an example, the power consumption “0 [Wh]” at time 1 of the date 1 of the power consumption source, the power consumption “0 [Wh]” at time 2, and the power consumption “8 [ Wh] ”, power consumption“ 8 [Wh] ”at time 4 is shown. Also, the power consumption “8 [Wh]” at time 5, the power consumption “16 [Wh]” at time 6, the power consumption “14 [Wh]” at time 7, and the power consumption “0 [Wh]” at time 8 It is shown.

(Storage contents of the predicted power consumption table 500)
Next, a predicted power consumption table 500 that stores the predicted power consumption in each time zone based on the power consumption of the power consumption source in the same time zone in a plurality of different measurement periods will be described using FIG. The predicted power consumption table 500 is realized by a storage device such as the RAM 303, the magnetic disk 305, and the optical disk 307 shown in FIG.

  FIG. 5 is an explanatory diagram showing an example of the stored contents of the predicted power consumption table 500. In FIG. 5, the predicted power consumption table 500 stores predicted power consumption information 500-1 to 500-6 for each time zone from 3 o'clock to 8 o'clock in a day. Specifically, the predicted power consumption information 500-1 to 500-6 indicates the predicted power consumption of the power consumption source for each prediction curve in each time zone.

  Here, the prediction curve is a curve representing the predicted power consumption of the power consumption source in each time zone based on the actual power consumption of the power consumption source. The prediction curve is, for example, the graphs 110 and 120 shown in FIG. In the figure, L1 and L2 are identifiers for identifying prediction curves.

  Taking the predicted power consumption information 500-1 as an example, the predicted power consumption “9 [Wh]” of the power consumption source of the prediction curve L1 at time 3 and the predicted power consumption of the power consumption source of the prediction curve L2 at time 3 “ 12 [Wh] ”. The predicted power consumption information 500-1 to 500-6 can be created, for example, with reference to the performance data table 400 shown in FIG.

(Contents stored in probability table 600)
Next, a probability table 600 that stores the probability for each prediction curve in which the power consumption of the power consumption source in the control target period becomes the predicted power consumption will be described with reference to FIG. The probability table 600 is realized by a storage device such as the RAM 303, the magnetic disk 305, and the optical disk 307 shown in FIG.

  FIG. 6 is an explanatory diagram showing an example of the stored contents of the probability table 600. In FIG. 6, the probability table 600 stores probability information 600-1 and 600-2 for each of the prediction curves L1 and L2. Specifically, the probability information 600-1 and 600-2 indicate probabilities for the prediction curves L1 and L2 in which the power consumption of the power consumption source in the control target period becomes the predicted power consumption.

  The probability information 600-1 and 600-2 can be created with reference to the record data table 400 shown in FIG. 4, for example. In the example of FIG. 6, the probability is set for each of the prediction curves L1 and L2. However, for example, the probability may be set for each time zone of each of the prediction curves L1 and L2.

(Functional configuration example of power control support apparatus 101)
FIG. 7 is a block diagram illustrating a functional configuration of the power control support apparatus 101. In FIG. 7, the power control support apparatus 101 includes an acquisition unit 701, a classification unit 702, a first calculation unit 703, a determination unit 704, a second calculation unit 705, a third calculation unit 706, The configuration includes a changing unit 707 and an output unit 708. The acquisition unit 701 to the output unit 708 are functions serving as control units. Specifically, for example, a program stored in a storage device such as the ROM 302, the RAM 303, the magnetic disk 305, and the optical disk 307 illustrated in FIG. The function is realized by executing or by the I / F 308. Further, the processing results of the respective functional units are stored in a storage device such as the RAM 303, the magnetic disk 305, and the optical disk 307, for example.

  The acquisition unit 701 has a function of acquiring performance data representing power consumption of a power consumption source for each time period in a plurality of different measurement periods for each measurement period. Here, the measurement period is a past period in which the power consumption of the power consumption source is measured. A period is a period from a certain time point to another time point. The period is, for example, 1 hour, 1 day, 1 week, 1 month, 1 year, or the like.

  A time zone is a time between a certain time and another time. The time zone is, for example, a certain time between one time of the day and another time. Also, the time zone may be set across days. For example, the time period may be a time from one day of one month to another day, or may be a time from one day of the year to another day.

  Specifically, for example, the acquisition unit 701 collects the power consumption of the control target device 201 for each time period in dates 1 to 5 which are a plurality of different measurement periods, so that the result data 400 illustrated in FIG. -1 to 400-5 may be acquired. Further, the acquisition unit 701 may acquire the record data 400-1 to 400-5 by a user operation input using the keyboard 310 and the mouse 311 illustrated in FIG.

  Moreover, the acquisition part 701 has a function which acquires the performance data showing the power consumption of the power consumption source for every time slot | zone in a control object period. Specifically, for example, the acquisition unit 701 acquires the performance data 400-6 illustrated in FIG. 4 by collecting the power consumption of the control target device 201 up to that day that is the control target period. Also good.

  In addition, the acquisition unit 701 may acquire the record data 400-6 by a user operation input using the keyboard 310 or the mouse 311. The acquired performance data (for example, performance data 400-1 to 400-6) is stored in, for example, the performance data table 400 shown in FIG.

  The acquisition unit 701 has a function of acquiring information on the storage battery 102. Here, the information of the storage battery 102 includes, for example, the remaining power storage capacity, the maximum storage capacity, the maximum discharge amount per unit time, the maximum charge amount per unit time, and the like.

  Specifically, for example, the acquisition unit 701 may acquire information indicating the maximum storage capacity of the storage battery 102, the maximum discharge amount per unit time, and the maximum charge amount per unit time by a user operation input. Good. Further, for example, the acquisition unit 701 collects and adds the remaining amount of power stored in the battery 202 of each control target device 201 from each control target device 201, thereby collecting the batteries 202 of each control target device 201. You may decide to acquire the electrical storage residual amount. In the case where the storage battery 102 is a device that charges and discharges electricity to and from the plurality of control target devices 201, the acquisition unit 701 may acquire the remaining power storage amount from the storage battery 102.

  The classification unit 702 has a function of classifying the acquired performance data for each measurement period. Specifically, for example, the classification unit 702 obtains n pieces of actual data for each measurement period based on the time period in which the power consumption of the power consumption source is the maximum among a plurality of time periods in the measurement period. Into a set of

  Here, n is a natural number of 2 or more. For example, n is set in advance and stored in a storage device such as the ROM 302, the RAM 303, the magnetic disk 305, and the optical disk 307. A specific example of the classification process of the classification unit 702 will be described later with reference to FIG.

  In the following description, a time zone in which the power consumption of the power consumption source is maximum may be referred to as a “peak time zone”. In addition, the n sets of classified result data may be referred to as “clusters C1 to Cn”. In addition, an arbitrary cluster among the clusters C1 to Cn may be referred to as “cluster Ci” (n = 1, 2,..., N). In addition, an arbitrary time zone among a plurality of time zones in the measurement period may be expressed as “time zone t”.

  For each classified cluster Ci, the first calculation unit 703 calculates the predicted consumption of the power consumption source in each time zone t based on the power consumption of the power consumption source in each time zone t of the performance data included in the cluster Ci. It has a function to calculate electric power. Specifically, for example, the first calculation unit 703 obtains an average value of the power consumption of the power consumption source in the time zone t of the record data included in the cluster Ci, so that the power consumption in the time zone t of the cluster Ci. The predicted power consumption of the source may be calculated.

  The calculated predicted power consumption of the power consumption source in each time zone t of the cluster Ci is stored in, for example, the predicted power consumption table 500 illustrated in FIG. Specifically, for example, the predicted power consumption of the power consumption source in the time zone t of the cluster Ci is stored as the predicted power consumption of the power consumption source in the time zone t represented by the prediction curve Li corresponding to the cluster Ci.

  In the following description, the predicted power consumption of the power consumption source in the time zone t represented by the prediction curve Li corresponding to the cluster Ci may be expressed as “predicted power consumption Li (t)”.

  In addition, the first calculation unit 703 uses the number of actual data included in the cluster Ci with respect to the number of actual data for each measurement period, and the cluster Ci in which the power consumption of the power consumption source in the control target period becomes the predicted power consumption. It has a function of calculating the accuracy of predicted power consumption for each. Here, the accuracy of the predicted power consumption of the cluster Ci is a degree representing the probability that the power consumption of the power consumption source in the control target period becomes the predicted power consumption.

  The accuracy of the predicted power consumption of the cluster Ci is, for example, the probability Pi that the power consumption of the power consumption source in the control target period changes according to the prediction curve Li corresponding to the cluster Ci. Specifically, for example, the first calculation unit 703 may calculate, as the probability Pi, the ratio of the number of performance data included in the cluster Ci to the total number of performance data for each measurement period.

  For example, the probability Pi of the prediction curve Li corresponding to the calculated cluster Ci is stored in the probability table 600 shown in FIG. A specific example of the calculation process of the first calculation unit 703 that calculates the predicted power consumption Li (t) and the probability Pi of the power consumption source in the time zone t of the cluster Ci will be described later with reference to FIG.

  The determination unit 704 sets the target of the maximum power in the time zone t supplied from the commercial power source 203 (see FIG. 2) when any one of the predicted power consumptions of the power consumption sources in the time zone t for each measurement period is supplied. It has a function of determining whether or not it is larger than the value d.

  Here, the predicted power consumption of the power consumption source in the time period t for each measurement period is the predicted power consumption for each measurement period based on the power consumption of the power consumption source in the time period t of the measurement period. Specifically, for example, the predicted power consumption of the power consumption source in the time zone t for each measurement period is the predicted power consumption Li (t) of the power consumption source in the time zone t of the prediction curve Li corresponding to the cluster Ci. .

  The target value d is a value that serves as an index for determining that the storage battery 102 should be discharged when the supply amount of power from the commercial power source 203 exceeds the target value d, for example. The initial value of the target value d is preset and stored in a storage device such as the ROM 302, the RAM 303, the magnetic disk 305, and the optical disk 307, for example.

  Specifically, for example, the determination unit 704 refers to the predicted power consumption table 500, and the predicted power consumption Li (t) of the power consumption source in the time zone t of the prediction curve Li corresponding to the cluster Ci is the target value d. It may be determined whether or not it is larger. A specific example of the determination process of the determination unit 704 will be described later with reference to FIG.

  When one of the predicted power consumptions of the power consumption source in the time zone t for each measurement period is larger than the target value d, the second calculation unit 705 determines the time zone t of the control target period of the storage battery 102. Has a function of calculating the amount of discharge to the power consumption source. In the following description, the discharge amount to the power consumption source in the time zone t of the control target period of the storage battery 102 may be referred to as “discharge amount Bout (t)”.

  Specifically, for example, the second calculation unit 705 determines that the difference between the predicted power consumption Li (t) and the target value d and the power consumption of the power consumption source in the time zone t are the predicted power consumption Li (t). Based on the probability Pi, the discharge amount Bout (t) to the power consumption source is calculated. This predicted power consumption Li (t) is any predicted power consumption that is larger than the target value d among the predicted power consumptions L1 (t) to Ln (t) in the time zone t. The probability Pi can be specified from the probability table 600, for example.

  In addition, when the predicted power consumption of the power consumption source in the time period t for each measurement period is equal to or less than the target value d, the second calculation unit 705 charges from the power consumption source in the time period t of the control target period of the storage battery 102. Has the function of calculating the quantity. In the following description, the charge amount from the power consumption source in the time zone t of the control target period of the storage battery 102 may be referred to as “charge amount Bin (t)”.

  Specifically, for example, the second calculation unit 705 calculates the charge amount Bin (t) from the power consumption source based on the difference between the predicted power consumption Li (t) and the target value d. This predicted power consumption Li (t) is any one of the predicted power consumption L1 (t) to Ln (t) in the time period t.

  The calculated discharge amount Bout (t) or charge amount Bin (t) in the time period t is stored, for example, in a control plan table 900 shown in FIG. Note that a specific example of the calculation process of the second calculation unit 705 that calculates the discharge amount Bout (t) and the charge amount Bin (t) will be described later with reference to FIG.

  The third calculation unit 706 is based on the remaining storage amount of the storage battery 102 in the time period t of the control target period and the calculation result calculated by the second calculation unit 705, and the stored amount of the storage battery 102 in the time period t. It has a function of calculating R (t). In the following description, the amount of power stored in the storage battery 102 in the time zone t may be referred to as “power storage amount R (t)”.

  Specifically, for example, the third calculation unit 706 adds the remaining amount of power stored in the storage battery 102 in the time zone t of the control target period and the discharge amount Bout (t) of the storage battery 102, thereby A storage amount R (t) is calculated. In addition, the third calculation unit 706 adds the remaining amount of electricity stored in the storage battery 102 and the amount of charge Bin (t) of the storage battery 102 in the time zone t of the control target period, whereby the amount of electricity stored R (t ) Is calculated.

  When the calculated storage amount R (t) of the storage battery 102 is less than the threshold value R1 that represents the lower limit amount of the remaining storage amount of the storage battery 102, the changing unit 707 changes the target value d to a value greater than the value. It has the function to do. Here, the threshold value Rl is preferably set to a value at which it is preferable not to discharge from the storage battery 102 when the remaining battery charge of the storage battery 102 falls below the threshold value Rl, or to prevent discharge. The threshold value Rl is preset and stored in a storage device such as the ROM 302, the RAM 303, the magnetic disk 305, and the optical disk 307, for example.

  Specifically, for example, when the storage amount R (t) of the storage battery 102 is less than the threshold value R1, the changing unit 707 changes the target value d by multiplying the target value d by a constant α. May be. Here, the constant α is a value larger than 1, for example, “α = 1.1”. Thereby, the target value d of the maximum power in the time zone t supplied from the commercial power source 203 can be raised.

  In addition, when the minimum storage amount of the storage battery 102 in each of the plurality of time zones included in the measurement period is greater than the threshold value Rh, the changing unit 707 sets the target value d to the value It has a function to change to a smaller value. Here, the threshold value Rh is a value that is larger than the threshold value Rl by an allowable value Rd, and is set to a value that is preferable to be discharged from the storage battery 102 when the remaining power amount of the storage battery 102 exceeds the threshold value Rh. That is, the threshold value Rh is “Rh = Rl + Rd”. For example, the allowable value Rd is set in advance and stored in a storage device such as the ROM 302, the RAM 303, the magnetic disk 305, and the optical disk 307.

  Specifically, for example, when the minimum storage amount of the storage battery 102 is greater than the threshold value Rh, the changing unit 707 may change the target value d by multiplying the target value d by a constant β. Good. Here, the constant β is a value smaller than 1, for example, “β = 0.9”. Thereby, the target value d of the maximum power in the time zone t supplied from the commercial power source 203 can be lowered. A specific example of the changing process of the changing unit 707 will be described later with reference to FIG.

  When the target value d is changed by the changing unit 707, the determining unit 704 determines whether the predicted power consumption Li (t) of the power consumption source in the time period t is larger than the changed target value d after the change. It may be determined. Thereby, the storage amount R (t) of the storage battery 102 in the time zone t can be obtained using the changed target value d.

  The output unit 708 has a function of outputting the calculation result calculated by the second calculation unit 705. The calculated discharge amount Bout (t) or charge amount Bin (t) in the time zone t is a control plan that supports the charge / discharge control of the storage battery 102 with respect to the power consumption source in the time zone t. Specifically, for example, the output unit 708 may output a control plan table 1400 shown in FIG.

  Examples of the output format of the output unit 708 include display on the display 309, print output to a printer (not shown), and transmission to an external computer via the I / F 308. Alternatively, the data may be stored in a storage area such as the RAM 303, the magnetic disk 305, and the optical disk 307.

  Moreover, although the above-mentioned description demonstrated the case where the predicted power consumption of the power consumption source in the time slot | zone t was calculated based on the actual power consumption of the power consumption source in the time slot | zone t, it is not restricted to this. For example, the power control support apparatus 101 may acquire the predicted power consumption for each measurement period based on the power consumption of the power consumption source in each time zone of a plurality of different measurement periods.

  In the above description, the case where the predicted power consumption Li (t) and the probability Pi of the power consumption source in the time zone t is calculated based on the actual power consumption of the power consumption source in the time zone t. Not limited to this. For example, the power control support apparatus 101 may acquire the predicted power consumption Li (t) and the probability Pi in the time zone t for each prediction curve Li.

  Specifically, for example, the acquisition unit 701 receives predicted power consumption information 500-1 to 500-6 (see FIG. 5) and probability information 600-1, 600- by user operation input or from an external computer. 2 (see FIG. 6) may be acquired. In this case, for example, the power control support apparatus 101 may not include the classification unit 702 and the first calculation unit 703 among the functional units described above.

(Calculation process of predicted power consumption Li (t) and probability Pi)
Next, a specific example of calculation processing for calculating the predicted power consumption Li (t) and the probability Pi of the power consumption source in the time zone t will be described based on the performance data 400-1 to 400-5 shown in FIG. . First, a specific example of the classification process of the classification unit 702 that classifies the record data 400-1 to 400-5 into two (n = 2) clusters C1 and C2 will be described with reference to FIG.

  In the following description, a plurality of different measurement periods may be expressed as “date 1 to date m”, and an arbitrary date among dates 1 to m may be expressed as “date j” (j = 1, 2). , ..., m). An arbitrary time zone of date j is expressed as “time zone t (j)”, and a time zone in which the power consumption of the power consumption source is the maximum among a plurality of time zones included in date j is designated as “peak time”. It may be expressed as “band tp (j)”.

  FIG. 8 is an explanatory diagram illustrating an example of classification of performance data. In FIG. 8, actual data 400-1 to 400-5 indicating the actual power consumption of the power consumption source in each time zone from time 1 to time 8 for each of date 1 to date 5 are shown.

  First, the classification unit 702 refers to the performance data 400-1 to 400-5, and for each date j, the peak at which the power consumption of the power consumption source in the plurality of time zones from time 1 to time 8 is maximized. The time zone tp (j) is specified. Here, the peak time zone tp (1) of date 1 is the time zone of time 6. The peak time zone tp (2) of date 2 is the time zone of time 7. The peak time zone tp (3) of date 3 is the time zone of time 3. The peak time zone tp (4) of date 4 is the time zone of time 4. The peak time zone tp (5) of date 5 is the time zone of time 3.

  Next, the classification unit 702 classifies the performance data 400-1 to 400-5 into clusters C1 and C2 based on the peak time zone tp (j) of each date j. Specifically, for example, the classifying unit 702 classifies the results data having the same time zone in which the power consumption of the power consumption source is maximum. As a result, when the result data 400-1 to 400-5 are classified into two clusters C1 and C2, the classification process of the classification unit 702 is terminated.

  On the other hand, when the data is not classified into the two clusters C1 and C2, the classifying unit 702 classifies the data by performance data in which the difference in the time zone in which the power consumption of the power consumption source is maximum is within the predetermined value Q. The initial value of the predetermined value Q is, for example, “Q = 1”. As a result, when the result data 400-1 to 400-5 are classified into two clusters C1 and C2, the classification process of the classification unit 702 is terminated.

  On the other hand, when the two clusters C1 and C2 are not classified, the classification unit 702 increments the predetermined value Q, and the difference in the time zone in which the power consumption of the power consumption source is maximum is within the predetermined value Q. Sort by performance data. For example, the classification unit 702 repeats the above-described processing until the result data 400-1 to 400-5 are classified into two clusters C1 and C2.

  In the example of FIG. 8, the results data 400-1 to 400-5 are classified as result data in which the difference in the time zone in which the power consumption of the power consumption source is maximum is within a predetermined value Q (Q = 1). Are classified into two clusters C1 and C2. Specifically, the performance data 400-1 and 400-2 are included in the cluster C1. The cluster C2 includes performance data 400-3 to 400-5.

  Thereby, it is possible to perform clustering focusing on the peak time period tp (j) in which the power consumption of the power consumption source is maximum. Note that the number n for classifying the performance data may be set, for example, by the user confirming the performance data for each date j and determining the tendency of the peak time period tp (j). In the example of the record data 400-1 to 400-5, the peak time zone tp (j) is accumulated in the vicinity of the time zones of the time 3 and the time 6, so the user sets the number n to “n = 2”.

  Next, a specific example of the calculation process of the first calculation unit 703 that calculates the predicted power consumption Li (t) of the power consumption source in each time zone t of the cluster Ci will be described.

  First, the first calculation unit 703 calculates the similarity S (j) between the actual measurement data of the date j included in the cluster Ci and the actual measurement data of the control target period. The actual measurement data of the control target period represents the actual power consumption of the power consumption source up to that day, and is, for example, the actual measurement data 400-6 shown in FIG.

  Specifically, for example, the first calculation unit 703 uses the Euclidean distance K (j) between the actual measurement data of the date j included in the cluster Ci and the actual measurement data of the control target period as the similarity S (j). You may decide to calculate. In this case, the smaller the value of the Euclidean distance K (j), the higher the degree of similarity with the measured data in the control target period.

Here, each time zone of the control target period in which actual power consumption is measured is taken as an axis, and power consumption in each time zone is taken as a coordinate value of each axis. For example, the Euclidean distance K (1) between the actual measurement data 400-1 of the date 1 included in the cluster C1 and the actual measurement data 400-6 of the control target period is “{(0-0) ² + (0-0) ^2. } ^1/2 = 0]. For example, the Euclidean distance K (5) between the actual measurement data 400-5 of the date 5 included in the cluster C2 and the actual measurement data 400-6 of the control target period is “{(0-2) ² + (0-2) ^2. } ^{1 /} 2≈2.8 ”.

  Next, the 1st calculation part 703 selects the performance data whose similarity S (j) with the measurement data of a control object period is more than a threshold value from the performance data contained in the cluster Ci. Specifically, for example, the first calculation unit 703 selects performance data having an Euclidean distance K (j) less than the threshold value V. Further, the first calculation unit 703 may select W pieces of performance data from the one having the lower Euclidean distance among the pieces of performance data included in the cluster Ci.

  Here, it is assumed that the threshold value V is “V = 1”. In this case, the first calculation unit 703 obtains the record data 400-1 and 400-2 whose Euclidean distance K (j) is less than the threshold value V from the record data 400-1 and 400-2 included in the cluster C1. Select (K (1) = K (2) = 0). Further, the first calculation unit 703 selects the record data 400-3 and 400-4 whose Euclidean distance K (j) is less than the threshold value V from the record data 400-3 to 400-5 included in the cluster C2. (K (3) = K (4) = 0, K (5) ≈2.8).

  Thereby, the performance data having a low degree of similarity with the actual measurement data in the control target period can be excluded from the actual data included in the cluster Ci. The threshold value V and the number W are set in advance and stored in a storage device such as the ROM 302, the RAM 303, the magnetic disk 305, and the optical disk 307, for example.

  Next, the first calculation unit 703 calculates, for each cluster Ci, the predicted power consumption Li (t) of the power consumption source in the time zone t of the cluster Ci based on the selected record data. Specifically, for example, the first calculation unit 703 obtains the average power consumption of the power consumption sources in the time zone t of the performance data selected by the cluster Ci, thereby predicting the predicted power consumption Li (t of the power consumption source. ) May be calculated.

  Taking the time zone at time 3 of the cluster C1 as an example, the first calculation unit 703 obtains the average of the power consumption of the power consumption sources in the time zone at time 3 of the record data 400-1 and 400-2. The predicted power consumption “L1 (3) = 9” of the power consumption source is calculated.

  Further, taking the time zone at time 3 of the cluster C2 as an example, the first calculation unit 703 obtains the average power consumption of the power consumption sources in the time zone at time 3 of the record data 400-3 and 400-4. Thus, the predicted power consumption “L2 (3) = 12” of the power consumption source is calculated. The calculated predicted power consumption Li (t) is stored in the predicted power consumption table 500, for example.

  Next, the first calculation unit 703 calculates, for each cluster Ci, the probability Pi that the power consumption of the power consumption source in the control target period becomes the predicted power consumption Li (t). Specifically, for example, the first calculation unit 703 calculates, as the probability Pi, the ratio of the number of performance data selected from the cluster Ci to the total number of performance data selected from the clusters C1 to Cn. To do.

  Here, the performance data selected from the clusters C1 and C2 is the performance data 400-1 to 400-4, and the total number is “4”. In addition, the number of performance data selected from the cluster C1 is “2”. The number of performance data selected from the cluster C2 is “2”.

  For this reason, the first calculation unit 703 calculates the probability P1 of the ratio of the number of actual data “2” selected from the cluster C1 to the total number “4” of actual data selected from the clusters C1 and C2. Calculate as Here, the probability P1 is “P1 = 0.5”.

  Further, the first calculation unit 703 sets the ratio of the number “2” of the actual data selected from the cluster C2 to the total number “4” of the actual data selected from the clusters C1 and C2 as the probability P2. calculate. Here, the probability P2 is “P2 = 0.5”. The calculated probability Pi is stored in the probability table 600, for example.

  As described above, the first calculation unit 703 can calculate the predicted power consumption Li (t) of the power consumption source in the time zone t of the control target period based on the record data included in the cluster Ci. In addition, the first calculation unit 703 may calculate the probability Pi of the prediction curve Li corresponding to the cluster Ci based on the number of performance data included in the cluster Ci with respect to the total number of performance data on the dates 1 to m. it can.

  In addition, the power control support apparatus 101 classifies the performance data of the dates 1 to m into the clusters C1 to Cn based on the peak time zones tp (1) to tp (m), for example, the determination unit 704, the first The amount of calculation required for the processing of the second calculation unit 705 can be reduced. Moreover, the power control support apparatus 101 can reduce the noise of the power consumption of the power consumption source in the time zone t for each measurement period by classifying the clusters into the clusters C1 to Cn.

(Calculation process of discharge amount Bout (t) and charge amount Bin (t))
Next, on the basis of the predicted power consumption information 500-1 to 500-6 shown in FIG. 5 and the probability information 600-1 and 600-2 shown in FIG. ) And a specific example of calculation processing for calculating the charge amount Bin (t) will be described.

  FIG. 9 is an explanatory diagram showing a transition example of the stored contents of the control plan table 900. In FIG. 9, the control plan table 900 has fields of time, prediction curve L1, prediction curve L2, target value d, charge amount Bin, and discharge amount Bout. By setting information in each field, control plan information 900-1 to 900-6 for each time zone from time 3 to time 8 is stored as a record.

  Here, the prediction curve L1 is a prediction curve corresponding to the cluster C1. The prediction curve L2 is a prediction curve corresponding to the cluster C2. The target value d is a target value of the maximum power in each time zone supplied from the commercial power source 203. The charge amount Bin is the charge amount of the storage battery 102 in each time zone. The discharge amount Bout is the discharge amount of the storage battery 102 in each time zone.

  In the following description, the maximum charge amount Din per unit time of the storage battery 102 is “Din = 3 [Wh]”, and the maximum discharge amount Dout of the storage battery 102 per unit time is “Dout = 3 [Wh]”. To do.

  In (9-1) of FIG. 9, the predicted power consumption of the power consumption source in each time zone from time 3 to time 8 of each prediction curve L1, L2 based on the predicted power consumption information 500-1 to 500-6 is set. ing. Further, the target value d “d = 11 [wh]” of the maximum power in each time zone supplied from the commercial power source 203 is set.

  The determination unit 704 determines whether one of the predicted power consumption L1 (t) and L2 (t) of the power consumption source in each time zone t of the prediction curves L1 and L2 is greater than the target value d. Determine whether. For example, it is determined that the predicted power consumption L2 (3) of the power consumption source in the time zone of time 3 is larger than the target value d.

  In this case, the 2nd calculation part 705 can calculate discharge amount Bout (3) of the storage battery 102 in the time slot | zone of the time 3 using the following formula (1), for example. However, Bout (t) is the discharge amount of the storage battery 102 in the time zone t. Li (t) is the predicted power consumption of the power consumption source in the time zone t of the prediction curve Li. d is a target value of the maximum power in the time zone t supplied from the commercial power source 203. Pi is the probability that the power consumption of the power consumption source will change according to the prediction curve Li, that is, the probability that the power consumption of the power consumption source in the time zone t will be the predicted power consumption Li (t).

    Bout (t) = {Li (t) −d} × Pi (1)

  Specifically, for example, first, the second calculation unit 705 calculates the difference between the predicted power consumption L2 (3) and the target value d. The difference here is “L2 (3) −d = 12−11 = 1”. Then, the second calculation unit 705 refers to the probability table 600 and multiplies the calculated difference by the probability P2 of the prediction curve L2 to thereby discharge the discharge amount Bout (3) of the storage battery 102 in the time zone at time 3. Is calculated. The discharge amount Bout (3) is “Bout (3) = 1 × 0.5 = 0.5”.

  Further, since the predicted power consumption L2 (4), L1 (6), L1 (7) of the power consumption source in each time zone of time 4, time 6 and time 7 is larger than the target value d, similarly, Discharge amounts Bout (4), Bout (6), and Bout (7) of the storage battery 102 in each time zone of time 6 and time 7 are calculated.

  As a result, in (9-2) of FIG. 9, the discharge amounts Bout (3), Bout (4), Bout (6), Bout of the storage battery 102 in the time zones of time 3, time 4, time 6 and time 7 (7) is set. When the discharge amount Bout (t) exceeds the maximum discharge amount Dout per unit time of the storage battery 102, the discharge amount Bout (t) is “Bout (t) = Dout”.

  In addition, the second calculation unit 705 calculates the charge amount Bin (t) of the storage battery 102 when both the predicted power consumption L1 (t) and L2 (t) are equal to or less than the target value d. For example, it is determined that both predicted power consumption L1 (5) and L2 (5) of the power consumption source in the time zone of time 5 are equal to or less than the target value d.

  In this case, for example, the second calculation unit 705 calculates the minimum difference among the differences between the predicted power consumptions L1 (5) and L2 (5) and the target value d of the storage battery 102 in the time zone at time 5. The charge amount Bin (5) may be calculated. Here, the difference between the predicted power consumption L1 (5) and the target value d is “2”. Further, the difference between the predicted power consumption L2 (5) and the target value d is “3”. Therefore, the charge amount Bin (5) is “charge amount Bin (5) = 2”.

  Further, since the predicted power consumption L1 (8), L2 (8) of the power consumption source in the time zone at time 8 is equal to or less than the target value d, similarly, the charge amount Bin of the storage battery 102 in each time zone at time 8 (8) is calculated. As a result, in (9-3) of FIG. 9, the charge amounts Bin (5) and Bin (8) of the storage battery 102 in the time zones of time 5 and time 8 are set.

  When the charge amount Bin (t) exceeds the maximum charge amount Din per unit time of the storage battery 102, the charge amount Bin (t) is “Bin (t) = Din”. Here, since the charge amount Bin (8) is “Bin (8) = 11” and exceeds the maximum charge amount Din per unit time of the storage battery 102, the charge amount Bin (8) is “Bin (8)”. = Din = 3 [Wh].

  In the example of FIG. 9, the case where there is one predicted power consumption greater than the target value d in the time zone t has been described, but there may be a plurality of predicted power consumptions greater than the target value d.

<When there are multiple predicted power consumptions larger than the target value d>
Here, a calculation process for calculating the discharge amount Bout (t) of the storage battery 102 when there are a plurality of predicted power consumptions larger than the target value d in the time zone t will be described. Here, as an example, a case where the predicted power consumption L1 (t) and the predicted power consumption L2 (t) in the time period t are larger than the target value d will be described as an example.

  In this case, the second calculation unit 705 uses, for example, the following formula (2) to discharge the storage battery 102 for each of the predicted power consumption L1 (t) and the predicted power consumption L2 (t) that are larger than the target value d. The amount X1 (t) and the discharge amount X2 (t) can be calculated. However, Xi (t) is the discharge amount of the storage battery 102 in the time zone t for each predicted power consumption Li (t) larger than the target value d.

    Xi (t) = {Li (t) -d} * Pi (2)

  Then, the second calculation unit 705 calculates the discharge amount Bout (t) of the storage battery 102 in the time zone t by adding the calculated discharge amount X1 (t) and the discharge amount X2 (t). Also good. Thereby, the discharge amount Bout (t) of the storage battery 102 in the time zone t can be calculated in consideration of a plurality of predicted power consumptions larger than the target value d in the time zone t.

  On the other hand, when the time zone t in which there are a plurality of predicted power consumptions Li (t) larger than the target value d is not the peak time zone tp (i) of each prediction curve Li, the discharge amount Bout ( t) may be concentrated.

  FIG. 10 is an explanatory diagram showing an example of concentration of the discharge amount Bout (t) of the storage battery 102. In FIG. 10, the prediction curve La is a curve representing the predicted power consumption of the power consumption source in each time zone t of the cluster Ca. The prediction curve Lb is a curve representing the predicted power consumption of the power consumption source in each time zone t of the cluster Cb.

  Here, the peak time zone tp (a) of the prediction curve La is the time zone of time 2. The peak time zone tp (b) of the prediction curve Lb is the time zone at time 4. Further, the predicted power consumption La (t) of the prediction curve La and the predicted power consumption Lb (t) of the prediction curve Lb in the time zone at time 3 are larger than the target value d.

  That is, the time zone at time 3 in which there are a plurality of predicted power consumptions larger than the target value d is not the peak time zone of each prediction curve La, Lb. In this case, when the discharge amount Bout (3) of the storage battery 102 is obtained using the above formula (2), as shown in the graph 1010, the discharge amount Bout (3) of the storage battery 102 is at the peak time period during the time zone at time 3. It will increase as well.

  Therefore, the second calculation unit 705 uses the maximum predicted power consumption Li (t) among the plurality of predicted power consumptions larger than the target value d in the time zone t, and the discharge amount Bout of the storage battery 102 in the time zone t. (T) may be calculated. Specifically, for example, the second calculation unit 705 substitutes the maximum predicted power consumption Li (t), the target value d, and the probability Pi into the above formula (1), so that the storage battery 102 in the time zone t A discharge amount Bout (t) is calculated.

  Thereby, as shown in the graph 1020, the discharge amount Bout (3) in the time zone at time 3 in which a plurality of predicted power consumptions larger than the target value d exist can be suppressed. As a result, for example, the discharge amount of the storage battery 102 in a time zone other than the peak time zone can be reduced, and a large discharge amount of the storage battery 102 in the peak time zone can be secured.

  Further, in each prediction curve Li, when the actual power consumption of the power consumption source is below the target value d by a certain amount F in the vicinity of the peak time period tp (i) of the control target period, The probability Pi in the time zone tp (i) may be “0” or low. Thereby, the discharge amount of the storage battery 102 in the peak time zone tp (i) of the prediction curve Li can be suppressed, and the discharge effect can be enhanced by turning the storage amount of the storage battery 102 to the peak time zone of another prediction curve. .

  The vicinity of the peak time zone tp (i) is a predetermined period before the peak time zone tp (i). For example, when the peak time zone tp (i) is a time zone at time 5, the time zones at time 3 and time 4 may be set near the peak time zone tp (i). Further, the fixed amount F and the fixed time T can be arbitrarily set.

(Target value d change processing)
Next, a specific example of the changing process of the changing unit 707 that changes the target value d of the maximum power in the time zone t supplied from the commercial power source 203 will be described with reference to FIG. The target value d before the change is “d = 11”. The maximum storage capacity Ru of the storage battery 102 is “Ru = 6”.

  FIG. 11 is an explanatory diagram showing a transition example of the stored contents of the power storage amount table. In FIG. 11, the storage amount table 1100 has fields for time, control value B, and storage amount R. By setting information in each field, the storage amount information of the storage battery 102 in each time zone t is stored as a record.

  Here, the control value B represents the charge amount or discharge amount of the storage battery 102 in each time zone t. Specifically, the control value B (t) is “B (t) = Bin (t) −Bout (t)”. The storage amount R represents the storage amount R (t) of the storage battery 102 at the start time of each time slot t, that is, at the end time of the time slot (t−1).

  In (11-1) of FIG. 11, control values B (3) to B (8) for each time zone from time 3 to time 8 are set. The control values B (3) to B (8) correspond to the charge amount Bin and the discharge amount Bout in each time zone from time 3 to time 8 in the control plan table 900 shown in FIG. In addition, the storage amount R (2) of the storage battery 102 at the start time of the 3 o'clock time zone, that is, the end time of the 2 o'clock time zone is set.

  The third calculation unit 706 adds the storage amount R (t−1) of the storage battery 102 in the time zone (t−1) and the control value B (t−1) of the storage battery 102 to obtain the time zone t. The storage amount R (t) of the storage battery 102 is calculated.

  For example, the third calculation unit 706 adds the storage amount R (3) of the storage battery 102 in the time zone at time 3 and the control value B (3) of the storage battery 102 to thereby obtain the storage battery in the time zone at time 4. A storage amount R (4) of 102 is calculated. Here, the charged amount R (4) is “R (4) = R (3) + B (3) = 5.5”.

  In (11-2) of FIG. 11, the storage amounts R (4) to R (9) of the storage battery 102 in each time zone from time 4 to time 9 are set. Here, time 9 is a control end point. Further, when the storage amount R (t) exceeds the maximum storage capacity Ru of the storage battery 102, the storage amount R (t) becomes “R (t) = Ru”. For example, the storage amount R (6) of the storage battery 102 in the time zone of time 6 is “R (6) = R (5) + B (5) = 7”, which exceeds the maximum storage capacity Ru. The storage amount R (6) is “R (6) = Ru = 6”.

  The changing unit 707 determines whether or not there is a storage amount R (t) that is less than a threshold value Rl that represents a lower limit amount of the remaining storage amount of the storage battery 102 among the calculated storage amounts R (4) to R (9) of the storage battery 102. Determine whether. Here, the threshold value Rl is “Rl = 0”. In this case, the changing unit 707 determines that there is no storage amount R (t) less than the threshold value Rl among the storage amounts R (4) to R (9) of the storage battery 102.

  In addition, the changing unit 707 determines whether or not the minimum storage amount Rmin of the calculated storage amounts R (4) to R (9) of the storage battery 102 is greater than the threshold value Rh. Here, the allowable value Rd is “Rd = 1”, and the threshold value Rh is “Rh = Rl + Rd = 1”. Further, the minimum charged amount Rmin among the charged amounts R (4) to R (9) is “Rmin = R (8) = 2”.

  For this reason, the changing unit 707 determines that the charged amount Rmin is larger than the threshold value Rh. In this case, since there is a margin in the storage amount Rmin of the storage battery 102, the changing unit 707 changes the value of the target value d to a value smaller than the value. Specifically, for example, the changing unit 707 changes the value “11” of the target value d to the value “10”.

  As described above, when the storage amount Rmin of the storage battery 102 has a margin, the target value d of the maximum power supplied from the commercial power source 203 can be lowered. As a result, the discharge amount R (t) of the storage battery 102 in the time zone t can be increased, the power supply amount from the commercial power supply 203 can be suppressed, and the electricity stored in the storage battery 102 can be used efficiently. It becomes like this.

  In addition, when there is no allowance for the storage amount Rmin of the storage battery 102, the target value d of the maximum power supplied from the commercial power source 203 can be increased. Thereby, the discharge amount R (t) of the storage battery 102 in the time zone t can be reduced, and the electricity stored in the storage battery 102 can be prevented from being depleted.

  Here, the storage contents of the control plan table 900 and the storage amount table 1100 when the target value d is changed from “d = 11” to “d = 10” will be described.

  FIG. 12 is an explanatory diagram showing an example of the stored contents of the control plan table 900 when the target value is changed. FIG. 13 is an explanatory diagram showing an example of the stored contents of the power storage amount table 1100 when the target value is changed.

  As shown in FIG. 12, as a result of the target value d being changed from “11” to “10”, the discharge amount Bout (3) of the storage battery 102 in each time zone of time 3, time 4, time 6, and time 7 Bout (4), Bout (6), and Bout (7) are increased compared to the example shown in FIG. In addition, the charge amount Bin (5) of the storage battery 102 in the time zone of time 5 is reduced compared to the example shown in FIG.

  As a result, as shown in FIG. 13, the minimum charged amount Rmin among the charged amounts R (4) to R (9) of the storage battery 102 is smaller than the threshold value Rh. Specifically, the minimum storage amount R (8) among the storage amounts R (4) to R (9) is “R (8) = 0”, and the storage amount R (8) is smaller than the threshold value Rh. (Rh = 1).

(Specific example of control plan table)
Next, a specific example of the control plan table based on the stored contents of the control plan table 900 shown in FIG. 12 will be described. FIG. 14 is an explanatory diagram of a specific example of the control plan table. In FIG. 14, the control plan table 1400 shows control values in each time zone from time 3 to time 8.

  Here, the control value represents the charge amount or discharge amount of the storage battery 102 in each time zone. Here, the control value B (t) is “B (t) = Bin (t) −Bout (t)”. That is, when the control value is positive, it represents the charge amount of the storage battery 102, and when the control value is negative, it represents the discharge amount of the storage battery 102.

  According to the control plan table 1400, control of charging / discharging of the storage battery 102 with respect to the power consumption source can be supported. Specifically, by controlling the charging / discharging of the storage battery 102 in each time zone from time 3 to time 8 based on the control plan table 1400, while reducing the risk when the power consumption is unpredictable, the power load Can be suppressed.

(Control result of charging / discharging of storage battery 102)
Next, an example of a control result when charging / discharging of the storage battery 102 with respect to the power consumption source is controlled based on the control plan table 1400 illustrated in FIG. 14 will be described.

  FIG. 15 is an explanatory diagram illustrating an example of a charge / discharge control result of the storage battery 102. In FIG. 15, the prediction curve L1 is a curve representing the predicted power consumption L1 (3) to L1 (8) of the power consumption source in each time zone from time 3 to time 8. The prediction curve L2 is a curve representing the predicted power consumption L2 (3) to L2 (8) of the power consumption source in each time zone from time 3 to time 8.

  A graph 1510 represents the load power of the power consumption source in each time zone from time 3 to time 8 when charging / discharging of the storage battery 102 is not controlled. The load power represents the actual power consumption of the power consumption source or the power supplied to the power consumption source. A graph 1520 represents a control result when charging / discharging of the storage battery 102 with respect to the power consumption source is controlled based on the control plan table 1400.

  The peak time zone of the graph 1510 is a time zone of 3 o'clock. Further, the load power in the 3 o'clock time zone of the graph 1510, that is, the peak power consumption is 10 [Wh]. On the other hand, the peak time zones of the graph 1520 are the 3 o'clock and 5 o'clock time zones. Further, the control results in the time zone of 3 o'clock and 5 o'clock in the graph 1520, that is, the peak power consumption is 9 [Wh].

  In this way, by controlling charging / discharging of the storage battery 102 with respect to the power consumption source based on the control plan table 1400, the peak power consumption of the power consumption source is set to 1 as compared with the case where charging / discharging of the storage battery 102 is not controlled. [Wh] can be suppressed.

(Power control support processing procedure of power control support apparatus 101)
Next, a power control support processing procedure of the power control support apparatus 101 will be described. FIG. 16 is a flowchart illustrating an example of a power control support processing procedure of the power control support apparatus 101.

  In the flowchart of FIG. 16, first, the power control support apparatus 101 determines whether or not performance data representing the power consumption of the power consumption source has been acquired (step S1601). The actual data is actual data of a plurality of different measurement periods and actual data of the control target period.

  Here, the power control support apparatus 101 waits for acquisition of performance data (step S1601: No). If the power control support apparatus 101 acquires the actual data (step S1601: Yes), the power control support apparatus 101 executes a predicted power consumption calculation process for calculating the predicted power consumption of the power consumption source (step S1602).

  Next, the power control support apparatus 101 executes a control plan creation process for creating a control plan table for charging and discharging the storage battery 102 with respect to the power consumption source (step S1603). Then, the power control support apparatus 101 outputs the created control plan table (step S1604), and ends a series of processes according to this flowchart.

  Thereby, the control plan table | surface for controlling charging / discharging of the storage battery 102 with respect to an electric power consumption source can be output.

<Predicted power consumption calculation processing procedure>
Next, a specific processing procedure of the predicted power consumption calculation process shown in step S1602 of FIG. 16 will be described. However, a plurality of different measurement periods are denoted as “date 1 to date m”, and an arbitrary date among the dates 1 to m is denoted as “date j” (j = 1, 2,..., M).

  FIG. 17 is a flowchart illustrating an example of a specific processing procedure of predicted power consumption calculation processing. In the flowchart of FIG. 17, first, the power control support apparatus 101 specifies the peak time zone tp (j) of each date j based on the actual data of each date j (step S1701).

  Next, the power control support apparatus 101 classifies the performance data groups from date 1 to date m into clusters C1 to Cn based on the peak time zone tp (j) of each date j (step S1702). Then, the power control support apparatus 101 sets “i” of the cluster Ci to “i = 1” (step S1703), and selects the cluster Ci from the clusters C1 to Cn (step S1704).

  Next, the power control support apparatus 101 calculates the similarity S (j) between the actual measurement data of the date j included in the cluster Ci and the actual measurement data of the control target period (step S1705). Then, the power control support apparatus 101 selects performance data having a similarity equal to or higher than a threshold value from the performance data included in the cluster Ci (step S1706).

  Next, the power control support apparatus 101 calculates the predicted power consumption Li (t) of the power consumption source in each time zone t of the prediction curve Li corresponding to the cluster Ci based on the selected result data (step S1707). . The power control support apparatus 101 increments “i” of the cluster Ci (step S1708), and determines whether “i” is larger than “n” (step S1709).

  If “i” is equal to or less than “n” (step S1709: NO), the process returns to step S1704. On the other hand, when “i” becomes larger than “n” (step S1709: Yes), the power control support apparatus 101 determines that the power consumption of the power consumption source in the control target period is the predicted power consumption Li (t) of each cluster Ci. Is calculated (step S1710), and the process returns to the step of calling the predicted power consumption calculation process.

  Thereby, the predicted power consumption Li (t) of the power consumption source in the time zone t of the control target period can be calculated. In addition, the probability Pi of the prediction curve Li corresponding to the cluster Ci can be calculated.

<Control plan creation processing procedure>
Next, a specific processing procedure of the control plan creation processing shown in step S1603 of FIG. 16 will be described. However, the time zone of the control start time of the control target period is expressed as “time zone t ₀ ”. The time zone of the control end time of the control target period is expressed as “time zone t _end ”.

18 and 19 are flowcharts showing an example of a specific processing procedure of the control plan creation process. In the flowchart of FIG. 18, first, the power control support apparatus 101 sets “t” in the time zone t to “t = t ₀ ”, and sets the charge amount Bin (t) of the storage battery 102 in the time zone t to “Bin (t) = 0 ”, the discharge amount Bout (t) of the storage battery 102 in the time zone t is set to“ Bout (t) = 0 ”(step S1801).

  Next, the power control support apparatus 101 determines whether there is a prediction curve Li in which the predicted power consumption Li (t) in the time zone t is larger than the target value d (step S1802). When there is a prediction curve Li that is larger than the target value d (step S1802: Yes), the power control support apparatus 101 sets “i” of the prediction curve Li to “i = 1” (step S1803).

  Then, the power control support apparatus 101 selects a prediction curve Li from the prediction curves L1 to Ln (step S1804), and determines whether or not the predicted power consumption Li (t) is larger than the target value d (step S1804). S1805). If the predicted power consumption Li (t) is equal to or less than the target value d (step S1805: NO), the process proceeds to step S1808.

  On the other hand, when the predicted power consumption Li (t) is larger than the target value d (step S1805: Yes), the power control support apparatus 101 uses the above equation (2) to discharge the discharge amount Xi ( t) is calculated (step S1806). Then, the power control support apparatus 101 adds the discharge amount Xi (t) to the discharge amount Bout (t) of the storage battery 102 in the time zone t (step S1807).

  Next, the power control support apparatus 101 increments “i” of the prediction curve Li (step S1808), and determines whether “i” is greater than “n” (step S1809). If “i” is equal to or less than “n” (step S1809: NO), the process returns to step S1804.

  On the other hand, when “i” becomes larger than “n” (step S1809: Yes), the power control support apparatus 101 determines that the discharge amount Bout (t) of the storage battery 102 in the time zone t is per unit time of the storage battery 102. It is determined whether or not it is larger than the maximum discharge amount Dout (step S1810).

  If the discharge amount Bout (t) of the storage battery 102 is equal to or less than the maximum discharge amount Dout (step S1810: No), the process proceeds to step S1812. On the other hand, when the discharge amount Bout (t) of the storage battery 102 is larger than the maximum discharge amount Dout (step S1810: Yes), the power control support apparatus 101 sets the discharge amount Bout (t) of the storage battery 102 as the maximum discharge amount Dout ( Step S1811).

  Next, the power control support apparatus 101 sets the charge amount Bin (t) of the storage battery 102 in the time zone t to “Bin (t) = 0” (step S1812), and uses the following formula (3) to set the time zone t The control value B (t) at is calculated (step S1813).

    B (t) = Bin (t) −Bout (t) (3)

The power control support apparatus 101 registers the control value B (t) in the time zone t in the control plan table (step S1814), and determines whether the time zone t is the time zone _end (step S1815). . Here, when the time zone t is not the time zone _end (step S1815: No), the power control support apparatus 101 increments “t” of the time zone t (step S1816) and returns to step S1802.

On the other hand, when the time zone t is the time zone t _end (step S1815: Yes), the process returns to the step that called the control plan creation process. In Step S1802, when there is no prediction curve Li that is larger than the target value d (Step S1802: No), the process proceeds to Step S1901 shown in FIG.

  In the flowchart of FIG. 19, first, the power control support apparatus 101 sets the discharge power Bout (t) of the storage battery 102 in the time zone t to “Bout (t) = 0” (step S1901), and “i” of the prediction curve Li. Is set to “i = 1” (step S1902).

  And the electric power control assistance apparatus 101 selects the prediction curve Li from the prediction curves L1-Ln (step S1903), and calculates the charge amount Yi (t) of the storage battery 102 using following formula (4). (Step S1904).

    Yi (t) = d−Li (t) (4)

  Next, the power control support apparatus 101 increments “i” of the prediction curve Li (step S1905), and determines whether “i” is greater than “n” (step S1906). If “i” is equal to or less than “n” (step S1906: NO), the process returns to step S1903.

  On the other hand, when “i” becomes larger than “n” (step S1906: Yes), the power control support apparatus 101 determines the minimum charge amount Ymin (t) among the charge amounts Y1 (t) to Yn (t). Is identified (step S1907). Then, the power control support apparatus 101 sets the charge amount Bin (t) of the storage battery 102 in the time zone t as the charge amount Ymin (t) (step S1908).

  Next, the power control support apparatus 101 determines whether or not the charge amount Bin (t) of the storage battery 102 in the time zone t is larger than the maximum charge amount Din per unit time of the storage battery 102 (step S1909). Here, when the charge amount Bin (t) of the storage battery 102 is equal to or less than the maximum charge amount Din (step S1909: No), the process proceeds to step S1813 shown in FIG.

  On the other hand, when the charge amount Bin (t) of the storage battery 102 is larger than the maximum charge amount Din (step S1909: Yes), the power control support apparatus 101 sets the charge amount Bin (t) of the storage battery 102 as the maximum charge amount Din (step S1909). S1910), the process proceeds to step S1813 shown in FIG.

  As a result, a control plan is established for controlling the discharge amount Bout (t) of the storage battery 102 in the time zone t when the power consumption of the power consumption source is predicted to exceed the target value d, thereby suppressing the peak power of the power consumption source. Can do. Further, the amount of charge Bin (t) of the storage battery 102 in the time period t where the power consumption of the power consumption source is predicted not to exceed the target value d is controlled, and the storage battery 102 is discharged in preparation for discharge in other time periods. You can make a control plan that enhances the effectiveness.

(Control plan evaluation processing procedure of power control support apparatus 101)
Next, a control plan evaluation process procedure of the power control support apparatus 101 will be described. 20 and 21 are flowcharts illustrating an example of a control plan evaluation process procedure of the power control support apparatus 101.

  In the flowchart of FIG. 20, first, the power control support apparatus 101 determines whether or not the control plan table for controlling charging / discharging of the storage battery 102 and the remaining power storage capacity of the storage battery 102 at the control start time of the control target period have been acquired. (Step S2001). Here, the power control support apparatus 101 waits to acquire the control plan table and the remaining amount of power stored in the storage battery 102 (No in step S2001).

Then, when the power control support apparatus 101 acquires the control plan table and the remaining power level of the storage battery 102 (step S2001: Yes), the power control support apparatus 101 sets the remaining power level of the storage battery 102 as the stored power amount R (t) (step S2002). Next, the power control support apparatus 101 sets “t” in the time zone t to “t = t ₀ ” (step S2003), and sets the minimum storage amount Rmin of the storage battery 102 to “Rmin = R (t)” (step S2003). S2004).

Then, the power control support apparatus 101 increments “t” of the time zone t (step S2005), and determines whether or not the time zone t becomes the time zone (t _end +1) (step S2006). Here, when the time zone t is not the time zone (t _end +1) (step S2006: No), the power control support apparatus 101 uses the following formula (5) to refer to the control plan table, thereby storing the storage battery. The storage amount R (t) of 102 is calculated (step S2007).

    R (t) = R (t-1) + B (t-1) (5)

  Then, the power control support apparatus 101 determines whether or not the storage amount R (t) of the storage battery 102 is larger than the maximum storage capacity Ru of the storage battery 102 (step S2008). If the storage amount R (t) of the storage battery 102 is equal to or less than the maximum storage capacity Ru (step S2008: No), the process proceeds to step S2011.

  On the other hand, when the storage amount R (t) of the storage battery 102 is larger than the maximum storage capacity Ru (step S2008: Yes), the power control support apparatus 101 uses the following formula (6) to calculate the time period (t-1). The control value B (t−1) is corrected (step S2009).

    B (t-1) = Ru-R (t) (6)

  Then, the power control support apparatus 101 sets the storage amount R (t) of the storage battery 102 as the maximum storage capacity Ru (step S2010). Next, the power control support apparatus 101 determines whether or not the storage amount R (t) of the storage battery 102 is smaller than the minimum storage amount Rmin (step S2011).

  Here, when the charged amount R (t) of the storage battery 102 is smaller than the minimum charged amount Rmin (step S2011: Yes), the process returns to step S2004. On the other hand, when the charged amount R (t) of the storage battery 102 is not less than the minimum charged amount Rmin (step S2011: No), the process returns to step S2005.

In step S2006, when the time zone t becomes the time zone t _end (step S2006: Yes), the process proceeds to step S2101 shown in FIG.

  In the flowchart of FIG. 21, first, the power control support apparatus 101 determines whether or not the minimum storage amount Rmin of the storage battery 102 is smaller than the threshold value Rl (step S2101). Here, when the minimum storage amount Rmin of the storage battery 102 is equal to or greater than the threshold value Rl (step S2101: No), the power control support apparatus 101 determines whether the minimum storage amount Rmin of the storage battery 102 is greater than the threshold value Rh (step S2101: No). S2102).

  Here, when the minimum charged amount Rmin of the storage battery 102 is equal to or less than the threshold value Rh (step S2102: No), the power control support apparatus 101 outputs a control plan table (step S2103), and ends a series of processes according to this flowchart. To do. When the control value B (t−1) is corrected in step S2009, a corrected control plan table in which the control value B (t−1) is corrected is output.

  In step S2101, when the minimum storage amount Rmin of the storage battery 102 is smaller than the threshold value Rl (step S2101: Yes), the power control support apparatus 101 changes the value of the target value d to a value larger than the value ( In step S2104), a series of processing according to this flowchart is terminated.

  In step S2102, when the minimum storage amount Rmin of the storage battery 102 is larger than the threshold value Rh (step S2102: Yes), the power control support apparatus 101 changes the value of the target value d to a value smaller than the value ( Step S2105), a series of processing according to this flowchart is terminated.

  Thereby, when there is a margin in the storage amount Rmin of the storage battery 102, the target value d of the maximum power supplied from the commercial power source 203 can be lowered. In addition, when there is no allowance for the storage amount Rmin of the storage battery 102, the target value d of the maximum power supplied from the commercial power source 203 can be increased.

  In addition, the control value B (t−1) of the control plan table can be corrected so as not to be charged when the storage amount R (t) of the storage battery 102 exceeds the maximum storage capacity Ru. Moreover, when the target value d is changed in step S2104 or step S2105, the power control support process shown in FIG. 16 may be re-executed. Thereby, the control plan table | surface which controls charging / discharging of the storage battery 102 can be created using the target value d after a change.

  As described above, according to the power control support apparatus 101 according to the embodiment, the power consumption source in each time zone from date 1 to date m based on the peak time zone in which the power consumption of the power consumption source is maximum. Measured data representing the power consumption can be classified into clusters C1 to Cn. Thereby, it is possible to perform clustering with an emphasis on the peak time zone in which the power consumption of the power consumption source is maximized.

  Moreover, according to the power control support apparatus 101, the predicted power consumption Li (t) of the power consumption source in the time zone t of the control target period can be calculated based on the actual data included in the cluster Ci. Further, according to the power control support apparatus 101, the power consumption of the power consumption source in the control target period is transferred to the cluster Ci based on the number of the actual data included in the cluster Ci with respect to the total actual data of the dates 1 to m. The probability Pi of transition according to the corresponding prediction curve Li can be calculated.

  Further, according to the power control support apparatus 101, the similarity S (j) between the actual measurement data of the date j included in the cluster Ci and the actual measurement data of the control target period can be calculated. Accordingly, the predicted power consumption Li (t) of the power consumption source can be calculated based on the actual data having a high degree of similarity with the actual measurement data in the control target period among the actual measurement data included in the cluster Ci.

  Further, according to the power control support device 101, when the predicted power consumption Li (t) is larger than the target value d, the difference between the predicted power consumption Li (t) and the target value d is multiplied by the probability Pi, so that time The discharge amount Bout (t) of the storage battery 102 in the band t can be calculated.

  As a result, a control plan is established for controlling the discharge amount Bout (t) of the storage battery 102 in the time zone t when the power consumption of the power consumption source is predicted to exceed the target value d, thereby suppressing the peak power of the power consumption source. Can do. Further, by calculating the discharge amount Bout (t) in consideration of the probability Pi that the power consumption of the power consumption source becomes the predicted power consumption Li (t), it is possible to reduce the risk when the prediction is lost.

  Further, according to the power control support device 101, when the predicted power consumption L1 (t) to Ln (t) is equal to or less than the target value d, the predicted power consumption L1 (t) to Ln (t) and the target value d Based on the smallest difference among the differences, the charge amount Bin (t) of the storage battery 102 in the time zone t can be calculated. Thereby, the amount of charge Bin (t) of the storage battery 102 in the time zone t in which the power consumption of the power consumption source is predicted not to exceed the target value d is controlled to prepare for the discharge in other time zones. A control plan that enhances the discharge effect can be made.

  Further, according to the power control support apparatus 101, when there are a plurality of predicted power consumptions larger than the target value d in the time zone t, each predicted power consumption L1 (t) to Ln (t) is calculated by the above equation (2). The discharge amount Bout (t) of the storage battery 102 can be calculated by obtaining the maximum value of X1 (t) to Xn (t). Thereby, the discharge amount Bout (t) of the storage battery 102 in the time zone t can be suppressed. For example, it is possible to reduce the discharge amount of the storage battery 102 in a time zone other than the peak time zone, and to secure a large discharge amount of the storage battery 102 in the peak time zone.

  Further, according to the power control support device 101, when the storage amount R (t) of the storage battery 102 is less than the threshold value R1, the value of the target value d can be changed to a value larger than the value. Thereby, the target value d of the maximum power in the time zone t supplied from the commercial power source 203 can be raised, and a control plan is established so that the stored amount R (t) of the storage battery 102 does not fall below the lower limit amount in the time zone t. be able to.

  Further, according to the power control support device 101, when the storage amount R (t) of the storage battery 102 is larger than the threshold value Rh, the value of the target value d can be changed to a value smaller than the value. Thereby, the target value d of the maximum power in the time zone t supplied from the commercial power source 203 can be lowered, and a control plan that can efficiently use the electricity stored in the storage battery 102 can be made.

  Therefore, according to the power control support program, the power control support device, and the power control support method according to the present embodiment, the power load is reduced while reducing the risk when the power consumption of the power consumption source is unpredictable. It is possible to formulate a control plan that suppresses the peak.

  The power control support method described in this embodiment can be realized by executing a program prepared in advance on a computer such as a personal computer or a workstation. The power control support program is recorded on a computer-readable recording medium such as a hard disk, a flexible disk, a CD-ROM, an MO, and a DVD, and is executed by being read from the recording medium by the computer. The power control support program may be distributed via a network such as the Internet.

  The following additional notes are disclosed with respect to the embodiment described above.

(Supplementary note 1)
The predicted power consumption for each measurement period based on the power consumption of the power consumption source in the same time zone in a plurality of different measurement periods, and the measurement power consumption for each measurement period in which the power consumption of the power consumption source in the control target period becomes the predicted power consumption Get the predicted power consumption accuracy,
It is determined whether any predicted power consumption of the obtained predicted power consumption for each measurement period is greater than a target value of maximum power in the time zone supplied from a commercial power source,
When the determined predicted power consumption is larger than the target value, the storage battery that charges and discharges electricity based on the difference between the determined predicted power consumption and the target value and the accuracy of the determined predicted power consumption. Calculate the amount of discharge to the power consumption source in the time zone of the control target period,
Outputting the amount of discharge to the power consumption source in the calculated time zone,
A power control support program characterized by causing a process to be executed.

(Additional remark 2) The said process to calculate is
When the predicted power consumption for each measurement period is less than or equal to the target value, the control target of the storage battery is based on the difference between the predicted power consumption of the predicted power consumption for each measurement period and the target value. Calculating the amount of charge from the power consumption source in the time period of the period;
The output process is as follows:
The power control support program according to appendix 1, wherein a charge amount from the power consumption source in the calculated time zone is output.

(Supplementary note 3) The calculation process is as follows.
When there are a plurality of predicted power consumptions larger than the target value, the discharge amount is calculated based on the difference between the predicted power consumption and the target value and the accuracy for each of the plurality of predicted power consumptions larger than the target value. The power control program according to appendix 1 or 2, wherein a maximum discharge amount among the amounts is set as a discharge amount to the power consumption source.

(Supplementary Note 4) The calculation process is as follows.
When the predicted power consumption for each measurement period is less than or equal to the target value, the amount of charge from the power consumption source is calculated based on the smallest difference between the predicted power consumption for each measurement period and the target value. The power control program according to any one of appendices 1 to 3, wherein the power control program is calculated.

(Supplementary note 5)
Based on the remaining storage amount of the storage battery in the time period of the control target period and the calculated calculation result, the storage amount of the storage battery in the time period is calculated,
When the calculated amount of electricity stored in the storage battery is less than a first threshold value indicating the lower limit amount of the remaining amount of electricity stored in the storage battery, the value of the target value is changed to a value greater than the value, and a process is executed.
The determination process is as follows.
The power control program according to any one of appendices 1 to 4, wherein it is determined whether any one of the predicted power consumptions is greater than the changed target value after the change.

(Additional remark 6) The process which calculates the electrical storage amount of the said storage battery is as follows.
Calculating the storage amount of the storage battery in each of the plurality of time zones in the measurement period;
The process to change is
When the minimum storage amount of the storage battery in each calculated time zone is greater than a second threshold value that is greater than the first threshold value, the target value is set to a value smaller than the value. The power control program according to appendix 5, wherein the power control program is changed.

(Appendix 7)
Acquiring performance data representing the power consumption of the power consumption source for each time period of a plurality of time periods included in the measurement period for each measurement period,
Based on the time zone in which the power consumption of the power consumption source is the maximum among the plurality of time zones, classify the acquired performance data for each measurement period,
A process of calculating the predicted power consumption of the power consumption source in the time zone based on the power consumption of the power consumption source in the time zone of the performance data included in the set for each group of the classified performance data. Let it run
The determination process is as follows.
Additional notes 1 to 6, wherein one of the calculated predicted power consumptions of the power consumption source in the time period for each set is determined to be greater than the target value. The power control program according to any one of the above.

(Supplementary note 8)
Based on the number of actual data included in the set with respect to the actual data number for each measurement period, the accuracy of the predicted power consumption for each set in which the power consumption of the power consumption source in the control target period becomes the predicted power consumption Execute the process to calculate
The calculation process is as follows:
If any one of the predicted power consumptions is greater than the target value, the power based on the difference between any one of the predicted power consumptions and the target value and the calculated probability of any one of the predicted power consumptions. The power control program according to appendix 7, wherein the amount of discharge to the consumption source is calculated.

(Supplementary note 9) The predicted power consumption for each measurement period based on the power consumption of the power consumption source in the same time zone in a plurality of different measurement periods, and the power consumption of the power consumption source in the control target period is the predicted power consumption An acquisition unit that acquires the accuracy of predicted power consumption for each measurement period;
A determination unit that determines whether any one of the predicted power consumption for each of the measurement periods acquired by the acquisition unit is larger than a target value of the maximum power in the time zone supplied from a commercial power source. When,
If the predicted power consumption determined by the determination unit is larger than the target value, electricity is calculated based on the difference between the determined predicted power consumption and the target value and the accuracy of the determined predicted power consumption. A calculation unit that calculates a discharge amount to the power consumption source in the time period of the control target period of the storage battery to be charged and discharged;
An output unit that outputs a discharge amount to the power consumption source in the time period calculated by the calculation unit;
A power control support device comprising:

(Supplementary note 10)
The predicted power consumption for each measurement period based on the power consumption of the power consumption source in the same time zone in a plurality of different measurement periods, and the measurement power consumption for each measurement period in which the power consumption of the power consumption source in the control target period becomes the predicted power consumption Get the predicted power consumption accuracy,
It is determined whether any predicted power consumption of the obtained predicted power consumption for each measurement period is greater than a target value of maximum power in the time zone supplied from a commercial power source,
When the determined predicted power consumption is larger than the target value, the storage battery that charges and discharges electricity based on the difference between the determined predicted power consumption and the target value and the accuracy of the determined predicted power consumption. Calculate the amount of discharge to the power consumption source in the time zone of the control target period,
Outputting the amount of discharge to the power consumption source in the calculated time zone,
A power control support method characterized by executing processing.

DESCRIPTION OF SYMBOLS 101 Power control assistance apparatus 102 Storage battery 201 Control object apparatus 701 Acquisition part 702 Classification | category part 703 1st calculation part 704 Determination part 705 2nd calculation part 706 3rd calculation part 707 Change part 708 Output part

Claims (8)

On the computer,
The predicted power consumption for each measurement period based on the power consumption of the power consumption source in the same time zone in a plurality of different measurement periods, and the measurement power consumption for each measurement period in which the power consumption of the power consumption source in the control target period becomes the predicted power consumption Get the predicted power consumption accuracy,
It is determined whether any predicted power consumption of the obtained predicted power consumption for each measurement period is greater than a target value of maximum power in the time zone supplied from a commercial power source,
When the determined predicted power consumption is larger than the target value, the storage battery that charges and discharges electricity based on the difference between the determined predicted power consumption and the target value and the accuracy of the determined predicted power consumption. Calculate the amount of discharge to the power consumption source in the time zone of the control target period,
Outputting the amount of discharge to the power consumption source in the calculated time zone,
A power control support program characterized by causing a process to be executed. The calculation process is as follows:
When all the predicted power consumptions of the predicted power consumption for each measurement period are equal to or less than the target value, based on the difference between any one of the predicted power consumptions for each measurement period and the target value , Calculating the amount of charge from the power consumption source in the time zone of the control target period of the storage battery,
The output process is as follows:
The power control support program according to claim 1, wherein the calculated charge amount from the power consumption source in the time period is output. The calculation process is as follows:
When there are a plurality of predicted power consumptions larger than the target value, the discharge amount is calculated based on the difference between the predicted power consumption and the target value and the accuracy for each of the plurality of predicted power consumptions larger than the target value. The power control program according to claim 1 or 2, wherein a maximum discharge amount among the amounts is set as a discharge amount to the power consumption source. The calculation process is as follows:
When all the predicted power consumptions of the predicted power consumption for each measurement period are equal to or less than the target value, the power is calculated based on the smallest difference between the predicted power consumption for each measurement period and the target value. The power control program according to any one of claims 1 to 3, wherein a charge amount from a consumption source is calculated. In the computer,
Based on the remaining storage amount of the storage battery in the time period of the control target period and the calculated calculation result, the storage amount of the storage battery in the time period is calculated,
When the calculated amount of electricity stored in the storage battery is less than a first threshold value indicating the lower limit amount of the remaining amount of electricity stored in the storage battery, the value of the target value is changed to a value greater than the value, and a process is executed.
The determination process is as follows.
The power control program according to any one of claims 1 to 4, wherein one of the predicted power consumptions is determined to be greater than the changed target value after the change. The process of calculating the storage amount of the storage battery is as follows:
Calculating the storage amount of the storage battery in each of the plurality of time zones in the measurement period;
The process to change is
When the minimum storage amount of the storage battery in each calculated time zone is greater than a second threshold value that is greater than the first threshold value, the target value is set to a value smaller than the value. The power control program according to claim 5, wherein the power control program is changed. The predicted power consumption for each measurement period based on the power consumption of the power consumption source in the same time zone in a plurality of different measurement periods, and the measurement power consumption for each measurement period in which the power consumption of the power consumption source in the control target period becomes the predicted power consumption An acquisition unit for acquiring the accuracy of predicted power consumption;
A determination unit that determines whether any one of the predicted power consumption for each of the measurement periods acquired by the acquisition unit is larger than a target value of the maximum power in the time zone supplied from a commercial power source. When,
If the predicted power consumption determined by the determination unit is larger than the target value, electricity is calculated based on the difference between the determined predicted power consumption and the target value and the accuracy of the determined predicted power consumption. A calculation unit that calculates a discharge amount to the power consumption source in the time period of the control target period of the storage battery to be charged and discharged;
An output unit that outputs a discharge amount to the power consumption source in the time period calculated by the calculation unit;
A power control support device comprising: Computer
The predicted power consumption for each measurement period based on the power consumption of the power consumption source in the same time zone in a plurality of different measurement periods, and the measurement power consumption for each measurement period in which the power consumption of the power consumption source in the control target period becomes the predicted power consumption Get the predicted power consumption accuracy,
It is determined whether any predicted power consumption of the obtained predicted power consumption for each measurement period is greater than a target value of maximum power in the time zone supplied from a commercial power source,
When the determined predicted power consumption is larger than the target value, the storage battery that charges and discharges electricity based on the difference between the determined predicted power consumption and the target value and the accuracy of the determined predicted power consumption. Calculate the amount of discharge to the power consumption source in the time zone of the control target period,
Outputting the amount of discharge to the power consumption source in the calculated time zone,
A power control support method characterized by executing processing.

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