Connection Phase Determination Support System and Method

Abstract

To improve the accuracy of phase detection. [Solution] A connection phase determination support system is constructed. The system creates one or more load models from measurement data of a first hour length related to the power distribution network. Each load model consists of measurement data of a second hour length that is shorter than the first hour length. The system identifies one or more second hour length measurement data from among the multiple second hour length measurement data that constitute the first hour length measurement data of the equipment targeted for connection phase determination. Each of these one or more second hour length measurement data is a second hour length measurement data whose difference from at least one of the one or more load models satisfies a predetermined requirement. The system uses the identified one or more second hour length measurement data or the information necessary to acquire such one or more second hour length measurement data for connection phase determination.

Description

[Technical Field]

[0001] The present invention generally relates to connection phase determination, and particularly relates to technology for supporting connection phase determination. [Background Art]

[0002] In current power systems, the connection phases of transformers and photovoltaic power generation facilities (PV) are not accurately managed and are often unknown. Accordingly, the introduction of connection phase determination has been considered. As methods for connection phase determination, for example, techniques such as the PI (Phase Identification) method and the VV (Voltage Vector) method are known. Examples of the PI method are disclosed in Patent Document 1 and Patent Document 2. An example of the VV method is disclosed in Patent Document 2. [Prior Art Documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Unexamined Patent Application Publication No. 2024-130410 [Patent Document 2] Japanese Unexamined Patent Application Publication No. 2023-039562 [Summary of the Invention] [Problem to be Solved by the Invention]

[0004] In the PI method and the VV method, in connection phase determination, a correlation coefficient between reference measurement data for each connection phase and measurement data of a device to be determined is calculated, and the connection phase having the highest calculated correlation coefficient is determined as the correct phase.

[0005] The correlation coefficient is calculated for all time periods represented by the measurement data. However, the correlation is usually not the same across all time periods. For example, when phase determination is performed by segmenting the data by time period, there will be time periods with high accuracy and time periods with low accuracy. Therefore, the time period in which the correlation is high with respect to the correct phase and low with respect to other phases is the time period in which the correct phase is easiest to determine. However, because the correlation coefficient is calculated for measurement data that includes both time periods in which the correct phase is easy to determine and time periods in which it is not, the difference in the calculated correlation coefficient between connected phases may become small, leading to a decrease in the accuracy of phase determination. A decrease in the accuracy of phase determination can also occur for phase determination other than that which is based on the correlation coefficient between the measurement data and the reference measurement data for each connected phase. [Means for solving the problem]

[0006] A connection phase determination support system is constructed. This system creates one or more load models from measurement data of the first hour length related to the power distribution network. Each load model consists of measurement data of the second hour length, which is shorter than the first hour length. The system identifies one or more second hour length measurement data from among the multiple second hour length measurement data that constitute the first hour length measurement data of the equipment targeted for connection phase determination. Each of these one or more second hour length measurement data is a second hour length measurement data whose difference from at least one of the one or more load models satisfies a predetermined requirement. The system uses the identified one or more second hour length measurement data or the information necessary to acquire such one or more second hour length measurement data for connection phase determination. [Effects of the Invention]

[0007] According to the present invention, the accuracy of determining the connected phase can be increased. Other problems, configurations, and effects will be clarified by the following description of embodiments. [Brief explanation of the drawing]

[0008] [Figure 1] An example of a power distribution network according to the embodiment is shown. [Figure 2] This shows an example of the hardware configuration for a connection phase determination support system. [Figure 3] This shows an example of the functional block configuration of the connection phase determination support system. [Figure 4] This shows an example of the flow of the connection phase determination support process. [Figure 5] A schematic example of load model creation is shown below. [Figure 6] An example of feature identification is schematically shown. [Modes for carrying out the invention]

[0009] In the following description, "interface device" may refer to one or more interface devices. These one or more interface devices may be one or more I / O (Input / Output) interface devices and one or more communication interface devices. An I / O (Input / Output) interface device is an interface device to at least one of the following: an I / O device and a remote display computer. The I / O interface device to the display computer may be a communication interface device. The at least one I / O device may be either a user interface device, such as an input device like a keyboard and a pointing device, or an output device like a display device. The one or more communication interface devices may be one or more identical communication interface devices (e.g., one or more NICs (Network Interface Cards)) or two or more different communication interface devices (e.g., a NIC and an HBA (Host Bus Adapter)).

[0010] Furthermore, in the following explanation, "memory" refers to one or more memory devices, which are typically main memory devices. At least one memory device in memory may be a volatile memory device or a non-volatile memory device.

[0011] Furthermore, in the following explanation, "persistent storage device" refers to one or more persistent storage devices. Persistent storage devices are typically non-volatile storage devices (e.g., auxiliary storage devices), specifically, for example, HDDs (Hard Disk Drives) or SSDs (Solid State Drives).

[0012] Furthermore, in the following explanation, "storage device" may refer to at least memory, including both memory and persistent storage.

[0013] Furthermore, in the following explanation, "processor" refers to one or more processor devices. At least one processor device is typically a microprocessor device such as a CPU (Central Processing Unit), but may be other types of processor devices such as a GPU (Graphics Processing Unit). At least one processor device may be single-core or multi-core. At least one processor device may be a processor core. At least one processor device may be a broader processor device such as a hardware circuit that performs some or all of the processing (e.g., an FPGA (Field-Programmable Gate Array) or ASIC (Application Specific Integrated Circuit)).

[0014] Furthermore, in the following description, functions may be described using the expression "yyy unit". A function may be implemented by one or more computer programs executed by a processor, may be implemented by one or more hardware circuits (e.g., FPGA or ASIC), or may be implemented by a combination thereof. When a function is implemented by a program executed by a processor, predetermined processing is performed while appropriately using a storage device and / or an interface device, etc., and thus the function may be at least a part of the processor. Processing described with a function as the subject may be processing performed by a processor or an apparatus including the processor. The program may be installed from a program source. The program source may be, for example, a program distribution computer or a computer-readable recording medium (e.g., a non-transitory recording medium). The description of each function is an example, and a plurality of functions may be combined into one function, or one function may be divided into a plurality of functions.

[0015] Furthermore, in the following description, a common reference numeral will be used when elements of the same type are described without distinction, and reference numerals may be used when elements of the same type are described with distinction.

[0016] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0017] FIG. 1 shows an example of a part of a power distribution network according to the embodiment.

[0018] The power distribution network according to the embodiment includes a substation 102 that generates three-phase high-voltage (e.g., 6.6 kV) alternating-current power. For example, the distribution system is a three-phase three-wire system, and one end of each of three high-voltage distribution lines is connected to the substation 102. The three-phase high-voltage alternating-current power generated at the substation 102 is transmitted through three high-voltage distribution lines 104. In the following, when distinguishing the three high-voltage distribution lines 104 from each other, they are referred to as A line, B line, and C line, respectively.

[0019] A switch with built-in sensor 106 is installed in the middle of the high-voltage distribution line 104. The line current Ia of the A-phase line, the line current Ib of the B-phase line, and the line current Ic of the C-phase line are each measured at fixed time intervals (for example, every 30 minutes) by the switch with built-in sensor 106. Hereinafter, when the line currents Ia, Ib, and Ic are collectively referred to, the notation of line current Ix (x∈{a,b,c}) is used. The switch with built-in sensor 106 is an example of a switch, and it does not necessarily have to have a built-in sensor.

[0020] In a distribution network, a plurality of switches with built-in sensors 106 are provided. Therefore, one or more switch sections exist in the distribution network. A "switch section" is a section from a first switch with built-in sensor 106 to a second switch with built-in sensor 106. The second switch with built-in sensor 106 may be the next switch with built-in sensor 106 after the first switch with built-in sensor 106, or may be a switch with built-in sensor 106 that is separated from the first switch with built-in sensor 106 by one or more other switches with built-in sensors 106. In the example shown in Fig. 1, the section from the switch with built-in sensor 106A to the next switch with built-in sensor 106B is a switch section, and three pole-mounted transformers 108A to 108C are provided in one switch section.

[0021] For the high-voltage distribution line 104, the primary side of each pole-mounted transformer 108 provided on a utility pole is connected to a plurality of mutually different positions on the downstream side in the AC power transmission direction from the installation position of the switch with built-in sensor 106, respectively. Since there are three high-voltage distribution lines 104, there are three possible combinations of the high-voltage distribution lines 104 to which the pole-mounted transformer 108 is connected, that is, three possible connection phases. Hereinafter, the possible connection phases of the pole-mounted transformer 108 can be referred to as AB phase, BC phase, and CA phase, respectively.

[0022] Multiple low-voltage distribution lines 110 are connected to the secondary side of each pole-mounted transformer 108, and the single-phase, low-voltage (e.g., 105V) AC power converted by the pole-mounted transformer 108 is transmitted through the multiple low-voltage distribution lines 110. At multiple locations close to each individual customer 10, service drops corresponding to each customer 10 are connected to the low-voltage distribution lines 110. Single-phase, low-voltage AC power is supplied to each customer 10 via the low-voltage distribution lines 110 and service drops. Smart meters 116, which are power meters with communication functions, are installed at least some of the customers 10. The amount of electricity consumed at customers with smart meters 116 is measured periodically (e.g., every 30 minutes) by the smart meters 116, and the measurement results are input to the connection phase determination support system either directly via a communication line or via a power distribution company, etc. In the example shown in Figure 1, smart meters 116A to 116C are installed for customers 10A to 10C that are under the control of pole-mounted transformers 108A to 108C.

[0023] Figure 2 shows an example of the hardware configuration of the connection phase determination support system 200.

[0024] The connection phase determination support system 200 includes an interface device 201, a storage device 202, and a processor 203 connected thereto. The connection phase determination support system 200 may also include an input / output device 204 connected to the interface device 201. The connection phase determination support system 200 may be a physical computer system (e.g., one or more physical computers) having such hardware, or a logical computer system (e.g., a cloud computing system) implemented on a physical computer system (e.g., a cloud infrastructure). The input / output device 204 may be a user interface device such as a keyboard or display, or an information processing terminal (e.g., a client device) equipped with a user interface device and connected via a communication network. The connection phase determination support system 200 may also be a server.

[0025] Figure 3 shows an example of the functional block configuration of the connection phase determination support system 200.

[0026] The connection phase determination support system 200 includes SM (smart meter) power consumption data 301, switch phase current data 302, load model creation unit 303, feature identification unit 304, connection phase determination unit 305, and output unit 306. In this embodiment, the connection phase determination support system 200 has these elements, but as shown in the dashed box, it may be a system that has at least the load model creation unit 303 and the feature identification unit 304. The load model creation unit 303, feature identification unit 304, connection phase determination unit 305, and output unit 306 may be realized by the processor 203 executing a computer program stored in the storage device 202.

[0027] The load model creation unit 303 creates one or more load models from measurement data for a first hour length related to the power distribution network. Each of the one or more load models is based on measurement data for a second hour length, which is shorter than the first hour length.

[0028] The "measured data" referred to here is time-series data of the measured values. The "measured value" depends on the method used for determining the connection phase by the connection phase determination unit 305. For example, in this embodiment, the connection phase determination is performed according to the PI method, and therefore the "measured value" is the power consumption. If the connection phase determination is performed according to another method, such as the VV method, the "measured value" is the voltage (a vector such as the amplitude and phase angle of the voltage).

[0029] In this embodiment, the first time length is one year and the second time length is one day. However, these are just examples, and the first and second time lengths can be any length of time. For example, the user may specify the time length for at least one of the first and second time lengths using the input / output device 204, and data representing the specified time length may be recorded in the storage device 202. A load model may be created based on the first and second time lengths represented by the data recorded in the storage device 202.

[0030] The feature identification unit 304 identifies one or more second-hour measurement data from among a plurality of second-hour measurement data that constitute the first-hour measurement data of the equipment targeted for connection phase determination. Each of these one or more second-hour measurement data is a second-hour measurement data whose difference from one or more load models created by the load model creation unit 303 satisfies predetermined requirements. In other words, second-hour measurement data whose difference from a load model satisfies predetermined requirements is characteristic data that can correspond to data representing characteristic components in the switchgear section. An example of the "equipment targeted for connection phase determination" is any of the pole-mounted transformers 108.

[0031] The connection phase determination unit 305 performs connection phase determination based on the correlation coefficient between the measured data and the reference measured data for each connection phase. The "measured data" and "reference measured data for each connection phase" referred to here differ depending on the method adopted for connection phase determination. In this embodiment, as described above, the PI method is adopted, so the "measured data" is time-series data of power consumption, and the "reference measured data for each connection phase" is time-series data of current for each connection phase. The feature identification unit 304 inputs the above-described one or more second-time length measurements (characteristic data) or information necessary to acquire said one or more second-time length measurements (in this case, information representing the time period corresponding to the measured data) to the connection phase determination unit 305 and causes it to perform connection phase determination. Since such characteristic data is used for connection phase determination, an improvement in the accuracy of connection phase determination is expected. As one modification, the connection phase determination support system 200 may have a switching determination unit 351, and the switching determination unit 351 may be provided inside (or outside) the connection phase determination unit 305. The switching determination unit 351 will be described later.

[0032] The connection phase determination unit 305 stores data representing the result of the connection phase determination in the storage device 202 and outputs the data to the output unit 306. The output unit 306 outputs the data representing the result of the connection phase determination via the interface device 201. For example, the data may be transmitted to the input / output device 204, and the input / output device 204 may display the result of the connection phase determination represented by the data.

[0033] The SM power consumption data 301 is stored in the storage device 202 and includes time-series data of power consumption measured by the smart meter 116. Specifically, for example, the SM power consumption data 301 includes, for each pole-mounted transformer 108, the ID of the pole-mounted transformer 108, and for each of the one or more smart meters 116 under the control of the pole-mounted transformer 108, the ID of the smart meter 116 and time-series data of power consumption measured by the smart meter 116. The SM data of the pole-mounted transformer 108 (time-series data of power consumption from the smart meter 116) is used to create the load model. The SM power consumption data 301 may include, for each pole-mounted transformer 108, data relating to the location of the pole-mounted transformer 108, for example, the IDs of the sensor-integrated switches 106 at both ends of the switch section to which the pole-mounted transformer 108 belongs, and data representing the ID of the sensor-integrated switch 106 closest to the pole-mounted transformer 108. The SM energy consumption data 301 may be data constructed by, for example, the interface device 201 receiving data measured by each smart meter 116, and the interface device 201 storing the received data in the storage device 202. The SM energy consumption data 301 may be, for example, a database.

[0034] The switch phase current data 302 is stored in the storage device 202 and includes time-series data of the current for each connected phase measured by the sensor-integrated switch 106. Specifically, for example, the switch phase current data 302 includes, for each sensor-integrated switch 106, the ID of the sensor-integrated switch 106 and the time-series data of the current measured for each connected phase by the sensor-integrated switch 106. The "reference measurement data for each connected phase" used in the connection phase determination unit 305 for connection phase determination is the time-series data of the current for each connected phase included in the switch phase current data 302. Note that the switch phase current data 302 may be data constructed by, for example, the interface device 201 receiving input of data measured by each sensor-integrated switch 106, and the data received by the interface device 201 being stored in the storage device 202. The switch phase current data 302 may be, for example, a database.

[0035] Figure 4 shows an example of the flow of the connection phase determination support process. Figure 5 schematically shows an example of load model creation. Figure 6 schematically shows an example of feature identification. The connection phase determination support process will be explained below using Figures 4 to 6.

[0036] Assume that the pole-mounted transformer 108 targeted for connection phase determination is pole-mounted transformer 108A. The load model creation unit 303 obtains one year's worth of SM data from SM power consumption data 301 for smart meters 116 under the control of pole-mounted transformers 108 in the vicinity of pole-mounted transformer 108A, and creates a load model 503, which is one day's worth of SM data, from the obtained one year's worth of SM data (S401).

[0037] Here, "neighboring" in "neighboring pole-mounted transformers 108 of pole-mounted transformer 108A" can be defined as a range starting from pole-mounted transformer 108A (an example of the target equipment). An example of "neighboring" is one or more pole-mounted transformers 108 other than pole-mounted transformer 108A, which are connected to the switchgear space to which pole-mounted transformer 108A is connected. By defining neighboring as the same switchgear section, the dominant component in the switchgear section can be identified in the pre-processing of connection phase determination. Here, all pole-mounted transformers 108B and 108C other than pole-mounted transformer 108A in the switchgear space are taken as examples. The load model creation unit 303 refers to the SM energy data 301 to identify the other pole-mounted transformers 108B and 108C connected to the switchgear space to which pole-mounted transformer 108A is connected, and obtains one year's worth of SM data 501B corresponding to pole-mounted transformer 108B and one year's worth of SM data 501C corresponding to pole-mounted transformer 108C from the SM energy data 301, as shown in Figure 5. For each of pole-mounted transformers 108B and 108C, the load model creation unit 303 divides the one year's worth of SM data into two or more one-day worth of SM data 502. As a result, the one year's worth of SM data 501B is divided into one-day worth of SM data 502B1, 502B2, ... and the one year's worth of SM data 501C is divided into one-day worth of SM data 502C1, 502C2, ... The load model creation unit 303 creates one or more load models 503 based on multiple daily SM data 502 for pole-mounted transformers 108B and 108C. For example, one load model 503 may be created by averaging or summing all daily SM data 502. Alternatively, one load model 503 may be created for each of the pole-mounted transformers 108B and 108C, or multiple load models 503 may be created according to other considerations.Furthermore, the one year's worth of SM data 501 acquired for the creation of the load model 503 may include the one year's worth of SM data 501 of the pole-mounted transformer 108A that is the target of the determination. However, since the one year's worth of SM data 501 of the pole-mounted transformer 108A is not used in the creation of the load model 503, the component of the pole-mounted transformer 108A is excluded from the load model 503. Therefore, the created load model 503 is expected to be a load model 503 that contributes to accurately identifying characteristic data in the subsequent feature identification stage.

[0038] As shown in Figure 6, the feature identification unit 304 obtains one year's worth of SM data 501A from the SM energy data 301 for all smart meters 116 under the pole-mounted transformer 108A, and divides the SM data 501A into multiple daily SM data 502A1, 502A2, ... (S402). The feature identification unit 304 compares each daily SM data 502A with one or more load models 503 created in S401 (S403). Based on the comparison results in S403, the feature identification unit 304 identifies one or more characteristic data 600 or the time period for each of them (S404), and outputs the identified data 600 or time period to the connection phase determination unit 305 (S405). The characteristic data 600 is a daily SM data 502A whose difference with one or more load models 503 satisfies a predetermined requirement. The time period for characteristic data 600 corresponds to one day of SM data 502A, which is characteristic data 600 (i.e., any day of the year).

[0039] "One or more load models 503" in "a day's worth of SM data 502A in which the difference with one or more load models 503 satisfies the predetermined requirements" may be at least one of the one or more load models 503, or it may be one load model 503 obtained based on the average or sum of one or more load models 503. The "difference" may be obtained by spectral analysis in the frequency domain or correlation analysis in the time domain. "The difference satisfies the predetermined requirements" may mean that the difference with one load model 503 is above a certain degree, or that the statistical value (e.g., the average) of the difference with each load model 503 is above a certain degree, or that the difference is the largest. As a result, for example, a day's worth of SM data 502A with different waveform trends is identified as characteristic data 600.

[0040] Whether the characteristic data 600 or the time period is output to the connection phase determination unit 305 may depend on the specifications of the connection phase determination unit 305. For example, if the connection phase determination unit 305 is specified to acquire data using the time period as the key, then the time period may be output to the connection phase determination unit 305.

[0041] Although one embodiment of the present invention has been described above, this is merely an example for the purpose of explaining the present invention and is not intended to limit the scope of the present invention to this embodiment. The present invention can be carried out in various other forms.

[0042] For example, the "measurement data" used to create the load model 503 is, in this embodiment, power consumption data measured by the smart meter 116 located under each pole-mounted transformer 108. However, the present invention is not limited to such data, and other data may be used. For example, the measurement data used to create the load model 503, i.e., the first hourly length (e.g., one year's worth) of measurement data related to the power distribution network, may be replaced with or in addition to the first hourly length measurement data of pole-mounted transformers 108B and 108C (examples of some or all equipment other than the target equipment) connected to the switchgear space to which pole-mounted transformer 108A (an example of the target equipment) is connected, and may be at least one of the following: first hourly length measurement data obtained from smart meters 116 of customers that meet the requirements of large-scale customers (customers whose capacity is greater than the sum of the capacities of all nearby pole-mounted transformers 108); first hourly length measurement data of discharge resource equipment (e.g., renewable energy power generation equipment (e.g., PV), or storage batteries); or first hourly length measurement data obtained by NILM (Non-Intrusive Load Monitoring). For each switchgear section, the load of the capacity that is considered dominant in that switchgear section should be modeled as the load model 503. Specifically, for example, if a large-scale consumer is connected to the switchgear section, it is expected that creating the load model 503 using the power consumption measurement data of the large-scale consumer will be more effective in improving accuracy.

[0043] Furthermore, the switching determination unit 351 may calculate an unbalance index indicating the degree to which the amount of power used in the connection phase determined by the connection phase determination unit 305 (the connection phase to which the pole-mounted transformer 108A connected to the high-voltage distribution line 104 is estimated to be currently connected) for the pole-mounted transformer 108A is unbalanced, and an unbalance index when connected to a different connection phase. The switching determination unit 351 may compare the calculated unbalance indices and determine whether the unbalance index will improve if the connection phase is changed from the determined connection phase to any other connection phase. If the result of this determination is true, the switching determination unit 351 may decide to change the connection phase of the pole-mounted transformer 108A to a connection phase different from the connection phase to which it is currently determined, and the output unit 306 may propose the determined different connection phase to the user. The switching determination unit 351 may be a function included in the connection phase determination unit 305, or it may be a function that exists outside of the connection phase determination unit 305.

[0044] Furthermore, if data indicating that the determination result by the connection phase determination unit 305 was incorrect, or data indicating that the connection phase switching was not performed correctly, the connection phase determination support process (load model creation and feature identification) shown in Figure 4 may be executed again.

[0045] Furthermore, the connection phase determination unit 305 performs connection phase determination based on the correlation coefficient between the measurement data and the reference measurement data for each connection phase. However, connection phase determination may be performed using a method other than the correlation coefficient. Any known method may be adopted for connection phase determination using the measurement data and the reference measurement data for each connection phase. [Explanation of Symbols]

[0046] 200: Connection Phase Determination Support System

Claims

1. It includes a load model creation unit and a feature identification unit, The load model creation unit creates one or more load models from the measurement data for the first hour length related to the power distribution network. Each of the aforementioned one or more load models is measurement data for a second time length that is shorter than the first time length. The feature identification unit identifies one or more measurement data points for the second time length from among a plurality of measurement data points for the second time length that constitute the measurement data for the first time length of the device targeted for connection phase determination. Each of the one or more second-hour measurement data is a second-hour measurement data whose difference from the one or more load models satisfies the predetermined requirements. The feature identification unit inputs the identified measurement data for one or more second time lengths or the information necessary to acquire such measurement data for one or more second time lengths into the connection phase determination unit, which performs connection phase determination using the measurement data and reference measurement data for each connection phase, and causes it to perform connection phase determination. Connection phase determination support system.

2. The measurement data for the first hour duration relating to the power distribution network is the measurement data for the first hour duration of one or more devices, which are some or all of the devices other than the target device, connected to the switchgear space to which the target device is connected. The connection phase determination support system according to claim 1.

3. The load model creation unit divides the measurement data for the first hour of each of the one or more devices into two or more measurement data for the second hour, and creates one or more load models based on the measurement data for the multiple second hour lengths of the one or more devices. The connection phase determination support system according to claim 2.

4. The measurement data for the first hour duration related to the distribution network is at least one of the following: measurement data for the first hour duration obtained from smart meters of customers that meet the requirements of large-scale customers; measurement data for the first hour duration obtained from discharge resource equipment; and measurement data for the first hour duration obtained by NILM (Non-Intrusive Load Monitoring). The connection phase determination support system according to claim 1.

5. The aforementioned connection phase determination unit, The connection phase determination support system according to claim 1, further comprising:

6. It further includes a switching determination unit, The switching determination unit is, The unit determines whether there is a different connecting phase that is expected to improve the unbalance index compared to the connecting phase determined by the connecting phase determination unit. If there are different connection phases, the connection phase determination unit will propose a change of connection phase from the determined connection phase to the different connection phase. The connection phase determination support system according to claim 5.

7. At least one of the first time length and the second time length is a time length specified by the user. The connection phase determination support system according to claim 1.

8. The aforementioned equipment is a transformer connected to the power distribution network, The measurement data for the first hour of the aforementioned target equipment is data measured by smart meters of customers, which are connected to the aforementioned transformers as the target equipment. The reference measurement data for each connected phase is the measurement data of at least one switch at one end and the other end of the switch section. The connection phase determination support system according to claim 2.

9. From the first hour of measurement data related to the power distribution network, one or more load models are created. Each of the aforementioned one or more load models is measurement data for a second time length that is shorter than the first time length. From among the multiple measurement data points for the second time length that constitute the first time length measurement data of the device targeted for connection phase determination, one or more measurement data points for the second time length are identified. Each of the one or more second-hour measurement data is a second-hour measurement data whose difference from the one or more load models satisfies the predetermined requirements. The connection phase determination, which is performed using measurement data and reference measurement data for each connection phase, utilizes the one or more specified second time-length measurement data or the information necessary to acquire said one or more second time-length measurement data. A computer-assisted method for determining the connection phase.

10. From the first hour of measurement data related to the power distribution network, one or more load models are created. Each of the aforementioned one or more load models is measurement data for a second time length that is shorter than the first time length. From among the multiple measurement data points for the second time length that constitute the first time length measurement data of the device targeted for connection phase determination, one or more measurement data points for the second time length are identified. Each of the one or more second-hour measurement data is a second-hour measurement data whose difference from the one or more load models satisfies the predetermined requirements. The connection phase determination, which is performed using measurement data and reference measurement data for each connection phase, utilizes the one or more specified second time-length measurement data or the information necessary to acquire said one or more second time-length measurement data. A computer program that causes a computer to perform a task.

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