Power transmission line management device, power transmission line temperature estimation method, and power transmission line temperature estimation program

Abstract

This power transmission line management device comprises: a first acquiring part that acquires weather data that indicates air temperature, wind speed, and amount of sunshine; a second acquiring part that acquires precipitation data that indicates a precipitation amount; and an estimating part that estimates the temperature of the power transmission line on the basis of the weather data acquired by the first acquiring part, the precipitation data acquired by the second acquiring part, and a value of the current flowing through a power transmission line.

Description

[Technical Field]

[0001] The present disclosure relates to a power transmission line management device, a power transmission line temperature estimation method, and a power transmission line temperature estimation program. This application claims priority based on Japanese Patent Application No. 2022-151072, filed on September 22, 2022, the disclosure of which is incorporated herein in its entirety. [Background technology]

[0002] Patent Document 1 (JP 2009-65796 A) discloses the following dynamic current capacity determination device: That is, the dynamic current capacity determination device includes an information processing unit having a data input unit for inputting data and a data output unit for outputting data and performing information processing, means for the information processing unit to input weather condition data including temperature, wind speed, and solar radiation at a plurality of weather observation points along a transmission line route on which an overhead transmission line is installed from the data input unit, means for the information processing unit to calculate the current capacity for each of the weather observation points by applying the values of the weather condition data input for each of the weather observation points to a formula for calculating the current capacity of the overhead transmission line using the values of the weather conditions including the temperature, wind speed, and solar radiation as variables, and means for the information processing unit to output the minimum value of the calculated current capacities for each of the weather observation points from the data output unit as the current capacity of the overhead transmission line. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2009-65796 [Non-patent literature]

[0004] [Non-Patent Document 1] "JCS Bare Wire Allowable Current Calculation Standard JCS0374:2003", Japan Electric Wire & Cable Makers' Association, July 2003, pp.1-10 Summary of the Invention

[0005] The power transmission line management device of the present disclosure includes a first acquisition unit that acquires weather data indicating temperature, wind speed, and solar radiation, a second acquisition unit that acquires precipitation data indicating precipitation, and an estimation unit that estimates the temperature of the power transmission line based on the weather data acquired by the first acquisition unit, the precipitation data acquired by the second acquisition unit, and the value of the current flowing through the power transmission line.

[0006] One aspect of the present disclosure can be realized not only as a power transmission line management device equipped with such a characteristic processing unit, but also as a semiconductor integrated circuit that realizes part or all of the power transmission line management device, or as a system that includes the power transmission line management device. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram illustrating a configuration of a power transmission line management system according to an embodiment of the present disclosure. [Figure 2] FIG. 2 is a diagram illustrating an application example of a power transmission line management system according to an embodiment of the present disclosure. [Figure 3] FIG. 3 is a diagram illustrating a configuration of a power transmission line management device according to an embodiment of the present disclosure. [Figure 4] FIG. 4 is a diagram illustrating an example of an actual temperature calculated value calculated by a calculation unit in the power transmission line management device according to the embodiment of the present disclosure. [Figure 5] FIG. 5 is a flowchart illustrating an example of an operation procedure when the power transmission line management device according to the embodiment of the present disclosure estimates the temperature of the power transmission line. [Figure 6] FIG. 6 is a flowchart defining another example of an operation procedure when the power transmission line management device according to the embodiment of the present disclosure estimates the temperature of the power transmission line. DETAILED DESCRIPTION OF THE INVENTION

[0008] Conventionally, a technique has been proposed for dynamically determining the transmission capacity of a transmission line based on weather conditions and the temperature of the transmission line.

[0009] [Problem to be solved by this disclosure] There is a need for a technology that can estimate the temperature of a power transmission line more accurately than the technology described in Patent Document 1.

[0010] The present disclosure has been made to solve the above-mentioned problems, and its purpose is to provide a power transmission line management device, a power transmission line temperature estimation method, and a power transmission line temperature estimation program that can more accurately estimate the temperature of a power transmission line.

[0011] [Effects of this disclosure] According to the present disclosure, the temperature of a power transmission line can be estimated more accurately.

[0012] [Description of the embodiments of the present disclosure] First, the contents of the embodiments of the present disclosure will be listed and described.

[0013] (1) A power transmission line management device according to an embodiment of the present disclosure includes a first acquisition unit that acquires meteorological data indicating temperature, wind speed, and solar radiation; a second acquisition unit that acquires precipitation data indicating precipitation; and an estimation unit that estimates the temperature of the power transmission line based on the meteorological data acquired by the first acquisition unit, the precipitation data acquired by the second acquisition unit, and the value of the current flowing through the power transmission line.

[0014] In this way, by estimating the temperature of the power line based on the amount of precipitation in addition to the air temperature, wind speed, amount of solar radiation, and the value of the current flowing through the power line, the temperature of the power line can be estimated taking into account the cooling effect of precipitation on the power line, thereby enabling more accurate estimation of the temperature of the power line.

[0015] (2) In the above (1), the power transmission line management device may further include a third acquisition unit that acquires a first temperature calculation value, which is a calculation value of the temperature calculated based on the weather data and the value of the current; a fourth acquisition unit that acquires a measurement result of the temperature; and a difference calculation unit that calculates a first difference, which is a difference between the first temperature calculation value at the first time acquired by the third acquisition unit and the measurement result of the temperature at the first time acquired by the fourth acquisition unit, and the estimation unit may estimate the temperature at the first target time based on the weather data at a first target time different from the first time acquired by the first acquisition unit, the precipitation data at the first target time acquired by the second acquisition unit, the first temperature calculation value at the first target time acquired by the third acquisition unit, and the first difference calculated by the difference calculation unit.

[0016] With this configuration, the temperature of the power transmission line can be estimated based on a first temperature calculation value calculated based on weather data and current values according to conventional technology and a first difference that indicates the effect of precipitation on the temperature of the power transmission line, so that the temperature of the power transmission line can be accurately estimated with simple processing using existing technology.

[0017] (3) In the above (2), the power transmission line management device may further include a fifth acquisition unit that acquires current data that is a measurement result of the current, and a creation unit that creates a learning model for estimating an amount of temperature decrease of the power transmission line due to precipitation using the weather data, the precipitation data, the first difference, and the current data acquired by the fifth acquisition unit, and the estimation unit may acquire a first estimated value that is an estimate of the amount of temperature decrease at the first target time using the weather data at the first target time, the precipitation data at the first target time, the value of the current at the first target time, and the learning model, and the estimation unit may estimate the temperature at the first target time based on the acquired first estimated value and the first calculated temperature value at the first target time.

[0018] With this configuration, the temperature of the power transmission line can be estimated based on an estimated value indicating the amount of temperature drop of the power transmission line due to precipitation at the first target time, obtained using the learning model, and the first temperature calculation value.Therefore, for example, by adding the estimated value to the first temperature calculation value, the temperature of the power transmission line can be estimated more accurately with simple processing.

[0019] (4) In the above (3), the difference calculation unit may further calculate a second difference which is the difference between the first temperature calculation value at a second time when precipitation has stopped, acquired by the third acquisition unit, and the temperature measurement result at the second time, acquired by the fourth acquisition unit, and the estimation unit may estimate the temperature further based on the second difference calculated by the difference calculation unit.

[0020] With this configuration, in addition to the cooling effect of precipitation on the first power transmission line, the temperature of the first power transmission line can be estimated more accurately by taking into account the influence of factors other than precipitation, such as individual differences in the first power transmission line, on the temperature of the first power transmission line.

[0021] (5) In the above (3) or (4), the third acquisition unit may further acquire a second temperature calculation value, which is a calculation value of the temperature of the other transmission line, calculated based on the weather data and the value of the current flowing through the other transmission line, and the estimation unit may acquire a second estimate value, which is an estimate of the amount of temperature drop at the second target time, using the weather data at the second target time, the precipitation data at the second target time, the value of the current flowing through the other transmission line at the second target time, and the learning model, and the estimation unit may further estimate the temperature of the other transmission line at the second target time based on the second temperature calculation value at the second target time acquired by the third acquisition unit and the second estimate value.

[0022] With this configuration, the temperature of transmission lines other than the first transmission line can be accurately estimated with simple processing, so that, for example, the future temperature of transmission lines other than the first transmission line can be accurately predicted with simple processing.

[0023] (6) The power line temperature estimation method disclosed herein is a power line temperature estimation method in a power line management device, and includes the steps of acquiring meteorological data indicating air temperature, wind speed, and solar radiation, acquiring precipitation data indicating precipitation, and estimating the temperature of the power line based on the acquired meteorological data, the acquired precipitation data, and the value of the current flowing through the power line.

[0024] In this way, by using a method for estimating the temperature of a power line based on the amount of precipitation in addition to the values of air temperature, wind speed, solar radiation, and the current flowing through the power line, the temperature of the power line can be estimated taking into account the cooling effect of precipitation on the power line, thereby enabling a more accurate estimation of the temperature of the power line.

[0025] (7) The power transmission line temperature estimation program disclosed herein is a power transmission line temperature estimation program used in a power transmission line management device, and is a program for causing a computer to function as a first acquisition unit that acquires meteorological data indicating air temperature, wind speed, and solar radiation, a second acquisition unit that acquires precipitation data indicating precipitation, and an estimation unit that estimates the temperature of the power transmission line based on the meteorological data acquired by the first acquisition unit, the precipitation data acquired by the second acquisition unit, and the value of the current flowing through the power transmission line.

[0026] In this way, by estimating the temperature of the power line based on the amount of precipitation in addition to the air temperature, wind speed, amount of solar radiation, and the value of the current flowing through the power line, the temperature of the power line can be estimated taking into account the cooling effect of precipitation on the power line, thereby enabling more accurate estimation of the temperature of the power line.

[0027] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In the drawings, identical or corresponding parts are designated by the same reference numerals, and their description will not be repeated. Furthermore, at least some of the embodiments described below may be combined in any manner.

[0028] [Configuration and basic operation] <Power transmission line management system> FIG. 1 is a diagram illustrating a configuration of a power transmission line management system according to an embodiment of the present disclosure.

[0029] Referring to FIG. 1, the power transmission line management system 401 includes contact units 101A, 101B, and 101C, contact units 102A, 102B, and 102C, collection units 201 and 202, and a power transmission line management device 301.

[0030] Contact unit 101A includes current sensor 111A, temperature sensor 121A, and forwarding device 151A. Contact unit 101B includes current sensor 111B, temperature sensor 121B, and forwarding device 151B. Contact unit 101C includes current sensor 111C, temperature sensor 121C, and forwarding device 151C. Hereinafter, each of contact units 101A, 101B, and 101C will also be referred to as contact unit 101, each of current sensors 111A, 111B, and 111C will also be referred to as current sensor 111, each of temperature sensors 121A, 121B, and 121C will also be referred to as temperature sensor 121, and each of forwarding devices 151A, 151B, and 151C will also be referred to as forwarding device 151.

[0031] The contact unit 102A includes a current sensor 112A and a forwarding device 152A. The contact unit 102B includes a current sensor 112B and a forwarding device 152B. The contact unit 102C includes a current sensor 112C and a forwarding device 152C. Hereinafter, each of the contact units 102A, 102B, and 102C will also be referred to as a contact unit 102, each of the current sensors 112A, 112B, and 112C will also be referred to as a current sensor 112, and each of the forwarding devices 152A, 152B, and 152C will also be referred to as a forwarding device 152.

[0032] The collection unit 201 includes a weather sensor 211 and a collection device 251. The collection unit 202 includes a weather sensor 212 and a collection device 252.

[0033] In the following description, it is assumed that the IDs of the transfer devices 151A, 151B, 151C, 152A, 152B, and 152C are ID_1A, ID_1B, ID_1C, ID_2A, ID_2B, and ID_2C, respectively, and that the IDs of the collection devices 251 and 252 are ID_X1 and ID_X2, respectively.

[0034] 2 is a diagram illustrating an application example of a power transmission line management system according to an embodiment of the present disclosure. Referring to FIG. 1 and FIG. 2, for example, a collection unit 201 is provided on a steel tower 2A. Furthermore, for example, a collection unit 202 is provided on a steel tower 2B.

[0035] Power transmission lines 1AU, 1AV, and 1AW are U-phase, V-phase, and W-phase transmission lines in a power grid, respectively, and are supported by multiple steel towers 2A. Power transmission lines 1AU, 1AV, and 1AW form one circuit 3A. Hereinafter, each of power transmission lines 1AU, 1AV, and 1AW will also be referred to as power transmission line 1A. Power transmission line 1A is an example of a first power transmission line.

[0036] Transmission lines 1BU, 1BV, and 1BW are U-phase, V-phase, and W-phase transmission lines in the power system, respectively, and are supported by multiple steel towers 2B. Transmission lines 1BU, 1BV, and 1BW form one circuit 3B. Hereinafter, each of transmission lines 1BU, 1BV, and 1BW will also be referred to as transmission line 1B. Transmission line 1B is an example of a second transmission line. Note that in this specification, the terms "first" and "second" do not imply priority.

[0037] The contact units 101 are provided, for example, at corresponding positions on the multi-phase power transmission line 1A. More specifically, the contact units 101A, 101B, and 101C are provided, for example, on the power transmission lines 1AU, 1AV, and 1AW, at positions near the steel tower 2A. The distances between these three contact units 101 and the steel tower 2A are, for example, approximately the same.

[0038] The contact units 102 are provided, for example, at corresponding positions on the multi-phase power transmission line 1B. More specifically, the contact units 102A, 102B, and 102C are provided, for example, on the power transmission lines 1BU, 1BV, and 1BW, respectively, at positions near the steel tower 2B. The distances between these three contact units 102 and the steel tower 2B are, for example, approximately the same.

[0039] (Contact Unit 101) The current sensor 111 in the contact unit 101 measures the current flowing through the corresponding power line 1 A. The temperature sensor 121 in the contact unit 101 measures the temperature of the corresponding power line 1 A.

[0040] In the contact unit 101, the transfer device 151 acquires the measurement result of the current sensor 111 at a measurement timing according to a predetermined measurement period Cm, and generates sensor information S1 indicating the acquired measurement result and the measurement time tm. The sensor information S1 is an example of current data. The transfer device 151 may acquire, as the measurement result of the current sensor 111, an average value, a maximum value, or a minimum value of the current flowing through the power transmission line 1A over a predetermined period, or may acquire an instantaneous value.

[0041] The transfer device 151 also acquires the measurement result of the temperature sensor 121 at the measurement timing according to the measurement period Cm, and creates sensor information S2 indicating the acquired measurement result and the measurement time tm. The transfer device 151 may acquire, as the measurement result of the temperature sensor 121, an average value, a maximum value, or a minimum value of the temperature of the power transmission line 1A over a predetermined period, or may acquire an instantaneous value.

[0042] The transfer device 151 transmits the created sensor information S1 and S2 to the collection unit 201 by wireless communication.

[0043] Specifically, the transfer device 151 creates a sensor packet including the ID of the transfer device 151 as the sender, the ID_X1 of the collection device 251 as the destination, and sensor information S1 and S2, in accordance with the IEEE802.15.4 communication standard, for example, and transmits a 920 MHz wireless signal including the created sensor packet.

[0044] Furthermore, the forwarding device 151 forwards, for example, a sensor packet transmitted by another forwarding device 151. More specifically, when the forwarding device 151 receives a sensor packet from another forwarding device 151, the forwarding device 151 transmits the received sensor packet.

[0045] The transmission route of the sensor packet is automatically constructed by each transfer device 151 in accordance with, for example, the IEEE802.15.4 communication standard. An example of the transmission route of the sensor packet is indicated by a dashed line in Fig. 2. In this example, one contact unit 101A of the three contact units 101 provided at corresponding positions transmits the sensor packet it created and also forwards the sensor packets transmitted from contact units 101B and 101C.

[0046] (Contact unit 102) A current sensor 112 in the contactor unit 102 measures the current flowing through the corresponding power line 1B.

[0047] In the contact unit 102, the transfer device 152 acquires the measurement results of the current sensor 112 at measurement timings according to the measurement period Cm, and creates sensor information S1 indicating the acquired measurement results and the measurement time tm. The transfer device 152 may acquire, as the measurement results of the current sensor 112, an average value, a maximum value, or a minimum value of the current flowing through the power transmission line 1B over a predetermined period, or may acquire an instantaneous value. The transfer device 152 transmits the created sensor information S1 to the collection unit 202 via wireless communication.

[0048] Specifically, the transfer device 152 creates a sensor packet including the ID of the transfer device 152 as the sender, the ID_X2 of the collection device 252 as the destination, and sensor information S1, in accordance with the IEEE802.15.4 communication standard, for example, and transmits a wireless signal in the 920 MHz band including the created sensor packet.

[0049] Furthermore, the forwarding device 152 forwards, for example, a sensor packet transmitted by another forwarding device 152. More specifically, when the forwarding device 152 receives a sensor packet from another forwarding device 152, the forwarding device 152 transmits the received sensor packet.

[0050] The transmission route of the sensor packet is automatically constructed by each transfer device 152 in accordance with, for example, the IEEE802.15.4 communication standard. In Fig. 2, an example of the transmission route of the sensor packet is indicated by a dashed line. In this example, one contact unit 102A of the three contact units 102 provided at corresponding positions transmits the sensor packet it created and also forwards the sensor packets transmitted from contact units 102B and 102C.

[0051] (Collection Unit 201) When the collection device 251 in the collection unit 201 receives a sensor packet from the contact unit 101, it acquires the ID of the transfer device 151 that sent the sensor packet and the sensor information S1, S2 from the received sensor packet, and stores the acquired sensor information S1, S2 in association with the ID of the transfer device 151.

[0052] The weather sensor 211 in the collection unit 201 measures the temperature, wind speed, amount of solar radiation, and amount of precipitation that indicate the environment of the steel tower 2A.

[0053] The collecting device 251 acquires measurement results from the weather sensor 211 at measurement timings according to the measurement cycle Cm, and generates sensor information S3 indicating the measurement results of the temperature, wind speed, and solar radiation and the measurement time tm, and sensor information S4 indicating the measurement results of the precipitation and the measurement time tm. The sensor information S3 is an example of weather data. The sensor information S4 is an example of precipitation data. The collecting device 251 stores the generated sensor information S3 and S4 in association with the ID_X1 of the collecting device 251.

[0054] The collecting device 251 transmits the measurement results of the current sensor 111, the temperature sensor 121, and the weather sensor 211 to the power transmission line management device 301. More specifically, the collecting device 251 transmits collected information CD1 including the stored sensor information S1 and S2 and the ID of the corresponding transfer device 151, as well as the sensor information S3 and S4 and the ID_X1 of the collecting device 251, to the power transmission line management device 301 via wireless communication, for example, at each predetermined reporting period. Note that the collecting device 251 may transmit the collected information CD1 to the power transmission line management device 301 via wired communication.

[0055] (Collection Unit 202) When the collection device 252 in the collection unit 202 receives a sensor packet from the contact unit 102, it acquires the ID of the transfer device 152 that sent the sensor packet and the sensor information S1 from the received sensor packet, and stores the acquired sensor information S1 in association with the ID of the transfer device 152.

[0056] The weather sensor 212 in the collection unit 202 measures the temperature, wind speed, amount of solar radiation, and amount of precipitation that indicate the environment of the pylon 2B.

[0057] The collecting device 252 acquires the measurement results from the weather sensor 212 at the measurement timing according to the measurement period Cm, and generates sensor information S3 indicating the measurement results of the temperature, wind speed, and solar radiation and the measurement time tm, and sensor information S4 indicating the measurement results of the precipitation and the measurement time tm. The collecting device 252 stores the generated sensor information S3 and S4 in association with the ID_X2 of the collecting device 252.

[0058] The collecting device 252 transmits the measurement results of the current sensor 112 and the weather sensor 212 to the power transmission line management device 301. More specifically, the collecting device 252 transmits collected information CD2 including the stored sensor information S1 and the ID of the corresponding transfer device 152, as well as the sensor information S3, S4 and the ID_X2 of the collecting device 252, to the power transmission line management device 301 via wireless communication, for example, at each predetermined reporting period. Note that the collecting device 252 may transmit the collected information CD2 to the power transmission line management device 301 via wired communication.

[0059] <Transmission line management device> FIG. 3 is a diagram illustrating a configuration of a power transmission line management device according to an embodiment of the present disclosure. Referring to FIG. 3, the power transmission line management device 301 includes a receiving unit 31, a prediction information acquiring unit 32, a calculating unit 33, a creating unit 34, an estimating unit 35, and a storage unit 36. The receiving unit 31 and the prediction information acquiring unit 32 are examples of a first acquiring unit and an example of a second acquiring unit. The receiving unit 31 is an example of a fourth acquiring unit and an example of a fifth acquiring unit. The calculating unit 33 is an example of a third acquiring unit and an example of a difference calculating unit. Some or all of the receiving unit 31, the prediction information acquiring unit 32, the calculating unit 33, the creating unit 34, and the estimating unit 35 are implemented, for example, by a processing circuit including one or more processors. The storage unit 36 is, for example, a non-volatile memory included in the processing circuit.

[0060] For example, some or all of the functions of the power transmission line management device 301 may be provided by cloud computing. That is, the power transmission line management device 301 may be configured by a plurality of cloud servers or the like.

[0061] (Receiving unit 31) The receiving unit 31 acquires sensor information S1 indicating the measurement results of the current flowing through the power transmission line 1A, sensor information S2 indicating the measurement results of the temperature of the power transmission line 1A, sensor information S3 indicating the air temperature, wind speed, and amount of solar radiation at the position of the steel tower 2A on which the collection unit 201 is installed, and sensor information S4 indicating the amount of precipitation at the position of the steel tower 2A. More specifically, the receiving unit 31 receives collection information CD1 from the collection unit 201, and acquires the sensor information S1 and S2 and the ID of the transfer device 151, as well as the sensor information S3 and S4 and the ID_X1 of the collection device 251 from the received collection information CD1. The receiving unit 31 stores the acquired sensor information S1 and S2 in the storage unit 36 in association with the ID of the transfer device 151, and stores the acquired sensor information S3 and S4 in the storage unit 36 in association with the ID_X1 of the collection device 251.

[0062] The receiving unit 31 also acquires sensor information S1 indicating the measurement results of the current flowing through the power transmission line 1B, sensor information S3 indicating the temperature, wind speed, and amount of solar radiation at the position of the steel tower 2B on which the collection unit 202 is installed, and sensor information S4 indicating the amount of precipitation at the position of the steel tower 2B. More specifically, the receiving unit 31 receives collection information CD2 from the collection unit 202, and acquires the sensor information S1 and the ID of the transfer device 152, as well as the sensor information S3 and S4 and the ID_X2 of the collection device 252, from the received collection information CD2. The receiving unit 31 stores the acquired sensor information S1 in the storage unit 36 in association with the ID of the transfer device 152, and stores the acquired sensor information S3 and S4 in the storage unit 36 in association with the ID_X2 of the collection device 252.

[0063] (Prediction information acquisition unit 32) The forecast information acquisition unit 32 acquires weather forecast information W1A indicating forecast results for the temperature, wind speed, and solar radiation in an area including the location of the steel tower 2A on which the collection unit 201 is installed, and weather forecast information W2A indicating forecast results for the amount of precipitation in an area including the location of the steel tower 2A. The forecast information acquisition unit 32 also acquires weather forecast information W1B indicating forecast results for the temperature, wind speed, and solar radiation in an area including the location of the steel tower 2B on which the collection unit 201 is installed, and weather forecast information W2B indicating forecast results for the amount of precipitation in an area including the location of the steel tower 2B. The weather forecast information W1A and W1B are examples of weather data. The weather forecast information W2A and W2B are examples of precipitation data.

[0064] More specifically, for example, the forecast information acquisition unit 32 acquires weather forecast information W1A, W1B, W2A, and W2B for a predetermined time after a forecast timing according to a predetermined forecast cycle Ca from the Japan Meteorological Business Support Center. As an example, the forecast information acquisition unit 32 acquires weather forecast information W1A, W1B, W2A, and W2B for up to four hours after the forecast timing from the Japan Meteorological Business Support Center. The forecast information acquisition unit 32 stores the acquired weather forecast information W1A, W1B, W2A, and W2B in the storage unit 36.

[0065] (Calculation unit 33) (1) Calculation of actual temperature calculation value Tac1 The calculation unit 33 calculates an actual temperature calculation value Tac1, which is a calculation value of the temperature of the power transmission line 1A, based on the sensor information S3 indicating the air temperature, wind speed, and amount of solar radiation at the position of the steel tower 2A where the collection unit 201 is installed, and the value of the current flowing through the power transmission line 1A. The actual temperature calculation value Tac1 is an example of a first temperature calculation value.

[0066] More specifically, when the receiving unit 31 stores the sensor information S1, S2, S3, and S4 in the memory unit 36, the calculation unit 33 acquires the sensor information S3 corresponding to ID_X1 of the collection device 251 and the sensor information S1 corresponding to ID_1A of the transfer device 151A from the memory unit 36.

[0067] Calculation unit 33 calculates an actual temperature calculation value Tac1A, which is the actual temperature calculation value Tac1 of power transmission line 1AU at the same measurement time tm, based on the temperature, wind speed, and solar radiation at a certain measurement time tm indicated by acquired sensor information S3 and the value of the current flowing through power transmission line 1AU at the same measurement time tm indicated by acquired sensor information S1. Calculation unit 33 calculates actual temperature calculation value Tac1A based on the temperature, wind speed, solar radiation, and the values of the current flowing through power transmission line 1AU, for example, according to a calculation method described in Patent Document 1. The calculation method described in Patent Document 1 calculates the temperature of power transmission line 1 using an arithmetic equation that uses the temperature, wind speed, solar radiation, and values of the current flowing through power transmission line 1 as parameters, without using precipitation.

[0068] Similarly, calculation unit 33 calculates an actual temperature calculated value Tac1B, which is the actual temperature calculated value Tac1 of power transmission line 1AV, and an actual temperature calculated value Tac1C, which is the actual temperature calculated value Tac1 of power transmission line 1AW.

[0069] (2) Calculation of the difference D1 The calculation unit 33 calculates a difference D1 between the calculated actual temperature value Tac1 of the power transmission line 1A at the measurement time tm and the measurement result of the temperature of the power transmission line 1A at the same measurement time tm. The difference D1 is an example of a first difference.

[0070] More specifically, when the calculation unit 33 calculates an actual temperature calculation value Tac1A at a certain measurement time tm, the calculation unit 33 acquires sensor information S2 at the same measurement time tm that corresponds to ID_1A of the transfer device 151A from the storage unit 36. The calculation unit 33 calculates a difference D1A, which is the difference D1 between the calculated actual temperature calculation value Tac1A and the measured value of the temperature of the power transmission line 1AU indicated by the acquired sensor information S2.

[0071] Similarly, the calculation unit 33 calculates a difference D1B, which is the difference D1 between the actual temperature calculation value Tac1B and the measured value of the temperature of the power transmission line 1AV, and a difference D1C, which is the difference D1 between the actual temperature calculation value Tac1C and the measured value of the temperature of the power transmission line 1AW.

[0072] The calculation unit 33 calculates the actual temperature calculation value Tac1 and the difference D1 each time the receiving unit 31 stores the sensor information S1, S2, S3, and S4 in the memory unit 36, and stores the calculated actual temperature calculation value Tac1 and the difference D1 in the memory unit 36 in association with the measurement time tm.

[0073] (3) Calculation of actual temperature calculation value Tac2 The calculation unit 33 calculates an actual temperature calculation value Tac2, which is a calculation value of the temperature of the power transmission line 1B, based on the sensor information S3 indicating the air temperature, wind speed, and solar radiation at the position of the steel tower 2B where the collection unit 202 is installed, and the value of the current flowing through the power transmission line 1B. The actual temperature calculation value Tac2 is an example of a second temperature calculation value.

[0074] More specifically, when the receiving unit 31 stores the sensor information S1, S2, S3, and S4 in the memory unit 36, the calculation unit 33 acquires the sensor information S3 corresponding to ID_X2 of the collection device 252 and the sensor information S1 corresponding to ID_2A of the transfer device 152A from the memory unit 36.

[0075] Calculation unit 33 calculates an actual temperature calculated value Tac2A, which is the actual temperature calculated value Tac2 of power transmission line 1BU at the same measurement time tm, based on the temperature, wind speed, and amount of solar radiation at a certain measurement time tm indicated by acquired sensor information S3 and the value of the current flowing through power transmission line 1BU at the same measurement time tm indicated by acquired sensor information S1. Calculation unit 33 calculates actual temperature calculated value Tac2A based on the temperature, wind speed, amount of solar radiation, and the value of the current flowing through power transmission line 1BU, for example, according to a calculation method described in Patent Document 1 or the like.

[0076] Similarly, calculation unit 33 calculates an actual temperature calculated value Tac2B, which is the actual temperature calculated value Tac2 for power transmission line 1BV, and an actual temperature calculated value Tac2C, which is the actual temperature calculated value Tac2 for power transmission line 1BW.

[0077] The calculation unit 33 calculates the actual temperature calculation value Tac2 each time the receiving unit 31 stores the sensor information S1, S3, and S4 in the memory unit 36, and stores the calculated actual temperature calculation value Tac2 in the memory unit 36 in association with the measurement time tm.

[0078] (4) Calculation of the clear weather difference Dsur FIG. 4 is a diagram illustrating an example of an actual temperature calculation value calculated by a calculation unit in a power transmission line management device according to an embodiment of the present disclosure. In FIG. 4, the horizontal axis represents time, and the vertical axis represents temperature. The solid line in FIG. 4 represents the actual temperature calculation value Tac1. The dashed line in FIG. 4 represents the actual measured value Tmea of the temperature of power transmission line 1A. The dashed line in FIG. 4 represents the error ΔT between the actual temperature calculation value Tac1 and the actual measured value Tmea. FIG. 4 illustrates the changes over time in the actual temperature calculation value Tac1, the actual measured value Tmea, and the error ΔT when precipitation occurs until just before time ts and stops after time ts.

[0079] 4, the calculated actual temperature value Tac1 is greater than the measured value Tmea because the calculated actual temperature value Tac1 is a value calculated without taking into account the amount of precipitation and the cooling effect of precipitation on the power transmission line 1A.

[0080] Furthermore, the error ΔT decreases over time after time ts and converges to a constant value. The value at which the error ΔT converges is based on factors other than the cooling effect of the power transmission line 1A due to precipitation. Possible factors include the difference between the weather conditions at the location where the weather sensor 211 is attached on the tower 2A and the weather conditions at the measurement location of the actual measurement value Tmea, individual variations in the power transmission line 1A, and changes in physical quantities of the power transmission line 1A, such as emissivity, over time. In other words, the error ΔT is a value based on the amount of temperature drop of the power transmission line 1A due to precipitation and the other factors.

[0081] For example, the calculation unit 33 calculates a clear-weather difference Dsur, which is the difference between the actual temperature calculation value Tac1 at time ty when precipitation has stopped and the temperature measurement result of the power transmission line 1A at time ty. The clear-weather difference Dsur is an example of a second difference. Time ty is an example of a second time.

[0082] More specifically, calculation unit 33 calculates actual temperature calculation values Tac1A, Tac1B, and Tac1C at time ty, when a sufficient amount of time has passed since precipitation stopped. Specifically, when the difference between error ΔT at nth measurement time tmn and error ΔT at (n-1)th measurement time tm(n-1) is less than a predetermined value, for example, less than 1°C, calculation unit 33 determines that measurement time tmn is time ty, when a sufficient amount of time has passed since precipitation stopped, and calculates actual temperature calculation values Tac1A, Tac1B, and Tac1C at time ty, where n is an integer greater than or equal to 2.

[0083] Calculation unit 33 calculates the difference between the calculated actual temperature calculation value Tac1A and the measured temperature of power line 1AU at the time ty indicated by sensor information S2 as the sunny weather difference DsurA. Calculation unit 33 also calculates the difference between the calculated actual temperature calculation value Tac1B and the measured temperature of power line 1AV at the time ty indicated by sensor information S2 as the sunny weather difference DsurB. Calculation unit 33 also calculates the difference between the calculated actual temperature calculation value Tac1C and the measured temperature of power line 1AW at the time ty indicated by sensor information S2 as the sunny weather difference DsurC.

[0084] Calculation unit 33 stores the calculated clear weather differences DsurA, DsurB, DsurC in memory unit 36. For example, calculation unit 33 periodically calculates the clear weather differences DsurA, DsurB, DsurC and updates the clear weather differences DsurA, DsurB, DsurC in memory unit 36 to the calculated clear weather differences DsurA, DsurB, DsurC.

[0085] (Creation Department 34) The creation unit 34 uses the sensor information S1, S3, S4 and the difference D1 to create a learning model Md for estimating the precipitation difference Drain, which indicates the amount of temperature decrease of the power transmission line 1A due to precipitation, among the above-mentioned errors ΔT.

[0086] Here, the precipitation difference Drain is expressed by the following equations (1) and (2). D1(n)=D1(n-1)+f(n) (1) D1(y)=0 (2)

[0087] In equation (1), D1(n) is the precipitation difference Drain at time tn. D1(n-1) is the precipitation difference Drain at time t(n-1), which is before time tn. f(n) is a function of the temperature, wind speed, solar radiation, precipitation, and current flowing through power transmission line 1A during the period from time t(n-1) to time tn. D1(y) is the precipitation difference Drain at time ty, when a sufficient amount of time has passed since precipitation stopped. The creation unit 34 creates a learning model Md that estimates the precipitation difference Drain according to equation (1).

[0088] More specifically, the creation unit 34 acquires the sensor information S1, S3, and S4, the difference D1A, and the fine weather difference DsurA corresponding to ID_X1 of the collection device 251 from the storage unit 36. The creation unit 34 uses the acquired sensor information S1, S3, and S4 to create explanatory variables in the learning model Md.

[0089] Specifically, the creation unit 34 uses the acquired sensor information S3 to calculate an average temperature Av1 at three or more measurement times tm within a target period of a predetermined length T1 from the (nk)th measurement time tm(nk) to the nth measurement time tmn, where k is an integer smaller than n. The length T1 is, for example, one hour. Similarly, the creation unit 34 calculates an average temperature Av1 at three or more measurement times tm within a target period of length T1 from the measurement time tm(n-k+1) to the measurement time tm(n+1). The creation unit 34 shifts the measurement time tm, which is the start point of the target period, by one, to create time series data TDA1 consisting of multiple time series average values Av1.

[0090] Furthermore, the creation unit 34 uses the acquired sensor information S3 to calculate an average wind speed Av2 at three or more measurement times tm within a target period of a predetermined length T1 from the (nk)th measurement time tm(nk) to the nth measurement time tmn. Similarly, the creation unit 34 calculates an average wind speed Av2 at three or more measurement times tm within a target period of length T1 from the measurement time tm(n-k+1) to the measurement time tm(n+1). The creation unit 34 shifts the measurement time tm, which is the start point of the target period, by one, to create time series data TDA2 made up of multiple time series average values Av2.

[0091] Furthermore, the creation unit 34 uses the acquired sensor information S3 to calculate an average value Av4 of the amount of solar radiation at three or more measurement times tm within a target period of a predetermined length T1 from the (nk)th measurement time tm(nk) to the nth measurement time tmn. Similarly, the creation unit 34 calculates an average value Av4 of the amount of solar radiation at three or more measurement times tm within a target period of length T1 from the measurement time tm(n-k+1) to the measurement time tm(n+1). The creation unit 34 creates time series data TDA4 consisting of multiple time series average values Av4 by shifting the measurement time tm, which is the start point of the target period, by one.

[0092] Furthermore, the creation unit 34 uses the acquired sensor information S4 to calculate an average value Av5 of the precipitation at three or more measurement times tm within a target period of a predetermined length T1 from the (nk)th measurement time tm(nk) to the nth measurement time tmn. Similarly, the creation unit 34 calculates an average value Av5 of the precipitation at three or more measurement times tm within a target period of length T1 from the measurement time tm(n-k+1) to the measurement time tm(n+1). The creation unit 34 creates time series data TDA5 consisting of multiple time series average values Av5 by shifting the measurement time tm, which is the start point of the target period, by one.

[0093] Furthermore, the creation unit 34 uses the acquired sensor information S1 to calculate an average current value Av6 at three or more measurement times tm within a target period of a predetermined length T1 from the (nk)th measurement time tm(nk) to the nth measurement time tmn. Similarly, the creation unit 34 calculates an average current value Av6 at three or more measurement times tm within a target period of length T1 from the measurement time tm(n-k+1) to the measurement time tm(n+1). The creation unit 34 shifts the measurement time tm, which is the start point of the target period, by one, to create time series data TDA6 made up of multiple time series average values Av6.

[0094] In addition, the creation unit 34 calculates the precipitation difference Drain at the measurement time tmn by subtracting the clear weather difference DsurA from the difference D1A at the measurement time tmn, and stores the calculated precipitation difference Drain in the memory unit 36 in association with the measurement time tmn.

[0095] Similarly, the creation unit 34 calculates the precipitation difference Drain at the measurement time tm(n+1) by subtracting the clear weather difference DsurA from the difference D1A at the measurement time tm(n+1). The creation unit 34 creates time series data TDrain made up of a plurality of chronological precipitation differences Drain by shifting the measurement times tm, from which the precipitation difference Drain is calculated, by one.

[0096] The creation unit 34 creates the learning model Md using the time series data TDA1, TDA2, TDA4, TDA5, and TDA6 that are explanatory variables and the time series data TDrain that is a target variable. More specifically, the creation unit 34 creates the learning model Md by, for example, performing machine learning on a neural network using the created time series data TDA1, TDA2, TDA4, TDA5, and TDA6 and the created time series data TDrain as learning data so as to output the time series data TDrain for a predetermined period starting from time tn.

[0097] The creation unit 34 stores the created learning model Md in the storage unit 36.

[0098] (Estimation part 35) The estimation unit 35 estimates the temperature of the power transmission line 1A based on the sensor information S3, S4 acquired by the receiving unit 31 and the value of the current flowing through the power transmission line 1A. The estimation unit 35 also estimates the temperature of the power transmission line 1B based on the sensor information S3, S4 and the value of the current flowing through the power transmission line 1B.

[0099] (1) Temperature prediction for power line 1A The estimation unit 35 predicts the temperature of the power transmission line 1A at a future prediction time tp based on the sensor information S3, S4 and a tentative current value EAP, which is the value of a hypothetical current flowing through the power transmission line 1A, for example, at a prediction timing according to the prediction period Ca. The prediction time tp is an example of a first target time. The tentative current value EAP is a hypothetical current value set by the estimation unit 35. The estimation unit 35 sets the tentative current value EAP and outputs a calculation instruction including the set tentative current value EAP to the calculation unit 33. For example, the estimation unit 35 sets the tentative current value EAP to a value obtained by adding a predetermined value to the current value of the power transmission line 1A at a certain time indicated by the sensor information S1.

[0100] (1-1) Calculation of predicted temperature value Tpc1 Upon receiving a calculation instruction from the estimation unit 35, the calculation unit 33 calculates a predicted temperature calculation value Tpc1, which is a predicted temperature of the power transmission line 1A, based on the provisional current value EAp and weather forecast information W1A indicating the predicted results of the air temperature, wind speed, and solar radiation in an area including the location of the steel tower 2A on which the collection unit 201 is installed. The predicted temperature calculation value Tpc1 is an example of a first temperature calculation value.

[0101] More specifically, the calculation unit 33 acquires weather forecast information W1A from the storage unit 36. The calculation unit 33 calculates a predicted temperature calculated value Tpc1A, which is a predicted temperature calculated value Tpc1 of the power transmission line 1AU at the prediction time tp, based on the predicted values of the air temperature, wind speed, and solar radiation at the prediction time tp indicated by the acquired weather forecast information W1A and the provisional current value EAp, in accordance with a calculation method described in, for example, Patent Document 1.

[0102] For example, calculation unit 33 calculates predicted temperature calculation values Tpc1A at multiple prediction times tp at predetermined intervals based on weather forecast information W1A and provisional current value EAP. As an example, calculation unit 33 calculates predicted temperature calculation values Tpc1A at four prediction times tp at one-hour intervals based on weather forecast information W1A and provisional current value EAP.

[0103] Similarly, calculation unit 33 calculates predicted temperature calculation value Tpc1B, which is the predicted temperature calculation value Tpc1 of power transmission line 1AV at the four prediction times tp, and predicted temperature calculation value Tpc1C, which is the predicted temperature calculation value Tpc1 of power transmission line 1AW at the four prediction times tp. Calculation unit 33 outputs predicted temperature calculation values Tpc1A, Tpc1B, and Tpc1C at the prediction times tp to estimation unit 35.

[0104] (1-2) Calculation of the estimated precipitation difference Dprain1 The estimation unit 35 predicts the temperature of the power transmission line 1A at the predicted time tp based on the weather forecast information W1A, W2A at the predicted time tp acquired by the forecast information acquisition unit 32, the predicted temperature calculation value Tpc1 at the predicted time tp calculated by the calculation unit 33, and a learning model Md created using the difference D1.

[0105] More specifically, the estimation unit 35 acquires an estimated precipitation difference Dprain1, which is an estimate of the precipitation difference Drain at the prediction time tp, using the weather forecast information W1A, W2A, the provisional current value EAp, and the learning model Md in the storage unit 36. The estimated precipitation difference Dprain1 is an example of a first estimate.

[0106] Specifically, the estimation unit 35 uses sensor information S3, S4 and weather forecast information W1A, W2A related to the power transmission line 1A to create time series data of weather at a predetermined time interval, which includes actual weather values at multiple measurement times tm and predicted weather values at multiple prediction times tp.

[0107] More specifically, the estimation unit 35 uses the sensor information S3 corresponding to ID_X1 of the collection device 251 and the weather forecast information W1A to create time series data TDAp1 consisting of actual temperature values at eight past measurement times tm and predicted temperature values at four future predicted times tp.

[0108] In addition, the estimation unit 35 uses the sensor information S3 corresponding to ID_X1 of the collection device 251 and the weather forecast information W1A to create time series data TDAp2 consisting of actual wind speed values at eight past measurement times tm and predicted wind speed values at four future predicted times tp.

[0109] In addition, the estimation unit 35 uses the sensor information S3 corresponding to ID_X1 of the collection device 251 and the weather forecast information W1A to create time series data TDAp4 consisting of actual values of solar radiation at eight past measurement times tm and predicted values of solar radiation at four future predicted times tp.

[0110] In addition, the estimation unit 35 uses the sensor information S4 corresponding to ID_X1 of the collection device 251 and the weather forecast information W1A to create time series data TDAp5 consisting of actual precipitation values at eight past measurement times tm and predicted precipitation values at four future predicted times tp.

[0111] The estimation unit 35 provides the created time series data TDAp1, TDAp2, TDAp4, and TDAp5 and the provisional current value EAp to the learning model Md, thereby obtaining estimated precipitation differences Dprain1 at four future prediction times tp.

[0112] (1-3) Temperature prediction The estimation unit 35 predicts the temperature of the power transmission line 1A at the prediction time tp based on the acquired estimated precipitation differential Dprain1 and the predicted temperature calculation value Tpc1 at the prediction time tp. For example, the estimation unit 35 predicts the temperature of the power transmission line 1A at the prediction time tp further based on the clear-weather differential Dsur.

[0113] More specifically, the estimation unit 35 predicts that the value obtained by adding the predicted temperature calculation value Tpc1A at the predicted time tp received from the calculation unit 33 to the estimated precipitation difference Dprain1 and the sunny weather difference DsurA at the predicted time tp is the temperature of the transmission line 1AU when a current of the provisional current value EAp flows through the transmission line 1AU at the predicted time tp.

[0114] Similarly, the estimation unit 35 predicts that the value obtained by adding the estimated precipitation difference Dprain1 and the sunny weather difference DsurB at the predicted time tp to the predicted temperature calculation value Tpc1B at the predicted time tp received from the calculation unit 33 is the temperature of the transmission line 1AV when a current of the provisional current value EAp flows through the transmission line 1AV at the predicted time tp.

[0115] Similarly, the estimation unit 35 predicts that the value obtained by adding the estimated precipitation difference Dprain1 and the sunny weather difference DsurC at the predicted time tp to the predicted temperature calculation value Tpc1C at the predicted time tp received from the calculation unit 33 is the temperature of the transmission line 1AW when a current of the provisional current value EAp flows through the transmission line 1AW at the predicted time tp.

[0116] For example, the estimation unit 35 performs dynamic line rating to dynamically calculate the transmission capacity of the power transmission line 1A based on the predicted temperature of the power transmission line 1A at the predicted time tp.

[0117] More specifically, the estimation unit 35 searches for the tentative current value EAP when the predicted value of the temperature of the power transmission line 1A at the prediction time tp falls within a predetermined temperature range Rt including the rated temperature Trat, according to a well-known dynamic line rating technique. Specifically, the estimation unit 35 compares the predicted value of the temperature of the power transmission line 1A at the prediction time tp with the temperature range Rt, and if the predicted value is less than the lower limit of the temperature range Rt, the estimation unit 35 changes the tentative current value EAP to a higher value and outputs a calculation instruction including the changed tentative current value EAP to the calculation unit 33. On the other hand, if the predicted value is greater than the upper limit of the temperature range Rt, the estimation unit 35 changes the tentative current value EAP to a lower value and outputs a calculation instruction including the changed tentative current value EAP to the calculation unit 33. The estimation unit 35 searches for the tentative current value EAp when the predicted value of the temperature of the power transmission line 1A falls within the temperature range Rt by repeatedly comparing the predicted value with the temperature range Rt and changing the tentative current value EAp until the predicted value falls within the temperature range Rt. The estimation unit 35 determines that the tentative current value EAp when the predicted value of the temperature of the power transmission line 1A falls within the temperature range Rt is the transmission capacity of the power transmission line 1A, and notifies a power generation device (not shown) of the determined transmission capacity of the power transmission line 1A.

[0118] (2) Determining the temperature of power line 1B The estimation unit 35 determines the temperature of the power transmission line 1B at the measurement time tm based on the sensor information S3 and S4 at the measurement time tm, the actual temperature calculation value Tac2 at the measurement time tm calculated by the calculation unit 33, and the estimated precipitation difference Dprain. For example, the estimation unit 35 determines the temperature of the power transmission line 1B at the measurement time tm based on the actual temperature calculation value Tac2 at the measurement time tm and the estimated precipitation difference Dprain at the measurement time tm. The measurement time tm is an example of a second target time and may be the current time or a past time.

[0119] (2-1) Calculation of the estimated precipitation difference Dprain2 When the calculation unit 33 stores the actual temperature calculation value Tac2A calculated based on the sensor information S1 and S3 at the q-th measurement time tmq, the estimation unit 35 acquires an estimated precipitation difference Dprain2, which is an estimate of the precipitation difference Drain at the measurement time tmq, using the sensor information S3 and S4 at the measurement time tmq and the learning model Md in the storage unit 36. The estimated precipitation difference Dprain2 is an example of a second estimate.

[0120] Specifically, the estimation unit 35 uses the sensor information S3 and S4 related to the power transmission line 1B to generate time-series data of weather at predetermined time intervals, including actual values of weather at multiple measurement times tm. The estimation unit 35 also uses the sensor information S1 related to the power transmission line 1B to generate time-series data of current at predetermined time intervals, including actual values of current flowing through the power transmission line 1B at multiple measurement times tm.

[0121] More specifically, the estimation unit 35 uses the sensor information S3 corresponding to ID_X1 of the collection device 252 to create time-series data TDB1 made up of actual values of the air temperature at the most recent eight measurement times tm.

[0122] Furthermore, the estimation unit 35 uses the sensor information S3 corresponding to ID_X1 of the collection device 252 to create time-series data TDB2 consisting of actual values of wind speed at the most recent eight measurement times tm.

[0123] Furthermore, the estimation unit 35 uses the sensor information S3 corresponding to ID_X1 of the collection device 252 to create time-series data TDB4 including actual values of the amount of solar radiation at the most recent eight measurement times tm.

[0124] Furthermore, the estimation unit 35 uses the sensor information S4 corresponding to ID_X1 of the collection device 252 to create time-series data TDB5 consisting of actual values of the amount of precipitation at the most recent eight measurement times tm.

[0125] Furthermore, the estimation unit 35 uses the sensor information S1 corresponding to ID_2A of the transfer device 152A to create time-series data TDB6U including actual current values at the most recent eight measurement times tm.

[0126] Furthermore, the estimation unit 35 uses the sensor information S1 corresponding to ID_2B of the transfer device 152B to create time-series data TDB6V including actual current values at the most recent eight measurement times tm.

[0127] Furthermore, the estimation unit 35 uses the sensor information S1 corresponding to ID_2C of the transfer device 152C to create time-series data TDB6W including actual current values at the most recent eight measurement times tm.

[0128] The estimation unit 35 provides the created time series data TDB1, TDB2, TDB4, TDB5, and TDB6U to the learning model Md to obtain an estimated precipitation difference Dprain2U, which is the estimated precipitation difference Dprain2 for the power transmission line 1BU at the measurement time tmq.

[0129] The estimation unit 35 also provides the created time series data TDB1, TDB2, TDB4, TDB5, and TDB6V to the learning model Md to obtain an estimated precipitation difference Dprain2V, which is the estimated precipitation difference Dprain2 for the power transmission line 1BU at the measurement time tmq.

[0130] In addition, the estimation unit 35 provides the created time series data TDB1, TDB2, TDB4, TDB5, and TDB6W to the learning model Md to obtain an estimated precipitation difference Dprain2W, which is the estimated precipitation difference Dprain2 for the power transmission line 1BW at the measurement time tmq.

[0131] For example, every time the calculation unit 33 stores the actual temperature calculation value Tac2, the estimation unit 35 performs the above-described process to obtain the estimated precipitation differences Dprain2U, Dprain2V, and Dprain2W.

[0132] (2-2) Temperature determination The estimation unit 35 determines the temperature of the power transmission line 1B at the measurement time tmq based on the actual temperature calculated value Tac2 at the measurement time tmq and the estimated precipitation difference Dprain2 at the measurement time tmq.

[0133] More specifically, the estimation unit 35 determines that the value obtained by adding the estimated precipitation difference Dprain2U at the measurement time tmq to the actual temperature calculation value Tac2A at the measurement time tmq is the temperature of the power transmission line 1BU at the measurement time tmq. Note that the estimation unit 35 may be configured to determine that the value obtained by further adding the clear weather difference Dsur to the actual temperature calculation value Tac2A is the temperature of the power transmission line 1BU.

[0134] The estimation unit 35 determines that the value obtained by adding the estimated precipitation difference Dprain2V at the measurement time tmq to the actual temperature calculation value Tac2B at the measurement time tmq is the temperature of the power transmission line 1BV at the measurement time tmq. The estimation unit 35 may be configured to determine that the value obtained by further adding the clear weather difference Dsur to the actual temperature calculation value Tac2B is the temperature of the power transmission line 1BV.

[0135] The estimation unit 35 determines that the value obtained by adding the estimated precipitation difference Dprain2W at the measurement time tmq to the actual temperature calculation value Tac2C at the measurement time tmq is the temperature of the power transmission line 1BW at the measurement time tmq. The estimation unit 35 may be configured to determine that the value obtained by further adding the clear weather difference Dsur to the actual temperature calculation value Tac2C is the temperature of the power transmission line 1BW.

[0136] (3) Temperature prediction for transmission line 1B The estimation unit 35 predicts the temperature of the power transmission line 1B at a future prediction time tp based on the sensor information S3, S4 and a tentative current value EBp, which is the value of a hypothetical current flowing through the power transmission line 1B, for example, at a prediction timing according to the prediction period Ca. The prediction time tp is an example of a second target time. The prediction time tp of the temperature of the power transmission line 1A and the prediction time tp of the temperature of the power transmission line 1B may be the same or different. The tentative current value EBp is a hypothetical current value set by the estimation unit 35. The estimation unit 35 sets the tentative current value EBp and outputs a calculation instruction including the set tentative current value EBp to the calculation unit 33. For example, the estimation unit 35 sets the tentative current value EAp to a value obtained by adding a predetermined value to the current value of the power transmission line 1B at a certain time indicated by the sensor information S1.

[0137] (3-1) Calculation of predicted temperature value Tpc2 Upon receiving a calculation instruction from the estimation unit 35, the calculation unit 33 calculates a predicted temperature calculated value Tpc2, which is a predicted temperature of the power transmission line 1B, based on the tentative current value EBp and weather forecast information W1B indicating the predicted results of the air temperature, wind speed, and solar radiation in an area including the location of the steel tower 2B on which the collection unit 202 is installed. The predicted temperature calculated value Tpc2 is an example of a second temperature calculated value.

[0138] More specifically, the calculation unit 33 acquires weather forecast information W1B from the storage unit 36. The calculation unit 33 calculates a predicted temperature calculated value Tpc2A, which is a predicted temperature calculated value Tpc2 of the power transmission line 1BU at the prediction time tp, based on the predicted values of the air temperature, wind speed, and solar radiation at the prediction time tp indicated by the acquired weather forecast information W1B and the provisional current value EBp, in accordance with a calculation method described in, for example, Patent Document 1.

[0139] For example, calculation unit 33 calculates predicted temperature calculated values Tpc2A at multiple prediction times tp at predetermined intervals based on weather forecast information W1B and provisional current value EBp. As an example, calculation unit 33 calculates predicted temperature calculated values Tpc2A at four prediction times tp at one-hour intervals based on weather forecast information W1B and provisional current value EBp.

[0140] Similarly, calculation unit 33 calculates predicted temperature calculation values Tpc2B, which are predicted temperature calculation values Tpc2 for power transmission line 1BV at the four prediction times tp, and predicted temperature calculation values Tpc2C, which are predicted temperature calculation values Tpc2 for power transmission line 1BW at the four prediction times tp. Calculation unit 33 outputs predicted temperature calculation values Tpc2A, Tpc2B, and Tpc2C at the prediction times tp to estimation unit 35.

[0141] (3-2) Calculation of the estimated precipitation difference Dprain2 The estimation unit 35 acquires an estimated precipitation difference Dprain2, which is an estimate of the precipitation difference Drain at the prediction time tp, using the weather forecast information W1B, W2B, the tentative current value EBp, and the learning model Md in the memory unit 36. The estimated precipitation difference Dprain2 is an example of a second estimate.

[0142] Specifically, the estimation unit 35 uses sensor information S3, S4 and weather forecast information W1B, W2B related to the power transmission line 1B to create weather time series data for a predetermined time interval, which includes actual weather values at multiple measurement times tm and predicted weather values at multiple prediction times tp.

[0143] More specifically, the estimation unit 35 uses the sensor information S3 corresponding to ID_X2 of the collection device 252 and the weather forecast information W1B to create time series data TDBp1 consisting of actual temperature values at eight past measurement times tm and predicted temperature values at four future predicted times tp.

[0144] In addition, the estimation unit 35 uses the sensor information S3 corresponding to ID_X2 of the collection device 252 and the weather forecast information W1B to create time series data TDBp2 consisting of actual wind speed values at eight past measurement times tm and predicted wind speed values at four future predicted times tp.

[0145] In addition, the estimation unit 35 uses the sensor information S3 corresponding to ID_X2 of the collection device 252 and the weather forecast information W1B to create time series data TDBp4 consisting of actual values of solar radiation at eight past measurement times tm and predicted values of solar radiation at four future predicted times tp.

[0146] In addition, the estimation unit 35 uses the sensor information S4 corresponding to ID_X2 of the collection device 252 and the weather forecast information W1B to create time series data TDBp5 consisting of actual precipitation values at eight past measurement times tm and predicted precipitation values at four future predicted times tp.

[0147] The estimation unit 35 provides the created time series data TDBp1, TDBp2, TDBp4, and TDBp5 and the provisional current value EBp to the learning model Md, thereby obtaining estimated precipitation differences Dprain2 at four future prediction times tp.

[0148] (3-3) Temperature prediction The estimation unit 35 predicts the temperature of the power transmission line 1B at the prediction time tp based on the acquired estimated precipitation difference Dprain2 and the predicted temperature calculated value Tpc2 at the prediction time tp.

[0149] More specifically, the estimation unit 35 predicts that the value obtained by adding the predicted temperature calculation value Tpc2A at the predicted time tp received from the calculation unit 33 to the estimated precipitation difference Dprain2 at the predicted time tp is the temperature of the transmission line 1BU when a current of the tentative current value EBp flows through the transmission line 1BU at the predicted time tp.

[0150] In addition, the estimation unit 35 predicts that the value obtained by adding the estimated precipitation difference Dprain2 at the predicted time tp to the predicted temperature calculation value Tpc2B at the predicted time tp received from the calculation unit 33 is the temperature of the transmission line 1BV when a current of the provisional current value EBp flows through the transmission line 1BV at the predicted time tp.

[0151] In addition, the estimation unit 35 predicts that the value obtained by adding the estimated precipitation difference Dprain2 at the predicted time tp to the predicted temperature calculation value Tpc2C at the predicted time tp received from the calculation unit 33 is the temperature of the transmission line 1BW when a current of the provisional current value EBp flows through the transmission line 1BW at the predicted time tp.

[0152] For example, the estimation unit 35 performs dynamic line rating to dynamically calculate the transmission capacity of the power transmission line 1B based on the predicted temperature of the power transmission line 1B at the predicted time tp.

[0153] More specifically, the estimation unit 35 searches for a tentative current value EBp when the predicted temperature of the power transmission line 1B at the prediction time tp falls within a predetermined temperature range Rt including the rated temperature Trat, according to a well-known dynamic line rating technique. Specifically, the estimation unit 35 compares the predicted temperature of the power transmission line 1B at the prediction time tp with the temperature range Rt, and if the predicted temperature is less than the lower limit of the temperature range Rt, the estimation unit 35 changes the tentative current value EBp to a higher value and outputs a calculation instruction including the changed tentative current value EBp to the calculation unit 33. On the other hand, if the predicted temperature is greater than the upper limit of the temperature range Rt, the estimation unit 35 changes the tentative current value EBp to a lower value and outputs a calculation instruction including the changed tentative current value EBp to the calculation unit 33. The estimation unit 35 searches for the tentative current value EBp at which the predicted value of the temperature of the power transmission line 1B falls within the temperature range Rt by repeatedly comparing the predicted value with the temperature range Rt and changing the tentative current value EBp until the predicted value of the temperature of the power transmission line 1B falls within the temperature range Rt. The estimation unit 35 determines that the tentative current value EBp at which the predicted value of the temperature of the power transmission line 1B falls within the temperature range Rt is the transmission capacity of the power transmission line 1B, and notifies a power generation device (not shown) of the determined transmission capacity of the power transmission line 1B.

[0154] [Operation flow] 5 is a flowchart illustrating an example of an operation procedure when the power transmission line management device 301 according to the embodiment of the present disclosure estimates the temperature of the power transmission line 1AU.

[0155] Referring to FIG. 5, first, the power transmission line management device 301 waits for the arrival of the prediction timing according to the prediction cycle Ca (NO in step S11), and when the prediction timing arrives (YES in step S11), it acquires weather forecast information W1A, W2A for up to four hours in the future (step S12).

[0156] Next, the power transmission line management device 301 sets a tentative current value EAp. For example, the power transmission line management device 301 sets an initial value of the tentative current value EAp to a value obtained by adding a predetermined value to the actual current value of the power transmission line 1A at a certain time (step S13).

[0157] Next, the power transmission line management device 301 calculates a predicted temperature calculation value Tpc1A of the power transmission line 1AU at the prediction time tp based on the predicted values of the air temperature, wind speed, and solar radiation at the prediction time tp indicated by the weather forecast information W1A and the provisional current value EAp (step S14).

[0158] Next, the power transmission line management device 301 acquires an estimated precipitation difference Dprain1 at the prediction time tp using the weather forecast information W1A and W2A, the provisional current value EAp, and the learning model Md at the prediction time tp (step S15).

[0159] Next, the power transmission line management device 301 predicts that the temperature of the power transmission line 1AU at the prediction time tp is the value obtained by adding the estimated precipitation difference Dprain1 and the clear weather difference DsurA at the prediction time tp to the predicted temperature calculated value Tpc1A at the prediction time tp (step S16).

[0160] Next, the power transmission line management device 301 compares the predicted value of the temperature of the power transmission line 1AU at the prediction time tp with the temperature range Rt including the rated temperature Trat (step S17).

[0161] Next, if the predicted value is not within the temperature range Rt (NO in step S18), the power transmission line management device 301 resets the tentative current value EAp. Specifically, if the predicted value is less than the lower limit of the temperature range Rt, the power transmission line management device 301 changes the tentative current value EAp to a higher value, and if the predicted value is greater than the upper limit of the temperature range Rt, the power transmission line management device 301 changes the tentative current value EAp to a lower value (step S13). Then, the power transmission line management device 301 repeats steps S14, S15, S16, and S17.

[0162] On the other hand, if the predicted value is within the temperature range Rt, i.e., if the predicted value converges within the temperature range Rt (YES in step S18), the transmission line management device 301 determines that the provisional current value EAp when the predicted value of the temperature of the transmission line 1A converges within the temperature range Rt is the transmission capacity of the transmission line 1A, and notifies the power generation device (not shown) of the determined transmission capacity of the transmission line 1A (step S19).

[0163] Next, the power transmission line management device 301 waits for the arrival of a new prediction timing according to the prediction cycle Ca (NO in step S11).

[0164] 6 is a flowchart defining another example of an operation procedure when the power transmission line management device 301 according to the embodiment of the present disclosure estimates the temperature of the power transmission line 1BU.

[0165] Referring to FIG. 6, first, the power transmission line management device 301 waits for the arrival of the prediction timing according to the prediction cycle Ca (NO in step S21), and when the prediction timing arrives (YES in step S21), it acquires weather forecast information W1B, W2B for up to four hours in the future (step S22).

[0166] Next, the power transmission line management device 301 sets a tentative current value EBP. For example, the power transmission line management device 301 sets an initial value of the tentative current value EBP to a value obtained by adding a predetermined value to the actual current value of the power transmission line 1B at a certain time (step S23).

[0167] Next, the power transmission line management device 301 calculates a predicted temperature calculation value Tpc2A of the power transmission line 1BU at the prediction time tp based on the predicted values of the air temperature, wind speed, and solar radiation at the prediction time tp indicated by the weather forecast information W1B and the provisional current value EBp (step S24).

[0168] Next, the power transmission line management device 301 acquires an estimated precipitation difference Dprain2 at the prediction time tp using the weather forecast information W1B and W2B, the tentative current value EBp, and the learning model Md at the prediction time tp (step S25).

[0169] Next, the power transmission line management device 301 predicts that the temperature of the power transmission line 1BU at the prediction time tp is the value obtained by adding the estimated precipitation difference Dprain2 at the prediction time tp to the predicted temperature calculated value Tpc2A at the prediction time tp (step S26).

[0170] Next, the power transmission line management device 301 compares the predicted value of the temperature of the power transmission line 1BU at the prediction time tp with the temperature range Rt including the rated temperature Trat (step S27).

[0171] Next, if the predicted value is not within the temperature range Rt (NO in step S28), the power transmission line management device 301 resets the tentative current value EBP. Specifically, if the predicted value is less than the lower limit of the temperature range Rt, the power transmission line management device 301 changes the tentative current value EBP to a higher value, and if the predicted value is greater than the upper limit of the temperature range Rt, the power transmission line management device 301 changes the tentative current value EBP to a lower value (step S23). Then, the power transmission line management device 301 repeats steps S24, S25, S26, and S27.

[0172] On the other hand, if the predicted value is within the temperature range Rt, i.e., if the predicted value converges within the temperature range Rt (YES in step S28), the transmission line management device 301 determines that the tentative current value EBp when the predicted value of the temperature of transmission line 1B converges within the temperature range Rt is the transmission capacity of transmission line 1B, and notifies the power generation device (not shown) of the calculated result of the determined transmission capacity of transmission line 1BU (step S29).

[0173] Next, the power transmission line management device 301 waits for the arrival of a new prediction timing according to the prediction cycle Ca (NO in step S21).

[0174] In the power transmission line management device 301 according to the embodiment of the present disclosure, the estimation unit 35 is configured to predict the temperature of power transmission line 1A, predict the temperature of power transmission line 1B, and determine the temperature of power transmission line 1B, but this is not limited to this. The estimation unit 35 may be configured not to predict the temperature of power transmission line 1A, predict the temperature of power transmission line 1B, or determine the temperature of power transmission line 1B.

[0175] Furthermore, in the power transmission line management device 301 according to the embodiment of the present disclosure, the estimation unit 35 is configured to acquire the estimated precipitation difference Dprain using the learning model Md, but this is not limited thereto. The estimation unit 35 may be configured to calculate the estimated precipitation difference Dprain1 based on the weather forecast information W1A and W2A without using the learning model Md, or may be configured to acquire the estimated precipitation difference Dprain1 from a device external to the power transmission line management device 301. The estimation unit 35 may be configured to calculate the estimated precipitation difference Dprain2 based on the weather forecast information W1B and W2B without using the learning model Md, or may be configured to acquire the estimated precipitation difference Dprain2 from a device external to the power transmission line management device 301.

[0176] In the power transmission line management device 301 according to the embodiment of the present disclosure, the calculation unit 33 is configured to calculate the actual temperature calculated values Tac1 and Tac2 based on the air temperature, wind speed, and solar radiation indicated by the sensor information S3 and the current value indicated by the sensor information S1, but this is not limited to this. The calculation unit 33 may be configured to calculate the actual temperature calculated values Tac1 and Tac2 based on the current value indicated by the power generation result received from a power generation device (not shown) instead of the current value indicated by the sensor information S1.

[0177] <Modification> In the power transmission line management device 301 according to the embodiment of the present disclosure, the estimation unit 35 is configured to estimate the temperatures of the power transmission lines 1A and 1B based on the sensor information S3 and S4 and the value of the current flowing through the power transmission lines 1A and 1B, but this is not limited thereto. The estimation unit 35 may also be configured to estimate the temperatures of the power transmission lines 1A and 1B taking into account the wind direction.

[0178] For example, the weather sensor 211 further measures the wind direction indicative of the environment of the steel tower 2A, specifically, the wind direction based on the direction perpendicular to the power transmission line 1A. Also, for example, the weather sensor 212 further measures the wind direction indicative of the environment of the steel tower 2B, specifically, the wind direction based on the direction perpendicular to the power transmission line 1B. In this case, the collecting device 251 includes sensor information S3x further indicating the measurement result of the wind direction by the weather sensor 211 in the collected information CD1 instead of the sensor information S3, and transmits this information to the power transmission line management device 301. Also, the collecting device 252 includes sensor information S3x further indicating the measurement result of the wind direction by the weather sensor 212 in the collected information CD2 instead of the sensor information S3, and transmits this information to the power transmission line management device 301.

[0179] In this case, in the power transmission line management device 301, the receiver 31 acquires the sensor information S3x from each of the collected information CD1 and CD2 and stores it in the storage unit .

[0180] Instead of the weather forecast information W1A, the forecast information acquisition unit 32 acquires weather forecast information W1Ax that further indicates the forecast results of the wind direction in an area including the position of the steel tower 2A, and stores this in the memory unit 36. Moreover, instead of the weather forecast information W1B, the forecast information acquisition unit 32 acquires weather forecast information W1Bx that further indicates the forecast results of the wind direction in an area including the position of the steel tower 2B, and stores this in the memory unit 36.

[0181] The creation unit 34 uses the sensor information S3x acquired by the receiving unit 31 to calculate the average wind direction Av3 at three or more measurement times tm within a target period of a predetermined length T1 from the (nk)th measurement time tm(nk) to the nth measurement time tmn. Similarly, the creation unit 34 calculates the average wind direction Av3 at three or more measurement times tm within a target period of length T1 from the measurement time tm(n-k+1) to the measurement time tm(n+1). The creation unit 34 creates time series data TDA3 consisting of multiple time series average values Av3 by shifting the measurement time tm, which is the start point of the target period, by one. Then, the creation unit 34 creates a learning model Mdx using the time series data TDA1, TDA2, TDA3, TDA4, TDA5, and TDA6, which are explanatory variables, and the time series data TDrain, which is a target variable.

[0182] Calculation unit 33 calculates actual temperature calculated value Tac1 based on sensor information S3x instead of sensor information S3. More specifically, calculation unit 33 calculates actual temperature calculated value Tac1A at a certain measurement time tm based on the air temperature, wind speed, wind velocity, and amount of solar radiation at the same measurement time tm indicated by sensor information S3x and the value of the current flowing through power transmission line 1AU at the same measurement time tm indicated by sensor information S1, according to a calculation method described, for example, in Non-Patent Document 1. Calculation unit 33 similarly calculates actual temperature calculated values Tac1B and Tac1C based on sensor information S3x instead of sensor information S3.

[0183] Furthermore, calculation unit 33 calculates actual temperature calculated value Tac2 based on sensor information S3x instead of sensor information S3. More specifically, calculation unit 33 calculates actual temperature calculated value Tac2A at a certain measurement time tm based on the air temperature, wind speed, wind velocity, and amount of solar radiation at the same measurement time tm indicated by sensor information S3x and the value of the current flowing through power transmission line 1BU at the same measurement time tm indicated by sensor information S1, according to a calculation method described, for example, in Non-Patent Document 1. Calculation unit 33 similarly calculates actual temperature calculated values Tac2B and Tac2C based on sensor information S3x instead of sensor information S3.

[0184] The estimation unit 35 estimates the temperatures of the power transmission lines 1A and 1B using the above-described method based on the sensor information S3x instead of the sensor information S3.

[0185] However, a technology capable of more accurately estimating the temperature of a power transmission line is desired. Conventionally, the transmission capacity of a power transmission line is determined to a value within a range in which the temperature of the power transmission line is equal to or lower than a predetermined allowable temperature. However, conventional methods for estimating the temperature of a power transmission line estimate the temperature of the power transmission line under assumed environmental conditions that are more severe than the actual condition, without taking into account the cooling effect of precipitation on the power transmission line. Therefore, the transmission capacity determined based on the estimation result is an underestimated value.

[0186] In recent years, the expansion of renewable energy has led to a significant problem of insufficient transmission capacity. Therefore, it is desirable to estimate the temperature of transmission lines more accurately and determine the appropriate transmission capacity based on the estimation results.

[0187] In contrast, in the power transmission line management device 301 according to the embodiment of the present disclosure, the receiver 31 acquires sensor information S3 indicating the temperature, wind speed, and amount of solar radiation, and sensor information S4 indicating the amount of precipitation. The estimator 35 estimates the temperature of the power transmission line based on the sensor information S3 and S4 acquired by the receiver 31 and the value of the current flowing through the power transmission line.

[0188] In this way, by estimating the temperature of a power line based on the amount of precipitation in addition to the air temperature, wind speed, solar radiation, and current flowing through the power line, the temperature of the power line can be estimated taking into account the cooling effect of precipitation on the power line. This allows for more accurate estimation of the power line temperature. Furthermore, a more appropriate transmission capacity of the power line can be determined based on the more accurately estimated power line temperature. Therefore, for example, by performing dynamic line rating, the rate of increase in transmission capacity can be further improved compared to static line rating.

[0189] The above-described embodiments should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the above description, and is intended to include all modifications within the meaning and scope of the claims.

[0190] Each process (each function) in the above-described embodiments is realized by a processing circuit including one or more processors. The processing circuit may be configured as an integrated circuit or the like that combines one or more memories, various analog circuits, and various digital circuits in addition to the one or more processors. The one or more memories store programs (instructions) that cause the one or more processors to execute each of the processes. The one or more processors may execute each of the processes according to the program read from the one or more memories, or according to a logic circuit pre-designed to execute each of the processes. The processor may be various processors suitable for computer control, such as a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), a field programmable gate array (FPGA), and an application-specific integrated circuit (ASIC). Note that the physically separate processors may cooperate with each other to execute each of the processes. For example, the processors mounted on a plurality of physically separated computers may cooperate with each other to execute the above processes via a network such as a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, etc. The program may be installed into the memory from an external server device or the like via the network, or may be distributed in a state stored on a recording medium such as a CD-ROM (Compact Disc Read Only Memory), a DVD-ROM (Digital Versatile Disc Read Only Memory), or a semiconductor memory, and installed into the memory from the recording medium.

[0191] The above description includes the following additional features. [Appendix 1] a first acquisition unit that acquires meteorological data indicating temperature, wind speed, and solar radiation; a second acquisition unit that acquires precipitation data indicating an amount of precipitation; an estimation unit that estimates a temperature of the power transmission line based on the weather data acquired by the first acquisition unit, the precipitation data acquired by the second acquisition unit, and a value of a current flowing through the power transmission line, The estimation unit predicts a temperature of the power transmission line, and calculates a transmission capacity of the power transmission line based on a prediction result.

[0192] [Appendix 2] a processing circuit; The processing circuitry Obtain weather data showing temperature, wind speed and solar radiation, Obtain precipitation data showing the amount of precipitation, a power transmission line management device that estimates a temperature of the power transmission line based on the weather data acquired by the first acquisition unit, the precipitation data acquired by the second acquisition unit, and a value of a current flowing through the power transmission line; [Explanation of symbols]

[0193] 1A, 1AU, 1AV, 1AW power transmission lines 1B, 1BU, 1BV, 1BW transmission lines 2A, 2B towers 3A,3B line 31 receiving unit (first acquisition unit, second acquisition unit, fourth acquisition unit, fifth acquisition unit) 32 prediction information acquisition unit (first acquisition unit, second acquisition unit) 33 calculation unit (third acquisition unit, difference calculation unit) 34 Creation Department 35 Estimation part 36 Memory section 101, 101A, 101B, 101C contact unit 102, 102A, 102B, 102C contact unit 111, 111A, 111B, 111C Current Sensor 112, 112A, 112B, 112C Current Sensors 121, 121A, 121B, 121C temperature sensors 151, 151A, 151B, 151C Transfer Device 152, 152A, 152B, 152C Transfer Device 201,202 Collection Unit 211,212 Weather Sensor 251,252 Collection device 301 Power transmission line management equipment 401 Power Transmission Line Management System

Claims

1. a first acquisition unit that acquires meteorological data indicating temperature, wind speed, and solar radiation; a second acquisition unit that acquires precipitation data indicating an amount of precipitation; an estimation unit that estimates a temperature of the power transmission line based on the weather data acquired by the first acquisition unit, the precipitation data acquired by the second acquisition unit, and a value of a current flowing through the power transmission line; a third acquisition unit that acquires a first calculated temperature value, which is a calculated value of the temperature, calculated based on the meteorological data and the value of the current; a fourth acquisition unit that acquires the temperature measurement result; a difference calculation unit that calculates a first difference that is a difference between the first calculated temperature value at a first time acquired by the third acquisition unit and a measurement result of the temperature at the first time acquired by the fourth acquisition unit, the estimation unit estimates the temperature at the first target time based on the weather data at a first target time different from the first time acquired by the first acquisition unit, the precipitation data at the first target time acquired by the second acquisition unit, the first temperature calculation value at the first target time acquired by the third acquisition unit, and the first difference calculated by the difference calculation unit.

2. The power transmission line management device further a fifth acquisition unit that acquires current data that is a measurement result of the current; a creation unit that creates a learning model for estimating a temperature decrease amount of the power transmission line due to precipitation, using the weather data, the precipitation amount data, the first difference, and the current data acquired by the fifth acquisition unit; the estimation unit obtains a first estimated value, which is an estimated value of the temperature decrease amount at the first target time, using the weather data at the first target time, the precipitation data at the first target time, the current value at the first target time, and the learning model; The power transmission line management device according to claim 1 , wherein the estimation unit estimates the temperature at the first target time based on the acquired first estimated value and the first calculated temperature value at the first target time.

3. the difference calculation unit further calculates a second difference which is a difference between the first calculated temperature value at a second time when precipitation has stopped, which is acquired by the third acquisition unit, and the temperature measurement result at the second time, which is acquired by the fourth acquisition unit; The power transmission line management device according to claim 2 , wherein the estimation unit estimates the temperature further based on the second difference calculated by the difference calculation unit.

4. the third acquisition unit further acquires a second temperature calculation value that is a calculation value of the temperature of the other power transmission line, the second temperature calculation value being calculated based on the weather data and a value of the current flowing through the other power transmission line; the estimation unit obtains a second estimated value, which is an estimate of the amount of temperature decrease at the second target time, using the weather data at the second target time, the precipitation data at the second target time, the value of the current flowing through the other power transmission line at the second target time, and the learning model; 4. The power transmission line management device according to claim 2, wherein the estimation unit further estimates the temperature of the other power transmission line at the second target time based on the second temperature calculation value at the second target time and the second estimated value acquired by the third acquisition unit.

5. A method for estimating a power transmission line temperature in a power transmission line management device, comprising: obtaining weather data indicative of temperature, wind speed and solar radiation; obtaining precipitation data indicative of an amount of precipitation; estimating a temperature of the power line based on the acquired weather data, the acquired precipitation data, and a value of a current flowing through the power line; obtaining a first temperature calculation value, the first temperature calculation value being a calculation value of the temperature, calculated based on the meteorological data and the value of the current; obtaining the temperature measurement; calculating a first difference between the first calculated temperature value at the acquired first time and the temperature measurement result at the acquired first time, a power transmission line temperature estimation method, in which, in the step of estimating the temperature of the power transmission line, the temperature at the first target time is estimated based on the acquired weather data at a first target time different from the first time, the acquired precipitation data at the first target time, the acquired first temperature calculation value at the first target time, and the calculated first difference.

6. A power transmission line temperature estimation program used in a power transmission line management device, Computer, a first acquisition unit that acquires meteorological data indicating temperature, wind speed, and solar radiation; a second acquisition unit that acquires precipitation data indicating an amount of precipitation; an estimation unit that estimates a temperature of the power transmission line based on the weather data acquired by the first acquisition unit, the precipitation data acquired by the second acquisition unit, and a value of a current flowing through the power transmission line; a third acquisition unit that acquires a first calculated temperature value, which is a calculated value of the temperature, calculated based on the meteorological data and the value of the current; a fourth acquisition unit that acquires the temperature measurement result; a difference calculation unit that calculates a first difference that is a difference between the first calculated temperature value at the first time acquired by the third acquisition unit and the temperature measurement result at the first time acquired by the fourth acquisition unit; It is a program to function as the estimation unit estimates the temperature at the first target time based on the weather data at a first target time different from the first time acquired by the first acquisition unit, the precipitation data at the first target time acquired by the second acquisition unit, the first temperature calculation value at the first target time acquired by the third acquisition unit, and the first difference calculated by the difference calculation unit.

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