Power transmission capacity estimation device and power transmission capacity estimation method

Abstract

To provide a power transmission capacity estimation device capable of achieving flexible operation of a power transmission line with a simple configuration.SOLUTION: Power transmission capacity estimation device 100 includes acquisition section 110 that acquires first temperature prediction data and second temperature prediction data in a predetermined area in a first period before a predetermined time point and a second period after the predetermined time point, and actual temperature data in the predetermined area in the first period, calculation section 120 that calculates a maximum temperature estimation value of a power transmission line in the predetermined area in the second period and calculates a reduction ratio for reducing a power transmission capacity such that the maximum temperature estimation value is equal to or less than an allowable value, and correction section 130 that corrects the second temperature prediction data using the first temperature prediction data and the actual temperature data and calculates second temperature correction data. 140.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a power transmission capacity estimation device and a power transmission capacity estimation method for estimating the operable capacity of a power transmission line. [Background technology]

[0002] Conventionally, there are known techniques for calculating the operational capacity of a transmission line. For example, Patent Document 1 discloses a device that calculates the current capacity of an overhead transmission line for each sensor using the temperature, wind speed, and solar radiation measured by a plurality of sensors along a transmission line route on which the overhead transmission line is installed, and outputs the minimum value of the calculated current capacities as the current capacity of the overhead transmission line (operational capacity of the transmission line). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2009-65796 Summary of the Invention [Problem to be solved by the invention]

[0004] In the above-mentioned conventional technology, multiple sensors are attached to the transmission line route to measure temperature and other factors, and the operational capacity of the transmission line is calculated based on the local conditions. However, the above-mentioned conventional technology requires the attachment of multiple sensors to the transmission line route, resulting in a complex configuration. Furthermore, while the above-mentioned conventional technology calculates the operational capacity of the transmission line based on the current conditions, such as temperature, the operational capacity of the transmission line in the future is unknown, which may hinder flexible operation.

[0005] The present invention was made by the inventor of the present application with a new focus on the above-mentioned problem, and aims to provide a transmission capacity estimation device and a transmission capacity estimation method that have a simple configuration and can achieve flexible operation of transmission lines. [Means for solving the problem]

[0006] In order to achieve the above object, a transmission capacity estimation device according to one embodiment of the present invention is a transmission capacity estimation device that estimates a transmission capacity, which is the operational capacity of a transmission line, and includes: an acquisition unit that acquires first temperature forecast data indicating a predicted value of the temperature in a specified area for a first period before a predetermined point in time; second temperature forecast data indicating a predicted value of the temperature in the specified area for a second period after the predetermined point in time; and actual temperature data indicating an actual value of the temperature in the specified area for the first period; a calculation unit that calculates an estimated maximum temperature of the transmission line in the specified area for the second period and calculates a reduction ratio, which is a ratio by which the transmission capacity is reduced so that the estimated maximum temperature is equal to or less than an allowable value; a correction unit that corrects the second temperature forecast data using the first temperature forecast data and the actual temperature data and calculates second temperature corrected data, which is the corrected second temperature forecast data; and an estimation unit that calculates the transmission capacity in the specified area for the second period using the second temperature corrected data, and estimates the transmission capacity in the specified area for the second period by reducing the calculated transmission capacity using the reduction ratio.

[0007] According to this method, the power transmission capacity estimation device acquires first temperature forecast data for a first period, second temperature forecast data for a second period, and actual temperature data for the first period. For example, the power transmission capacity estimation device acquires first temperature forecast data and second temperature forecast data from the Japan Meteorological Agency's Mesoscale Model (MSM) or the like, and acquires actual temperature data from AMeDAS, thereby eliminating the need to install multiple sensors along the power transmission line route to acquire each data. Furthermore, the power transmission capacity estimation device corrects the second temperature forecast data using the first temperature forecast data and the actual temperature data to calculate second corrected temperature data, and then calculates the power transmission capacity for the second period using the second corrected temperature data. This allows the power transmission capacity estimation device to calculate the power transmission capacity for the second period with relatively high accuracy. Furthermore, the power transmission capacity estimation device calculates a reduction ratio for reducing the power transmission capacity so that the estimated maximum temperature of the power transmission line is equal to or less than the allowable value, and estimates the power transmission capacity for the second period by reducing the calculated power transmission capacity using the reduction ratio. In other words, it is preferable to reduce the calculated transmission capacity to be on the safe side, but reducing the transmission capacity too much would hinder flexible operation of the transmission line, so the transmission capacity is reduced at least so that the estimated maximum temperature of the transmission line is below the allowable value. This allows the transmission capacity estimation device to accurately estimate the transmission capacity in a specified area during the second period without reducing it too much, allowing flexible operation of the transmission line based on the estimated transmission capacity. Therefore, the transmission capacity estimation device enables flexible operation of the transmission line with a simple configuration.

[0008] The calculation unit may calculate a thermal degradation rate of the power transmission line from the maximum temperature estimate value, and calculate the reduction rate so that the thermal degradation rate is equal to or less than an allowable value.

[0009] According to this, the power transmission capacity estimation device calculates the thermal degradation rate of the power transmission line from the estimated maximum temperature of the power transmission line, and calculates the reduction rate so that the thermal degradation rate is equal to or less than the allowable value, thereby calculating the reduction rate that takes the thermal degradation rate of the power transmission line into consideration. As a result, the power transmission capacity estimation device can accurately estimate the power transmission capacity in a predetermined area during the second time period, taking the thermal degradation rate of the power transmission line into consideration.

[0010] The calculation unit may calculate, as the reduction rate, a rate at which the estimated maximum current value of the power transmission line is reduced so that the estimated maximum temperature value becomes equal to or less than an allowable value.

[0011] According to this, the transmission capacity estimation device can easily calculate the reduction ratio by calculating the ratio by which the estimated maximum current value of the transmission line is reduced so that the estimated maximum temperature value of the transmission line becomes equal to or less than the allowable value.

[0012] The calculation unit may also calculate an allowable current value of the power transmission line using the first temperature forecast data, and calculate the maximum current estimation value using the allowable current value.

[0013] According to this, the power transmission capacity estimation device can easily calculate the estimated maximum current value by calculating the allowable current value of the power transmission line using the first temperature forecast data and then calculating the estimated maximum current value of the power transmission line.

[0014] In addition, the correction unit may calculate the second temperature correction data using a temperature prediction model obtained from the first temperature prediction data and the actual temperature data, and the calculation unit may correct the first temperature prediction data using the temperature prediction model, calculate first temperature correction data which is the corrected first temperature prediction data, and calculate the allowable current value using the first temperature correction data.

[0015] According to this, the power transmission capacity estimation device can calculate the second temperature corrected data with relatively high accuracy by using a temperature prediction model obtained from the first temperature prediction data and the actual temperature data to calculate the second temperature corrected data. Furthermore, the power transmission capacity estimation device can calculate the allowable current value of the power transmission line with relatively high accuracy by correcting the first temperature prediction data using the temperature prediction model to calculate the first temperature corrected data, and calculating the allowable current value of the power transmission line using the first temperature corrected data.

[0016] The calculation unit may calculate the estimated maximum temperature value using the estimated maximum current value and the actual air temperature data.

[0017] According to this, the power transmission capacity estimation device calculates the estimated maximum temperature of the power transmission line using the estimated maximum current value of the power transmission line and the actual temperature data, thereby being able to calculate the estimated maximum temperature value with relatively high accuracy.

[0018] The calculation unit may calculate the estimated maximum temperature value by further using observation data indicating at least one of wind speed and solar radiation in the predetermined area during the first period.

[0019] The temperature of a power transmission line is also affected by wind speed or solar radiation. For example, a high wind speed around the power transmission line reduces the power line temperature, while a high amount of solar radiation increases the power line temperature. For this reason, the power transmission capacity estimation device calculates an estimated maximum temperature of the power transmission line by further using observation data indicating at least one of wind speed and solar radiation. This allows the power transmission capacity estimation device to calculate the estimated maximum temperature with relatively high accuracy.

[0020] The estimation unit may estimate the power transmission capacity by further using a predicted value of at least one of a wind speed and an amount of solar radiation in the predetermined area during the second time period.

[0021] The power transmission capacity is also affected by wind speed or solar radiation. For example, high wind speed around a power transmission line reduces the temperature of the power transmission line, while high solar radiation increases the temperature of the power transmission line, thereby affecting the power transmission capacity. For this reason, the power transmission capacity estimation device estimates the power transmission capacity by further using a predicted value of at least one of wind speed and solar radiation. This allows the power transmission capacity estimation device to calculate the power transmission capacity in a specified area during the second time period with relatively high accuracy.

[0022] Furthermore, the present invention can be realized not only as such a power transmission capacity estimation device, but also as a power transmission capacity estimation method having steps corresponding to characteristic processes performed by a processing unit included in the power transmission capacity estimation device. The present invention can also be realized as a program for causing a computer to execute the steps included in the power transmission capacity estimation method, or as a computer-readable recording medium such as a CD-ROM on which the program is recorded. The program can then be distributed via the recording medium or a transmission medium such as the Internet. The present invention can also be realized as an integrated circuit including a processing unit included in the power transmission capacity estimation device. [Effects of the Invention]

[0023] According to the power transmission capacity estimation device and the like according to the present invention, flexible operation of power transmission lines can be achieved with a simple configuration. [Brief explanation of the drawings]

[0024] [Figure 1] 2 is a diagram illustrating a connection relationship between a power transmission capacity estimation device and a meteorological data management device according to an embodiment. FIG. [Figure 2] 1 is a block diagram showing a functional configuration of a power transmission capacity estimation device according to an embodiment. [Figure 3A] 4 is a diagram showing an example of first temperature forecast data or second temperature forecast data included in weather forecast data stored in a storage unit of the power transmission capacity estimation device according to the embodiment. FIG. [Figure 3B] 5 is a diagram showing an example of actual temperature data included in meteorological observation data stored in a storage unit of the power transmission capacity estimation device according to the embodiment; FIG. [Figure 4] 1 is a flowchart showing a process (a method for estimating a power transmission capacity) in which the power transmission capacity estimation device according to the embodiment estimates a power transmission capacity, which is an operable capacity of a power transmission line. [Figure 5] 10 is a flowchart illustrating a process for calculating a reduction ratio by a calculation unit according to an embodiment. [Figure 6]10 is a flowchart showing a process in which a correction unit according to an embodiment calculates second air temperature correction data. [Figure 7] 10 is a flowchart illustrating a process in which an estimation unit according to an embodiment estimates a power transmission capacity. DETAILED DESCRIPTION OF THE INVENTION

[0025] Hereinafter, a power transmission capacity estimation device and a power transmission capacity estimation method according to embodiments of the present invention (including variations thereof) will be described with reference to the drawings. Note that the embodiments described below all show comprehensive or specific examples. The numerical values, components, arrangement and connection of components, steps, order of steps, etc. shown in the following embodiments are merely examples and are not intended to limit the present invention.

[0026] (Embodiment) [1. Description of the Configuration of the Power Transmission Capacity Estimation Device 100] First, the configuration of the power transmission capacity estimation device 100 will be described. Fig. 1 is a diagram showing the connection relationship between the power transmission capacity estimation device 100 according to the present embodiment and a meteorological data management device 200. Fig. 2 is a block diagram showing the functional configuration of the power transmission capacity estimation device 100 according to the present embodiment. Fig. 3A is a diagram showing an example of first temperature forecast data or second temperature forecast data included in the meteorological forecast data 161 stored in the storage unit 160 of the power transmission capacity estimation device 100 according to the present embodiment. Fig. 3B is a diagram showing an example of actual temperature data included in the meteorological observation data 162 stored in the storage unit 160 of the power transmission capacity estimation device 100 according to the present embodiment.

[0027] The power transmission capacity estimation device 100 is a device that estimates the transmission capacity, which is the operational capacity of a power transmission line. A power transmission line is an overhead high-voltage power line (high-voltage line) that transmits power generated by a power generation facility such as a power plant to a substation, a distribution station, or a consumer, and is installed, for example, on a commercial power grid operated by a power company. The operational capacity (transmission capacity) of a power transmission line is the amount of power (e.g., MW) that can be supplied by the power transmission line during operation, and varies depending on factors such as the ambient temperature around the power transmission line. In other words, to avoid a decrease in the strength of the power transmission line due to heat (thermal degradation), it is desirable to keep the temperature of the power transmission line below a certain level. However, if the ambient temperature around the power transmission line is high, the temperature of the power transmission line is likely to rise. Therefore, the upper limit of the current is lowered to reduce the transmission capacity in order to keep the temperature of the power transmission line below a certain level.

[0028] 1 and 2, the power transmission capacity estimation device 100 is a computer connected to a meteorological data management device 200 via a communication network 300, and acquires information from the meteorological data management device 200 to estimate the power transmission capacity. The power transmission capacity estimation device 100 may be realized by a general-purpose computer system such as a personal computer executing a program, or may be realized by a dedicated computer system. The communication network 300 is a computer network such as the Internet, including a wired or wireless LAN (Local Area Network).

[0029] The meteorological data management device 200 is a device that stores information about meteorology, such as temperature, wind speed, and solar radiation at a specific time and location. For example, the meteorological data management device 200 is a device such as a computer installed in the Japan Meteorological Agency, or a device such as a computer that acquires data from the Japan Meteorological Agency. As shown in FIG. 1 , the meteorological data management device 200 includes a weather forecast data storage unit 210 and an AMeDAS data storage unit 220.

[0030] The weather forecast data storage unit 210 is a memory or the like that stores (stores) data forecasted by the Japan Meteorological Agency's Mesoscale Model (MSM) and Global Surface Model (GSM), etc. The Mesoscale Model (MSM) divides the entire area of ​​Japan into horizontal 5-km meshes, and each mesh contains information on temperature, wind speed, solar radiation, precipitation, altitude, etc., for 39 cross sections, with each cross section being on the hour. Specifically, the Mesoscale Model (MSM) is a model that can forecast weather phenomena using information on temperature, wind speed (east-west wind components, north-south wind components), solar radiation, precipitation, altitude, atmospheric pressure, humidity, cloud cover, etc., with a horizontal resolution of 5 km mesh (approximately 10 km mesh for pressure surfaces), prediction time periods of up to 39 hours in one-hour intervals for the ground and up to 39 hours in three-hour intervals for the pressure surfaces, and an update frequency of every three hours (eight times a day). The Global Spherical Model (GSM) divides the entire Earth into horizontal 20km meshes, and each mesh contains information on temperature, wind speed, solar radiation, precipitation, altitude, etc., with one cross section at every hour, for a total of 132 cross sections (132 hours' worth of data at every hour). Specifically, the Global Spherical Model (GSM) is a model that can predict weather phenomena using information on temperature, wind speed (east-west wind components, north-south wind components), solar radiation, precipitation, altitude, atmospheric pressure, humidity, cloud cover, etc., with a horizontal resolution of 20km mesh, prediction time periods of one hour up to 84 hours ahead (surface), three hourly up to 84 hours ahead (pressure surface), three hourly up to 132 hours ahead (surface), and six hourly up to 132 hours ahead (pressure surface), and is updated every six hours (four times a day).

[0031] Specifically, the weather forecast data storage unit 210 stores weather forecast data 211. The weather forecast data 211 is a collection of data including predicted values ​​of weather information such as temperature, wind speed, solar radiation, precipitation, altitude, atmospheric pressure, humidity, and cloud cover. The weather forecast data 211 includes data on these weather information predicted by the above-mentioned mesoscale model (MSM), global scale model (GSM), etc. It is preferable that the weather forecast data 211 includes at least data predicted by the mesoscale model (MSM), and more preferably includes both data predicted by the mesoscale model (MSM) and data predicted by the global scale model (GSM).

[0032] The AMeDAS data storage unit 220 is a memory or the like that stores (stores) data observed by the Japan Meteorological Agency's AMeDAS (regional weather observation system). The AMeDAS data storage unit 220 can acquire data every hour from each AMeDAS with a delivery delay of about several minutes. The AMeDAS data storage unit 220 stores meteorological observation data 221. The meteorological observation data 221 is a collection of data including observed values ​​of meteorological information such as temperature, wind speed, wind direction, sunshine hours, and precipitation. The meteorological observation data 221 contains hourly data on these meteorological information at each AMeDAS observation point.

[0033] The power transmission capacity estimation device 100 acquires weather forecast data 211 and weather observation data 221 from the weather data management device 200 via the communication network 300. Then, the power transmission capacity estimation device 100 estimates the power transmission capacity, which is the operable capacity of the power transmission line, using the weather forecast data 211 and the weather observation data 221. The specific configuration of this power transmission capacity estimation device 100 will be described in detail below.

[0034] 2, the power transmission capacity estimation device 100 includes an acquisition unit 110, a calculation unit 120, a correction unit 130, an estimation unit 140, an output unit 150, and a storage unit 160. As shown in FIG. 1, the power transmission capacity estimation device 100 also includes input units such as a keyboard and a mouse, and a display unit such as a liquid crystal display, but detailed description of these will be omitted.

[0035] The acquiring unit 110 acquires the weather forecast data 211 and the weather observation data 221. Specifically, the acquiring unit 110 acquires the weather forecast data 211 and the weather observation data 221 from the weather data management device 200 via the communication network 300.

[0036] As described above, the weather forecast data 211 is a collection of data including predicted temperatures. Therefore, the weather forecast data 211 includes predicted temperatures in a predetermined area for a first period before a predetermined time point (e.g., one year from the present time) and predicted temperatures in a predetermined area for a second period after the predetermined time point (e.g., from one hour before the present time to 36 hours after the present time). The predetermined area may be an area of ​​any size, but may be, for example, an area based on the Japan Meteorological Agency's primary subdivisions (areas for which weather forecasts are issued), such as the Osaka Prefecture area, the northern Hyogo Prefecture area, or the southern Hyogo Prefecture area. The same applies below. Thus, the weather forecast data 211 includes first temperature forecast data indicating predicted temperatures in the predetermined area for a first period before the predetermined time point, and second temperature forecast data indicating predicted temperatures in the predetermined area for a second period after the predetermined time point. In other words, the acquisition unit 110 acquires first temperature forecast data indicating predicted temperatures in the predetermined area for a first period before the predetermined time point, and second temperature forecast data indicating predicted temperatures in the predetermined area for a second period after the predetermined time point.

[0037] The first temperature forecast data includes, for example, data collected over a first period (e.g., one year from the present time) of predicted temperatures for the past 39 hours at each location in a specified area (five locations A to E in FIG. 3A ) predicted using a mesoscale model (MSM), as shown in FIG. 3A . The first temperature forecast data may also include data collected over a first period of time of predicted temperatures for the past 132 hours at each location in a specified area predicted using a global surface model (GSM). Similarly, the second temperature forecast data includes, for example, data indicating predicted temperatures for a second period (e.g., one hour from the present time to 36 hours from the present time) at each location in a specified area (five locations A to E in FIG. 3A ).

[0038] Furthermore, as described above, the weather forecast data 211 also includes predicted values ​​of wind speed, solar radiation, etc. In other words, the weather forecast data 211 further includes data indicating at least one predicted value of wind speed and solar radiation in a predetermined area for a first time period and a second time period. The data indicating the predicted values ​​of wind speed and solar radiation included in the weather forecast data 211 is also data corresponding to each location and each time period, as shown in FIG. 3A .

[0039] As described above, the meteorological observation data 221 is a collection of data including actual values ​​of temperature and the like. Therefore, the meteorological observation data 221 includes actual temperature data indicating actual values ​​of temperature in a predetermined area during a first period before a predetermined point in time (e.g., one year from the present time). That is, the acquiring unit 110 acquires actual temperature data indicating actual values ​​of temperature in a predetermined area during a first period before a predetermined point in time. The actual temperature data is, for example, data collected over a first period (e.g., one year from the present time) of actual temperature values ​​observed by AMeDAS at various locations in a predetermined area (five locations A to E in FIG. 3B ), as shown in FIG. 3B . If the meteorological observation data 221 includes five years' worth of actual temperature data, the actual temperature data is actual temperature data (AMeDAS observation data) for all time sections over the past five years (43,824 sections (= 24 hours × 365 days × 4 years + 24 hours × 366 days (leap year))).

[0040] Furthermore, the meteorological observation data 221 also includes observation values ​​such as wind speed and sunshine hours. That is, the meteorological observation data 221 further includes observation data indicating at least one of wind speed and solar radiation (sunshine hours) in a predetermined area during a first period. The observation data indicating wind speed, solar radiation (sunshine hours), etc. included in the meteorological observation data 221 is also data corresponding to each location and each time, as shown in FIG. 3B.

[0041] The acquiring unit 110 writes the acquired weather forecast data 211 and weather observation data 221 to the weather forecast data 161 and weather observation data 162 stored in the storage unit 160. That is, the acquiring unit 110 writes temperature forecast data such as the first temperature forecast data and the second temperature forecast data included in the weather forecast data 211, as well as data indicating forecast values ​​such as wind speed and solar radiation, into the weather forecast data 161, thereby updating the weather forecast data 161. Furthermore, the acquiring unit 110 writes actual temperature data included in the weather observation data 221, as well as observation data indicating wind speed and solar radiation (sunshine hours), into the weather observation data 162, thereby updating the weather observation data 162.

[0042] The calculation unit 120 calculates the estimated maximum temperature of the power line in a predetermined area during the second time period, and calculates a reduction ratio, which is a ratio by which the transmission capacity is reduced so that the estimated maximum temperature becomes equal to or less than the allowable value. Specifically, the calculation unit 120 calculates the thermal degradation rate of the power line from the estimated maximum temperature of the power line, and calculates a reduction ratio so that the thermal degradation rate of the power line becomes equal to or less than the allowable value. The calculation unit 120 calculates, as the reduction ratio, a ratio by which the estimated maximum current of the power line is reduced so that the estimated maximum temperature of the power line becomes equal to or less than the allowable value. The calculation unit 120 calculates an allowable current value of the power line using first temperature forecast data, and calculates an estimated maximum current value of the power line using the allowable current value. The calculation unit 120 corrects the first temperature forecast data using a temperature forecast model, calculates first temperature correction data, which is the corrected first temperature forecast data, and calculates an allowable current value of the power line using the first temperature correction data. The calculation unit 120 calculates the estimated maximum temperature of the power line using the estimated maximum current of the power line and actual temperature data. The calculation unit 120 further uses observation data indicating at least one of wind speed and solar radiation in a predetermined area during the first time period to calculate an estimated maximum temperature of the power transmission line. The above process performed by the calculation unit 120 will be described in more detail later.

[0043] In the above process performed by the calculation unit 120, the acquisition unit 110 first reads and acquires each piece of data, such as first temperature forecast data, written in the weather forecast data 161 of the storage unit 160, and each piece of data, such as actual temperature data, written in the weather observation data 162. The calculation unit 120 then creates a temperature forecast model using the acquired data. The calculation unit 120 then writes the created temperature forecast model into estimation data 163 stored in the storage unit 160 to update the estimation data 163. The calculation unit 120 also calculates a reduction ratio using the created temperature forecast model and observation data indicating at least one of the first temperature forecast data, actual temperature data, wind speed, and solar radiation acquired by the acquisition unit 110. The calculation unit 120 then writes the calculated reduction ratio into the estimation data 163 stored in the storage unit 160 to update the estimation data 163.

[0044] The correction unit 130 corrects the second temperature prediction data using the first temperature prediction data and the actual temperature data, and calculates second corrected temperature data, which is the corrected second temperature prediction data. Specifically, the correction unit 130 calculates the second corrected temperature data using a temperature prediction model obtained from the first temperature prediction data and the actual temperature data. A more detailed description of the above processing performed by the correction unit 130 will be given later.

[0045] In the above process performed by correction unit 130, first, acquisition unit 110 reads and acquires the second temperature forecast data written in weather forecast data 161 in storage unit 160. Correction unit 130 reads and acquires the temperature forecast model written in estimation data 163 in storage unit 160. Correction unit 130 then calculates second temperature corrected data using the acquired second temperature forecast data and temperature forecast model. Correction unit 130 then writes the calculated second temperature corrected data into estimation data 163 stored in storage unit 160, thereby updating estimation data 163.

[0046] The estimation unit 140 uses the second temperature correction data to calculate the power transmission capacity in the specified area for the second time period, and reduces the calculated power transmission capacity using the reduction ratio, thereby estimating the power transmission capacity in the specified area for the second time period. The estimation unit 140 further uses a predicted value of at least one of wind speed and solar radiation in the specified area for the second time period to estimate the power transmission capacity. The above processing performed by the estimation unit 140 will be described in more detail below.

[0047] In the above process performed by the estimation unit 140, first, the acquisition unit 110 reads and acquires at least one predicted value of wind speed and solar radiation amount written in weather forecast data 161 in the storage unit 160. The estimation unit 140 reads and acquires the second temperature correction data and the reduction ratio written in estimation data 163 in the storage unit 160. Then, the estimation unit 140 uses the acquired data to estimate the power transmission capacity in a predetermined area for a second time period. Then, the estimation unit 140 writes the estimated power transmission capacity into the estimation data 163 stored in the storage unit 160, thereby updating the estimation data 163.

[0048] The output unit 150 outputs the power transmission capacity estimated by the estimation unit 140. For example, the output unit 150 reads and acquires the estimated value of the power transmission capacity written in the estimation data 163 in the storage unit 160. Then, the output unit 150 transmits the acquired estimated value of the power transmission capacity to an external device. Alternatively, the output unit 150 outputs the estimated value of the power transmission capacity to a display unit such as a liquid crystal display provided in the power transmission capacity estimation device 100, and displays the estimated value of the power transmission capacity.

[0049] The storage unit 160 is a memory that stores data for estimating the transmission capacity, which is the operable capacity of a transmission line. Specifically, the storage unit 160 stores the above-mentioned weather forecast data 161, weather observation data 162, and estimation data 163. The weather forecast data 161 is a collection of data including each piece of data included in the weather forecast data 211. The weather observation data 162 is a collection of data including each piece of data included in the weather observation data 221. The estimation data 163 is a collection of a temperature forecast model, a reduction ratio, second temperature correction data, and other data that are generated in the process of the power transmission capacity estimation device 100 estimating the transmission capacity. Note that the weather forecast data 161, the weather observation data 162, and the estimation data 163 may be rewritten each time the data is updated, or the data may be accumulated.

[0050] [2. Description of the processing flow of the power transmission capacity estimation device 100] Next, a description will be given of a process for estimating a transmission capacity, which is the operable capacity of a transmission line, by the power transmission capacity estimation device 100. Fig. 4 is a flowchart showing a process (power transmission capacity estimation method) for estimating a transmission capacity, which is the operable capacity of a transmission line, by the power transmission capacity estimation device 100 according to this embodiment.

[0051] As shown in FIG. 4, first, the acquiring unit 110 acquires weather forecast data 211 and weather observation data 221 (S101, acquiring step). That is, the acquiring unit 110 acquires each data included in the weather forecast data 211 and the weather observation data 221 from the weather data management device 200 via the communication network 300. Specifically, the acquiring unit 110 acquires first temperature forecast data indicating a forecast value of the temperature in a predetermined area for a first time period before a predetermined time point, second temperature forecast data indicating a forecast value of the temperature in the predetermined area for a second time period after the predetermined time point, and temperature record data indicating a real-world value of the temperature in the predetermined area for the first time period. Furthermore, the acquiring unit 110 acquires data indicating a forecast value of at least one of wind speed and solar radiation amount in the predetermined area for the first time period and the second time period, and observation data indicating at least one of wind speed and solar radiation amount in the predetermined area for the first time period.

[0052] For example, the acquiring unit 110 acquires first temperature forecast data and the like for each point in time from the present time to the past five years (a period including a first period) for each point in a predetermined area (such as points A to E shown in FIG. 3A ) for which the temperature is to be predicted, which is included in the weather forecast data 211. The acquiring unit 110 also acquires second temperature forecast data and the like for each point in the predetermined area from 1 hour to 39 hours or 132 hours from the present time (a period including a second period), which is included in the weather forecast data 211. The acquiring unit 110 also acquires actual temperature data and the like for each point in the predetermined area from the present time to each point in the past five years (a period including a first period), which is included in the weather observation data 221.

[0053] The acquisition unit 110 writes each piece of data included in the acquired weather forecast data 211 and weather observation data 221 into the weather forecast data 161 and weather observation data 162 stored in the storage unit 160. Then, the acquisition unit 110 reads and acquires various pieces of data required for each subsequent process from the weather forecast data 161 and weather observation data 162 stored in the storage unit 160 (S101, acquisition step).

[0054] Then, the calculation unit 120 calculates the maximum temperature estimate value of the power transmission line in the predetermined area during the second time period, and calculates a reduction ratio, which is a ratio by which the power transmission capacity is reduced so that the maximum temperature estimate value becomes equal to or less than the allowable value (S102, calculation step). A detailed description of the process (S102) by the calculation unit 120 to calculate the reduction ratio will be given later.

[0055] Then, the correction unit 130 corrects the second temperature prediction data using the first temperature prediction data and the actual temperature data, and calculates second temperature correction data, which is the corrected second temperature prediction data (S103, correction step). A detailed description of the process (S103) in which the correction unit 130 calculates the second temperature correction data will be given later.

[0056] Then, the estimation unit 140 calculates the power transmission capacity in the predetermined area for the second time period using the second temperature correction data, and reduces the calculated power transmission capacity using the reduction ratio, thereby estimating the power transmission capacity in the predetermined area for the second time period (S104, estimation step). A detailed description of the process (S104) in which the estimation unit 140 estimates the power transmission capacity will be given later.

[0057] Then, the output unit 150 outputs the power transmission capacity estimated by the estimation unit 140 (S105, output step). For example, the output unit 150 transmits the power transmission capacity to an external device, or outputs it to a display unit such as a liquid crystal display of the power transmission capacity estimation device 100 to display the estimated value of the power transmission capacity. Specifically, the output unit 150 outputs a graph of the estimated value of the power transmission capacity, or a numerical value indicating the estimated value of the power transmission capacity. The output unit 150 may output various information acquired by the acquisition unit 110, the reduction ratio calculated by the calculation unit 120, or the second temperature corrected data calculated by the correction unit 130. For example, the output unit 150 may output a graph of the reduction ratio or the second temperature corrected data, or a numerical value indicating the reduction ratio or the second temperature corrected data.

[0058] The power transmission capacity estimation device 100 executes the above process for all areas for which the power transmission capacity is to be estimated, and estimates the power transmission capacity for all areas. In this way, the process of estimating the power transmission capacity, which is the operable capacity of the power transmission line, by the power transmission capacity estimation device 100 is completed.

[0059] Next, a detailed description will be given of the process (S102 in FIG. 4) performed by the calculation unit 120 to calculate the reduction ratio. Fig. 5 is a flowchart showing the process (S102 in FIG. 4) performed by the calculation unit 120 according to this embodiment to calculate the reduction ratio.

[0060] As shown in FIG. 5, first, the calculation unit 120 creates a temperature prediction model (S201). Specifically, the calculation unit 120 creates one temperature prediction model for each point in a predetermined area. In this embodiment, the temperature prediction model is a mathematical model such as a neural network. The calculation unit 120 creates the neural network model using various data such as the first temperature prediction data and actual temperature data acquired by the acquisition unit 110. The calculation unit 120 writes the created temperature prediction model (neural network model) for each point in the predetermined area into the estimation data 163 stored in the storage unit 160, and updates the estimation data 163.

[0061] In creating a neural network model, a machine learning model (using a neural network algorithm) is constructed using observed data such as actual temperature data as the dependent variable and predicted data such as first temperature forecast data as the explanatory variable. The explanatory variables used in the neural network model are ground data (pressure, temperature, humidity, east-west wind components, north-south wind components, low cloud cover, mid-level cloud cover, upper cloud cover, and total cloud cover) and pressure surface data (altitude, temperature, humidity, east-west wind components, and north-south wind components). Three-hourly pressure surface data is converted to hourly data using linear interpolation. Model creation involves standardizing the data, training using the holdout method (using three years of training data and two years of test data), and cross-validation to prevent overfitting (dividing the data into 100 parts and using 1% of that as validation data). Other processes commonly used in neural networks are also performed in model creation.

[0062] Furthermore, the neural network model is set so that the greater the amount of cloud cover, the lower the temperature, or vice versa, depending on the time of day. Specifically, this is as follows: The amount of cloud cover has an opposite effect on ground temperature during the day and at night. That is, during the day, a greater amount of cloud cover suppresses the rise in temperature, while at night, a greater amount of cloud cover suppresses the drop in temperature. For this reason, the neural network model performs data conversion using the following procedure. First, the sunrise and sunset times for a given year are calculated from the latitude and longitude of each point in a specified area. Then, the period from sunrise to sunset is defined as daytime, and the period from sunset to sunrise is defined as nighttime. Coefficients are then set for each time of day and night. The conversion formula is as follows:

[0063] Daytime: Converted value = (100 - cloud cover) x hourly coefficient x 1 Nighttime: Converted value = (100 - cloud cover) x hourly coefficient x (-1)

[0064] Next, the calculation unit 120 corrects the first temperature forecast data using the temperature forecast model and calculates first corrected temperature data, which is the corrected first temperature forecast data (S202). That is, the calculation unit 120 corrects the first temperature forecast data by applying (inputting) the first temperature forecast data acquired by the acquisition unit 110 to the temperature forecast model created in step S201, thereby calculating the first corrected temperature data obtained by correcting the first temperature forecast data. In this embodiment, the first corrected temperature data is the predicted temperature for x hours (1≦x≦36) ahead in a first period (from the present time to the past one year) at each point in a specified area. Hereinafter, the first corrected temperature data will be referred to as T(x,t) using x (1≦x≦36) and the elapsed time t (1≦t<8760) in one-hour increments from the initial date and time in the past one year. The definitions of x and t will be the same hereinafter.

[0065] Next, calculation unit 120 calculates the allowable current value of the power transmission line using the first temperature correction data (S203). Specifically, calculation unit 120 acquires the upper limit temperature of the power transmission line, and calculates the allowable current value of the power transmission line in a predetermined area for the first time period using the first temperature correction data calculated in step S202 and the predicted values ​​of wind speed and solar radiation acquired by acquisition unit 110. Calculation unit 120 may acquire the upper limit temperature of the power transmission line by reading it from data previously written in estimation data 163 in storage unit 160, or may acquire it externally, such as through user input, or may calculate it itself.

[0066] Below, we will define the upper limit temperature of the power transmission line (which varies depending on the type of power transmission line) as H max The predicted value of the allowable current value of the power line for the first period (from the present time to the past one year) up to x hours ahead (1≦x≦36) is referred to as L(x,t). The calculation unit 120 applies the first temperature correction data T(x,t), the predicted wind speed value W(x,t), the predicted amount of solar radiation S(x,t), and the upper limit temperature H of the power line to a predetermined allowable current value calculation formula f. max By substituting the above, the allowable current value L(x, t) is calculated as follows: As the allowable current value calculation formula f, a known mathematical formula (function) can be used as appropriate.

[0067] L(x,t)=f(T(x,t),W(x,t),S(x,t),H max )

[0068] Next, the calculation unit 120 calculates the estimated maximum current value of the power transmission line (S204). Specifically, the calculation unit 120 calculates the estimated maximum current value of the power transmission line in a predetermined area during a first period (the past one year from the present time) taking into account an error margin α (0≦α≦1). Hereinafter, the estimated maximum current value of the power transmission line will be referred to as I(x,t,α). The calculation unit 120 calculates the estimated maximum current value I(x,t,α) using the allowable current value L(x,t) and the error margin α as follows:

[0069] I(x,t,α)=L(x,t)×(1-α)

[0070] In this way, the calculation unit 120 uses the first temperature forecast data to calculate the allowable current value L(x, t) in a specified area for a first period (one year from the present time), and uses the allowable current value L(x, t) to calculate the maximum current estimate I(x, t, α) of the transmission line in the specified area for the first period.

[0071] Next, the calculation unit 120 calculates the estimated maximum temperature of the power line (S205). Specifically, the calculation unit 120 calculates the estimated maximum temperature of the power line using the estimated maximum current of the power line and the actual temperature data. The calculation unit 120 calculates the estimated maximum temperature of the power line using observation data indicating at least one of wind speed and solar radiation (in this embodiment, wind speed and solar radiation) in a predetermined area during a first period. That is, the calculation unit 120 calculates the estimated maximum temperature of the power line using the estimated maximum current of the power line calculated in step S204, actual temperature data for each point in the predetermined area during a first period (the past one year from the current time), and observation data indicating wind speed and solar radiation (which may be simulated observation data created using random numbers, etc.). The calculation unit 120 calculates the estimated maximum temperature of the power line in the predetermined area during the first period (the past one year from the current time).

[0072] Below, we will use the actual temperature data as real The observed data showing the wind speed is called W(t). real (t) is the observation data showing the amount of solar radiation. real The calculation unit 120 calculates the maximum temperature estimate value g by applying the actual temperature data T real (t), wind speed observation data W real (t), solar radiation observation data S real By substituting (t) and the maximum current estimation value I(x,t,α), the maximum temperature estimation value H(x,t,α) can be calculated as follows: The maximum temperature estimation value calculation formula g can be calculated backward from the allowable current value calculation formula f.

[0073] H(x,t,α)=g(T real (t),W real (t),S real (t),I(x,t,α))

[0074] Next, the calculation unit 120 calculates the thermal degradation rate of the power line from the estimated maximum temperature of the power line (S206). That is, the calculation unit 120 calculates the thermal degradation rate of the power line in the predetermined area in the first period (the past one year from the present time) from the estimated maximum temperature H(x, t, α) of the power line in the predetermined area in the first period (the past one year from the present time) calculated in step S205. Hereinafter, the thermal degradation rate calculated by the calculation unit 120 is referred to as R year (x, α) is called the thermal degradation rate R year (x, α) is the rate at which the power transmission line deteriorates due to heat over a one-year period (the rate at which the line deteriorates). The calculation unit 120 sorts H(x, t, α) for each pair of x and α in descending order, creates a duration curve, and calculates the thermal deterioration rate R year The calculation unit 120 calculates the thermal degradation rate R (x, t, α) at ​​which H(x, t, α) is maximized for the pair of x and α. year Calculated as (x, α).

[0075] Next, the calculation unit 120 calculates a reduction ratio so that the thermal degradation rate of the power transmission line is equal to or less than the allowable value (S207). Specifically, the calculation unit 120 calculates the allowable value (hereinafter referred to as R max ) is obtained, and the thermal degradation rate R calculated in step S206 is year (x,α) and for each x, R year (x, α)≦R max The minimum error margin α that satisfies m (x) is calculated. This error margin α m (x) is the thermal degradation rate of the transmission line R year This is the ratio by which the estimated maximum current I(x,t,α) of the transmission line is reduced so that (x,α) is equal to or less than the allowable value. Hereinafter, the reduction ratio α mThe calculation unit 120 may obtain the allowable value of the thermal degradation rate of the power transmission line by reading it from data previously written in the estimation data 163 in the storage unit 160, by externally obtaining it from a user's input, or by calculating it itself.

[0076] If the thermal degradation rate of a transmission line is high, there is a risk that the lifespan of the transmission line will be shorter than expected. Therefore, in order to protect the transmission line by keeping the thermal degradation rate below the allowable value, the maximum current estimate of the transmission line is reduced so that the maximum temperature estimate of the transmission line is below the allowable value. For this reason, the reduction ratio α m (x) can be said to be a ratio by which the estimated maximum current value I(x, t, α) of the power line is reduced so that the estimated maximum temperature value H(x, t, α) of the power line is equal to or less than the allowable value. In other words, the calculation unit 120 determines the ratio by which the estimated maximum current value of the power line is reduced so that the estimated maximum temperature value of the power line is equal to or less than the allowable value by the reduction ratio α m Calculate as (x).

[0077] Furthermore, the maximum temperature estimate H(x, t, α) is the maximum temperature estimate of the power line in the specified area in the first period (one year from the present time), but it can be assumed that it will be the same value in the second period (from one hour from the present time to 36 hours from the present time). Therefore, the calculation unit 120 calculates the maximum temperature estimate of the power line in the specified area in the second period by calculating the maximum temperature estimate H(x, t, α). Reduction ratio α m (x) is the ratio by which the estimated maximum current value of the transmission line is reduced, and therefore the ratio by which the transmission capacity is reduced. In other words, the reduction ratio α m (x) is the ratio by which the transmission capacity of the power transmission line is reduced so that the estimated maximum temperature of the power transmission line is equal to or less than the allowable value. Therefore, the calculation unit 120 calculates the estimated maximum temperature of the power transmission line in the predetermined area in the second time period, and calculates a reduction ratio α m The calculation unit 120 calculates the calculated reduction ratio α m (x) is written into estimation data 163 stored in storage unit 160, and estimation data 163 is updated.

[0078] In this way, the process in which the calculation unit 120 calculates the reduction ratio (S102 in FIG. 4) ends.

[0079] Next, the process (S103 in FIG. 4) by which the correction unit 130 calculates the second temperature correction data will be described in detail. Fig. 6 is a flowchart showing the process (S103 in FIG. 4) by which the correction unit 130 according to this embodiment calculates the second temperature correction data.

[0080] 6, first, the correction unit 130 acquires a temperature prediction model (S301). Specifically, the correction unit 130 reads and acquires the temperature prediction model (neural network model) written in the estimation data 163 in the storage unit 160.

[0081] Next, the correction unit 130 calculates second temperature corrected data (S302). Specifically, the correction unit 130 corrects the second temperature forecast data using the first temperature forecast data and the actual temperature data, and calculates second corrected temperature data, which is the corrected second temperature forecast data. Even more specifically, the correction unit 130 calculates the second corrected temperature data using a temperature forecast model obtained from the first temperature forecast data and the actual temperature data. In other words, the correction unit 130 corrects the second temperature forecast data by applying (inputting) the second temperature forecast data acquired by the acquisition unit 110 to the temperature forecast model acquired in step S301, and calculates second corrected temperature data in which the second temperature forecast data has been corrected.

[0082] In this embodiment, the second temperature correction data is the predicted temperature for a second period (from one hour from the present time to 36 hours from the present time) at each location in a specified area. In other words, the second temperature correction data is the predicted temperature for x hours from the present time (1≦x≦36, in one-hour increments), and hereinafter, the second temperature correction data will be referred to as T(x). If multiple second temperature correction data T(x) exist for one location, the correction unit 130 uses the second temperature correction data T(x) with the highest temperature. The correction unit 130 then writes the calculated second temperature correction data T(x) into the estimation data 163 stored in the memory unit 160, thereby updating the estimation data 163.

[0083] In this manner, the process (S103 in FIG. 4) in which the corrector 130 calculates the second temperature corrected data is completed.

[0084] Next, a detailed description will be given of the process (S104 in FIG. 4) of estimating the power transmission capacity by the estimation unit 140. Fig. 7 is a flowchart showing the process (S104 in FIG. 4) of estimating the power transmission capacity by the estimation unit 140 according to this embodiment.

[0085] 7, first, the estimation unit 140 acquires the second temperature-corrected data (S401). Specifically, the estimation unit 140 reads and acquires the second temperature-corrected data T(x) written in the estimation data 163 in the storage unit 160.

[0086] Next, the estimation unit 140 calculates the allowable current value of the power transmission line in the predetermined area in the second time period using the second temperature correction data (S402). The estimation unit 140 calculates the allowable current value by further using at least one predicted value of the wind speed and the amount of solar radiation in the predetermined area in the second time period. In this embodiment, the estimation unit 140 calculates the allowable current value by using the power transmission line upper limit temperature H max The estimation unit 140 calculates the allowable current value of the power transmission line by using the second temperature correction data T(x) acquired in step S401 and the predicted values ​​of wind speed and solar radiation for the second period acquired by the acquisition unit 110. The estimation unit 140 calculates the allowable current value of the power transmission line by using the same method as the calculation unit 120. maxThe above predicted values ​​of wind speed and solar radiation are predicted values ​​for the second period (from 1 hour from the current time to 36 hours from now) at each point in the specified area. In other words, the predicted values ​​of wind speed and solar radiation are predicted values ​​for x hours from the current time (1≦x≦36, in 1-hour increments). Hereinafter, the predicted value of wind speed (which may be a fixed value) will be referred to as W(x), and the predicted value of solar radiation will be referred to as S(x). The predicted value of allowable current value for the second period (from the current time to x hours from now (1≦x≦36, in 1-hour increments)) at each point in the specified area will be referred to as L(x).

[0087] The estimation unit 140 applies the second temperature correction data T(x), the predicted wind speed value W(x), the predicted solar radiation amount value S(x), and the upper limit temperature H of the power transmission line to a predetermined allowable current value calculation formula f. max By substituting the above, the allowable current value L(x) is calculated as follows: The allowable current value calculation formula f is the same as that used by the calculation unit 120 when calculating the allowable current value L(x, t), and any publicly known formula (function) can be used as appropriate.

[0088] L(x)=f(T(x),W(x),S(x),H max )

[0089] Next, the estimation unit 140 acquires the reduction ratio α m Read and get (x).

[0090] Next, the estimation unit 140 calculates the power transmission capacity in the predetermined area for the second time period, and reduces the calculated power transmission capacity using the reduction ratio, thereby estimating the power transmission capacity in the predetermined area for the second time period (S404). Specifically, the estimation unit 140 acquires the voltage (line voltage) of the power transmission line, converts the allowable current value calculated in step S402 to the power transmission capacity in the predetermined area for the second time period, and estimates the power transmission capacity in the predetermined area for the second time period by taking into account the reduction ratio acquired in step S403. The estimation unit 140 may acquire the power transmission line voltage (line voltage) by reading it from data previously written in estimation data 163 in the storage unit 160, may acquire it externally, such as through user input, or may calculate it itself.

[0091] Hereinafter, the voltage (line voltage) of the transmission line is referred to as V, and the estimated value of the transmission capacity for each point in the predetermined area for the second period (from the present time to x hours ahead (1≦x≦36, in 1-hour increments)) estimated by the estimation unit 140 is referred to as P(x). The estimation unit 140 estimates the voltage (line voltage) V of the transmission line, the allowable current value L(x), the power factor cosθ, and the reduction ratio α m Using (x), the transmission capacity P(x) is calculated as follows:

[0092] P(x)=√3×V×L(x)×cosθ×(1-α m (x))

[0093] In this way, the estimation unit 140 calculates the power transmission capacity in the specified area for the second time period using the second temperature correction data, and reduces the calculated power transmission capacity using the reduction ratio to estimate the power transmission capacity P(x) in the specified area for the second time period. Then, the estimation unit 140 writes the estimated power transmission capacity P(x) into the estimation data 163 stored in the storage unit 160, and updates the estimation data 163.

[0094] In this way, the process of estimating the power transmission capacity by the estimating unit 140 (S104 in FIG. 4) ends.

[0095] [3 Explanation of effects] The power transmission capacity estimation device 100 according to an embodiment of the present invention acquires first temperature forecast data for a first time period, second temperature forecast data for a second time period, and actual temperature data for the first time period. For example, the power transmission capacity estimation device 100 acquires first temperature forecast data and second temperature forecast data from the Japan Meteorological Agency's Mesoscale Model (MSM) or the like, and acquires actual temperature data from AMeDAS, thereby eliminating the need to install multiple sensors along the power transmission line route to acquire each data. Furthermore, the power transmission capacity estimation device 100 corrects the second temperature forecast data using the first temperature forecast data and the actual temperature data to calculate second corrected temperature data, and then calculates the power transmission capacity for the second time period using the second corrected temperature data. This allows the power transmission capacity estimation device 100 to calculate the power transmission capacity for the second time period with relatively high accuracy. Furthermore, the power transmission capacity estimation device 100 calculates a reduction ratio for reducing the power transmission capacity so that the estimated maximum temperature of the power transmission line is equal to or less than the allowable value, and estimates the power transmission capacity for the second time period by reducing the calculated power transmission capacity using the reduction ratio. In other words, it is preferable to reduce the calculated transmission capacity on the safe side, but reducing the transmission capacity too much would hinder flexible operation of the transmission line, so the transmission capacity is reduced at least so that the estimated maximum temperature of the transmission line is below the allowable value. This allows the power transmission capacity estimation device 100 to accurately estimate the transmission capacity in a specified area during the second time period without reducing it too much, allowing flexible operation of the transmission line based on the estimated transmission capacity. Therefore, the power transmission capacity estimation device 100 enables flexible operation of the transmission line with a simple configuration.

[0096] The power transmission capacity estimation device 100 calculates the thermal degradation rate of the power transmission line from the estimated maximum temperature of the power transmission line, and calculates the reduction rate so that the thermal degradation rate is equal to or less than the allowable value, thereby calculating the reduction rate that takes the thermal degradation rate of the power transmission line into consideration. As a result, the power transmission capacity estimation device 100 can accurately estimate the power transmission capacity in a predetermined area during the second time period, taking the thermal degradation rate of the power transmission line into consideration.

[0097] The power transmission capacity estimation device 100 can easily calculate the reduction ratio by calculating the ratio at which the estimated maximum current value of the power transmission line is reduced so that the estimated maximum temperature value of the power transmission line becomes equal to or less than the allowable value.

[0098] The power transmission capacity estimation device 100 can easily calculate the estimated maximum current value by calculating the allowable current value of the power transmission line using the first temperature forecast data and then calculating the estimated maximum current value of the power transmission line.

[0099] The power transmission capacity estimation device 100 can calculate the second temperature corrected data with relatively high accuracy by using a temperature prediction model obtained from the first temperature prediction data and the actual temperature data to calculate the second temperature corrected data. Furthermore, the power transmission capacity estimation device 100 can calculate the allowable current value of the transmission line with relatively high accuracy by correcting the first temperature prediction data using the temperature prediction model to calculate the first temperature corrected data, and then using the first temperature corrected data to calculate the allowable current value of the transmission line.

[0100] The power transmission capacity estimation device 100 calculates the estimated maximum temperature of the power transmission line using the estimated maximum current value of the power transmission line and the temperature record data, thereby being able to calculate the estimated maximum temperature value with relatively high accuracy.

[0101] The temperature of a power transmission line is also affected by wind speed or solar radiation. For example, when the wind speed around the power transmission line is high, the temperature of the power transmission line decreases, and when the solar radiation is high, the temperature of the power transmission line increases. Therefore, the power transmission capacity estimation device 100 calculates the maximum temperature estimate of the power transmission line by further using observation data indicating at least one of the wind speed and the solar radiation. This allows the power transmission capacity estimation device 100 to calculate the maximum temperature estimate with relatively high accuracy.

[0102] The power transmission capacity is also affected by wind speed or solar radiation. For example, a high wind speed around a power transmission line reduces the temperature of the power transmission line, while a high amount of solar radiation increases the temperature of the power transmission line, thereby affecting the power transmission capacity. For this reason, the power transmission capacity estimation device 100 estimates the power transmission capacity by further using a predicted value of at least one of wind speed and solar radiation. This allows the power transmission capacity estimation device 100 to calculate the power transmission capacity in a specified area during the second time period with relatively high accuracy.

[0103] [4 Explanation of Variations] Although the power transmission capacity estimation device 100 and the power transmission capacity estimation method according to the present embodiment have been described above, the present invention is not limited to the above embodiment. The embodiment disclosed herein is illustrative in all respects and is not restrictive, and the scope of the present invention includes all modifications within the meaning and scope of the claims.

[0104] For example, in the above embodiment, the first period before the predetermined time point is set to one year from the present time point, and the second period after the predetermined time point is set to one hour from the present time point to 36 hours from the present time point. However, the first period may be any time and length as long as it is a past period, and the second period may be any time and length as long as it is a future period. The predetermined time point does not have to be the present time point, but may be a time point slightly shifted from the present time point.

[0105] In addition, in the above embodiment, the acquisition unit 110 acquires each piece of data contained in the weather forecast data 211 and the weather observation data 221 from the weather data management device 200, but the data may be acquired from any device.

[0106] In the above embodiment, the calculation unit 120 calculates the thermal degradation rate of the power transmission line from the estimated maximum temperature of the power transmission line, and calculates the reduction ratio so that the thermal degradation rate is equal to or less than the allowable value. However, the reduction ratio may be calculated without using the thermal degradation rate of the power transmission line.

[0107] In the above embodiment, the calculation unit 120 calculates the reduction ratio as the ratio by which the estimated maximum current value of the power transmission line is reduced so that the estimated maximum temperature value of the power transmission line becomes equal to or less than the allowable value. However, the reduction ratio may be calculated without using the estimated maximum current value.

[0108] In the above embodiment, the calculation unit 120 calculates the allowable current value of the power transmission line using the first temperature forecast data, and then calculates the estimated maximum current value of the power transmission line using the allowable current value, but this is not limited to this. The calculation unit 120 may calculate the estimated maximum current value without using the first temperature forecast data. Alternatively, the calculation unit 120 may calculate the estimated maximum current value without calculating the allowable current value.

[0109] Furthermore, in the above embodiment, the correction unit 130 calculates the second temperature correction data using a temperature prediction model, but the second temperature correction data may be calculated without using a temperature prediction model.

[0110] Furthermore, in the above embodiment, calculation unit 120 corrects the first temperature forecast data using a temperature forecast model and calculates first corrected temperature data, which is the corrected first temperature forecast data. However, the first corrected temperature data may be calculated without using a temperature forecast model. The temperature forecast model is a model obtained from the first temperature forecast data and actual temperature data. However, the model may be obtained from any data. Calculation unit 120 calculates the allowable current value of the power transmission line using the first corrected temperature data. However, the allowable current value may be calculated without using the first corrected temperature data.

[0111] In addition, in the above embodiment, the calculation unit 120 calculates the maximum temperature estimate of the power transmission line using the maximum current estimate of the power transmission line and actual air temperature data, but the maximum temperature estimate may be calculated using any data.

[0112] In addition, in the above embodiment, the calculation unit 120 calculates the maximum temperature estimate of the power transmission line using observation data indicating at least one of wind speed and solar radiation, but the maximum temperature estimate may be calculated without using either wind speed or solar radiation.

[0113] In addition, in the above embodiment, the estimation unit 140 estimates the power transmission capacity using at least one predicted value of the wind speed and the amount of solar radiation, but the power transmission capacity may be calculated without using either the wind speed or the amount of solar radiation.

[0114] The present invention can be realized not only as the power transmission capacity estimation device 100 and a power transmission capacity estimation method, but also as a program for causing a computer to execute steps included in the power transmission capacity estimation method. That is, each component of the power transmission capacity estimation device 100 may be realized by a program execution unit such as a CPU or processor reading and executing a software program recorded on a recording medium such as a hard disk or semiconductor memory. Furthermore, the present invention can also be realized as a computer-readable non-transitory recording medium on which the program is recorded, such as a flexible disk, hard disk, CD-ROM, MO, DVD, DVD-ROM, DVD-RAM, BD (Blu-ray (registered trademark) Disc), or semiconductor memory. The program can then be distributed via the recording medium or a transmission medium such as the Internet. The present invention can also be realized as an integrated circuit including a processing unit included in the power transmission capacity estimation device 100. That is, each functional block of the power transmission capacity estimation device 100 shown in FIG. 2 may be realized as an LSI (Large Scale Integration) integrated circuit. These functional blocks may be individually implemented on a single chip, or some or all of them may be integrated on a single chip. In this way, each component of the power transmission capacity estimation device 100 may be configured with dedicated hardware, or may be realized by executing a software program suitable for each component.

[0115] Furthermore, configurations constructed by combining any of the components in the above-described embodiments and their modifications are also included within the scope of the present invention. [Industrial Applicability]

[0116] The present invention can be applied to a power transmission capacity estimation device that estimates the transmission capacity, which is the operable capacity of a power transmission line. [Explanation of symbols]

[0117] 100 Transmission capacity estimation device 110 Acquisition Department 120 Calculation Unit 130 Correction unit 140 Estimation part 150 Output section 160 Storage section 161, 211 Weather forecast data 162, 221 Meteorological observation data 163 Estimation Data 200 Weather data management device 210 Weather forecast data storage unit 220 AMeDAS Data Storage Unit 300 Communication Network

Claims

1. A power transmission capacity estimation device that estimates a power transmission capacity, which is an operable capacity of a power transmission line, comprising: an acquisition unit that acquires first temperature forecast data indicating a forecast value of the temperature in a specified area during a first period before a specified time point, second temperature forecast data indicating a forecast value of the temperature in the specified area during a second period after the specified time point, and temperature record data indicating a record value of the temperature in the specified area during the first period; a calculation unit that calculates an estimated maximum temperature value of the power transmission line in the predetermined area during the second time period, and calculates a reduction ratio that is a ratio by which the power transmission capacity is reduced so that the estimated maximum temperature value is equal to or less than an allowable value; a correction unit that corrects the second temperature prediction data using the first temperature prediction data and the actual temperature data, and calculates second temperature correction data, which is the corrected second temperature prediction data; an estimation unit that calculates the power transmission capacity in the specified area during the second time period using the second temperature correction data, and estimates the power transmission capacity in the specified area during the second time period by reducing the calculated power transmission capacity using the reduction ratio; A transmission capacity estimation device comprising:

2. The calculation unit calculates a thermal degradation rate of the power transmission line from the maximum temperature estimated value, and calculates the reduction ratio so that the thermal degradation rate is equal to or less than an allowable value. The power transmission capacity estimation device according to claim 1 .

3. The calculation unit calculates, as the reduction rate, a rate at which the estimated maximum current value of the power transmission line is reduced so that the estimated maximum temperature value becomes equal to or less than a tolerance value. The power transmission capacity estimation device according to claim 1 or 2.

4. The calculation unit calculates an allowable current value of the power transmission line using the first temperature forecast data, and calculates the maximum current estimation value using the allowable current value. The power transmission capacity estimation device according to claim 3 .

5. the correction unit calculates the second temperature correction data using a temperature prediction model obtained from the first temperature prediction data and the actual temperature data; The calculation unit corrects the first temperature prediction data using the temperature prediction model, calculates first temperature corrected data which is the first temperature prediction data after the correction, and calculates the allowable current value using the first temperature corrected data. The power transmission capacity estimation device according to claim 4.

6. The calculation unit calculates the estimated maximum temperature value using the estimated maximum current value and the actual temperature data. The power transmission capacity estimation device according to claim 4.

7. The calculation unit calculates the estimated maximum temperature value by further using observation data indicating at least one of wind speed and solar radiation amount in the predetermined area during the first period. The power transmission capacity estimation device according to claim 6.

8. The estimation unit estimates the power transmission capacity by further using a predicted value of at least one of a wind speed and an amount of solar radiation in the predetermined area during the second time period. The power transmission capacity estimation device according to claim 1 or 2.

9. A method for estimating a transmission capacity, which is an operational capacity of a transmission line, comprising: an acquisition step of acquiring first temperature forecast data indicating a forecast value of the temperature in a specified area in a first period before a specified time point, second temperature forecast data indicating a forecast value of the temperature in the specified area in a second period after the specified time point, and temperature actual data indicating a forecast value of the temperature in the specified area in the first period; a calculation step of calculating an estimated maximum temperature of the power transmission line in the predetermined area during the second time period, and calculating a reduction ratio that is a ratio by which the power transmission capacity is reduced so that the estimated maximum temperature is equal to or less than an allowable value; a correction step of correcting the second temperature prediction data using the first temperature prediction data and the actual temperature data, and calculating second corrected temperature data, which is the corrected second temperature prediction data; an estimation step of calculating the power transmission capacity in the specified area during the second time period using the second temperature correction data, and reducing the calculated power transmission capacity using the reduction ratio, thereby estimating the power transmission capacity in the specified area during the second time period; A method for estimating transmission capacity, including:

10. A program for causing a computer to execute the steps included in the method for estimating power transmission capacity according to claim 9.

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