Power Transmission Capacity Estimation Device and Power Transmission Capacity Estimation Method

Abstract

To provide a transmittable capacity estimation device capable of realizing a flexible operation of a power line by a simple configuration.SOLUTION: A transmittable capacity estimation device 100 estimating a transmittable capacity that is an operation possible capacity of a power line has an acquisition part 110 acquiring first weather predicting data 211 including first temperature predicting data and second temperature predicting data indicating predicted values of a temperature in a predetermined area in a first period before a predetermined time point and a second period after the predetermined time point, and weather observation data 231 including temperature record data indicating a recorded value of the temperature in the predetermined area in the first period, a correction part 120 calculating temperature error data indicating a prediction error of the temperature in the predetermined area by using the first temperature predicting data and the temperature record data and correcting the second temperature predicting data by using the calculated temperature error data, and an estimation part 130 estimating the transmittable capacity in the predetermined area in the second period by using the corrected second temperature predicting data.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 available capacity of a power transmission line.

Background Art

[0002] Conventionally, a technique for calculating the available capacity of a power transmission line has been known. For example, in Patent Document 1, using the temperature, wind speed, and solar radiation measured by a plurality of sensors on the power transmission line route where the overhead power transmission line is installed, the current capacity of the overhead power transmission line is calculated for each individual sensor, and the minimum value among the calculated current capacities is output as the current capacity of the overhead power transmission line (the available capacity of the power transmission line).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the above conventional technology, a plurality of sensors are attached on the power transmission line route to measure the temperature and the like, and the available capacity of the power transmission line is calculated according to the local conditions. However, in the above conventional technology, since it is necessary to attach a plurality of sensors on the power transmission line route, the configuration is complicated. Further, in the above conventional technology, the available capacity of the power transmission line is calculated according to the current situation of the temperature and the like, but since the available capacity of the power transmission line at a future time point is unknown, there is a possibility that flexible operation cannot be performed.

[0005] The present invention has been newly made by the inventors of the present application paying attention to the above problems, and an object thereof is to provide a power transmission capacity estimation device and a power transmission capacity estimation method that can achieve flexible operation of a power transmission line with a simple configuration.

Means for Solving the Problems

[0006] In order to achieve the above object, a transmission capacity estimation device according to one aspect of the present invention is a transmission capacity estimation device that estimates a transmission capacity that is an operable capacity of a transmission line, and includes first temperature prediction data and second temperature prediction data indicating predicted values of temperatures in a predetermined area during a first period before a predetermined time point and a second period after the predetermined time point, and acquisition means for acquiring first weather prediction data, and weather observation data including temperature actual data indicating actual values of temperatures in the predetermined area during the first period; a correction unit that calculates temperature error data indicating a prediction error of the temperature in the predetermined area using the first temperature prediction data and the temperature actual data, and corrects the second temperature prediction data using the calculated temperature error data; and an estimation unit that estimates the transmission capacity in the predetermined area during the second period using the corrected second temperature prediction data.

[0007] According to this, the transmission capacity estimation device acquires first weather prediction data including first temperature prediction data and second temperature prediction data during the first period and the second period, and weather observation data including temperature actual data during the first period. For example, the transmission capacity estimation device can acquire the prediction data from the Mesoscale Model (MSM) of the Japan Meteorological Agency and the observation data from AMeDAS, without the need to install a plurality of sensors on the transmission line route, and can acquire the first weather prediction data and the weather observation data. Further, the transmission capacity estimation device calculates temperature error data using the first temperature prediction data and the temperature actual data, corrects the second temperature prediction data using the temperature error data, and estimates the transmission capacity during the second period using the corrected second temperature prediction data. In this way, the transmission capacity estimation device estimates the transmission capacity during the second period using the second temperature prediction data with the error corrected. Thereby, the transmission capacity estimation device can estimate relatively accurately the transmission capacity that is the operable capacity of the transmission line during the second period after the predetermined time point, and thus can operate the transmission line flexibly based on the estimation result of the transmission capacity. Therefore, according to the transmission capacity estimation device, flexible operation of the transmission line can be achieved with a simple configuration.

[0008] Further, the correction unit may calculate, as the temperature error data, a difference between the maximum value of the predicted temperature indicated by the first temperature prediction data and the maximum value of the actual temperature indicated by the actual temperature data.

[0009] According to this, the power transmission capacity estimation device calculates, as the temperature error data, a difference between the maximum value of the predicted temperature and the maximum value of the actual temperature in the first period. That is, when the temperature is maximum, since the influence of the temperature on the power transmission capacity becomes large, the power transmission capacity estimation device calculates the temperature error data when the temperature is maximum. Thereby, the power transmission capacity estimation device can estimate the power transmission capacity by correcting the second temperature prediction data based on the case with a large influence, and can estimate the power transmission capacity on the safe side. Therefore, according to the power transmission capacity estimation device, the flexible and safe operation of the transmission line can be achieved with a simple configuration.

[0010] Further, the correction unit determines whether the predicted temperature value indicated by the first temperature prediction data is smaller than the actual temperature value indicated by the actual temperature data, and extracts the predicted temperature value and the actual temperature value when the predicted temperature value is smaller than the actual temperature value, and may calculate the temperature error data.

[0011] According to this, the power transmission capacity estimation device determines whether the predicted temperature value in the first period is smaller than the actual temperature value, extracts the predicted temperature value and the actual temperature value when the predicted temperature value is smaller than the actual temperature value, and calculates the temperature error data. That is, the power transmission capacity estimation device calculates the temperature error data using the data when the predicted temperature value is smaller than the actual temperature value on the safe side. Thereby, according to the power transmission capacity estimation device, the flexible and safe operation of the transmission line can be achieved with a simple configuration.

[0012] Further, the correction unit may calculate the temperature error data by extracting values within a predetermined range from the predicted temperature value indicated by the second temperature prediction data from the predicted temperature value indicated by the first temperature prediction data.

[0013] If the past predicted value deviates too much from the future predicted value, using such a past predicted value for calculating the error of the future predicted value may reduce the calculation accuracy. Therefore, the power transmission capacity estimation device extracts values within a predetermined range from the predicted temperature value in the first period from the predicted temperature value in the second period and calculates the temperature error data. Thereby, in calculating the temperature error data, the power transmission capacity estimation device does not use values outside the predetermined range from the predicted temperature value in the future second period in the predicted temperature value in the past first period, so that the calculation accuracy of the temperature error data can be improved. Thereby, according to the power transmission capacity estimation device, it is possible to achieve flexible and accurate operation of the transmission line with a simple configuration.

[0014] Further, the correction unit may calculate the temperature error data using, as the prediction error of the temperature, the value at the 100th percentile in the difference between the predicted temperature value indicated by the first temperature prediction data and the actual temperature value indicated by the temperature actual data.

[0015] According to this, the power transmission capacity estimation device calculates the temperature error data using, as the prediction error of the temperature, the value at the 100th percentile in the difference between the predicted temperature value and the actual temperature value in the first period. That is, when the difference between the predicted temperature value and the actual temperature value varies, the power transmission capacity estimation device adopts, on the safe side, the value at the 100th percentile in the difference as the prediction error of the temperature and calculates the temperature error data. Thereby, according to the power transmission capacity estimation device, it is possible to achieve flexible and safe operation of the transmission line with a simple configuration.

[0016] Further, the acquisition unit may further acquire second weather prediction data having a shorter prediction period and a shorter distribution delay time than the first weather prediction data, and the correction unit may correct the second temperature prediction data in a period shorter than the second period after the predetermined time point using the second weather prediction data.

[0017] When the power transmission capacity estimation device acquires the first weather prediction data, if the distribution delay time of the first weather prediction data is long, the accuracy of correcting the second temperature prediction data using the first weather prediction data may decrease. For this reason, the power transmission capacity estimation device acquires second weather prediction data having a shorter prediction period but a shorter distribution delay time than the first weather prediction data, and corrects the second temperature prediction data in a period shorter than the second period after the predetermined time point using the second weather prediction data. Thereby, the power transmission capacity estimation device can improve the accuracy of correcting the second temperature prediction data in a period shorter than the second period after the predetermined time point. Further, the power transmission capacity estimation device can easily acquire the second weather prediction data from, for example, the Local Model (LFM) of the Japan Meteorological Agency. Thus, according to the power transmission capacity estimation device, flexible and accurate operation of the power transmission line can be achieved with a simple configuration.

[0018] Further, the acquisition unit may further acquire second weather prediction data having a shorter prediction period and a shorter update interval than the first weather prediction data, and the correction unit may correct the second temperature prediction data in a period shorter than the second period after the predetermined time point using the second weather prediction data.

[0019] When the power transmission capacity estimation device acquires the first weather prediction data, if the update interval of the first weather prediction data is long, the accuracy of correcting the second temperature prediction data using the first weather prediction data may decrease. Therefore, although the prediction period of the second weather prediction data is shorter than that of the first weather prediction data, the power transmission capacity estimation device acquires the second weather prediction data with a short update interval, and uses the second weather prediction data to correct the second temperature prediction data in a period shorter than the second period after a predetermined time point. Thereby, the power transmission capacity estimation device can improve the accuracy of correcting the second temperature prediction data in a period shorter than the second period after a predetermined time point. Further, the power transmission capacity estimation device can easily acquire the second weather prediction data from, for example, the Local Model (LFM) of the Japan Meteorological Agency. As a result, according to the power transmission capacity estimation device, it is possible to achieve flexible and accurate operation of the power transmission line with a simple configuration.

[0020] Further, the acquisition unit may acquire the first weather prediction data further including first altitude data indicating the altitude of the prediction point and the weather observation data further including second altitude data indicating the altitude of the observation point, and the correction unit may further use the first altitude data and the second altitude data to correct the second temperature prediction data according to the altitude of the power transmission line in the predetermined area.

[0021] Temperature changes with altitude. For example, as the altitude increases, the temperature decreases, and as the altitude decreases, the temperature increases. Therefore, the power transmission capacity estimation device corrects the second temperature prediction data according to the altitude of the power transmission line using the first altitude data of the prediction point and the second altitude data of the observation point. Thereby, since the power transmission capacity estimation device can accurately correct the second temperature prediction data, it is possible to achieve flexible and accurate operation of the power transmission line with a simple configuration.

[0022] Further, the acquisition unit may acquire the first weather prediction data further including data indicating at least one predicted value of wind speed, solar radiation amount, and precipitation amount in the predetermined area, and the estimation unit may further use the data indicating at least one predicted value of wind speed, solar radiation amount, and precipitation amount included in the first weather prediction data to estimate the power transmission capacity.

[0023] The power transmission capacity is also affected by wind speed, solar radiation amount, or precipitation amount. For example, when the wind speed around the power transmission line is high, the temperature of the power transmission line decreases; when the solar radiation amount is high, the temperature of the power transmission line increases; and when the precipitation amount is large, the temperature of the power transmission line decreases, so the power transmission capacity is affected. Therefore, the power transmission capacity estimation device acquires the first weather prediction data further including data indicating at least one predicted value of wind speed, solar radiation amount, and precipitation amount, and further uses the data indicating at least one predicted value of wind speed, solar radiation amount, and precipitation amount to estimate the power transmission capacity. Thereby, since the power transmission capacity estimation device can accurately estimate the power transmission capacity, it can achieve flexible and accurate operation of the power transmission line with a simple configuration.

[0024] Further, 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, as steps, characteristic processes performed by a processing unit included in the power transmission capacity estimation device. Further, the present invention can 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. And the program can be distributed via the recording medium and a transmission medium such as the Internet. Further, 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

[0025] According to the power transmission capacity estimation device and the like according to the present invention, flexible operation of the power transmission line can be achieved with a simple configuration.

Brief Description of the Drawings

[0026]

Figure 1

Figure 2

Figure 3A

Figure 3B

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Figure 11

Figure 12

Embodiments for Carrying Out the Invention

[0027] Hereinafter, with reference to the drawings, a power transmission capacity estimation device and a power transmission capacity estimation method according to embodiments (including modifications thereof) of the present invention will be described. Note that all of the embodiments described below are illustrative of comprehensive or specific examples. The numerical values, components, arrangement positions and connection forms of the components, steps, order of steps, etc. shown in the following embodiments are merely examples and are not intended to limit the present invention.

[0028] (Embodiment) [1 Explanation 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 the weather 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 the first temperature prediction data or the second temperature prediction data included in the first weather prediction data 151 stored in the storage unit 150 of the power transmission capacity estimation device 100 according to the present embodiment. FIG. 3B is a diagram showing an example of the temperature actual data included in the weather observation data 153 stored in the storage unit 150 of the power transmission capacity estimation device 100 according to the present embodiment.

[0029] The power transmission capacity estimation device 100 is a device that estimates the power transmission capacity, which is the operable capacity of a power transmission line. A power transmission line is an overhead high-voltage electric wire (high-voltage line) for transmitting the electric power generated by power generation facilities such as power plants to substations, distribution substations, or consumers, etc., and is arranged, for example, on the commercial power system of an electric power company. The operable capacity (power transmission capacity) of a power transmission line is the capacity of electric power that can be supplied by the power transmission line in operation (e.g., MW), and it varies depending on the ambient temperature around the power transmission line, etc. For example, when the ambient temperature around the power transmission line is high, the operable capacity (power transmission capacity) of the power transmission line decreases due to the decrease in the strength of the power transmission line caused by heat, etc., and when the ambient temperature around the power transmission line is low, the operable capacity (power transmission capacity) of the power transmission line increases.

[0030] Specifically, as shown in FIGS. 1 and 2, the power transmission capacity estimation device 100 is connected to the meteorological data management device 200 via the communication network 300, and is a computer that acquires information from the meteorological data management device 200 and estimates the power transmission capacity. Note that the power transmission capacity estimation device 100 may be realized by a general 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, such as a wired or wireless LAN (Local Area Network).

[0031] The meteorological data management device 200 is a device that holds information related to meteorology such as the ambient temperature, wind speed, solar radiation amount, and precipitation amount at a predetermined time point and a predetermined location. For example, the meteorological data management device 200 is a device such as a computer installed in the Meteorological Agency, or a computer that has acquired data from the Meteorological Agency. As shown in FIG. 1, the meteorological data management device 200 includes a mesoscale model data holding unit 210, a local model data holding unit 220, and an Amedas data holding unit 230.

[0032] The meso-model data holding unit 210 is a memory or the like that holds (stores) data predicted by the Meteorological Agency's meso-model (MSM). The meso-model (MSM) uses a horizontal grid interval of 5 km with Japan and its adjacent seas as the computational domain, has a distribution delay time of approximately 2.5 hours, and is updated every 3 hours (8 times a day), performing prediction calculations up to 39 hours ahead, and can predict meteorological phenomena from several hours to one day ahead. Specifically, the meso-model data holding unit 210 stores the first meteorological prediction data 211. The first meteorological prediction data 211 is a collection of data including predicted values of meteorological information such as air temperature, wind speed, solar radiation amount, precipitation amount, altitude, atmospheric pressure, humidity, cloud amount, etc. The first meteorological prediction data 211 has data for these meteorological information at a resolution of a mesh with a horizontal grid interval of 5 km, and with an update frequency of every 3 hours (8 times a day), taking each hour on the hour as one cross-section, and having a total of 39 cross-sections (39 hours of data for each hour on the hour).

[0033] The local model data holding unit 220 is a memory or the like that holds (stores) data predicted by the Meteorological Agency's local model (LFM). The local model (LFM) has a finer horizontal grid interval (2 km) than the meso-model, a shorter distribution delay time (approximately 1.5 hours), and a shorter update interval (updated every 1 hour (24 times a day)), performing prediction calculations for a short prediction period (up to 10 hours ahead), and can grasp meteorological phenomena for about several hours ahead. Specifically, the local model data holding unit 220 stores the second meteorological prediction data 221. The second meteorological prediction data 221 is a collection of data including predicted values of meteorological information similar to the first meteorological prediction data 211 such as air temperature. The second meteorological prediction data 221 has data for these meteorological information at a high resolution of a mesh with a horizontal grid interval of 2 km, and with an update frequency of every 1 hour (24 times a day), taking each hour on the hour as one cross-section, and having a total of 10 cross-sections (10 hours of data for each hour on the hour).

[0034] The AMeDAS data storage unit 230 is a memory or the like that stores (memorizes) data observed by the AMeDAS (Regional Meteorological Observation System) of the Japan Meteorological Agency. The AMeDAS data storage unit 230 can acquire data with a distribution delay time of about several minutes from each AMeDAS every hour. The AMeDAS data storage unit 230 stores the meteorological observation data 231. The meteorological observation data 231 is a collection of data including observed values of meteorological information such as temperature, wind speed, wind direction, sunshine duration, and precipitation. The meteorological observation data 231 has data for each hour at each AMeDAS observation point regarding these meteorological information.

[0035] The power transmission capacity estimation device 100 acquires the first meteorological prediction data 211, the second meteorological prediction data 221, and the meteorological observation data 231 from the meteorological 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 first meteorological prediction data 211, the second meteorological prediction data 221, and the meteorological observation data 231. The specific configuration of this power transmission capacity estimation device 100 will be described in detail below.

[0036] As shown in FIG. 2, the power transmission capacity estimation device 100 includes an acquisition unit 110, a correction unit 120, an estimation unit 130, an output unit 140, and a storage unit 150. As shown in FIG. 1, the power transmission capacity estimation device 100 also includes an input unit such as a keyboard and a mouse, and a display unit such as a liquid crystal display, but detailed descriptions of these are omitted.

[0037] The acquisition unit 110 acquires the first meteorological prediction data 211, the second meteorological prediction data 221, and the meteorological observation data 231. Specifically, the acquisition unit 110 acquires the first meteorological prediction data 211, the second meteorological prediction data 221, and the meteorological observation data 231 from the meteorological data management device 200 via the communication network 300.

[0038] The first meteorological prediction data 211 is, as described above, a collection of data including predicted temperature values. Therefore, the first meteorological prediction data 211 includes predicted temperature values in a predetermined area during a first period (e.g., the past three years from the current time) before a predetermined time point, and predicted temperature values in the predetermined area during a second period (e.g., from one hour later to 39 hours later) after the predetermined time point. The predetermined area can be an area of any size, but for example, it is an area in units of primary sub - regions (weather forecast announcement areas) of the Japan Meteorological Agency such as the Osaka Prefecture area, the northern Hyogo Prefecture area, the southern Hyogo Prefecture area, etc. The same applies hereinafter. Thus, the first meteorological prediction data 211 includes first temperature prediction data and second temperature prediction data indicating predicted temperature values in the predetermined area during the first period before the predetermined time point and the second period after the predetermined time point.

[0039] The first temperature prediction data is, for example, data collected over a first period (e.g., the past three years from the current time) of predicted temperature values for the past 39 hours at each location (five locations from location A to location E in Fig. 3A) in a predetermined area predicted by a mesoscale model (MSM) as shown in Fig. 3A. Similarly, the second temperature prediction data is, for example, data indicating predicted temperature values during a second period (e.g., from one hour later to 39 hours later) at each location (five locations from location A to location E in Fig. 3A) in a predetermined area predicted by a mesoscale model (MSM) as shown in Fig. 3A.

[0040] Furthermore, the first meteorological prediction data 211, as described above, also includes predicted values such as altitude, wind speed, solar radiation amount, and precipitation amount. That is, the first meteorological prediction data 211 further includes first altitude data indicating the altitude of the predicted location in the predetermined area. And the first meteorological prediction data 211 further includes data indicating predicted values of at least one of wind speed, solar radiation amount, and precipitation amount in the predetermined area during the first period and the second period. Regarding the first altitude data included in the first meteorological prediction data 211, and data indicating predicted values of wind speed, solar radiation amount, and precipitation amount, etc., as shown in Fig. 3A, they become data corresponding to each location and each time.

[0041] Regarding the second weather prediction data 221 as well, similar to the first weather prediction data 211, it includes third temperature prediction data indicating predicted temperature values in a predetermined area. In the present embodiment, the third temperature prediction data indicates, in the predetermined area, the predicted temperature value at a predetermined time point (for example, the current time point) a predetermined period (for example, 1 hour) before the prediction, and the predicted temperature value for a period shorter than the second period after the predetermined time point (for example, from 1 hour ahead to 10 hours ahead). Further, the second weather prediction data 221, similar to the first weather prediction data 211, includes third altitude data indicating the altitude of the predicted location in the predetermined area, and data indicating at least one predicted value of wind speed, solar radiation amount, and precipitation amount in the predetermined area during the first period.

[0042] Also, as described above, the second weather prediction data 221 has a shorter prediction period (up to 10 hours ahead) than the prediction period of the first weather prediction data 211 (up to 39 hours ahead), and a shorter distribution delay time (about 1.5 hours) than the distribution delay time of the first weather prediction data 211 (about 2.5 hours). Further, as described above, the second weather prediction data 221 has a shorter update interval (every 1 hour) than the update interval of the first weather prediction data 211 (every 3 hours). For this reason, the second weather prediction data 221 has a shorter prediction period and a shorter distribution delay time than the first weather prediction data 211. Further, the second weather prediction data 221 has a shorter prediction period and a shorter update interval than the first weather prediction data 211. Each data included in the second weather prediction data 221 becomes data such that, for example, the time on the horizontal axis shown in FIG. 3A is 10 hours.

[0043] As described above, the meteorological observation data 231 is a collection of data including actual values such as temperature. Therefore, the meteorological observation data 231 includes temperature actual data indicating the actual values of the temperature in a predetermined area during a first period (for example, the past three years from the current time) before a predetermined time point. The meteorological observation data 231 further includes second altitude data indicating the altitude of the observation points in the predetermined area. The temperature actual data is data collected over a first period (for example, the past three years from the current time) of the actual values of the temperature for 39 hours in the past at each point (five points from point A to point E in FIG. 3B) in the predetermined area observed by AMeDAS as shown in FIG. 3B. The second altitude data is data indicating the altitude of each point.

[0044] The acquisition unit 110 writes the acquired first meteorological prediction data 211, second meteorological prediction data 221, and meteorological observation data 231 to the first meteorological prediction data 151, second meteorological prediction data 152, and meteorological observation data 153 stored in the storage unit 150. That is, the acquisition unit 110 writes the first temperature prediction data, second temperature prediction data, first altitude data, and data indicating the predicted values of wind speed, solar radiation amount, and precipitation amount included in the first meteorological prediction data 211 to the first meteorological prediction data 151 to update the first meteorological prediction data 151. Further, the acquisition unit 110 writes the third temperature prediction data, third altitude data, and data indicating the predicted values of wind speed, solar radiation amount, and precipitation amount included in the second meteorological prediction data 221 to the second meteorological prediction data 152 to update the second meteorological prediction data 152. Furthermore, the acquisition unit 110 writes the temperature actual data and second altitude data included in the meteorological observation data 231 to the meteorological observation data 153 to update the meteorological observation data 153.

[0045] Note that, for example, since the thermometer at the AMeDAS observation site is installed at an altitude of 1.5 m above the ground, etc., the second altitude data in the meteorological observation data 231 may be known in advance. In this case, the meteorological observation data 231 does not include the second altitude data, and the second altitude data is written in the meteorological observation data 153 in advance. The acquisition unit 110 may acquire the second altitude data from the meteorological observation data 153. The same applies to other data.

[0046] The correction unit 120 calculates temperature error data indicating the prediction error of the temperature in a predetermined area using the first temperature prediction data and the actual temperature data. The prediction error of the temperature is the deviation amount (error) of the predicted value of the temperature from the actual value of the temperature. Specifically, the correction unit 120 calculates the difference between the maximum value of the predicted temperature value indicated by the first temperature prediction data and the maximum value of the actual temperature value indicated by the actual temperature data as the temperature error data. Further, the correction unit 120 determines whether the predicted temperature value indicated by the first temperature prediction data is smaller than the actual temperature value indicated by the actual temperature data, extracts the predicted temperature value and the actual temperature value when the predicted temperature value is smaller than the actual temperature value, and calculates the temperature error data. Further, the correction unit 120 extracts values within a predetermined range from the predicted temperature value indicated by the second temperature prediction data in the predicted temperature value indicated by the first temperature prediction data, and calculates the temperature error data. Furthermore, the correction unit 120 calculates the temperature error data using the value at the 100th percentile in the difference between the predicted temperature value indicated by the first temperature prediction data and the actual temperature value indicated by the actual temperature data as the prediction error of the temperature.

[0047] In addition, the correction unit 120 corrects the second temperature prediction data using the calculated temperature error data. Specifically, the correction unit 120 further uses the first altitude data and the second altitude data to correct the second temperature prediction data according to the altitude of the transmission line in a predetermined area. More specifically, the correction unit 120 uses the second meteorological prediction data 152 to correct the second temperature prediction data in a period shorter than the second period after a predetermined time point. A more detailed description of these processes performed by the correction unit 120 will be described later.

[0048] In the above processing performed by the correction unit 120, first, the acquisition unit 110 acquires the first weather prediction data 151, the second weather prediction data 152, and the weather observation data 153 stored in the storage unit 150. Then, the correction unit 120 calculates temperature error data using the first temperature prediction data included in the acquired first weather prediction data 151 and the temperature actual data included in the weather observation data 153. Then, the correction unit 120 corrects the second temperature prediction data included in the first weather prediction data 151 using the calculated temperature error data, the first altitude data included in the first weather prediction data 151, the second altitude data included in the weather observation data 153, and the third altitude data included in the second weather prediction data 152. Then, the correction unit 120 writes the corrected second temperature prediction data into the first weather prediction data 151 stored in the storage unit 150 to update the second temperature prediction data of the first weather prediction data 151. Note that the correction unit 120 may temporarily write the calculated temperature error data into the estimation data 154 stored in the storage unit 150, read the temperature error data from the storage unit 150, and correct the second temperature prediction data.

[0049] The estimation unit 130 estimates the power transmission capacity in a predetermined area during the second period using the corrected second temperature prediction data. Specifically, the estimation unit 130 further uses data indicating at least one predicted value of wind speed, solar radiation amount, and precipitation included in the first weather prediction data 151 to estimate the power transmission capacity. For example, the acquisition unit 110 acquires the corrected first weather prediction data 151 stored in the storage unit 150. Then, the estimation unit 130 calculates an estimated value of the power transmission capacity, which is the operable capacity of the power transmission line, using the second temperature prediction data included in the acquired first weather prediction data 151 and data indicating predicted values of wind speed, solar radiation amount, and precipitation. Then, the estimation unit 130 writes the calculated estimated value of the power transmission capacity into the estimation data 154 stored in the storage unit 150 to update the estimation data 154. A more detailed description of the above processing performed by the estimation unit 130 will be described later.

[0050] The output unit 140 outputs the power transmission capacity estimated by the estimation unit 130. For example, the acquisition unit 110 acquires the estimation data 154 stored in the storage unit 150. Then, the output unit 140 reads out the estimated value of the power transmission capacity included in the acquired estimation data 154 and transmits it to an external device. Alternatively, the output unit 140 outputs the estimated value of the power transmission capacity to a display unit such as a liquid crystal display included in the power transmission capacity estimation device 100 to display the estimated value of the power transmission capacity.

[0051] The storage unit 150 is a memory that stores data and the like for estimating the power transmission capacity, which is the operable capacity of the transmission line. Specifically, the storage unit 150 stores the above-described first weather prediction data 151, second weather prediction data 152, weather observation data 153, and estimation data 154. Note that the first weather prediction data 151, second weather prediction data 152, weather observation data 153, and estimation data 154 may be rewritten each time the data is updated, or the data may be accumulated.

[0052] [Explanation of the processing flow of the power transmission capacity estimation device 100] Next, the process by which the power transmission capacity estimation device 100 estimates the power transmission capacity, which is the operable capacity of the transmission line, will be described. FIG. 4 is a flowchart showing the process (power transmission capacity estimation method) by which the power transmission capacity estimation device 100 according to the present embodiment estimates the power transmission capacity, which is the operable capacity of the transmission line.

[0053] As shown in FIG. 4, first, the acquisition unit 110 acquires first weather prediction data 211 (151), second weather prediction data 221 (152), and weather observation data 231 (153) (S102, acquisition step). Specifically, the acquisition unit 110 acquires first weather prediction data 211 (151) including first temperature prediction data for a first period in a predetermined area, second temperature prediction data for a second period, first altitude data of a prediction point, and data indicating at least one predicted value of wind speed, solar radiation amount, and precipitation amount. Further, the acquisition unit 110 acquires weather observation data 231 (153) including temperature actual data for the first period in the predetermined area and second altitude data of an observation point. Furthermore, the acquisition unit 110 acquires second weather prediction data 221 (152) with a shorter prediction period, a shorter distribution delay time, and a shorter update interval than the first weather prediction data 211 (151).

[0054] For example, in the first weather prediction data 211 (151), the acquisition unit 110 can acquire predicted temperature values for 8,760 points (= 8 times / day × 365 days × 3 years) at each point within a predetermined area where the temperature is to be predicted from the MSM model (MSM) for each time point in the past three years (first period) from the current time. In the example shown in FIG. 3A, the acquisition unit 110 acquires first temperature prediction data including predicted temperature values for 8,760 points at each time point in the past three years at points A to E within the predetermined area. Further, the acquisition unit 110 acquires second temperature prediction data including predicted temperature values from 1 hour ahead to 39 hours ahead at points A to E within the predetermined area.

[0055] In the second weather prediction data 221 (152), the acquisition unit 110 acquires third temperature prediction data including predicted temperature values at 1 hour ahead (current time) predicted 1 hour ago and predicted temperature values from 1 hour ahead to 10 hours ahead at each point within the predetermined area from the local model (LFM). In the weather observation data 231 (153), the acquisition unit 110 acquires actual temperature values at each point within the predetermined area for each time point in the past three years (first period) from Amedas.

[0056] Then, the correction unit 120 calculates temperature error data indicating the prediction error of the temperature in a predetermined area by using the first temperature prediction data and the actual temperature data acquired by the acquisition unit 110 (S104), and corrects the second temperature prediction data by using the calculated temperature error data (S106) (correction step). Details of the process (S104) in which the correction unit 120 calculates the temperature error data and the process (S106) in which the correction unit 120 corrects the second temperature prediction data will be described later.

[0057] Then, the estimation unit 130 estimates the power transmission capacity in a predetermined area during the second period by using the first weather prediction data 151 including the second temperature prediction data corrected by the correction unit 120 (S108, estimation step). Details of the process (S108) in which the estimation unit 130 estimates the power transmission capacity will be described later.

[0058] Then, the output unit 140 outputs the power transmission capacity estimated by the estimation unit 130 (S110, output step). For example, the output unit 140 transmits the power transmission capacity to an external device, or outputs the power transmission capacity 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 140 outputs a graph of the estimated value of the power transmission capacity shown in FIG. 12 described later, or a numerical value indicating the estimated value of the power transmission capacity. Note that the output unit 140 may output the temperature error data calculated by the correction unit 120 or the second temperature prediction data corrected by the correction unit 120. For example, the output unit 140 may output a graph of the second temperature prediction data shown in FIG. 10 described later, or a numerical value indicating the second temperature prediction data.

[0059] The power transmission capacity estimation device 100 executes the above processes 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 in which the power transmission capacity estimation device 100 estimates the power transmission capacity, which is the operable capacity of the power transmission line, ends.

[0060] Next, the correction unit 120 will be described in detail regarding the process of calculating the air temperature error data (S104 in FIG. 4). FIG. 5 is a flowchart showing the process of the correction unit 120 according to the present embodiment calculating the air temperature error data (S104 in FIG. 4). FIG. 6 is a diagram for explaining the process of the correction unit 120 according to the present embodiment obtaining the maximum value of the predicted air temperature and the maximum value of the actual air temperature (S206 in FIG. 5). FIG. 7 is a diagram for explaining the process of the correction unit 120 according to the present embodiment calculating the value at the 100th percentile in the difference between the predicted air temperature and the actual air temperature (S216 in FIG. 5).

[0061] First, the correction unit 120 acquires the first air temperature prediction data and the actual air temperature data from the first weather prediction data 151 and the weather observation data 153 (S202). Specifically, the correction unit 120 acquires the first air temperature prediction data from the first weather prediction data 151 acquired by the acquisition unit 110, and acquires the actual air temperature data from the weather observation data 153 acquired by the acquisition unit 110.

[0062] Then, the correction unit 120 performs correction to match the altitude of the predicted air temperature of the first air temperature prediction data with the actual altitude of the actual air temperature of the actual air temperature data (S204). Specifically, the correction unit 120 acquires the first altitude data from the first weather prediction data 151 and acquires the second altitude data from the weather observation data 153. Then, the correction unit 120 uses the first altitude data and the second altitude data to perform correction to match the altitudes of the first air temperature prediction data and the actual air temperature data. For example, the correction unit 120 corrects the actual air temperature data at a correction rate of 0.65 °C / 100 m so that the actual air temperature data at the second altitude data becomes the data at the first altitude data.

[0063] Then, the correction unit 120 acquires the maximum value of the predicted temperature indicated by the first temperature prediction data and the maximum value of the actual temperature indicated by the actual temperature data (S206). Specifically, the correction unit 120 acquires the maximum value of the predicted temperature and the maximum value of the actual temperature for the first temperature prediction data and the actual temperature data for which the correction for matching the altitude is performed in the above process (S204). For example, as shown in FIG. 6, the correction unit 120 acquires the predicted temperature TA38 = 34.0°C at 38 hours ahead at point A, which is the maximum value of the predicted temperature, and the actual temperature TD39 = 36.0°C at 39 hours ahead at point D, which is the maximum value of the actual temperature. That is, the correction unit 120 acquires the maximum value of the predicted temperature and the maximum value of the actual temperature for each period corresponding to the second period in the first period in a predetermined area. The period corresponding to the second period in the first period is a period having the same length as the second period in the same season or the same month as the second period in the first period.

[0064] Then, the correction unit 120 determines whether the predicted temperature indicated by the first temperature prediction data is less than the actual temperature indicated by the actual temperature data (S208). Specifically, the correction unit 120 determines whether the maximum value of the predicted temperature is less than the maximum value of the actual temperature for each of the maximum value of the predicted temperature and the maximum value of the actual temperature acquired in the above process (S206).

[0065] When the predicted temperature indicated by the first temperature prediction data is less than the actual temperature indicated by the actual temperature data (YES in S208), the correction unit 120 extracts the predicted temperature and the actual temperature (S210). When the predicted temperature indicated by the first temperature prediction data is greater than or equal to the actual temperature indicated by the actual temperature data (NO in S208), the correction unit 120 does not extract the predicted temperature and the actual temperature (S212). That is, the correction unit 120 extracts only the maximum value of the predicted temperature and the maximum value of the actual temperature when the maximum value of the predicted temperature is less than the maximum value of the actual temperature.

[0066] Then, the correction unit 120 extracts values within a predetermined range from the predicted temperature value indicated by the second temperature prediction data among the predicted temperature values indicated by the first temperature prediction data (S214). Specifically, the correction unit 120 determines whether the maximum value of the predicted temperature value extracted in the above process (S210) is within a predetermined range from the maximum value of the predicted temperature value indicated by the second temperature prediction data, and when the maximum value of the predicted temperature value is within the predetermined range, extracts the maximum value of the predicted temperature value. Note that the correction unit 120 acquires the maximum value of the predicted temperature value indicated by the second temperature prediction data by the same method as the process (S206) of acquiring the maximum value of the predicted temperature value indicated by the first temperature prediction data. For example, when the maximum value of the predicted temperature value indicated by the second temperature prediction data is 25°C, the correction unit 120 extracts values within the range of 25°C ± 2°C (23°C to 27°C) from the maximum values of the predicted temperature values indicated by the first temperature prediction data.

[0067] Then, the correction unit 120 calculates temperature error data using, as the temperature prediction error, the value at the 100th percentile in the difference between the predicted temperature value indicated by the first temperature prediction data and the actual temperature value indicated by the temperature actual data (S216). Specifically, the correction unit 120 calculates the value at the 100th percentile in the difference between the maximum value of the predicted temperature value extracted in the above process (S214) and the maximum value of the corresponding actual temperature value. For example, when the maximum value of the predicted temperature value indicated by the second temperature prediction data is 25°C, if the value at the 100th percentile in the difference between the maximum value of the predicted temperature value indicated by the first temperature prediction data and the maximum value of the actual temperature value is 5.7°C, the correction unit 120 calculates that the temperature error data is 5.7°C.

[0068] In this embodiment, in the above processing (S214 and S216), the correction unit 120 performs the following processing. As shown in FIG. 7, the correction unit 120 samples, at 1°C intervals, the prediction error (difference) in the case where the maximum value of the predicted temperature indicated by the first air temperature prediction data is within the range of -10 to 40°C and the maximum value of the predicted temperature is within ±2°C of the corresponding temperature, and calculates the percentile value of the prediction error. Next, the correction unit 120 obtains the maximum value of the predicted temperature indicated by the second air temperature prediction data. For example, when the maximum value of the predicted temperature indicated by the second air temperature prediction data is 25°C, the correction unit 120 calculates from the data as shown in FIG. 7 that the value at the 100th percentile in the prediction error when the predicted temperature is 25°C is 5.7°C. Thereby, the correction unit 120 calculates that the air temperature error data is 5.7°C.

[0069] As described above, the process (S104 in FIG. 4) in which the correction unit 120 calculates the air temperature error data ends.

[0070] Next, the process (S106 in FIG. 4) in which the correction unit 120 corrects the second air temperature prediction data will be described in detail. FIG. 8 is a flowchart showing the process (S106 in FIG. 4) in which the correction unit 120 according to this embodiment corrects the second air temperature prediction data. FIG. 9 is a flowchart showing the process (S304 in FIG. 8) in which the correction unit 120 according to this embodiment corrects the second air temperature prediction data using the second weather prediction data 152. FIG. 10 is a diagram showing the second air temperature prediction data after correction by the correction unit 120 according to this embodiment.

[0071] First, the correction unit 120 corrects the second air temperature prediction data using the air temperature error data (S302). Specifically, the correction unit 120 obtains the second air temperature prediction data from the first weather prediction data 151, and adds the air temperature error data calculated in the above process (S104 in FIG. 4) to the second air temperature prediction data to correct the second air temperature prediction data. For example, when the correction unit 120 calculates that the air temperature error data is 5.7 °C, 5.7 °C is added to the predicted value of the air temperature at each time of the second air temperature prediction data from 1 hour ahead to 39 hours ahead to correct the second air temperature prediction data.

[0072] Then, the correction unit 120 further corrects the second air temperature prediction data using the second weather prediction data 152 (S304). Specifically, the correction unit 120 corrects the second air temperature prediction data in a period shorter than the second period after a predetermined time point using the second weather prediction data 152. The process by which the correction unit 120 further corrects the second air temperature prediction data will be described in detail below.

[0073] As shown in FIG. 9, the correction unit 120 obtains the third air temperature prediction data and the air temperature actual data from the second weather prediction data 152 and the weather observation data 153 (S402). Specifically, the correction unit 120 obtains the third air temperature prediction data from the second weather prediction data 152 and obtains the air temperature actual data from the weather observation data 153. In the present embodiment, the third air temperature prediction data is, for example, data indicating the predicted value of the air temperature one hour before predicting the current time and the predicted values of the air temperatures predicted for the time points from 1 hour ahead to 10 hours ahead in a predetermined area.

[0074] Then, the correction unit 120 performs correction to match the altitude of the predicted value of the air temperature in the third air temperature prediction data and the actual value of the air temperature in the air temperature actual data (S404). Specifically, the correction unit 120 performs correction to match the altitude of the third air temperature prediction data and the air temperature actual data in the same manner as the correction to match the altitude of the first air temperature prediction data and the air temperature actual data (S204 in FIG. 5).

[0075] Then, the correction unit 120 obtains the maximum value of the predicted temperature indicated by the third temperature prediction data and the maximum value of the actual temperature indicated by the temperature actual data (S406). Specifically, the correction unit 120 obtains the maximum value of the predicted temperature and the maximum value of the actual temperature for the third temperature prediction data and the temperature actual data for which the correction for matching the altitude is performed in the above process (S404). For example, the correction unit 120 obtains the maximum value of the predicted temperature one hour before predicting the current time and the maximum value of the actual temperature at the current time in a predetermined area.

[0076] Then, the correction unit 120 determines whether the predicted temperature indicated by the third temperature prediction data is less than the actual temperature indicated by the temperature actual data (S408). Specifically, the correction unit 120 determines whether the maximum value of the predicted temperature obtained in the above process (S406) is less than the maximum value of the actual temperature.

[0077] When the predicted temperature is less than the actual temperature (YES in S408), the correction unit 120 calculates, as temperature error data, the value obtained by subtracting the predicted temperature from the actual temperature (S410). When the predicted temperature is greater than or equal to the actual temperature (NO in S408), the correction unit 120 calculates that the temperature error data is 0 (S412).

[0078] Then, the correction unit 120 corrects the second air temperature prediction data in a period shorter than the second period after a predetermined time point (S414). Specifically, the correction unit 120 adds the air temperature error data calculated in the above processes (S410 and S412) to the predicted value of the air temperature in a period shorter than the second period after the predetermined time point among the third air temperature prediction data, and corrects the predicted value of the air temperature in the short period of the third air temperature prediction data. Then, the correction unit 120 corrects the second air temperature prediction data by rewriting the predicted value of the air temperature in the short period of the second air temperature prediction data with the predicted value of the air temperature in the short period of the corrected third air temperature prediction data. For example, the correction unit 120 adds the air temperature error data to the predicted values of the air temperature from 1 hour ahead to 2 hours ahead of the third air temperature prediction data to correct the predicted values of the air temperature from 1 hour ahead to 2 hours ahead of the third air temperature prediction data. Then, the correction unit 120 corrects the second air temperature prediction data by rewriting the predicted value of the air temperature from 1 hour ahead to 2 hours ahead of the second air temperature prediction data with the predicted value of the air temperature from 1 hour ahead to 2 hours ahead of the corrected third air temperature prediction data.

[0079] Returning to FIG. 8, the correction unit 120 corrects the second air temperature prediction data using the first altitude data (S306). Specifically, the correction unit 120 corrects the second air temperature prediction data to the second air temperature prediction data corresponding to the altitude of the transmission line in a predetermined area. That is, the correction unit 120 corrects the second air temperature prediction data at a correction rate of 0.65 ° C. / 100 m so that the second air temperature prediction data at the first altitude data becomes data at the same height as the transmission line arranged in the predetermined area.

[0080] In this way, the correction unit 120 corrects the second air temperature prediction data to obtain the corrected second air temperature prediction data as shown in FIG. 10. As shown in FIG. 10, the corrected second air temperature prediction data is a value smaller than the conventional study value considered in the most severe cross section.

[0081] In the above manner, the process (S106 in FIG. 4) in which the correction unit 120 corrects the second air temperature prediction data ends.

[0082] Next, the process of estimating the power transmission capacity by the estimation unit 130 (S108 in FIG. 4) will be described in detail. FIG. 11 is a flowchart showing the process of estimating the power transmission capacity by the estimation unit 130 according to the present embodiment (S108 in FIG. 4). FIG. 12 is a diagram showing the estimated value of the power transmission capacity calculated by the estimation unit 130 according to the present embodiment.

[0083] First, the estimation unit 130 calculates the power transmission capacity using the second temperature prediction data (S502). Specifically, the estimation unit 130 calculates the power transmission capacity in a predetermined area during the second period using the first weather prediction data 151 including the second temperature prediction data corrected by the correction unit 120. For example, the estimation unit 130 calculates the power transmission capacity in a predetermined area during the second period by substituting the second temperature prediction data in a predetermined area during the second period into a relational expression showing the relationship between the second temperature prediction data and the power transmission capacity. Any relational expression may be used as the relational expression. For example, it is a mathematical formula such that the higher the predicted value of the temperature indicated by the second temperature prediction data, the smaller the power transmission capacity.

[0084] Then, the estimation unit 130 further corrects the power transmission capacity using the data indicating at least one predicted value of the wind speed, solar radiation amount, and precipitation amount included in the first weather prediction data 151 (S504). That is, the estimation unit 130 further corrects the power transmission capacity calculated in the above process (S502) using the data indicating the predicted values of weather information other than temperature, such as the wind speed, solar radiation amount, and precipitation amount, in a predetermined area during the second period. For example, the estimation unit 130 corrects the power transmission capacity in a predetermined area during the second period by substituting the data of the wind speed, solar radiation amount, and precipitation amount in a predetermined area during the second period into a relational expression showing the relationship between the wind speed, solar radiation amount, and precipitation amount and the power transmission capacity. Any relational expression may be used as the relational expression. For example, it is a mathematical formula such that the larger the wind speed, the larger the power transmission capacity, the larger the solar radiation amount, the smaller the power transmission capacity, and the larger the precipitation amount, the larger the power transmission capacity.

[0085] Note that the estimation unit 130 may calculate the power transmission capacity in a predetermined area during the second period by substituting the second temperature prediction data, wind speed, solar radiation amount, and precipitation amount data in the predetermined area during the second period into the relational expression showing the relationship between the second temperature prediction data, wind speed, solar radiation amount, precipitation amount, and the power transmission capacity.

[0086] In this way, the estimation unit 130 estimates the power transmission capacity and obtains an estimated value of the power transmission capacity as shown in FIG. 12. As shown in FIG. 12, the estimated value of the power transmission capacity is larger than the conventionally estimated power transmission capacity. Therefore, even when the predicted power flow without considering the power transmission capacity exceeds the conventional power transmission capacity, the predicted power flow does not exceed the estimated value of the power transmission capacity, so that the predicted power flow can be operated without being restricted.

[0087] As described above, the process (S108 in FIG. 4) in which the estimation unit 130 estimates the power transmission capacity ends.

[0088] [Description of Effects] The power transmission capacity estimation device 100 according to an embodiment of the present invention acquires first weather prediction data 211 including first temperature prediction data and second temperature prediction data in a first period and a second period, and weather observation data 231 including temperature actual data in the first period. For example, the power transmission capacity estimation device 100 can acquire the prediction data from the Mesoscale Model (MSM) of the Japan Meteorological Agency and the observation data from AMeDAS, without the need to install a plurality of sensors on the power transmission line route, and can acquire the first weather prediction data 211 and the weather observation data 231. Further, the power transmission capacity estimation device 100 calculates temperature error data using the first temperature prediction data and the temperature actual data, corrects the second temperature prediction data using the temperature error data, and estimates the power transmission capacity in the second period using the corrected second temperature prediction data. In this way, the power transmission capacity estimation device 100 estimates the power transmission capacity in the second period using the second temperature prediction data with the error corrected. Thereby, the power transmission capacity estimation device 100 can relatively accurately estimate the power transmission capacity, which is the operable capacity of the power transmission line in the second period after a predetermined time point, and thus can flexibly operate the power transmission line based on the estimation result of the power transmission capacity. Therefore, according to the power transmission capacity estimation device 100, flexible operation of the power transmission line can be achieved with a simple configuration.

[0089] In addition, since there is no need to install a plurality of sensors on the power transmission line route, cost reduction can be achieved. Also, although the power transmission line is arranged across multiple points within a predetermined area, calculating temperature error data for each point may cause the error to become too large. If the temperature error data is calculated for each point and the power transmission capacity is estimated for each point, the control of the power transmission capacity also becomes complicated. Therefore, the power transmission capacity estimation device 100 calculates the temperature error data for each area, so that the power transmission capacity does not become too small, and with a power transmission capacity that conforms to the actual situation, flexible operation of the power transmission line can be achieved.

[0090] Further, the power transmission capacity estimation device 100 calculates the difference between the maximum value of the predicted temperature in the first period and the maximum value of the actual temperature as temperature error data. That is, when the temperature is at its maximum, the impact of temperature on the power transmission capacity is significant. Therefore, the power transmission capacity estimation device 100 calculates the temperature error data when the temperature is at its maximum. Thereby, the power transmission capacity estimation device 100 can estimate the power transmission capacity by correcting the second temperature prediction data based on the case with a large impact, and can estimate the power transmission capacity on the safe side. Therefore, according to the power transmission capacity estimation device 100, the flexible and safe operation of the transmission line can be achieved with a simple configuration.

[0091] In addition, the power transmission capacity estimation device 100 determines whether the predicted temperature in the first period is smaller than the actual temperature, extracts the predicted temperature and the actual temperature when the predicted temperature is smaller than the actual temperature, and calculates the temperature error data. That is, the power transmission capacity estimation device 100 calculates the temperature error data using the data when the predicted temperature is smaller than the actual temperature on the safe side. Thereby, according to the power transmission capacity estimation device 100, the flexible and safe operation of the transmission line can be achieved with a simple configuration.

[0092] Also, if the past predicted value deviates too much from the future predicted value, using such a past predicted value for calculating the error of the future predicted value may reduce the calculation accuracy. Therefore, the power transmission capacity estimation device 100 extracts values within a predetermined range from the predicted value of the temperature in the second period in the predicted value of the temperature in the first period, and calculates temperature error data. Thereby, in calculating the temperature error data, the power transmission capacity estimation device 100 does not use values outside the predetermined range from the predicted value of the temperature in the future second period in the predicted value of the temperature in the past first period, so that the calculation accuracy of the temperature error data can be improved. Also, the error of the predicted value of the temperature is assumed to differ depending on the predicted value of the temperature (if the predicted temperature is 25°C, there may be an error of 5°C, but it is unlikely that an error of 5°C will occur at a predicted temperature of 38°C). Therefore, the power transmission capacity estimation device 100 extracts values within a predetermined range from the predicted value of the temperature in the second period and calculates the error of the predicted value. Thereby, the power transmission capacity estimation device 100 can improve the calculation accuracy of the temperature error data. Thus, according to the power transmission capacity estimation device 100, with a simple configuration, flexible and accurate operation of the transmission line can be achieved.

[0093] Also, the power transmission capacity estimation device 100 calculates temperature error data using the value at the 100th percentile in the difference between the predicted value of the temperature in the first period and the actual value of the temperature as the predicted error of the temperature. That is, when the difference between the predicted value of the temperature and the actual value of the temperature varies, the power transmission capacity estimation device 100 adopts, on the safe side, the value at the 100th percentile in the difference as the predicted error of the temperature and calculates the temperature error data. Thereby, according to the power transmission capacity estimation device 100, with a simple configuration, flexible and safe operation of the transmission line can be achieved.

[0094] In addition, when the power transmission capacity estimation device 100 acquires the first weather prediction data 211, if the distribution delay time of the first weather prediction data 211 is long, the accuracy of correcting the second temperature prediction data using the first weather prediction data 211 may decrease. For this reason, although the prediction period of the second weather prediction data 221 is shorter than that of the first weather prediction data 211, the power transmission capacity estimation device 100 acquires the second weather prediction data 221 with a short distribution delay time, and uses the second weather prediction data 221 (152) to correct the second temperature prediction data in a period shorter than the second period after a predetermined time point. Thereby, the power transmission capacity estimation device 100 can improve the accuracy of correcting the second temperature prediction data in a period shorter than the second period after a predetermined time point. Further, the power transmission capacity estimation device 100 can easily acquire the second weather prediction data 221 from, for example, the Local Model (LFM) of the Japan Meteorological Agency. Thus, according to the power transmission capacity estimation device 100, flexible and accurate operation of the power transmission line can be achieved with a simple configuration.

[0095] In addition, when the power transmission capacity estimation device 100 acquires the first weather prediction data 211, if the update interval of the first weather prediction data 211 is long, the accuracy of correcting the second temperature prediction data using the first weather prediction data 211 may decrease. For this reason, although the prediction period of the second weather prediction data 221 is shorter than that of the first weather prediction data 211, the power transmission capacity estimation device 100 acquires the second weather prediction data 221 with a short update interval, and uses the second weather prediction data 221 (152) to correct the second temperature prediction data in a period shorter than the second period after a predetermined time point. Thereby, the power transmission capacity estimation device 100 can improve the accuracy of correcting the second temperature prediction data in a period shorter than the second period after a predetermined time point. Further, the power transmission capacity estimation device 100 can easily acquire the second weather prediction data 221 from, for example, the Local Model (LFM) of the Japan Meteorological Agency. Thus, according to the power transmission capacity estimation device 100, flexible and accurate operation of the power transmission line can be achieved with a simple configuration.

[0096] In addition, the temperature varies with altitude. For example, as the altitude increases, the temperature decreases, and as the altitude decreases, the temperature increases. Therefore, the power transmission capacity estimation device 100 corrects the second temperature prediction data according to the altitude of the transmission line by using the first altitude data of the prediction point and the second altitude data of the observation point. As a result, since the power transmission capacity estimation device 100 can correct the second temperature prediction data with high accuracy, it can achieve flexible and accurate operation of the transmission line with a simple configuration.

[0097] In addition, the power transmission capacity is also affected by the wind speed, solar radiation amount, or precipitation amount. For example, when the wind speed around the transmission line is high, the temperature of the transmission line decreases; when the solar radiation amount is high, the temperature of the transmission line increases; and when the precipitation amount is large, the temperature of the transmission line decreases, so the power transmission capacity is affected. Therefore, the power transmission capacity estimation device 100 acquires first meteorological prediction data 211 further including data indicating at least one predicted value of the wind speed, solar radiation amount, and precipitation amount, and further uses the data indicating at least one predicted value of the wind speed, solar radiation amount, and precipitation amount to estimate the power transmission capacity. As a result, since the power transmission capacity estimation device 100 can estimate the power transmission capacity with high accuracy, it can achieve flexible and accurate operation of the transmission line with a simple configuration.

[0098] [Description of Modification Example 4] As described above, the power transmission capacity estimation device 100 according to the present embodiment has been described. However, the present invention is not limited to the above embodiment. The embodiments disclosed this time are illustrative in all respects and not restrictive, and the scope of the present invention includes all modifications within the meaning and scope equivalent to the claims.

[0099] For example, in the above embodiment, the first period before the predetermined time point is set to the past three years from the current time point, and the second period after the predetermined time point is set to from one hour ahead to 39 hours ahead. However, the first period may be any period and length as long as it is a past period, and the second period may be any period and length as long as it is a future period.

[0100] In the above-described embodiment, the correction unit 120 calculates the difference between the maximum value of the predicted temperature indicated by the first temperature prediction data and the maximum value of the actual temperature indicated by the temperature actual data as the temperature error data. However, the numerical value adopted by the correction unit 120 when calculating the temperature error data does not have to be the above maximum value, and any numerical value in any cross-section may be adopted.

[0101] In the above-described embodiment, the correction unit 120 extracts the predicted temperature value and the actual temperature value when the predicted temperature value indicated by the first temperature prediction data is smaller than the actual temperature value indicated by the temperature actual data. However, the correction unit 120 may extract all data without determining whether the predicted temperature value is smaller than the actual temperature value.

[0102] In the above-described embodiment, the correction unit 120 extracts values within a predetermined range from the predicted temperature value indicated by the second temperature prediction data in the predicted temperature value indicated by the first temperature prediction data. However, the correction unit 120 may also extract values outside the said predetermined range.

[0103] In the above-described embodiment, the correction unit 120 calculates the temperature error data using the value at the 100th percentile in the difference between the predicted temperature value indicated by the first temperature prediction data and the actual temperature value indicated by the temperature actual data as the predicted temperature error. However, the correction unit 120 may calculate the temperature error data using a value at the 98th, 95th, 90th, or 80th percentile instead of the value at the 100th percentile as the predicted temperature error.

[0104] In the above-described embodiment, the acquisition unit 110 acquires the second weather prediction data, and the correction unit 120 corrects the second temperature prediction data using the second weather prediction data. However, the acquisition unit 110 may not acquire the second weather prediction data, and the correction unit 120 may not correct the second temperature prediction data using the second weather prediction data.

[0105] In the above-described embodiment, the acquisition unit 110 acquires altitude data, and the correction unit 120 corrects the second air temperature prediction data using the altitude data. However, the acquisition unit 110 may not acquire altitude data, and the correction unit 120 may not correct the second air temperature prediction data using the altitude data.

[0106] In the above-described embodiment, the acquisition unit 110 acquires data indicating at least one predicted value of wind speed, solar radiation amount, and precipitation amount, and the estimation unit 130 estimates the power transmission available capacity using the data. However, the acquisition unit 110 may not acquire wind speed, solar radiation amount, and precipitation amount, and the estimation unit 130 may not estimate the power transmission available capacity using the data.

[0107] Furthermore, the present invention can be realized not only as the power transmission capacity estimation device 100 and the power transmission capacity estimation method, but also as a program for causing a computer to execute the steps included in the power transmission capacity estimation method. That is, each component included in the power transmission capacity estimation device 100 may be realized by a program execution unit such as a CPU or a processor reading and executing a software program recorded on a recording medium such as a hard disk or a semiconductor memory. Further, the present invention can be realized as a computer-readable non-transitory recording medium on which the program is recorded, for example, a flexible disk, a hard disk, a CD-ROM, an MO, a DVD, a DVD-ROM, a DVD-RAM, a BD (Blu-ray (registered trademark) Disc), a semiconductor memory. And the program can be distributed via the recording medium and a transmission medium such as the Internet. Also, the present invention can 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 a large scale integration (LSI) which is an integrated circuit. These may be individually formed into one chip, or may be formed into one chip so as to include some or all of them. Thus, each component of the power transmission capacity estimation device 100 may be configured by dedicated hardware, or may be realized by executing a software program suitable for each component.

[0108] Also, a form constructed by combining any components in the above-described embodiment and its modification is also included in the scope of the present invention.

Industrial Applicability

[0109] The present invention can be applied to a power transmission capacity estimation device that estimates the power transmission capacity, which is the operable capacity of a power transmission line.

Explanation of Signs

[0110] 100 Power transmission capacity estimation device 110 Acquisition Unit 120 Correction Unit 130 Estimation Unit 140 Output Unit 150 Memory Unit 151, 211 First Weather Forecast Data 152, 221 Second Weather Forecast Data 153, 231 Weather Observation Data 154 Estimation Data 200 Weather Data Management Device 210 Meso-Model Data Holding Unit 220 Local Model Data Holding Unit 230 Amedas Data Holding Unit 300 Communication Network

Claims

1. A transmission capacity estimation device for estimating a transmission capacity that is the operable capacity of a transmission line, an acquisition unit that acquires first weather prediction data including first temperature prediction data and second temperature prediction data indicating predicted values of temperatures in a predetermined area during a first period before a predetermined time point and a second period after the predetermined time point, and weather observation data including temperature actual data indicating actual values of temperatures in the predetermined area during the first period; a correction unit that calculates temperature error data indicating a prediction error of the temperature in the predetermined area using the first temperature prediction data and the temperature actual data, and corrects the second temperature prediction data using the calculated temperature error data; an estimation unit that estimates the transmission capacity in the predetermined area during the second period using the corrected second temperature prediction data, and the correction unit calculates the difference between the maximum value of the predicted temperature indicated by the first temperature prediction data and the maximum value of the actual temperature indicated by the temperature actual data as the temperature error data Transmission capacity estimation device.

2. A transmission capacity estimation device for estimating a transmission capacity that is the operable capacity of a transmission line, an acquisition unit that acquires first weather prediction data including first temperature prediction data and second temperature prediction data indicating predicted values of temperatures in a predetermined area during a first period before a predetermined time point and a second period after the predetermined time point, and weather observation data including temperature actual data indicating actual values of temperatures in the predetermined area during the first period; a correction unit that calculates temperature error data indicating a prediction error of the temperature in the predetermined area using the first temperature prediction data and the temperature actual data, and corrects the second temperature prediction data using the calculated temperature error data; an estimation unit that estimates the transmission capacity in the predetermined area during the second period using the corrected second temperature prediction data, and the correction unit determines whether the predicted temperature indicated by the first temperature prediction data is less than the actual temperature indicated by the temperature actual data, extracts the predicted temperature and the actual temperature when the predicted temperature is less than the actual temperature, and calculates the temperature error data Transmission capacity estimation device.

3. A transmission capacity estimation device for estimating a transmission capacity that is the operable capacity of a transmission line, An acquisition unit that acquires first weather prediction data including first temperature prediction data and second temperature prediction data indicating predicted values of temperature in a predetermined area during a first period before a predetermined time point and a second period after the predetermined time point, and weather observation data including temperature actual data indicating actual values of temperature in the predetermined area during the first period; A correction unit that calculates temperature error data indicating a prediction error of temperature in the predetermined area using the first temperature prediction data and the temperature actual data, and corrects the second temperature prediction data using the calculated temperature error data; An estimation unit that estimates the power transmission capacity in the predetermined area during the second period using the corrected second temperature prediction data; and is provided with The correction unit extracts values within a predetermined range from the predicted value of temperature indicated by the second temperature prediction data among the predicted values of temperature indicated by the first temperature prediction data, and calculates the temperature error data Power transmission capacity estimation device.

4. A power transmission capacity estimation device that estimates the power transmission capacity that is the operable capacity of a power transmission line, An acquisition unit that acquires first weather prediction data including first temperature prediction data and second temperature prediction data indicating predicted values of temperature in a predetermined area during a first period before a predetermined time point and a second period after the predetermined time point, and weather observation data including temperature actual data indicating actual values of temperature in the predetermined area during the first period; A correction unit that calculates temperature error data indicating a prediction error of temperature in the predetermined area using the first temperature prediction data and the temperature actual data, and corrects the second temperature prediction data using the calculated temperature error data; An estimation unit that estimates the power transmission capacity in the predetermined area during the second period using the corrected second temperature prediction data; and is provided with The correction unit calculates the temperature error data by using, as the prediction error of temperature, the value at the 100th percentile in the difference between the predicted value of temperature indicated by the first temperature prediction data and the actual value of temperature indicated by the temperature actual data Power transmission capacity estimation device.

5. A power transmission capacity estimation device that estimates the power transmission capacity that is the operable capacity of a power transmission line, First weather prediction data including first temperature prediction data and second temperature prediction data indicating predicted values of air temperature in a predetermined area during a first period before a predetermined time point and a second period after the predetermined time point, and weather observation data including temperature actual data indicating actual values of air temperature in the predetermined area during the first period, an acquisition unit that acquires the data; A correction unit that calculates temperature error data indicating a prediction error of air temperature in the predetermined area using the first temperature prediction data and the temperature actual data, and corrects the second temperature prediction data using the calculated temperature error data; An estimation unit that estimates the power transmission capacity in the predetermined area during the second period using the corrected second temperature prediction data; and The acquisition unit further acquires second weather prediction data having a shorter prediction period and a shorter distribution delay time than the first weather prediction data; The correction unit corrects the second temperature prediction data for a period shorter than the second period after the predetermined time point using the second weather prediction data; Power transmission capacity estimation device. **Claim 6**: A power transmission capacity estimation device that estimates a power transmission capacity that is an operable capacity of a power transmission line, First weather prediction data including first temperature prediction data and second temperature prediction data indicating predicted values of air temperature in a predetermined area during a first period before a predetermined time point and a second period after the predetermined time point, and weather observation data including temperature actual data indicating actual values of air temperature in the predetermined area during the first period, an acquisition unit that acquires the data; A correction unit that calculates temperature error data indicating a prediction error of air temperature in the predetermined area using the first temperature prediction data and the temperature actual data, and corrects the second temperature prediction data using the calculated temperature error data; An estimation unit that estimates the power transmission capacity in the predetermined area during the second period using the corrected second temperature prediction data; and The acquisition unit further acquires second weather prediction data having a shorter prediction period and a shorter update interval than the first weather prediction data; The correction unit corrects the second temperature prediction data for a period shorter than the second period after the predetermined time point using the second weather prediction data; Power transmission capacity estimation device. **Claim 7**: A power transmission capacity estimation device that estimates a power transmission capacity that is an operable capacity of a power transmission line, First weather prediction data including first temperature prediction data and second temperature prediction data indicating predicted values of temperature in a predetermined area during a first period before a predetermined time point and a second period after the predetermined time point, and weather observation data including temperature actual data indicating actual values of temperature in the predetermined area during the first period, and an acquisition unit that acquires the data; A correction unit that calculates temperature error data indicating a prediction error of temperature in the predetermined area using the first temperature prediction data and the temperature actual data, and corrects the second temperature prediction data using the calculated temperature error data; An estimation unit that estimates the power transmission capacity in the predetermined area during the second period using the corrected second temperature prediction data, and includes: The acquisition unit further acquires the first weather prediction data further including first altitude data indicating the altitude of the prediction point, and the weather observation data further including second altitude data indicating the altitude of the observation point; The correction unit further corrects the second temperature prediction data according to the altitude of the power transmission line in the predetermined area using the first altitude data and the second altitude data; Power transmission capacity estimation device.

8. The acquisition unit further acquires the first weather prediction data further including data indicating predicted values of at least one of wind speed, solar radiation amount, and precipitation amount in the predetermined area; The estimation unit further estimates the power transmission capacity using data indicating predicted values of at least one of the wind speed, the solar radiation amount, and the precipitation amount included in the first weather prediction data; The power transmission capacity estimation device according to any one of claims 1 to 7.

9. A power transmission capacity estimation method for estimating a power transmission capacity that is an operable capacity of a power transmission line, An acquisition step of acquiring first weather prediction data including first temperature prediction data and second temperature prediction data indicating predicted values of temperature in a predetermined area during a first period before a predetermined time point and a second period after the predetermined time point, and weather observation data including temperature actual data indicating actual values of temperature in the predetermined area during the first period; A correction step of calculating temperature error data indicating a prediction error of temperature in the predetermined area using the first temperature prediction data and the temperature actual data, and correcting the second temperature prediction data using the calculated temperature error data; An estimation step of estimating the power transmission capacity in the predetermined area during the second period using the corrected second temperature prediction data, and including: In the correction step, a difference between a maximum value of the predicted temperature indicated by the first temperature prediction data and a maximum value of the actual temperature indicated by the actual temperature data is calculated as the temperature error data. Transmissible capacity estimation method. **Claim 10**: A transmissible capacity estimation method for estimating a transmissible capacity that is an operable capacity of a transmission line, an acquisition step of acquiring first meteorological prediction data including first temperature prediction data and second temperature prediction data indicating predicted values of temperature in a predetermined area in a first period before a predetermined time point and a second period after the predetermined time point, and meteorological observation data including actual temperature data indicating actual values of temperature in the predetermined area in the first period; a correction step of calculating temperature error data indicating a prediction error of temperature in the predetermined area using the first temperature prediction data and the actual temperature data, and correcting the second temperature prediction data using the calculated temperature error data; an estimation step of estimating the transmissible capacity in the predetermined area in the second period using the corrected second temperature prediction data, In the correction step, it is determined whether the predicted value of temperature indicated by the first temperature prediction data is smaller than the actual value of temperature indicated by the actual temperature data, and when the predicted value of temperature is smaller than the actual value of temperature, the predicted value of temperature and the actual value of temperature are extracted to calculate the temperature error data. Transmissible capacity estimation method. **Claim 11** A program for causing a computer to execute the steps included in the transmissible capacity estimation method according to claim 9 or 10.

Images