JP7689664B2 - Apparatus and method for estimating available power transmission capacity - Google Patents

Description

The present invention relates to a transmission capacity estimation device and a transmission capacity estimation method for estimating the operational capacity of a power transmission line.

Technologies for calculating the operational capacity of a power transmission line are known. For example, Patent Document 1 discloses a device that uses the temperature, wind speed, and solar radiation measured by multiple sensors along the power transmission line route on which the overhead power transmission lines are installed to calculate the current capacity of the overhead power transmission line for each sensor, and outputs the minimum value of the calculated current capacities as the current capacity of the overhead power transmission line (the operational capacity of the power transmission line).

JP 2009-65796 A

In the above conventional technology, multiple sensors are attached to the transmission line route to measure temperature, etc., and the operational capacity of the transmission line is calculated based on the local conditions. However, the above conventional technology requires the attachment of multiple sensors to the transmission line route, making the configuration complicated. Furthermore, in the above conventional technology, the operational capacity of the transmission line is calculated based on the current conditions, such as temperature, but the operational capacity of the transmission line in the future is unknown, which may prevent flexible operation.

The present invention was made by the inventors with a new focus on the above-mentioned problems, and aims to provide a transmission capacity estimation device and a transmission capacity estimation method that can flexibly operate a power transmission line with a simple configuration.

In order to achieve the above object, a power transmission capacity estimation device according to one embodiment of the present invention is a power transmission capacity estimation device that estimates the power transmission capacity, which is the operational capacity of a power transmission line, and includes an acquisition unit that acquires first weather forecast data including first temperature forecast data and second temperature forecast data indicating predicted values of air temperature in a specified area in a first period before a specified time point and a second period after the specified time point, and weather observation data including actual air temperature data indicating actual values of air temperature in the specified area in the first period, a correction unit that uses the first temperature forecast data and the actual air temperature data to calculate air temperature error data indicating a prediction error of the air temperature in the specified area and corrects the second temperature forecast data using the calculated air temperature error data, and an estimation unit that estimates the power transmission capacity in the specified area in the second period using the corrected second temperature forecast data.

According to this, the transmission capacity estimation device acquires first weather forecast data including first temperature forecast data and second temperature forecast data for the first period and the second period, and meteorological observation data including actual temperature data for the first period. For example, the transmission capacity estimation device acquires forecast data from the Meso Model (MSM) of the Japan Meteorological Agency and acquires observation data from AMeDAS, so that the first weather forecast data and meteorological observation data can be acquired without the need to install multiple sensors on the transmission line route. In addition, the transmission capacity estimation device calculates temperature error data using the first temperature forecast data and the actual temperature data, corrects the second temperature forecast data using the temperature error data, and estimates the transmission capacity for the second period using the corrected second temperature forecast data. In this way, the transmission capacity estimation device estimates the transmission capacity for the second period using the second temperature forecast data with the error corrected. As a result, the transmission capacity estimation device can estimate the transmission capacity, which is the operational capacity of the transmission line for the second period after a predetermined time point, with relatively high accuracy, so that the transmission line can be flexibly operated based on the estimation result of the transmission capacity. Therefore, the power transmission capacity estimation device can achieve flexible operation of power transmission lines with a simple configuration.

The correction unit may also calculate the temperature error data as the difference between the maximum predicted value of the temperature indicated by the first temperature prediction data and the maximum actual value of the temperature indicated by the actual temperature data.

According to this, the available power transmission capacity estimation device calculates the difference between the maximum predicted temperature value and the maximum actual temperature value in the first period as temperature error data. In other words, when the temperature is at its maximum, the impact of the temperature on the available power transmission capacity is large, so the available power transmission capacity estimation device calculates the temperature error data when the temperature is at its maximum. In this way, the available power transmission capacity estimation device can estimate the available power transmission capacity on the safe side by correcting the second temperature prediction data based on the case where the impact is large. Therefore, the available power transmission capacity estimation device can achieve flexible and safe operation of the transmission line with a simple configuration.

The correction unit may also determine 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 extract the predicted temperature value and the actual temperature value when the predicted temperature value is smaller than the actual temperature value, and calculate the temperature error data.

According to this, the power transmission capacity estimation device determines whether the predicted temperature value in the first time period is smaller than the actual temperature value, and when the predicted temperature value is smaller than the actual temperature value, extracts the predicted temperature value and the actual temperature value, and calculates temperature error data. In other words, the power transmission capacity estimation device calculates temperature error data using data when the predicted temperature value is smaller than the actual temperature value, on the safe side. In this way, the power transmission capacity estimation device can achieve flexible and safe operation of power lines with a simple configuration.

The correction unit may also calculate the temperature error data by extracting a value within a predetermined range from the predicted value of the temperature indicated by the second temperature forecast data, from the predicted value of the temperature indicated by the first temperature forecast data.

If past predicted values deviate too far from future predicted values, there is a risk that the calculation accuracy will decrease if such past predicted values are used to calculate the error in the future predicted values. For this reason, the power transmission capacity estimation device extracts values for the predicted temperature in the first period that are within a predetermined range from the predicted temperature in the second period, and calculates the temperature error data. As a result, the power transmission capacity estimation device does not use values for the predicted temperature in the past in the first period that are outside the predetermined range from the predicted temperature in the future in the second period when calculating the temperature error data, and therefore the calculation accuracy of the temperature error data can be improved. As a result, the power transmission capacity estimation device can achieve flexible and accurate operation of transmission lines with a simple configuration.

The correction unit may also calculate the temperature error data by taking the 100th percentile value of 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 temperature prediction error.

According to this, the power transmission capacity estimation device calculates temperature error data by taking the 100th percentile value of the difference between the predicted temperature value and the actual temperature value in the first period as the temperature prediction error. In other words, when the difference between the predicted temperature value and the actual temperature value varies, the power transmission capacity estimation device takes the 100th percentile value of the difference as the temperature prediction error to be on the safe side, and calculates the temperature error data. In this way, the power transmission capacity estimation device can achieve flexible and safe operation of power lines with a simple configuration.

The acquisition unit may further acquire second weather forecast data having a shorter forecast period and a shorter delivery delay time than the first weather forecast data, and the correction unit may use the second weather forecast data to correct the second temperature forecast data for a period that is shorter than the second period after the specified time point.

When the transmission capacity estimation device acquires the first weather forecast data, if the delivery delay time of the first weather forecast data is long, the accuracy of the correction of the second temperature forecast data using the first weather forecast data may decrease. Therefore, the transmission capacity estimation device acquires second weather forecast data, which has a shorter prediction period than the first weather forecast data but a shorter delivery delay time, and uses the second weather forecast data to correct the second temperature forecast data for a period shorter than the second period after the specified time point. This allows the transmission capacity estimation device to improve the accuracy of the correction of the second temperature forecast data for a period shorter than the second period after the specified time point. In addition, the transmission capacity estimation device can easily acquire the second weather forecast data from, for example, the local model (LFM) of the Japan Meteorological Agency. As a result, the transmission capacity estimation device can achieve flexible and accurate operation of the transmission line with a simple configuration.

The acquisition unit may further acquire second weather forecast data having a shorter forecast period and a shorter update interval than the first weather forecast data, and the correction unit may use the second weather forecast data to correct the second temperature forecast data for a period that is shorter than the second period after the specified time point.

When the transmission capacity estimation device acquires the first weather forecast data, if the update interval of the first weather forecast data is long, there is a risk that the accuracy of the correction of the second temperature forecast data using the first weather forecast data will decrease. For this reason, the transmission capacity estimation device acquires second weather forecast data, which has a shorter forecast period than the first weather forecast data but a shorter update interval, and uses the second weather forecast data to correct the second temperature forecast data for a period shorter than the second period after the specified time point. This allows the transmission capacity estimation device to improve the accuracy of the correction of the second temperature forecast data for a period shorter than the second period after the specified time point. In addition, the transmission capacity estimation device can easily acquire the second weather forecast data, for example, from the local model (LFM) of the Japan Meteorological Agency. As a result, the transmission capacity estimation device can achieve flexible and accurate operation of the transmission line with a simple configuration.

The acquisition unit may also acquire the first weather forecast data, which further includes first altitude data indicating the altitude of a prediction point, and the weather observation data, which further includes second altitude data indicating the altitude of an observation point, and the correction unit may further use the first altitude data and the second altitude data to correct the second temperature forecast data according to the altitude of the power transmission line in the specified area.

Temperature changes depending on the altitude. For example, as the altitude increases, the temperature decreases, and as the altitude decreases, the temperature increases. For this reason, the power transmission capacity estimation device uses the first altitude data of the prediction point and the second altitude data of the observation point to correct the second temperature prediction data according to the altitude of the power transmission line. In this way, the power transmission capacity estimation device can accurately correct the second temperature prediction data, thereby enabling flexible and accurate operation of the power transmission line with a simple configuration.

The acquisition unit may also acquire the first weather forecast data further including data indicating at least one predicted value of the wind speed, the amount of solar radiation, and the amount of precipitation in the specified area, and the estimation unit may estimate the available power transmission capacity further using data indicating at least one predicted value of the wind speed, the amount of solar radiation, and the amount of precipitation included in the first weather forecast data.

The available power transmission capacity is also affected by wind speed, solar radiation, or precipitation. For example, high wind speed around a power transmission line reduces the temperature of the power transmission line, high solar radiation increases the temperature of the power transmission line, and high precipitation reduces the temperature of the power transmission line, thereby affecting the available power transmission capacity. For this reason, the available power transmission capacity estimation device acquires first weather forecast data that further includes data indicating at least one predicted value of wind speed, solar radiation, and precipitation, and estimates the available power transmission capacity using further data indicating at least one predicted value of wind speed, solar radiation, and precipitation. As a result, the available power transmission capacity estimation device can accurately estimate the available power transmission capacity, thereby enabling flexible and accurate operation of the power transmission line with a simple configuration.

The present invention can be realized not only as such a transmission capacity estimation device, but also as a transmission capacity estimation method in which steps correspond to characteristic processes performed by a processing unit included in the transmission capacity estimation device. The present invention can also be realized as a program for causing a computer to execute the steps included in the transmission capacity estimation method, or as a computer-readable recording medium such as a CD-ROM on which the program is recorded. The program can then be distributed via the recording medium and a transmission medium such as the Internet. The present invention can also be realized as an integrated circuit equipped with a processing unit included in the transmission capacity estimation device.

The transmission capacity estimation device and the like according to the present invention can achieve flexible operation of transmission lines with a simple configuration.

2 is a diagram showing a connection relationship between an available power transmission capacity estimation device and a meteorological data management device according to an embodiment. FIG. 1 is a block diagram showing a functional configuration of an available power transmission capacity estimation device according to an embodiment; 10 is a diagram showing an example of first temperature forecast data or second temperature forecast data included in first weather forecast data stored in a memory unit of the power transmission available capacity estimation device according to the embodiment. FIG. 5 is a diagram showing an example of temperature record data included in meteorological observation data stored in a storage unit of the power transmission available capacity estimation device according to the embodiment; FIG. 1 is a flowchart showing a process (a method for estimating an available power transmission capacity) in which an available power transmission capacity estimation device according to an embodiment estimates an available power transmission capacity, which is an operable capacity of a transmission line. 6 is a flowchart showing a process for calculating air temperature error data by a correction unit according to the embodiment. 13A and 13B are diagrams illustrating a process in which a correction unit according to an embodiment obtains the maximum predicted value of air temperature and the maximum actual value of air temperature. 13 is a diagram illustrating a process in which a correction unit according to an embodiment calculates a 100th percentile value of the difference between a predicted temperature value and a result temperature value. FIG. 11 is a flowchart showing a process in which a correction unit according to the embodiment corrects second temperature prediction data. 11 is a flowchart showing a process in which a correction unit in the embodiment corrects second temperature forecast data using second weather forecast data. FIG. 11 is a diagram showing second temperature forecast data after correction by the correction unit in the embodiment. 10 is a flowchart showing a process in which an estimating unit according to the embodiment estimates a transmittable capacity. 11 is a diagram showing an estimated value of a transmittable capacity calculated by an estimation unit according to the embodiment. FIG.

The following describes an available power transmission capacity estimation device and an available power transmission capacity estimation method according to an embodiment of the present invention (including its modified examples) with reference to the drawings. Note that the embodiments described below are all comprehensive or specific examples. The numerical values, components, the arrangement and connection of the components, steps, and the order of steps shown in the following embodiments are merely examples and are not intended to limit the present invention.

(Embodiment)
[1. Description of the configuration of the power transmission capacity estimation device 100]
First, the configuration of the available power transmission capacity estimation device 100 will be described. Fig. 1 is a diagram showing a connection relationship between the available power transmission capacity estimation device 100 and a meteorological data management device 200 according to the present embodiment. Fig. 2 is a block diagram showing a functional configuration of the available power transmission capacity estimation device 100 according to the present embodiment. Fig. 3A is a diagram showing an example of first temperature forecast data or second temperature forecast data included in the first weather forecast data 151 stored in the storage unit 150 of the available power transmission capacity estimation device 100 according to the present embodiment. Fig. 3B is a diagram showing an example of temperature record data included in the meteorological observation data 153 stored in the storage unit 150 of the available power transmission capacity estimation device 100 according to the present embodiment.

The transmission capacity estimation device 100 is a device that estimates the transmission capacity, which is the operational capacity of a transmission line. A transmission line is an overhead high-voltage power line (high-voltage line) for transmitting power generated at a power generation facility such as a power plant to a substation, a distribution station, or a consumer, and is arranged, for example, on a commercial power system of a power company. The operational capacity (transmission capacity) of a transmission line is the capacity (e.g., MW) of power that can be supplied by the transmission line in operation, and varies depending on the temperature around the transmission line, etc. For example, if the temperature around the transmission line is high, the operational capacity (transmission capacity) of the transmission line decreases due to a decrease in the strength of the transmission line caused by heat, and if the temperature around the transmission line is low, the operational capacity (transmission capacity) of the transmission line increases.

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

The meteorological data management device 200 is a device that holds meteorological information such as temperature, wind speed, solar radiation, and precipitation at a specific time and a specific location. For example, the meteorological data management device 200 is a computer or other device installed in the Japan Meteorological Agency, or a computer or other device that acquires data from the Japan Meteorological Agency. As shown in FIG. 1, the meteorological data management device 200 includes a mesomodel data holding unit 210, a local model data holding unit 220, and an AMeDAS data holding unit 230.

The meso model data storage unit 210 is a memory or the like that stores (stores) data predicted by the Meso Model (MSM) of the Japan Meteorological Agency. The Meso Model (MSM) is a model that has a horizontal grid interval of 5 km, a calculation domain of Japan and its adjacent seas, a distribution delay time of about 2.5 hours, and updates every 3 hours (8 times a day), and can perform forecast calculations up to 39 hours in advance, thereby predicting meteorological phenomena from several hours to one day in advance. Specifically, the meso model data storage unit 210 stores the first weather forecast data 211. The first weather forecast data 211 is a collection of data including forecast values of meteorological information such as temperature, wind speed, solar radiation, precipitation, altitude, air pressure, humidity, and cloud cover. The first weather forecast data 211 has data for these meteorological information at a mesh resolution of 5 km horizontal grid interval, an update frequency of every 3 hours (8 times a day), and has data for a total of 39 sections (39 hours of data for every hour on the hour) with one section at every hour on the hour.

The local model data storage unit 220 is a memory or the like that stores (stores) data predicted by the local model (LFM) of the Japan Meteorological Agency. The local model (LFM) is a model that performs forecast calculations for a short forecast period (up to 10 hours ahead) with a finer horizontal grid interval (2 km), a short delivery delay time (about 1.5 hours), and a short update interval (updated every hour (24 times a day)) than the mesomodel, and can grasp weather phenomena for about a few hours in the future. Specifically, the local model data storage unit 220 stores second weather forecast data 221. The second weather forecast data 221 is a collection of data including forecast values of weather information similar to the first weather forecast data 211, such as temperature. The second weather forecast data 221 has high resolution of a horizontal grid interval of 2 km mesh, an update frequency of every hour (24 times a day), and data for a total of 10 sections (10 hours' worth of data for every hour on the hour) with one section at every hour on the hour.

The AMeDAS data storage unit 230 is a memory or the like that stores (stores) data observed by the Japan Meteorological Agency's AMeDAS (regional weather observation system). The AMeDAS data storage unit 230 can acquire data from each AMeDAS every hour, with a delivery delay of about a few minutes. The AMeDAS data storage unit 230 stores 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, hours of sunshine, and precipitation. The meteorological observation data 231 contains hourly data on these meteorological information at each AMeDAS observation point.

The available power transmission capacity estimation device 100 acquires first weather forecast data 211, second weather forecast data 221, and weather observation data 231 from the weather data management device 200 via the communication network 300. The available power transmission capacity estimation device 100 then estimates the available power transmission capacity, which is the operational capacity of the power transmission line, using the first weather forecast data 211, the second weather forecast data 221, and the weather observation data 231. The specific configuration of the available power transmission capacity estimation device 100 will be described in detail below.

As shown in FIG. 2, the available 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 available 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 description of these will be omitted.

The acquisition unit 110 acquires the first weather forecast data 211, the second weather forecast data 221, and the weather observation data 231. Specifically, the acquisition unit 110 acquires the first weather forecast data 211, the second weather forecast data 221, and the weather observation data 231 from the weather data management device 200 via the communication network 300.

As described above, the first weather forecast data 211 is a collection of data including predicted values of temperature. Therefore, the first weather forecast data 211 includes predicted values of temperature in a specified area in a first period before a specified time point (e.g., the past three years from the present time) and predicted values of temperature in a specified area in a second period after the specified time point (e.g., from one hour to 39 hours ahead). The specified area may be an area of any size, but is, for example, an area in units of the Japan Meteorological Agency's primary subdivision area (area for which weather forecasts are issued), such as the Osaka Prefecture area, the northern Hyogo Prefecture area, the southern Hyogo Prefecture area, etc. The same applies below. In this way, the first weather forecast data 211 includes first temperature forecast data and second temperature forecast data that indicate predicted values of temperature in a specified area in a first period before the specified time point and in a second period after the specified time point.

The first temperature forecast data is data that indicates the predicted temperature values for the past 39 hours at each point (five points A to E in FIG. 3A) in a specified area predicted by a meso model (MSM) as shown in FIG. 3A, collected over a first period (e.g., the past three years from the present). Similarly, the second temperature forecast data is data that indicates the predicted temperature values for a second period (e.g., from one hour ahead to 39 hours ahead) at each point (five points A to E in FIG. 3A) in a specified area predicted by a meso model (MSM), as shown in FIG. 3A.

Furthermore, as described above, the first weather forecast data 211 also includes predicted values of altitude, wind speed, solar radiation, precipitation, and the like. That is, the first weather forecast data 211 further includes first altitude data indicating the altitude of a predicted point in a specified area. The first weather forecast data 211 further includes data indicating at least one predicted value of wind speed, solar radiation, and precipitation in a specified area in a first period and a second period. The first altitude data included in the first weather forecast data 211, as well as the data indicating the predicted values of wind speed, solar radiation, and precipitation, are also data corresponding to each location and each time, as shown in FIG. 3A.

The second weather forecast data 221, like the first weather forecast data 211, also includes third temperature forecast data indicating a predicted value of the temperature in a specified area. In this embodiment, the third temperature forecast data is data indicating a predicted value of the temperature in a specified area a specified period (e.g., one hour) before a specified time point (e.g., the present time) and a predicted value of the temperature for a period shorter than the second period after the specified time point (e.g., from one hour to ten hours ahead). Furthermore, like the first weather forecast data 211, the second weather forecast data 221 includes third altitude data indicating the altitude of a predicted point in the specified area, and data indicating at least one predicted value of wind speed, solar radiation, and precipitation in the specified area during the first period.

As described above, the second weather forecast data 221 has a shorter prediction period (up to 10 hours ahead) than the first weather forecast data 211's prediction period (up to 39 hours ahead), and a shorter delivery delay time (about 1.5 hours) than the first weather forecast data 211's delivery delay time (about 2.5 hours). As described above, the second weather forecast data 221 has a shorter update interval (every hour) than the first weather forecast data 211's update interval (every three hours). Therefore, the second weather forecast data 221 has a shorter prediction period and a shorter delivery delay time than the first weather forecast data 211. Furthermore, the second weather forecast data 221 has a shorter prediction period and a shorter update interval than the first weather forecast data 211. Each data included in the second weather forecast data 221 is, for example, data in which the time on the horizontal axis shown in FIG. 3A is 10 hours.

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

The acquisition unit 110 writes the acquired first weather forecast data 211, second weather forecast data 221, and weather observation data 231 to the first weather forecast data 151, second weather forecast data 152, and weather observation data 153 stored in the storage unit 150. That is, the acquisition unit 110 writes the first temperature forecast data, second temperature forecast data, first altitude data, and data indicating the forecast values of wind speed, solar radiation, and precipitation included in the first weather forecast data 211 to the first weather forecast data 151 to update the first weather forecast data 151. In addition, the acquisition unit 110 writes the third temperature forecast data, third altitude data, and data indicating the forecast values of wind speed, solar radiation, and precipitation included in the second weather forecast data 221 to the second weather forecast data 152 to update the second weather forecast data 152. Furthermore, the acquisition unit 110 writes the actual temperature data and second altitude data included in the weather observation data 231 to the weather observation data 153 to update the weather observation data 153.

For example, the thermometer at the AMeDAS observation point may be installed at an altitude of 1.5 m above ground, and 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 may be written in advance to the meteorological observation data 153, and the acquisition unit 110 may acquire the second altitude data from the meteorological observation data 153. The same applies to other data.

The correction unit 120 uses the first temperature forecast data and the actual temperature data to calculate temperature error data indicating the forecast error of the temperature in a specified area. The forecast error of the temperature is the deviation (error) of the forecast 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 forecast value of the temperature indicated by the first temperature forecast data and the maximum value of the actual value of the temperature indicated by the actual temperature data as the temperature error data. The correction unit 120 also determines whether the forecast value of the temperature indicated by the first temperature forecast data is smaller than the actual value of the temperature indicated by the actual temperature data, extracts the forecast value of the temperature and the actual value of the temperature when the forecast value of the temperature is smaller than the actual value of the temperature, and calculates the temperature error data. The correction unit 120 also extracts a value within a specified range from the forecast value of the temperature indicated by the second temperature forecast data in the forecast value of the temperature indicated by the first temperature forecast data, and calculates the temperature error data. Furthermore, the correction unit 120 calculates temperature error data by taking the 100th percentile value of the difference between the predicted temperature value indicated in the first temperature prediction data and the actual temperature value indicated in the actual temperature data as the temperature prediction error.

The correction unit 120 also corrects the second temperature forecast 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 forecast data according to the altitude of the power line in the specified area. More specifically, the correction unit 120 uses the second weather forecast data 152 to correct the second temperature forecast data for a period shorter than the second period after the specified point in time. A more detailed explanation of these processes performed by the correction unit 120 will be given later.

In the above process performed by the correction unit 120, the acquisition unit 110 first acquires the first weather forecast data 151, the second weather forecast data 152, and the weather observation data 153 stored in the memory unit 150. Then, the correction unit 120 calculates the temperature error data using the first temperature forecast data included in the acquired first weather forecast data 151 and the actual temperature data included in the weather observation data 153. Then, the correction unit 120 corrects the second temperature forecast data included in the first weather forecast data 151 using the calculated temperature error data, the first altitude data included in the first weather forecast data 151, the second altitude data included in the weather observation data 153, and the third altitude data included in the second weather forecast data 152. Then, the correction unit 120 writes the corrected second temperature forecast data to the first weather forecast data 151 stored in the memory unit 150, and updates the second temperature forecast data of the first weather forecast data 151. The correction unit 120 may temporarily write the calculated temperature error data to the estimation data 154 stored in the storage unit 150, and then read the temperature error data from the storage unit 150 to correct the second temperature prediction data.

The estimation unit 130 estimates the transmission capacity in a specified area in the second period using the corrected second temperature forecast data. Specifically, the estimation unit 130 estimates the transmission capacity by further using data indicating at least one of the forecast values of wind speed, solar radiation, and precipitation included in the first weather forecast data 151. For example, the acquisition unit 110 acquires the corrected first weather forecast data 151 stored in the storage unit 150. Then, the estimation unit 130 calculates an estimate of the transmission capacity, which is the operational capacity of the transmission line, using the second temperature forecast data included in the acquired first weather forecast data 151 and the data indicating the forecast values of wind speed, solar radiation, and precipitation. Then, the estimation unit 130 writes the calculated estimate of the transmission capacity to the estimation data 154 stored in the storage unit 150, and updates the estimation data 154. A more detailed explanation of the above process performed by the estimation unit 130 will be described later.

The output unit 140 outputs the available 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. The output unit 140 then reads out the estimated value of the available 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 available power transmission capacity to a display unit such as a liquid crystal display provided in the available power transmission capacity estimation device 100, and displays the estimated value of the available power transmission capacity.

The storage unit 150 is a memory that stores data for estimating the transmission capacity, which is the operational capacity of the power transmission line. Specifically, the storage unit 150 stores the above-mentioned first weather forecast data 151, second weather forecast data 152, meteorological observation data 153, and estimation data 154. Note that the first weather forecast data 151, second weather forecast data 152, meteorological observation data 153, and estimation data 154 may be rewritten each time the data is updated, or the data may be accumulated.

[2. Description of the Processing Flow of the Available Power Transmission Capacity Estimation Device 100]
Next, a process of estimating the available power transmission capacity, which is the operable capacity of a transmission line, performed by the available power transmission capacity estimation device 100 will be described. Fig. 4 is a flowchart showing a process (available power transmission capacity estimation method) performed by the available power transmission capacity estimation device 100 according to the present embodiment to estimate the available power transmission capacity, which is the operable capacity of a transmission line.

As shown in FIG. 4, first, the acquisition unit 110 acquires the first weather forecast data 211 (151), the second weather forecast data 221 (152), and the weather observation data 231 (153) (S102, acquisition step). Specifically, the acquisition unit 110 acquires the first weather forecast data 211 (151) including the first temperature forecast data for the first period, the second temperature forecast data for the second period, the first altitude data of the forecast point, and data indicating at least one forecast value of the wind speed, the amount of solar radiation, and the amount of precipitation in a specified area. The acquisition unit 110 also acquires the weather observation data 231 (153) including the actual temperature data for the first period in the specified area and the second altitude data of the observation point. Furthermore, the acquisition unit 110 acquires the second weather forecast data 221 (152) which has a shorter forecast period, a shorter delivery delay time, and a shorter update interval than the first weather forecast data 211 (151).

For example, in the first weather forecast data 211 (151), the acquisition unit 110 can acquire 8,760 (= 8 times/day x 365 days x 3 years) predicted temperature values from a meso model (MSM) for each point in a specified area for which the temperature is to be predicted, for each point in time over the past three years (first period) from the present time. In the example shown in FIG. 3A, the acquisition unit 110 acquires first temperature forecast data including 8,760 predicted temperature values for each point in time over the past three years at points A to E in the specified area. In addition, the acquisition unit 110 acquires second temperature forecast data including predicted temperature values from 1 hour to 39 hours ahead at points A to E in the specified area.

In the second weather forecast data 221 (152), the acquisition unit 110 acquires from a local model (LFM) third temperature forecast data including a forecast value of the temperature one hour ahead (current time) predicted, for example, one hour ago, at each point in the specified area, and forecast values of the temperature from one hour ahead to ten hours ahead from the current time. In addition, in the meteorological observation data 231 (153), the acquisition unit 110 acquires from AMeDAS actual values of the temperature at each point in the specified area for each time point in the past three years (first period) from the current time.

Then, the correction unit 120 uses the first temperature forecast data and the actual temperature data acquired by the acquisition unit 110 to calculate temperature error data indicating the forecast error of the temperature in the specified area (S104), and corrects the second temperature forecast data using the calculated temperature error data (S106) (correction step). A detailed explanation of the process by which the correction unit 120 calculates the temperature error data (S104) and the process by which the correction unit 120 corrects the second temperature forecast data (S106) will be given later.

Then, the estimation unit 130 estimates the available power transmission capacity in the specified area in the second time period using the first weather forecast data 151 including the second temperature forecast data corrected by the correction unit 120 (S108, estimation step). A detailed explanation of the process (S108) in which the estimation unit 130 estimates the available power transmission capacity will be described later.

Then, the output unit 140 outputs the transmittable capacity estimated by the estimation unit 130 (S110, output step). For example, the output unit 140 transmits the transmittable capacity to an external device, or outputs it to a display unit such as a liquid crystal display of the transmittable capacity estimation device 100 to display the estimated value of the transmittable capacity. Specifically, the output unit 140 outputs a graph of the estimated value of the transmittable capacity shown in FIG. 12 described later, or a numerical value indicating the estimated value of the transmittable capacity. The output unit 140 may output the temperature error data calculated by the correction unit 120, or the second temperature forecast data corrected by the correction unit 120. For example, the output unit 140 may output a graph of the second temperature forecast data shown in FIG. 10 described later, or a numerical value indicating the second temperature forecast data.

The available power transmission capacity estimation device 100 executes the above process for all areas for which it is desired to estimate the available power transmission capacity, and estimates the available power transmission capacity for all areas. In this manner, the process in which the available power transmission capacity estimation device 100 estimates the available power transmission capacity, which is the operational capacity of the transmission line, is completed.

Next, the process (S104 in FIG. 4) in which the correction unit 120 calculates the temperature error data will be described in detail. FIG. 5 is a flowchart showing the process (S104 in FIG. 4) in which the correction unit 120 according to this embodiment calculates the temperature error data. FIG. 6 is a diagram explaining the process (S206 in FIG. 5) in which the correction unit 120 according to this embodiment acquires the maximum predicted value of the temperature and the maximum actual value of the temperature. FIG. 7 is a diagram explaining the process (S216 in FIG. 5) in which the correction unit 120 according to this embodiment calculates the 100th percentile value of the difference between the predicted value of the temperature and the actual value of the temperature.

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

Then, the correction unit 120 performs a correction to align the altitude of the temperature forecast value in the first temperature forecast data and the actual temperature value in the actual temperature data (S204). Specifically, the correction unit 120 acquires first altitude data from the first weather forecast data 151, and acquires second altitude data from the meteorological observation data 153. The correction unit 120 then performs a correction to align the altitude of the first temperature forecast data and the actual temperature data using the first altitude data and the second altitude data. For example, the correction unit 120 corrects the actual temperature data with a correction rate of 0.65°C/100m so that the actual temperature data at the second altitude data becomes the data at the first altitude data.

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 corrected to match the altitude in the above process (S204). For example, as shown in FIG. 6, the correction unit 120 acquires the predicted temperature value TA38 = 34.0°C 38 hours ahead at point A, which is the maximum value of the predicted temperature, and the actual temperature value TD39 = 36.0°C 39 hours ahead at point D, which is the maximum value of the actual temperature. In other words, 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 of the first period in the specified area. The period corresponding to the second period of the first period is a period of the same length as the second period in the same season or month as the second period of the first period.

Then, 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 (S208). Specifically, the correction unit 120 determines whether the maximum predicted temperature value is smaller than the maximum actual temperature value for each of the maximum predicted temperature value and the maximum actual temperature value obtained in the above process (S206).

If the predicted temperature value indicated by the first temperature prediction data is smaller than the actual temperature value indicated by the actual temperature data (YES in S208), the correction unit 120 extracts the predicted temperature value and the actual temperature value (S210). If the predicted temperature value indicated by the first temperature prediction data is equal to or greater than the actual temperature value indicated by the actual temperature data (NO in S208), the correction unit 120 does not extract the predicted temperature value and the actual temperature value (S212). In other words, the correction unit 120 extracts the maximum predicted temperature value and the maximum actual temperature value only if the maximum predicted temperature value is smaller than the maximum actual temperature value.

Then, the correction unit 120 extracts a value within a predetermined range from the predicted value of the temperature indicated by the second temperature forecast data from the predicted value of the temperature indicated by the first temperature forecast data (S214). Specifically, the correction unit 120 determines whether the maximum value of the predicted value of the temperature extracted in the above process (S210) is within a predetermined range from the maximum value of the predicted value of the temperature indicated by the second temperature forecast data, and extracts the maximum value of the predicted value of the temperature if the maximum value of the predicted value of the temperature is within the predetermined range. The correction unit 120 obtains the maximum value of the predicted value of the temperature indicated by the second temperature forecast data using a method similar to the process (S206) for obtaining the maximum value of the predicted value of the temperature indicated by the first temperature forecast data. For example, if the maximum value of the predicted value of the temperature indicated by the second temperature forecast data is 25°C, the correction unit 120 extracts a value within the range of 25°C ± 2°C (23°C to 27°C) from the maximum value of the predicted value of the temperature indicated by the first temperature forecast data.

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

In this embodiment, in the above process (S214 and S216), the correction unit 120 performs the following process. As shown in FIG. 7, the correction unit 120 samples the prediction error (difference) in the case where the maximum value of the predicted value of the temperature indicated by the first temperature prediction data is the temperature ±2°C in increments of 1°C for the range of -10 to 40°C, and calculates the percentile value of the prediction error. Next, the correction unit 120 obtains the maximum value of the predicted value of the temperature indicated by the second temperature prediction data. For example, if the maximum value of the predicted value of the temperature indicated by the second temperature prediction data is 25°C, the correction unit 120 calculates from the data shown in FIG. 7 that the 100th percentile value of the prediction error when the predicted value of the temperature is 25°C is 5.7°C. As a result, the correction unit 120 calculates that the temperature error data is 5.7°C.

In this way, the process in which the correction unit 120 calculates the temperature error data (S104 in FIG. 4) is completed.

Next, the process (S106 in FIG. 4) in which the correction unit 120 corrects the second temperature forecast 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 temperature forecast 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 temperature forecast data using the second weather forecast data 152. FIG. 10 is a diagram showing the second temperature forecast data after correction by the correction unit 120 according to this embodiment.

First, the correction unit 120 corrects the second temperature forecast data using the temperature error data (S302). Specifically, the correction unit 120 obtains the second temperature forecast data from the first weather forecast data 151, and adds the temperature error data calculated in the above process (S104 in FIG. 4) to the second temperature forecast data to correct the second temperature forecast data. For example, if the correction unit 120 calculates that the temperature error data is 5.7°C, it adds 5.7°C to the predicted values of the temperatures at each time in the second temperature forecast data from 1 hour ahead to 39 hours ahead to correct the second temperature forecast data.

Then, the correction unit 120 further corrects the second temperature forecast data using the second weather forecast data 152 (S304). Specifically, the correction unit 120 corrects the second temperature forecast data for a period shorter than the second period after the specified point in time using the second weather forecast data 152. The process in which the correction unit 120 further corrects the second temperature forecast data is described in detail below.

As shown in FIG. 9, the correction unit 120 acquires third temperature forecast data and actual temperature data from the second weather forecast data 152 and the weather observation data 153 (S402). Specifically, the correction unit 120 acquires third temperature forecast data from the second weather forecast data 152, and acquires actual temperature data from the weather observation data 153. In this embodiment, the third temperature forecast data is data indicating, for example, a forecast value of the temperature one hour before the present time in a specified area, and a forecast value of the temperature one hour to ten hours ahead.

Then, the correction unit 120 performs a correction to match the altitude of the temperature prediction value in the third temperature prediction data and the actual temperature value in the actual temperature data (S404). Specifically, the correction unit 120 performs a correction to match the altitude of the third temperature prediction data and the actual temperature data using a method similar to the correction to match the altitude of the first temperature prediction data and the actual temperature data (S204 in FIG. 5).

Then, the correction unit 120 obtains the maximum value of the predicted temperature indicated in the third temperature prediction data and the maximum value of the actual temperature indicated in the actual temperature 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 actual temperature data corrected to match the altitude in the above process (S404). For example, the correction unit 120 obtains the maximum value of the predicted temperature one hour prior to the current time point predicted in the specified area and the maximum value of the actual temperature at the current time point.

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

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

Then, the correction unit 120 corrects the second temperature forecast data for a period shorter than the second period after the specified time point (S414). Specifically, the correction unit 120 adds the temperature error data calculated in the above processes (S410 and S412) to the predicted value of the temperature in the period shorter than the second period after the specified time point in the third temperature forecast data, and corrects the predicted value of the temperature in the short period of the third temperature forecast data. Then, the correction unit 120 corrects the second temperature forecast data by rewriting the predicted value of the temperature in the short period of the second temperature forecast data to the predicted value of the temperature in the short period of the corrected third temperature forecast data. For example, the correction unit 120 adds the temperature error data to the predicted value of the temperature from one hour ahead to two hours ahead in the third temperature forecast data, and corrects the predicted value of the temperature from one hour ahead to two hours ahead in the third temperature forecast data. Then, the correction unit 120 corrects the second temperature forecast data by rewriting the predicted values of the temperature from one hour to two hours ahead in the second temperature forecast data to the predicted values of the temperature from one hour to two hours ahead in the corrected third temperature forecast data.

Returning to FIG. 8, the correction unit 120 corrects the second temperature forecast data using the first altitude data (S306). Specifically, the correction unit 120 corrects the second temperature forecast data to second temperature forecast data according to the altitude of the power line in the specified area. In other words, the correction unit 120 corrects the second temperature forecast data with a correction rate of 0.65°C/100m so that the second temperature forecast data for the first altitude data becomes data at the same altitude as the power line located in the specified area.

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

In this manner, the process in which the correction unit 120 corrects the second temperature forecast data (S106 in FIG. 4) is completed.

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

First, the estimation unit 130 calculates the available power transmission capacity using the second temperature forecast data (S502). Specifically, the estimation unit 130 calculates the available power transmission capacity in a specified area in the second time period using the first weather forecast data 151 including the second temperature forecast data corrected by the correction unit 120. For example, the estimation unit 130 calculates the available power transmission capacity in a specified area in the second time period by substituting the second temperature forecast data in the specified area in the second time period into a relational equation indicating the relationship between the second temperature forecast data and the available power transmission capacity. Any relational equation may be used as the relational equation, but for example, it is a mathematical equation in which the available power transmission capacity decreases as the predicted value of the temperature indicated by the second temperature forecast data increases.

Then, the estimation unit 130 corrects the available power transmission capacity by further using data indicating at least one of the predicted values of wind speed, solar radiation, and precipitation included in the first weather forecast data 151 (S504). That is, the estimation unit 130 corrects the available power transmission capacity calculated in the above process (S502) by further using data indicating predicted values of meteorological information other than temperature, such as wind speed, solar radiation, and precipitation, in the specified area in the second period. For example, the estimation unit 130 corrects the available power transmission capacity in the specified area in the second period by substituting data on the wind speed, solar radiation, and precipitation in the specified area in the second period into a relational equation indicating the relationship between the wind speed, solar radiation, and precipitation and the available power transmission capacity. Any relational equation may be used as the relational equation, but for example, it is a mathematical equation in which the higher the wind speed, the higher the available power transmission capacity, the higher the amount of solar radiation, the lower the available power transmission capacity, and the higher the amount of precipitation, the higher the available power transmission capacity.

The estimation unit 130 may calculate the transmission capacity in a specified area in the second period by substituting the second temperature forecast data, wind speed, solar radiation, and precipitation data in the specified area in the second period into a relational equation showing the relationship between the second temperature forecast data, wind speed, solar radiation, and precipitation and the transmission capacity.

In this way, the estimation unit 130 estimates the available power transmission capacity and obtains an estimated value of the available power transmission capacity as shown in FIG. 12. As shown in FIG. 12, the estimated value of the available power transmission capacity is larger than the available power transmission capacity that was previously estimated. Therefore, even if the expected power flow without considering the available power transmission capacity exceeds the conventional available power transmission capacity, the expected power flow does not exceed the estimated value of the available power transmission capacity, and therefore operation can be performed without restricting the expected power flow.

In this manner, the process in which the estimation unit 130 estimates the available power transmission capacity (S108 in FIG. 4) ends.

[3. Description of Effects]
The power transmission capacity estimation device 100 according to the embodiment of the present invention acquires first weather forecast data 211 including first temperature forecast data and second temperature forecast data for the first period and the second period, and weather observation data 231 including actual temperature data for the first period. For example, the power transmission capacity estimation device 100 acquires forecast data from the Meso Model (MSM) of the Japan Meteorological Agency and acquires observation data from AMeDAS, so that the first weather forecast data 211 and the weather observation data 231 can be acquired without the need to install multiple sensors on the power transmission line route. In addition, the power transmission capacity estimation device 100 calculates temperature error data using the first temperature forecast data and the actual temperature data, corrects the second temperature forecast data using the temperature error data, and estimates the power transmission capacity in the second period using the corrected second temperature forecast data. In this way, the power transmission capacity estimation device 100 estimates the power transmission capacity in the second period using the second temperature forecast data with the error corrected. As a result, the available power transmission capacity estimation device 100 can estimate the available power transmission capacity, which is the operable capacity of the power transmission line in the second period after the predetermined time point, with relatively high accuracy, and therefore the power transmission line can be flexibly operated based on the estimated available power transmission capacity. Therefore, the available power transmission capacity estimation device 100 can flexibly operate the power transmission line with a simple configuration.

In addition, since there is no need to install multiple sensors on the power line route, costs can be reduced. Furthermore, power lines are placed across multiple points within a specified area, and if temperature error data is calculated for each point, the error may become too large. If temperature error data is calculated for each point and the transmittable capacity is estimated for each point, the control of the transmittable capacity also becomes complicated. For this reason, the transmittable capacity estimation device 100 calculates temperature error data for each area, so that the transmittable capacity is not too small, and flexible operation of the power lines can be achieved with a transmittable capacity that matches the actual situation.

The available power transmission capacity estimation device 100 also calculates the difference between the maximum predicted temperature value and the maximum actual temperature value during the first period as temperature error data. In other words, when the temperature is at its maximum, the impact of the temperature on the available power transmission capacity is large, so the available power transmission capacity estimation device 100 calculates the temperature error data when the temperature is at its maximum. In this way, the available power transmission capacity estimation device 100 can estimate the available power transmission capacity on the safe side by correcting the second temperature prediction data based on the case where the impact is large. Therefore, the available power transmission capacity estimation device 100 can achieve flexible and safe operation of the power transmission line with a simple configuration.

The power transmission capacity estimation device 100 also determines whether the predicted temperature value in the first period is smaller than the actual temperature value, and when the predicted temperature value is smaller than the actual temperature value, extracts the predicted temperature value and the actual temperature value, and calculates temperature error data. In other words, the power transmission capacity estimation device 100 calculates temperature error data using data when the predicted temperature value is smaller than the actual temperature value, on the safe side. In this way, the power transmission capacity estimation device 100 can achieve flexible and safe operation of power transmission lines with a simple configuration.

In addition, if the past predicted value is too far from the future predicted value, the calculation accuracy may decrease if such a past predicted value is used to calculate the error of the future predicted value. For this reason, the power transmission capacity estimation device 100 extracts a value 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 the temperature error data. As a result, the power transmission capacity estimation device 100 does not use a value 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 in calculating the temperature error data, so that the calculation accuracy of the temperature error data can be improved. In addition, it is assumed that the error of the predicted value of the temperature differs depending on the predicted value of the temperature (if the predicted temperature is 25°C, an error of 5°C may occur, but it is unlikely that an error of 5°C will occur at a predicted temperature of 38°C). For this reason, the power transmission capacity estimation device 100 extracts a value within a predetermined range from the predicted value of the temperature in the second period, and calculates the error of the predicted value. As a result, the power transmission capacity estimation device 100 can improve the calculation accuracy of the temperature error data. As a result, the power transmission capacity estimation device 100 can operate power transmission lines flexibly and accurately with a simple configuration.

The power transmission capacity estimation device 100 also calculates temperature error data by taking the 100th percentile value of the difference between the predicted temperature value and the actual temperature value in the first period as the temperature prediction error. In other words, when the difference between the predicted temperature value and the actual temperature value varies, the power transmission capacity estimation device 100 takes the 100th percentile value of the difference as the temperature prediction error to be on the safe side, and calculates the temperature error data. As a result, the power transmission capacity estimation device 100 can achieve flexible and safe operation of power transmission lines with a simple configuration.

In addition, when the transmission capacity estimation device 100 acquires the first weather forecast data 211, if the delivery delay time of the first weather forecast data 211 is long, the accuracy of the correction of the second temperature forecast data using the first weather forecast data 211 may decrease. For this reason, the transmission capacity estimation device 100 acquires the second weather forecast data 221, which has a shorter prediction period than the first weather forecast data 211 but a shorter delivery delay time, and corrects the second temperature forecast data for a period shorter than the second period after the specified time point using the second weather forecast data 221 (152). As a result, the transmission capacity estimation device 100 can improve the accuracy of the correction of the second temperature forecast data for a period shorter than the second period after the specified time point. In addition, the transmission capacity estimation device 100 can easily acquire the second weather forecast data 221 from, for example, the local model (LFM) of the Japan Meteorological Agency. As a result, the transmission capacity estimation device 100 can operate the power transmission line flexibly and accurately with a simple configuration.

In addition, when the transmission capacity estimation device 100 acquires the first weather forecast data 211, if the update interval of the first weather forecast data 211 is long, the accuracy of the correction of the second temperature forecast data using the first weather forecast data 211 may decrease. For this reason, the transmission capacity estimation device 100 acquires the second weather forecast data 221, which has a shorter prediction period than the first weather forecast data 211 but a shorter update interval, and corrects the second temperature forecast data for a period shorter than the second period after the specified time point using the second weather forecast data 221 (152). As a result, the transmission capacity estimation device 100 can improve the accuracy of the correction of the second temperature forecast data for a period shorter than the second period after the specified time point. In addition, the transmission capacity estimation device 100 can easily acquire the second weather forecast data 221 from, for example, the local model (LFM) of the Japan Meteorological Agency. As a result, the transmission capacity estimation device 100 can operate the power transmission line flexibly and accurately with a simple configuration.

Furthermore, the temperature changes depending on the altitude. For example, as the altitude increases, the temperature decreases, and as the altitude decreases, the temperature increases. For this reason, the power transmission capacity estimation device 100 uses the first altitude data of the prediction point and the second altitude data of the observation point to correct the second temperature prediction data according to the altitude of the power transmission line. This allows the power transmission capacity estimation device 100 to accurately correct the second temperature prediction data, thereby enabling flexible and accurate operation of the power transmission line with a simple configuration.

The available power transmission capacity is also affected by wind speed, solar radiation, or precipitation. For example, high wind speed around the power transmission line reduces the temperature of the power transmission line, high solar radiation increases the temperature of the power transmission line, and high precipitation reduces the temperature of the power transmission line, thereby affecting the available power transmission capacity. For this reason, the available power transmission capacity estimation device 100 acquires first weather forecast data 211 that further includes data indicating at least one predicted value of wind speed, solar radiation, and precipitation, and estimates the available power transmission capacity using further data indicating at least one predicted value of wind speed, solar radiation, and precipitation. As a result, the available power transmission capacity estimation device 100 can accurately estimate the available power transmission capacity, and therefore can operate the power transmission line flexibly and accurately with a simple configuration.

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

For example, in the above embodiment, the first period before the specified time point is set to the past three years from the present time, and the second period after the specified time point is set to the future time point from one hour to 39 hours in the future. However, the first period may be any time and any length of time in the past, and the second period may be any time and any length of time in the future.

In the above 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 actual temperature data as the temperature error data. However, the numerical value used by the correction unit 120 when calculating the temperature error data does not have to be the maximum value, and the correction unit 120 may use a numerical value for any cross section.

In the above embodiment, the correction unit 120 extracts the predicted temperature value and the actual temperature value when the predicted temperature value indicated in the first temperature prediction data is smaller than the actual temperature value indicated in the actual temperature data. However, the correction unit 120 may extract data for all cases without determining whether the predicted temperature value is smaller than the actual temperature value.

In the above embodiment, the correction unit 120 extracts a value within a predetermined range from the predicted value of the temperature indicated by the second temperature forecast data, from the predicted value of the temperature indicated by the first temperature forecast data. However, the correction unit 120 may also extract a value outside the predetermined range.

In the above embodiment, the correction unit 120 calculates the temperature error data by taking the 100th percentile value of 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 temperature prediction error. However, the correction unit 120 may calculate the temperature error data by taking the 98th, 95th, 90th, or 80th percentile value as the temperature prediction error instead of the 100th percentile value.

In the above embodiment, the acquisition unit 110 acquires the second weather forecast data, and the correction unit 120 corrects the second temperature forecast data using the second weather forecast data. However, the acquisition unit 110 may not acquire the second weather forecast data, and the correction unit 120 may not correct the second temperature forecast data using the second weather forecast data.

In the above embodiment, the acquisition unit 110 acquires altitude data, and the correction unit 120 corrects the second temperature forecast 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 temperature forecast data using the altitude data.

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

The present invention can be realized not only as the transmission capacity estimation device 100 and the transmission capacity estimation method, but also as a program for causing a computer to execute steps included in the transmission capacity estimation method. In other words, each component included in the 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. Furthermore, the present invention can be realized as a computer-readable non-transitory recording medium on which the program is recorded, such as 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), or a semiconductor memory. The program can be distributed via the recording medium and a transmission medium such as the Internet. The present invention can also be realized as an integrated circuit having a processing unit included in the transmission capacity estimation device 100. In other words, each functional block of the transmission capacity estimation device 100 shown in FIG. 2 may be realized as an LSI (Large Scale Integration) which is an integrated circuit. These may be individually integrated into a single chip, or may be integrated into a single chip that includes some or all of the components. In this way, each component of the power transmission capacity estimation device 100 may be configured with dedicated hardware, or may be realized by executing a software program suitable for each component.

In addition, configurations constructed by combining any of the components in the above embodiments and their variations are also included within the scope of the present invention.

The present invention can be applied to a transmission capacity estimation device that estimates the transmission capacity, which is the operational capacity of a transmission line.

REFERENCE SIGNS LIST 100 Transmission capacity estimation device 110 Acquisition unit 120 Correction unit 130 Estimation unit 140 Output unit 150 Storage 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 storage unit 220 Local model data storage unit 230 AMeDAS data storage unit 300 Communication network

Claims (11)

A power transmission capacity estimation device that estimates a power transmission capacity, which is an operational capacity of a power transmission line, comprising:
an acquisition unit that acquires first weather forecast data including first temperature forecast data and second temperature forecast data indicating predicted values of temperature in a specified area for a first period before a specified time point and a second period after the specified time point, and meteorological observation data including actual temperature data indicating actual values of temperature in the specified area for the first period;
a correction unit that calculates temperature error data indicating a prediction error of the temperature in the specified area using the first temperature prediction data and the temperature record data, and corrects the second temperature prediction data using the calculated temperature error data;
an estimation unit that estimates the available power transmission capacity in the specified area during the second period by using the corrected second temperature forecast data ,
The correction unit calculates, as the temperature error data, a difference between a maximum value of the predicted temperature value indicated by the first temperature prediction data and a maximum value of the actual temperature value indicated by the actual temperature data.
Transmission capacity estimation device. A power transmission capacity estimation device that estimates a power transmission capacity, which is an operational capacity of a power transmission line, comprising:
an acquisition unit that acquires first weather forecast data including first temperature forecast data and second temperature forecast data indicating predicted values of temperature in a specified area for a first period before a specified time point and a second period after the specified time point, and meteorological observation data including actual temperature data indicating actual values of temperature in the specified area for the first period;
a correction unit that calculates temperature error data indicating a prediction error of the temperature in the specified area using the first temperature prediction data and the temperature record data, and corrects the second temperature prediction data using the calculated temperature error data;
an estimation unit that estimates the available power transmission capacity in the specified area during the second period by using the corrected second temperature forecast data,
The correction unit determines whether the predicted value of the temperature indicated by the first temperature prediction data is smaller than the actual value of the temperature indicated by the actual temperature data, extracts the predicted value of the temperature and the actual value of the temperature when the predicted value of the temperature is smaller than the actual value of the temperature, and calculates the temperature error data.
Transmission capacity estimation device. A power transmission capacity estimation device that estimates a power transmission capacity, which is an operational capacity of a power transmission line, comprising:
an acquisition unit that acquires first weather forecast data including first temperature forecast data and second temperature forecast data indicating predicted values of temperature in a specified area for a first period before a specified time point and a second period after the specified time point, and meteorological observation data including actual temperature data indicating actual values of temperature in the specified area for the first period;
a correction unit that calculates temperature error data indicating a prediction error of the temperature in the specified area using the first temperature prediction data and the temperature record data, and corrects the second temperature prediction data using the calculated temperature error data;
an estimation unit that estimates the available power transmission capacity in the specified area during the second period by using the corrected second temperature forecast data,
The correction unit extracts a value within a predetermined range from the predicted value of the temperature indicated by the second temperature prediction data, from the predicted value of the temperature indicated by the first temperature prediction data, to calculate the temperature error data.
Transmission capacity estimation device. A power transmission capacity estimation device that estimates a power transmission capacity, which is an operational capacity of a power transmission line, comprising:
an acquisition unit that acquires first weather forecast data including first temperature forecast data and second temperature forecast data indicating predicted values of temperature in a specified area for a first period before a specified time point and a second period after the specified time point, and meteorological observation data including actual temperature data indicating actual values of temperature in the specified area for the first period;
a correction unit that calculates temperature error data indicating a prediction error of the temperature in the specified area using the first temperature prediction data and the temperature record data, and corrects the second temperature prediction data using the calculated temperature error data;
an estimation unit that estimates the available power transmission capacity in the specified area during the second period by using the corrected second temperature forecast data,
The correction unit calculates the temperature error data by taking a 100th percentile value of the difference between the predicted value of the temperature indicated by the first temperature prediction data and the actual value of the temperature indicated by the actual temperature data as a prediction error of the temperature.
Transmission capacity estimation device. A power transmission capacity estimation device that estimates a power transmission capacity, which is an operational capacity of a power transmission line, comprising:
an acquisition unit that acquires first weather forecast data including first temperature forecast data and second temperature forecast data indicating predicted values of temperature in a specified area for a first period before a specified time point and a second period after the specified time point, and meteorological observation data including actual temperature data indicating actual values of temperature in the specified area for the first period;
a correction unit that calculates temperature error data indicating a prediction error of the temperature in the specified area using the first temperature prediction data and the temperature record data, and corrects the second temperature prediction data using the calculated temperature error data;
an estimation unit that estimates the available power transmission capacity in the specified area during the second period by using the corrected second temperature forecast data,
the acquiring unit further acquires second weather forecast data having a shorter forecast period and a shorter delivery delay time than the first weather forecast data;
The correction unit corrects the second temperature prediction data for a period that is shorter than the second period after the predetermined time point, using the second weather prediction data.
Transmission capacity estimation device. A power transmission capacity estimation device that estimates a power transmission capacity, which is an operational capacity of a power transmission line, comprising:
an acquisition unit that acquires first weather forecast data including first temperature forecast data and second temperature forecast data indicating predicted values of temperature in a specified area for a first period before a specified time point and a second period after the specified time point, and meteorological observation data including actual temperature data indicating actual values of temperature in the specified area for the first period;
a correction unit that calculates temperature error data indicating a prediction error of the temperature in the specified area using the first temperature prediction data and the temperature record data, and corrects the second temperature prediction data using the calculated temperature error data;
an estimation unit that estimates the available power transmission capacity in the specified area during the second period by using the corrected second temperature forecast data,
The acquisition unit further acquires second weather forecast data having a shorter prediction period and a shorter update interval than the first weather forecast data,
The correction unit corrects the second temperature prediction data for a period that is shorter than the second period after the predetermined time point, using the second weather prediction data.
Transmission capacity estimation device. A power transmission capacity estimation device that estimates a power transmission capacity, which is an operational capacity of a power transmission line, comprising:
an acquisition unit that acquires first weather forecast data including first temperature forecast data and second temperature forecast data indicating predicted values of temperature in a specified area for a first period before a specified time point and a second period after the specified time point, and meteorological observation data including actual temperature data indicating actual values of temperature in the specified area for the first period;
a correction unit that calculates temperature error data indicating a prediction error of the temperature in the specified area using the first temperature prediction data and the temperature record data, and corrects the second temperature prediction data using the calculated temperature error data;
an estimation unit that estimates the available power transmission capacity in the specified area during the second period by using the corrected second temperature forecast data,
The acquisition unit acquires the first weather forecast data, which further includes first altitude data indicating an altitude of a prediction point, and the weather observation data, which further includes second altitude data indicating an altitude of an observation point;
The correction unit further uses the first altitude data and the second altitude data to correct the second temperature forecast data according to the altitude of the power transmission line in the specified area.
Transmission capacity estimation device. The acquisition unit acquires the first weather forecast data further including data indicating at least one predicted value of a wind speed, an amount of solar radiation, and an amount of precipitation in the specified area;
The transmission available capacity estimation device according to any one of claims 1 to 7, wherein the estimation unit estimates the transmission available capacity by further using data indicating at least one predicted value of the wind speed, the solar radiation, and the precipitation contained in the first weather forecast data. A method for estimating a transmission capacity that is an operational capacity of a transmission line, comprising the steps of:
an acquisition step of acquiring first weather forecast data including first temperature forecast data and second temperature forecast data indicating predicted values of temperatures in a specified area for a first period before a specified time point and a second period after the specified time point, and meteorological observation data including actual temperature data indicating actual values of temperatures in the specified area for the first period;
a correction step of calculating temperature error data indicating a prediction error of the temperature in the specified area using the first temperature prediction data and the temperature record data, and correcting the second temperature prediction data using the calculated temperature error data;
and estimating the available electricity transmission capacity in the specified area during the second period by using the corrected second temperature forecast data ,
In the correction step, a difference between a maximum predicted value of the temperature indicated by the first temperature prediction data and a maximum actual value of the temperature indicated by the actual temperature data is calculated as the temperature error data.
Method for estimating available power transmission capacity. A method for estimating a transmission capacity that is an operational capacity of a transmission line, comprising the steps of:
an acquisition step of acquiring first weather forecast data including first temperature forecast data and second temperature forecast data indicating predicted values of temperatures in a specified area for a first period before a specified time point and a second period after the specified time point, and meteorological observation data including actual temperature data indicating actual values of temperatures in the specified area for the first period;
a correction step of calculating temperature error data indicating a prediction error of the temperature in the specified area using the first temperature prediction data and the temperature record data, and correcting the second temperature prediction data using the calculated temperature error data;
and estimating the available electricity transmission capacity in the specified area during the second period by using the corrected second temperature forecast data,
In the correction step, it is determined whether the predicted value of the temperature indicated by the first temperature prediction data is smaller than the actual value of the temperature indicated by the actual temperature data, and the predicted value of the temperature and the actual value of the temperature are extracted when the predicted value of the temperature is smaller than the actual value of the temperature, and the temperature error data is calculated.
Method for estimating available power transmission capacity. A program for causing a computer to execute the steps included in the method for estimating available power transmission capacity according to claim 9 or 10.

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