JP7296599B1 - Wind forecast system and wind forecast method - Google Patents

Abstract

An object of the present invention is to make it possible to make a prediction based on a more realistic simulation result when predicting wind conditions at a predetermined location. Kind Code: A1 In a control unit 11 of a prediction support server 10, an information acquisition unit 101 performs observation for each predetermined wind direction at a wind condition observation position, including at least the influence of temperature changes on the ground surface on the movement of the atmosphere. Acquires wind condition information consisting of data and information on a target position for wind condition prediction, and the information generation unit 103 generates wind condition information and information on a prediction target position for wind condition prediction. Based on this, prediction support information is generated to support the prediction of the wind condition at the prediction target position. [Selection drawing] Fig. 3

Description

Application of Article 30, Paragraph 2 of the Patent Act Date November 19, 2021 Meeting name, Venue 43rd Wind Energy Utilization Symposium (held online) Sponsor: Japan Wind Energy Society Date posted on the website July 11, 2004 Website representative URL https://www. mdpi. com/1996-1073/15/14/5050

The present invention relates to a wind condition prediction system and a wind condition prediction method.

The business feasibility evaluation conducted before construction of a wind power plant is based on the annual power generation amount estimated from the predicted wind speed at the site where the wind turbine is to be installed. Prediction of the wind speed at the planned installation site of the wind turbine is performed based on observation data of wind conditions over a period of one year or more from a wind condition observation tower (hereinafter referred to as a "mast"). However, since the installation location of the mast and the installation location of the wind turbine usually do not match, it is necessary to consider differences in wind conditions due to differences in the installation environment (topography, etc.). Therefore, the wind speed ratio for converting the observation data into the wind speed of the planned installation site of the wind turbine is simulated for each wind direction obtained by dividing the 360-degree azimuth into 16 directions. (For example, Patent Document 1, Non-Patent Document 1).

JP 2019-203727 A

NKRE-GL-WFC01 Nippon Kaiji Kyokai wind farm certification onshore wind version https://www.classnk.or.jp/hp/pdf/authentication/renewableenergy/ja/windfarm/NKRE-GL-WFC01_July2021_Jpn_Corrected_October2021.pdf

When simulating the wind speed ratio for each wind direction with 360 degrees of direction divided into 16, there is a width of 22.5 degrees per wind direction, but depending on the terrain, a 10 degree change in wind direction can cause a large change in wind conditions. be. Furthermore, conventional simulations do not take into account the effects of surface temperature changes on atmospheric motion. For this reason, it is difficult to predict the actual wind conditions from the results of conventional simulations.

SUMMARY OF THE INVENTION An object of the present invention is to make it possible to predict wind conditions at a predetermined location based on results of simulations that are more realistic.

The invention described in claim 1 is a method for acquiring wind condition information consisting of observation data for each predetermined wind direction at a wind condition observation position, including at least the influence of temperature changes on the ground surface on the movement of the atmosphere. condition information acquisition means; target point information acquisition means for acquiring information about a target position for wind condition prediction; and based on the wind condition information and information about a prediction target position for wind condition prediction and prediction support means for generating prediction support information for supporting prediction of wind conditions at the prediction target position.
In the invention recited in claim 2, the prediction support means generates, as the prediction support information, information including at least a wind speed ratio for converting the wind speed at the observation position into the wind speed at the prediction target position. The wind condition prediction system according to claim 1, characterized by:
In the invention recited in claim 3, the prediction support means calculates the frequency of appearance for each wind direction of the value indicating the influence and the value indicating the wind speed, which are calculated from the wind condition information. 2. The wind condition prediction system according to claim 1, wherein said prediction support information is generated based on positional information.
In the invention described in claim 4, the prediction support means specifies one or more representative influences specified from the frequency of appearance for each wind direction of the value indicating the influence and the value indicating the wind speed. 4. The wind condition prediction system according to claim 3, wherein the prediction support information is generated based on a value indicating and the information about the prediction target position.
In the invention recited in claim 5, the prediction support means generates the prediction support information based on the average value of the appearance frequencies of the values indicating the representative influence and the information on the prediction target position. The wind condition prediction system according to claim 4, characterized by generating
In the invention according to claim 6, the value indicating the influence is calculated based on information including at least the altitude difference and temperature difference between the observation position and the ground surface, the wind speed at the observation position, and the gravitational acceleration. 4. The wind condition prediction system according to claim 3, characterized by being represented by the value of the Richardson number.
The invention according to claim 7 is characterized in that the value indicating the influence is represented by a value obtained by changing the calculated value of the Richardson's number according to the appearance frequency of the value indicating the influence. The wind condition prediction system according to claim 6, wherein
In the eighth aspect of the invention, the prediction support means divides the direction of the central angle of 360 degrees at the observation position into 16 wind directions, and divides each wind direction into 16 wind direction segments. Generating the prediction support information based on the frequency of appearance of each of the value indicating the influence and the value indicating the wind speed calculated from the wind condition information for each wind direction, and information on the prediction target position. The wind condition prediction system according to claim 3, characterized by:
In the invention recited in claim 9, the prediction support means changes the arrangement of the one wind direction segment in the azimuth of the central angle of 360 degrees while maintaining the size of the central angle of the one wind direction segment. The prediction support information is generated based on the observation data of each of the wind direction at the center and the wind directions at both ends in the one wind direction segment of the case, and the information on the prediction target position. The described wind forecast system.
According to the invention recited in claim 10, the step of acquiring wind condition information comprising observation data for each predetermined wind direction at a wind condition observation position, including at least the influence of changes in ground surface temperature on atmospheric movement. a step of acquiring information about a position to be predicted for wind conditions; and determining a target for wind condition prediction based on the wind condition information and the information about the position to be predicted for wind conditions. a step of generating prediction support information for supporting prediction of the wind conditions at the location.

ADVANTAGE OF THE INVENTION According to this invention of Claim 1, when predicting the wind condition of a predetermined place, it becomes possible to predict based on the result of the simulation more realistic.
According to the second aspect of the present invention, when predicting the wind speed at a predetermined location, it is possible to make a prediction based on the result of a simulation that is more realistic.
According to the present invention of claim 3, when predicting the wind conditions at a predetermined location, the results of simulations that take into account the effect of temperature changes on the ground surface on the movement of the atmosphere and the frequency of appearance of each of the wind speeds. Prediction based on
According to the present invention of claim 4, when predicting wind conditions at a predetermined location, one or more representative values among values indicating the influence of changes in the temperature of the ground surface on movement of the atmosphere and the target point Since the simulation is performed based on the information, it is possible to predict wind conditions in line with the actual situation while improving calculation efficiency.
According to the fifth aspect of the present invention, when predicting the wind conditions at a predetermined location, the frequency of occurrence of a plurality of representative values among the values indicating the influence of changes in the temperature of the ground surface on the motion of the atmosphere is calculated. Since the simulation is performed based on the average value and the target point information, it is possible to predict the wind condition in line with the actual situation while improving the efficiency of calculation.
According to the sixth aspect of the present invention, when calculating the value indicating the effect of the temperature change on the ground surface on the motion of the atmosphere, simple calculation using a formula that has been used conventionally becomes possible.
According to the seventh aspect of the present invention, the value to be analyzed among the values indicating the effect of the temperature change on the ground surface on the movement of the atmosphere can be finely adjusted according to the frequency of occurrence, so that the value is more realistic. Simulation becomes possible.
According to the eighth aspect of the present invention, the unit for obtaining wind condition information is increased from the conventional 16 divisions to 32 divisions, so that a more realistic simulation can be performed.
According to the ninth aspect of the present invention, since fine adjustment can be performed for each wind direction division, a more realistic simulation can be performed.
According to the tenth aspect of the present invention, when predicting the wind conditions at a predetermined location, it is possible to make predictions based on the results of simulations that are more realistic.

BRIEF DESCRIPTION OF THE DRAWINGS It is a figure which shows an example of the whole structure of the wind condition prediction system to which this Embodiment is applied. It is a figure which shows an example of the hardware constitutions of the prediction support server which comprises the wind condition prediction system of FIG. It is a figure showing an example of functional composition of a control part of a prediction support server. It is a flowchart which shows an example of the flow of a process of a prediction assistance server. It is an overall view of an island that is supposed to be a construction site for a wind power plant. (A) is a plan view of an island. (B) is a plan perspective view of an island. (A) to (C) are diagrams showing the effect of temperature changes on the ground surface on the movement of the atmosphere. (A)-(C) are graphs showing the wind speed correlation and wind speed ratio of three other masts to the mast located at the northern end of the island. (A) is a diagram showing a specific example of a formula used when calculating a Richardson number (Ri) representing atmospheric stability, which is an example of a temperature change influence value. (B) to (D) are graphs showing an example of the frequency of occurrence of atmospheric stability and wind speed for each wind direction. (A) is a graph showing the relationship between atmospheric stability variation and wind speed, which is an example of a temperature change influence value. (B) is a graph showing the appearance frequency of atmospheric stability, which is an example of the temperature change influence value. (A) is a diagram showing a specific example of one wind direction classification. (B) is a diagram showing an image of the wind direction to be analyzed. (A) to (C) are diagrams showing verification results of wind condition prediction.

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.
(Configuration of wind forecast system)
FIG. 1 is a diagram showing an example of the overall configuration of a wind condition prediction system 1 to which this embodiment is applied.
The wind condition prediction system 1 includes a prediction support server 10, mast terminals 30-1 to 30-n (where n is an integer value of 1 or more), an information providing server 50, and a user terminal 70 connected via a network 90. It is configured by being The network 90 is, for example, a LAN (Local Area Network), the Internet, or the like. Note that the mast terminals 30-1 to 30-n are collectively referred to as the mast terminal 30 when there is no need to explain each of the mast terminals 30-1 to 30-n individually.

The prediction support server 10 that configures the wind condition prediction system 1 is an information processing device that serves as a server that manages the entire wind condition prediction system 1 . The prediction support server 10 calculates the influence of changes in the temperature of the ground surface on the movement of the atmosphere observed at each of one or more observation positions in the height direction of the mast installed at the observation point where the mast is installed. Acquire at least information about wind conditions (hereinafter referred to as "wind condition information"). Wind condition information is transmitted from a mast terminal 30 installed for each mast. The wind condition information includes, for example, observation data near the ground, observation data for each altitude (for example, an altitude of 50 m (meters), 100 m (meters), etc.), and the like.

In addition, the prediction support server 10 acquires information about a target position for wind condition prediction (hereinafter referred to as a “prediction target position”). The prediction target positions include, for example, one or more positions in the height direction of the planned installation site of the wind turbine of the wind power plant that is scheduled to be constructed. The information about the prediction target position includes, for example, information about the position of the prediction target position and terrain.

Then, the prediction support server 10 provides information (hereinafter referred to as "prediction support information") that supports prediction of the wind conditions at the prediction target position based on the acquired wind condition information and information on the prediction target position. Generate. The prediction support information includes the wind speed ratio for converting the wind speed at the observation position to the wind speed at the prediction target position, the wind speed prediction value at the prediction target position, and the annual power generation amount estimated from the wind speed prediction value. . Details of the configuration and processing of the prediction support server 10 will be described later.

A mast terminal 30 constituting the wind condition prediction system 1 is an information processing device installed for each mast and acquires observation data of an observation position. The observation data includes measurement results of one or more sensors installed on the mast. The mast is equipped with, for example, a wind speed sensor, a wind direction sensor, a temperature sensor, a humidity sensor, an atmospheric pressure sensor, and the like. The mast terminal 30 acquires measurement results of wind speed, wind direction, temperature, humidity, atmospheric pressure, etc. measured by these sensors as observation data.

Here, the mast terminal 30 acquires observation data for each wind direction at the observation site. For example, the mast terminal 30 acquires observation data for each wind direction obtained by dividing the 360-degree azimuth of the observation position into 16 (hereinafter referred to as "16 wind directions"). In other words, when acquiring observation data for 16 wind directions, the mast terminal 30 can be used for north, north-northeast, northeast, east-northeast, east, east-southeast, southeast, south-southeast, south, south-southwest, southwest, west-southwest, west, west-southwest, northwest, Observation data for each wind direction of north-northwest and north-northwest is acquired for each observation position. The mast terminal 30 transmits wind condition information made up of the acquired observation data to the prediction support server 10 .

The information providing server 50 that constitutes the wind condition prediction system 1 is an information processing device as a server that provides the prediction support server 10 with information regarding observation positions, information regarding prediction target positions, and the like. For example, observation position information includes meteorological data provided by public and private organizations, including observation positions, and terrain data provided by public and private organizations, and observation positions. etc. In addition, as the information on the prediction target position, for example, weather data provided by public or private organizations related to the prediction target position, topography data provided by public or private organizations, etc. Examples include those related to prediction target positions. The information providing server 50 transmits information about the observation position and information about the prediction target position to the prediction support server 10 in response to an inquiry from the prediction support server 10 or at a predetermined timing.

A user terminal 70 that configures the wind condition prediction system 1 is an information processing device such as a personal computer, a smart phone, or a tablet terminal operated by a user who uses the prediction support information. The user terminal 70 transmits information input by the user to the prediction support server 10 . The information input by the user includes, for example, information input to inquire about provision of prediction support information for the prediction target position (hereinafter referred to as “inquiry information”), information regarding the prediction target position, and the like. Also, the user terminal 70 acquires and displays information transmitted from the prediction support server 10 . For example, the user terminal 70 acquires and displays prediction support information transmitted from the prediction support server 10 in response to an inquiry about provision of prediction support information on the prediction target position.

The configuration of the wind condition prediction system 1 described above is merely an example, and the wind condition prediction system 1 as a whole only needs to have the function of realizing the above-described processing. Therefore, some or all of the functions for realizing the above-described processing may be shared by each device or device in the wind condition prediction system 1 or may be cooperated. That is, some or all of the functions of the prediction support server 10 may be used as the functions of the master terminal 30 and the information providing server 50 . Also, some or all of the functions of the mast terminal 30 may be functions of the prediction support server 10 and the information providing server 50 . Further, part or all of the functions of the prediction support server 10, the mast terminal 30, and the information providing server 50, which constitute the wind condition prediction system 1, may be transferred to another server or the like (not shown). As a result, the processing of the wind condition prediction system 1 as a whole is promoted, and the processing can be complemented each other.

(Hardware configuration of prediction support server)
FIG. 2 is a diagram showing an example of the hardware configuration of the prediction support server 10 that constitutes the wind condition prediction system of FIG.
The prediction support server 10 has a control unit 11 , a memory 12 , a storage unit 13 , a communication unit 14 , an operation unit 15 and a display unit 16 . These units are connected by a data bus, an address bus, a PCI (Peripheral Component Interconnect) bus, or the like.

The control unit 11 is a processor that controls functions of the prediction support server 10 through execution of various software such as an OS (basic software) and application software (applied software). The control unit 11 is configured by, for example, a CPU (Central Processing Unit). The memory 12 is a storage area for storing various software and data used for executing the software, and is used as a work area for calculation. The memory 12 is composed of, for example, a RAM (Random Access Memory) or the like.

The storage unit 13 is a storage area that stores input data for various software, output data from various software, and the like. The storage unit 13 is composed of, for example, a HDD (Hard Disk Drive), an SSD (Solid State Drive), a semiconductor memory, or the like used for storing programs and various setting data. In the storage unit 13, as a database for storing various kinds of information, for example, a wind condition DB 131 storing acquired wind condition information, a target position DB 132 storing information on an acquired prediction target position, a generated prediction A prediction support DB 133 or the like storing support information is stored.

The communication unit 14 transmits and receives data to and from the master terminal 30, the information providing server 50, and the outside via the network 90. FIG. The operation unit 15 includes, for example, a keyboard, a mouse, mechanical buttons and switches, and receives input operations. The operation unit 15 also includes a touch sensor that constitutes a touch panel integrally with the display unit 16 . The display unit 16 is composed of, for example, a liquid crystal display or an organic EL (Electro Luminescence) display used for displaying information, and displays data such as images and text.

(Hardware configuration of master terminal, information providing server, and user terminal)
The hardware configurations of the mast terminal 30, the information providing server 50, and the user terminal 70 are all similar to the hardware configuration of the prediction support server 10 shown in FIG. That is, the master terminal 30, the information providing server 50, and the user terminal 70 are the control unit 11, the memory 12, the storage unit 13, the communication unit 14, the operation unit 15, and the display unit 16 of the prediction support server 10 shown in FIG. It has a control section, a memory, a storage section, a communication section, an operation section, and a display section similar to each of them. Therefore, illustration and description of the hardware configurations of the master terminal 30, the information providing server 50, and the user terminal 70 are omitted.

(Functional configuration of control unit of prediction support server)
FIG. 3 is a diagram showing an example of the functional configuration of the control unit 11 of the prediction support server 10. As shown in FIG.
In the control unit 11 of the prediction support server 10, an information acquisition unit 101, an information management unit 102, an information generation unit 103, and a transmission control unit 104 function.

The information acquisition unit 101 acquires various types of information transmitted to the prediction support server 10 . The information acquired by the information acquisition unit 101 includes, for example, wind condition information transmitted from the mast terminal 30 and information regarding the prediction target position transmitted from the information providing server 50 .

The information management unit 102 stores and manages the information acquired by the information acquisition unit 101 in a database. For example, the information management unit 102 stores and manages the wind condition information transmitted from the mast terminal 30 in the wind condition DB 131 of the storage unit 13 . In addition, the information management unit 102 stores and manages the information regarding the predicted target position transmitted from the information providing server 50 in the target position DB 132 of the storage unit 13 . The information management unit 102 also stores and manages various types of information generated by the information generation unit 103, which will be described later, in a database. For example, the information management unit 102 stores and manages the prediction support information generated by the information generation unit 103 in the prediction support DB 133 of the storage unit 13 .

The information generation unit 103 generates various types of information. For example, the information generation unit 103 generates the prediction support information based on the wind condition information for each mast and the information on the prediction target position managed by the information management unit 102 . Specifically, the information generation unit 103 generates the frequency of occurrence for each value indicating wind speed calculated from the wind condition information for each wind direction, and the value indicating the effect of temperature changes on the ground surface on the movement of the atmosphere (hereinafter referred to as Prediction support information is generated based on the frequency of occurrence of each (referred to as "temperature change influence value") and information on the prediction target position. The temperature change influence value includes, for example, atmospheric stability. Atmospheric stability is represented by the value of Richardson's number calculated based on information including at least the difference in altitude and temperature between the observation position of the mast and the ground surface, the wind speed at the observation position of the mast, and the gravitational acceleration. . A specific example of the equation used to calculate the Richardson number (Ri) indicating atmospheric stability will be described later with reference to FIG. 8(A).

The value of the calculated Richardson number can be changed according to the appearance frequency. In this case, a plurality of atmospheric stabilities are selected, and the Richardson number (Ri) is calculated for each of them, but the Richardson number (Ri) is gradually changed during one calculation. The gradual change speed may be set according to the distribution shape of the frequency of appearance of the Richardson number (Ri). Gradually changing the Richardson number (Ri) in one calculation requires more calculation time, but reduces the number of cases, making the results easier to manage and post-process.

When the information generation unit 103 generates the prediction support information, for example, one or more representative temperature changes specified from the appearance frequency for each value indicating the wind speed and the appearance frequency for each temperature change influence value Prediction support information is generated based on the influence value and information on the prediction target position. At this time, if there are a plurality of identified representative temperature change influence values, the information generation unit 103 generates the average value of the appearance frequency of the identified representative temperature change influence values, the prediction target position Generate prediction support information based on information about and.

Further, when generating the prediction support information, the information generation unit 103, for example, treats each of the 16 wind directions at the observation position as one wind direction segment, and the wind conditions of each of the wind direction in the center and the wind directions at both ends in the one wind direction segment. Prediction support information is generated based on the frequency of appearance of each of the temperature change influence value and the value indicating the wind speed calculated from the information, and information on the prediction target position. Here, the information generation unit 103 determines the central wind direction and Prediction support information can also be generated based on the observation data for each of the wind directions at both ends and the information on the prediction target position. In this case, one set of wind direction divisions consists of the wind direction at the center and the wind direction at both ends. As in the case of gradually changing the Richardson number (Ri) in , one calculation per wind direction segment is sufficient. Gradually changing the Richardson number (Ri) in one calculation requires more calculation time, but reduces the number of cases, making the results easier to manage and post-process. Furthermore, one wind direction segment may be gradually swung to the left or right while gradually changing the Richardson number (Ri) in one calculation. As a result, the number of calculation cases can be greatly reduced, although the time required for one calculation is greatly increased.

The transmission control unit 104 controls transmission of various information via the communication unit 14 . For example, the transmission control unit 104 controls transmission of the prediction support information generated by the information generation unit 103 to the user terminal 70 .

(Processing flow of prediction support server)
FIG. 4 is a flowchart showing an example of the processing flow of the prediction support server 10. As shown in FIG.
When wind condition information is transmitted from the mast terminal 30 (YES in step 401), the prediction support server 10 acquires the transmitted wind condition information (step 402), and stores the acquired wind condition information in a database (for example, , wind condition DB 131 in FIG. 2) for management (step 403). On the other hand, if wind condition information has not been transmitted from the mast terminal 30 (NO in step 401 ), the prediction support server 10 repeats step 401 until wind condition information is transmitted from the mast terminal 30 .

When the target position information is transmitted from the information providing server 50 (YES in step 404), the prediction support server 10 acquires the transmitted target position information (step 405), stores the acquired target position information in the database ( For example, it is stored and managed in the target position DB 132 in FIG. 2 (step 406). On the other hand, if the target position information has not been transmitted from the information providing server 50 (NO in step 404), the prediction support server 10 repeats step 404 until the target position information is transmitted from the information providing server 50. repeat.

When the prediction support server 10 receives inquiry information regarding provision of prediction support information from the user terminal 70 (YES in step 407), it acquires the transmitted inquiry information (step 408). Then, the prediction support server 10 generates prediction support information corresponding to the inquiry information based on the wind condition information for each mast stored and managed in the database and the information on the prediction target position (step 409). , the generated prediction support information is transmitted to the user terminal 70, which is the transmission source of the inquiry information (step 410). Thus, the processing of the prediction support server 10 ends. On the other hand, if inquiry information regarding provision of prediction support information has not been transmitted from the user terminal 70 (NO in step 407), the prediction support server 10 receives inquiry information regarding provision of prediction support information from the user terminal 70. Step 407 is repeated until the data is transmitted.

(Concrete example)
5 to 13 show a specific example of wind condition prediction for a planned construction site of a wind farm as an application example of the wind condition prediction system 1 of FIG.
FIGS. 5A and 5B are general views of an island 500, which is the planned construction site for the wind farm. FIG. 5A is a plan view of the island 500, showing the size, shape, etc. of the island 500. FIG. FIG. 5B is a plan perspective view of the island 500, showing an image of the undulations, elevation, etc. of the island 500. FIG. 5A and 5B, the upper side indicates north (N), the lower side indicates south (S), the right side indicates east (E), and the left side indicates west (W).

The island 500, as shown in FIGS. 5A and 5B, is an undulating solitary island measuring about 3 km (kilometers) from north to south and about 2 km (kilometers) from east to west. Inside the island 500, a mast 601 (MastA), a mast 602 (MastB), a mast 603 (MastC), and a mast 604 (MastD) are distributed from the north end to the south end of the island 500 and installed. Of these, the northernmost mast 601 is installed at the highest altitude (altitude 139 m (meters)) of the four masts, as shown in FIG. 5(B). A mast 602 located slightly southward and west of the mast 601 is installed at a slightly lower altitude than the mast 601 . Also, a mast 603 located slightly to the west and south of the mast 602 is installed at a slightly lower altitude than the mast 602 . Also, the southernmost mast 604 is installed at the lowest altitude. Each of the masts 601 to 604 has a height of 58 m (meters).

FIGS. 6A to 6C are diagrams showing the effects of temperature changes on the ground surface on atmospheric motion. In FIGS. 6A to 6C, the atmosphere 700 extends vertically with respect to the ground surface line connecting the mast 601 installed at the northern end of the island 500 and the mast 604 installed at the southern end. A cross-sectional view when cut is shown. Also, the color shading of the cross-sectional view of the atmosphere 700 represents the temperature distribution of the air.

FIG. 6A shows the air temperature distribution in the atmosphere 700 when the weather on the island 500 is, for example, fine weather. On sunny days, the ground is warmed by heat from the sun, and the temperature of the atmosphere 700 near the ground surface of the island 500 rises. On the other hand, since the temperature of the atmosphere 700 far from the ground surface of the island 500 is low, a vertical air current is generated due to the temperature difference in the atmosphere 700 of the island 500 . In this case, the atmosphere 700 of the island 500 is in a state where the temperature distribution of the air does not form a plurality of layers and is uneven, as shown in FIG. 6(A). That is, if the weather on the island 500 is fine, for example, the change in the temperature of the ground surface will have a large effect on the movement of the atmosphere.

FIG. 6B shows the air temperature distribution in the atmosphere 700 when the weather on the island 500 is cloudy or windy, for example. On a cloudy day or a strong wind day, the temperature gradual lapse rate and the dry adiabatic lapse rate are almost equal. In this case, the atmosphere 700 of the island 500 has a plurality of layers of air temperature distribution as shown in FIG. That is, if the weather on the island 500 is cloudy or windy, for example, the change in the temperature of the ground surface will have little effect on the movement of the atmosphere. The temperature gradual rate is the rate at which the temperature of the air decreases as altitude increases. The dry adiabatic lapse rate is the rate at which the temperature of a small air mass moves vertically adiabatically without condensation of water vapor (0.977 per 100 m altitude). ℃).

FIG. 6C shows the temperature distribution of the air in the atmosphere 700 when the weather on the island 500 is, for example, a sunny winter night with weak wind. During winter nights when the wind is weak and the weather is clear, the intensity of radiation (infrared radiation) from the ground surface increases, and the heat of the atmosphere 700 near the ground surface of the island 500 is taken away, resulting in a decrease in temperature (radiative cooling). )become. On the other hand, since the temperature of the air 700 far from the ground surface of the island 500 is high, no vertical airflow is generated due to the temperature difference in the air 700 of the island 500 . In this case, the atmosphere 700 of the island 500 forms a plurality of layers in the temperature distribution of the air as shown in FIG. That is, if the weather on the island 500 is, for example, a sunny winter night with weak winds, changes in the temperature of the ground surface will have little effect on the movement of the atmosphere.

In this way, the ground surface temperature changes depending on the weather and season, and these changes have a large impact on the movement of the atmosphere. not On the other hand, according to the present invention, since the influence of temperature changes on the ground surface on the motion of the atmosphere is taken into account, it is possible to predict wind conditions in line with the actual situation. As a result, it is possible to obtain prediction results with higher accuracy than conventional wind condition prediction results.

7(A)-(C) are graphs showing the wind speed correlation and wind speed ratio of the other three masts 602-604 to the mast 601 installed at the northern end of the island 500. FIG. Note that the graphs of FIGS. 7A to 7C use the average value of the wind speed of the north wind per hour.
The left diagram of FIG. 7(A) is a graph showing the correlation of the wind speed between the mast 601 (MastA) and the mast 602 (MastB). The horizontal axis of the graph indicates the wind speed (m/s) of the mast 601 (MastA), and the vertical axis of the graph indicates the wind speed (m/s) of the mast 602 (MastB).
As shown in the left diagram of FIG. 7(A), the wind speed correlation between masts 601 (MastA) and masts 602 (MastB) is almost linear. ), the wind speed (m/s) of the mast 602 (MastB) is greater than that of the mast.

The right diagram of FIG. 7A is a graph showing the wind speed ratio between the mast 601 (MastA) and the mast 602 (MastB). The horizontal axis of the graph indicates the wind speed (m/s) of the mast 601 (MastA), and the vertical axis of the graph indicates the ratio of the wind speed (m/s) of the mast 602 (MastB) to the wind speed (m/s) of the mast 601 (MastA). ing.
As shown in the right diagram of FIG. 7A, the wind speed ratio of the mast 602 (MastB) to the wind speed (m/s) of the mast 601 (MastA) varies. /s) is small, the variation is large.

The left diagram of FIG. 7(B) is a graph showing the correlation of the wind speed between the mast 601 (MastA) and the mast 603 (MastC). The horizontal axis of the graph indicates the wind speed (m/s) of the mast 601 (MastA), and the vertical axis of the graph indicates the wind speed (m/s) of the mast 603 (MastC).
As shown in the left diagram of FIG. 7(B), the wind speed correlation between masts 601 (MastA) and masts 603 (MastC) is also approximately linear. ) at the mast 603 (MastC).

The right diagram of FIG. 7B is a graph showing the wind speed ratio between the mast 601 (MastA) and the mast 603 (MastC). The horizontal axis of the graph indicates the wind speed (m/s) of the mast 601 (MastA), and the vertical axis of the graph indicates the ratio of the wind speed (m/s) of the mast 601 (MastA) to the wind speed (m/s) of the mast 603 (MastC). ing.
As shown in the right diagram of FIG. 7B, the wind speed ratio of the mast 603 (MastC) to the wind speed (m/s) of the mast 601 (MastA) varies. /s) is small, the variation is large.

The left diagram of FIG. 7(C) is a graph showing the correlation of wind speed between mast 601 (MastA) and mast 604 (MastD). The horizontal axis of the graph indicates the wind speed (m/s) of the mast 601 (MastA), and the vertical axis of the graph indicates the wind speed (m/s) of the mast 604 (MastD).
As shown in the left diagram of FIG. 7(C), the wind speed correlation between masts 601 (MastA) and masts 604 (MastD) is also approximately linear. ), the wind speed (m/s) of the mast 604 (MastD) is smaller than that of m/s.

The right diagram of FIG. 7(C) is a graph showing the wind speed ratio between the mast 601 (MastA) and the mast 604 (MastD). The horizontal axis of the graph indicates the wind speed (m/s) of the mast 601 (MastA), and the vertical axis of the graph indicates the ratio of the wind speed (m/s) of the mast 601 (MastA) to the wind speed (m/s) of the mast 604 (MastD). ing.
As shown in the right diagram of FIG. 7C, the wind speed ratio of the mast 604 (MastD) to the wind speed (m/s) of the mast 601 (MastA) varies. /s) is small, the variation is large.

7A to 7C, the wind speed correlations of each of the other three masts 602 to 604 with respect to the mast 601 are all in a linear relationship, but the mast It can be seen that the wind speed ratios of each of the other three masts 602-604 relative to 601 vary widely.

FIG. 8A is a diagram showing a specific example of a formula used when calculating the value of the Richardson number (Ri) representing atmospheric stability, which is an example of the temperature change influence value.
As described above, the Richardson number (Ri) representing atmospheric stability, which is an example of the temperature change influence value, is the difference in altitude and temperature between the observation position of the mast and the ground surface, the wind speed at the observation position of the mast, It is calculated based on information including at least gravitational acceleration. Specifically, for example, it is calculated using the formula shown in FIG.

In the formula shown in FIG. 8A, "R _i " is Richardson's number. "g" is the gravitational acceleration. "H" is the maximum value of the difference in altitude at the observation point. “U” is the wind speed at the observation position obtained from the weather-related data provided by the information providing server 50 or the wind speed at the observation position obtained from the mast observation data. Note that when the wind speed at the observation position obtained from the weather-related data provided by the information providing server 50 is used as "U", the resolution is often insufficient. For this reason, in some cases, only meteorological data can be obtained at a location at a lower altitude than the installation location of the wind turbines of the wind power plants, which are usually installed on ridges. In this case, the wind speed is corrected according to the maximum value of the altitude difference at the observation point.

“θ _in ” is the temperature at the observation position obtained from the weather-related data provided by the information providing server 50 or the temperature obtained from the mast observation data. “θ _bottom ” is the ground surface temperature at the observation point obtained from the weather-related data provided by the information providing server 50 (or the sea surface temperature if the observation point is not on the ground but on the sea), or mast observation data. is the temperature of the ground surface at the observation point obtained from

Here, the relationship between “θ _in ” and “θ _bottom ” is not the relationship between the air temperature at the observation position and the surface temperature at the observation point, but the temperature difference between the two altitudes (i.e., (potential temperature difference obtained by subtracting atmospheric pressure change). In this case, "U" may be the difference in wind speed between the two altitudes and "H" may be the difference between the two altitudes. For example, when using data at an altitude of 50 m (meters) and data at an altitude of 100 m (meters) at an observation point obtained from weather-related data provided by the information providing server 50, “θ _in ” is the altitude The potential temperature is 100 m (meters), and "θ _bottom " is the potential temperature at an altitude of 50 m (meters). In addition, "U" is the difference between the wind speed at an altitude of 100m (meters) and the wind speed at an altitude of 50m (meters), and "H" is 50m (meters) (altitude 100m (meters) - altitude 50m (meters)). Become.

FIGS. 8B to 8D are graphs showing an example of the appearance frequency of atmospheric stability and wind speed for each wind direction. In FIGS. 8B to 8D, the horizontal axis represents the Richardson number (Ri) representing the atmospheric stability, which is an example of the temperature change influence value, and the vertical axis represents the atmospheric stability. The annual frequency of occurrence of each of Richardson's number (Ri) and wind speed is shown.

If the value of the Richardson number (Ri) is negative, the atmospheric stability is "unstable". This indicates that changes in ground surface temperature have a large effect on atmospheric motion. For example, the state of the atmosphere 700 in FIG. 6A described above indicates a state in which the atmospheric stability is "unstable". Also, when the value of the Richardson number (Ri) is 0 (zero), the atmospheric stability is "neutral." This indicates that changes in ground surface temperature have little effect on atmospheric motion. For example, the state of the atmosphere 700 in FIG. 6B described above indicates a state in which the atmospheric stability is "neutral." Also, when the value of the Richardson number (Ri) is a positive value, the atmospheric stability is "stable". This indicates that changes in surface temperature have little effect on atmospheric motion. For example, the state of the atmosphere 700 in FIG. 6C described above indicates a state in which the atmospheric stability is "stable."

FIG. 8(B) shows the annual appearance frequency of each of the atmospheric stability and wind speed in the north wind (N 0 deg) observed by the mast 601 installed at the northern end of the island 500 . "Appearance frequency" refers to the ratio of the number of occurrences of a target value to the total number of occurrences. In this embodiment, the appearance frequency is expressed in percent (%).
As shown in FIG. 8(B), the atmospheric stability values are widely distributed from negative values indicating "unstable" to positive values indicating "stable". Negative values are particularly distributed, and the total appearance frequency is about 82%. The range of the Richardson number (Ri) with the largest distribution is "-0.2 to 0", and the appearance frequency is about 24%. The values indicating the wind speed in this value range are widely distributed from "3 to 6 m/s" to "13 m/s<". In addition, the range of values of Richardson's number (Ri), which has the second largest distribution, is "<-1", and the appearance frequency is about 18%. The values indicating the wind speed in this value range are widely distributed from "<3 m/s" to "3 to 6 m/s".

FIG. 8(C) shows the annual appearance frequency (% )It is shown.
As shown in FIG. 8(C), the atmospheric stability values are widely distributed from negative values indicating "unstable" to positive values indicating "stable". Negative values are especially distributed, and the total appearance frequency is about 86%. The range of the Richardson number (Ri) with the largest distribution is "-0.2 to 0", and the appearance frequency is about 44%. The values indicating the wind speed in this value range are widely distributed from "3 to 6 m/s" to "13 m/s<". Moreover, the range of values of Richardson's number (Ri), which has the second largest distribution, is "-0.4 to -0.2", and the appearance frequency is about 15%. The values indicating the wind speed in this value range are widely distributed from "3 to 6 m/s" to "13 m/s<".

FIG. 8(D) shows the annual appearance frequency (% )It is shown.
As shown in FIG. 8(D), the atmospheric stability values are widely distributed from negative values indicating "unstable" to positive values indicating "stable". A relatively large number of negative values are distributed, and the total appearance frequency is about 73%. The range of the Richardson number (Ri) with the largest distribution is "-0.2 to 0", and the appearance frequency is about 22%. The values indicating the wind speed in this value range are widely distributed from "3 to 6 m/s" to "13 m/s<". Moreover, the range of values of Richardson's number (Ri), which has the second largest distribution, is "-0.4 to -0.2", and the appearance frequency is about 15%. The values indicating the wind speed in this value range are widely distributed from "<3 m/s" to "13 m/s<".

FIG. 9A is a graph showing the relationship between atmospheric stability variation and wind speed, which is an example of the temperature change influence value. The horizontal axis of the graph indicates the wind speed (m/s) of the north wind of the mast 601 installed at the northern end of the island 500 in FIG. The Richardson number (Ri) representing the degree is shown.

As described above, a negative value of the Richardson number (Ri), which represents atmospheric stability, indicates that the atmosphere is “unstable,” and a positive value indicates that the atmosphere is “stable.” Become. Also, if the value of the Richardson number (Ri) is 0 (zero), the atmosphere is "neutral". Therefore, in the graph of FIG. 9A, the atmosphere is "unstable" as it is plotted at the bottom, and the atmosphere is "stable" as it is plotted at the top. Looking at the graph in FIG. 9(A) under this premise, the value of Richardson's number (Ri) varies greatly in the range of wind speeds from about 2 to 10 m / s, but when the wind speed is 10 m / s , the Richardson number (Ri) converges at about -0.1.

FIG. 9B is a graph showing the appearance frequency of atmospheric stability, which is an example of the temperature change influence value. The horizontal axis of the graph represents the Richardson number (Ri) representing atmospheric stability, which is an example of the temperature change influence value, and the vertical axis of the graph represents the mast 601 (MastA) installed at the northern end of the island 500. 6 shows the wind speed ratio of each of the other masts 602 (MastB), 603 (MastC) and 604 (MastD) to the mast.

As described above, a negative value of the Richardson number (Ri), which represents atmospheric stability, indicates that the atmosphere is “unstable,” and a positive value indicates that the atmosphere is “stable.” Become. If the value of the Richardson number (Ri) is 0 (zero), the atmosphere is "neutral". Therefore, in the graph of FIG. 9B, the more plotted on the left side, the more "unstable" the atmosphere, and the more plotted on the right side, the more "stable" the atmosphere. Looking at the graph of FIG. 9(B) under this premise, it can be seen that mast 602 (MastB), mast 603 (MastC) and mast 604 (MastD) in a wind speed ratio range of approximately 0.8 to 1.3. , the appearance frequency of the Richardson number (Ri) varies greatly.

FIG. 10A is a diagram showing a specific example of one wind direction classification.
As described above, the prediction support information for the prediction target position includes the Richardson number (Ri) value representing atmospheric stability, which is an example of the temperature change influence value, calculated from the wind condition information at the observation position, and the wind speed. It is generated based on the appearance frequency for each wind direction with the indicated value and information on the prediction target position. Specifically, each of the 16 wind directions at the observation position is regarded as one wind direction division, and the Richardson number (Ri) value and wind speed calculated from the wind condition information for each of the wind direction in the center and the wind directions at both ends in one wind direction division are calculated. Prediction support information for the prediction target position is generated based on the appearance frequency of each of the indicated values and the information on the prediction target position. More specifically, based on the value of one or more representative Richardson numbers (Ri) that cover the whole, which are specified from the calculated appearance frequency, and the information on the prediction target position, the prediction target position Prediction aid information is generated. At this time, when a plurality of representative Richardson number (Ri) values are identified, the average value of the appearance frequency of the plurality of identified representative Richardson number (Ri) values and the prediction target position Prediction support information is generated based on the information about and. The specification of a representative Richardson number (Ri) value may be performed by a user's input operation, or may be automatically performed by the prediction support server 10 .

For example, FIG. 10A shows the north wind as an example of one wind direction division of 16 wind directions. Since the central angle of one wind direction segment is about 22 degrees (22.5 degrees) (360 divided by 16), the difference in central angle between the wind direction at the center and the wind directions at both ends in one wind direction segment is about 11 degrees (11 .25 degrees). In this case, the wind direction at the center of one wind direction division (0deg Center) is the north wind, and the wind directions at both ends (+11deg 349deg and +11deg 11deg) are about 11 degrees west of the north wind and about 11 degrees east of the north wind. become the wind. In addition, depending on the terrain, a change in wind direction of 10 degrees can cause a large change in wind conditions. becomes. That is, specifically, wind condition information for each of a wind that is about 5.5 degrees (5.625 degrees) westward from the north wind and a wind that is about 5.5 degrees (5.625 degrees) easterly from the north wind are also subject to analysis. This makes it possible to make precise wind forecasts based on wind condition information that is more realistic.

The frequency of occurrence of each of the Richardson number (Ri) value calculated from the wind condition information of the wind direction at the center and the wind direction at both ends and the value indicating the wind speed is the ratio of the total number of data falling into the areas 800 to 802. becomes. Here, representative values of Richardson's number (Ri) covering the whole specified from the calculated appearance frequency are "-0.5", "-0.2", "0", and "+0. 2”. In this case, the prediction target position of prediction support information is generated.

FIG. 10B is a diagram showing an image of wind directions to be analyzed.
As described above, the appearance frequency of each value of the Richardson number (Ri) calculated from the wind condition information of the wind direction at the center and the wind direction at both ends of one wind direction segment and the value indicating the wind speed, and the prediction target position Prediction support information for the prediction target position is generated based on the information about and. As a result, for example, as shown in FIG. 10B, it is possible to analyze wind condition information for 32 wind directions including wind condition information for 16 wind directions and wind condition information for intermediate wind directions among the 16 wind directions. Become. Furthermore, although not shown, it is possible to analyze wind condition information for 64 wind directions including wind condition information for 32 wind directions and wind condition information for intermediate wind directions of the 32 wind directions. Although FIG. 10B shows the wind direction at the center of the island 500, the analysis of the wind condition information for each wind direction at each observation position on each of the masts 601 to 604, which are actually observation points, is performed. done.

FIGS. 11A to 11C are diagrams showing verification results of wind condition prediction. FIG. 11A shows a graph representing the average values of the prediction errors of the masts 602 to 604 assumed as prediction target positions for each wind direction. FIG. 11B shows a graph representing the maximum error value among the masts 602 to 604 assumed as the prediction target position. In FIGS. 11A and 11B, "Method A" 900 indicates a conventionally used method. "Method B" 901 indicates a method of calculating only weather conditions in detail. "Method C" 902 indicates a method of calculating only the wind direction in detail. "Method D" 903 indicates the method according to this embodiment. FIG. 11(C) shows the average value for each Method of the values plotted in the graph of FIG. middle row) and the maximum value (lower row) for each method of the values plotted in the graph of FIG. 11B.

In the verification of the wind condition prediction, observation data of each of the masts 601 to 604 was used to perform wind condition prediction with the mast 601 as the observation point and the masts 602 to 604 as the prediction target positions. That is, the wind conditions were predicted based on the observation data of the mast 601 assuming that the wind turbines of the wind power plant were installed on each of the masts 602 to 604 . As a result, as shown in FIG. For any value, the value of "Method D" 903, which is the method according to this embodiment, is the smallest. This indicates that both the average error and the maximum error can be preferably controlled according to "Method D" 903, which is the method according to the present embodiment.

(Other embodiments)
Although the embodiment has been described above, the present invention is not limited to the embodiment described above. Moreover, the effects of the present invention are not limited to those described in the above embodiment. For example, the configuration of the wind condition prediction system 1 shown in FIG. 1, the hardware configuration of the prediction support server 10 shown in FIG. 2, and the functional configuration of the control unit 11 of the prediction support server 10 shown in FIG. It is only an example for achieving, and is not particularly limited. It is sufficient if the wind condition prediction system 1 of FIG. 1 has a function capable of executing the above-described processing as a whole. Not limited.

Also, the order of the processing steps of the prediction support server 10 shown in FIG. 4 is merely an example, and is not particularly limited. In addition to the processing performed chronologically along the order of the illustrated steps, the steps may not necessarily be processed chronologically, but may be performed in parallel or individually. Further, the specific examples shown in FIGS. 5 to 11 are only examples and are not particularly limited.

For example, in the above-described embodiment, wind condition information composed of observation data of each of the masts 601 to 604 is transmitted from each of the mast terminals 30 to the prediction support server 10, but the present invention is not limited to this. For example, when the information providing server 50 acquires wind condition information consisting of observation data for each of the masts 601 to 604, the information providing server 50 transmits the wind condition information to the prediction support server 10. good too.

Further, in the above-described embodiment, analysis is performed for each of the 16 wind directions, but depending on the observation point, winds in one or more specific wind directions may hardly blow, such as, for example, northeast winds rarely blow. . In such a case, wind directions in which the wind hardly blows may be excluded from the analysis targets. As a result, it is possible to improve the efficiency of business operations. In this case, in terms of data processing, setting may be made such that the wind at the observation position and the prediction target position are the same, such as setting the wind speed ratio between the mast and the windmill to 1:1. Even if such a setting is made, it is efficient because the appearance frequency is almost zero and the effect is slight.

Also, in the example of FIG. 10(A) described above, it is composed of the central wind (0deg Center), the wind 11 degrees west of the central wind (+11deg 349deg), and the wind 11 degrees east of the central wind (+11deg 11deg). A weighted average value may be calculated by setting the ratio to 0.25:0.5:0.25. As a result, work efficiency can be improved.

DESCRIPTION OF SYMBOLS 1... Wind condition prediction system 10... Prediction support server 11... Control part 12... Memory 13... Storage part 14... Communication part 15... Operation part 16... Display part 30... Mast terminal 50... Information Provision server 70 User terminal 101 Information acquisition unit 102 Information management unit 103 Information generation unit 104 Transmission control unit 90 Network

Claims (9)

wind condition information acquisition means for acquiring wind condition information consisting of observation data for each predetermined wind direction at a wind condition observation position, including at least the effect of changes in temperature on the ground surface on atmospheric movement;
target point information acquiring means for acquiring information about a target position for wind condition prediction;
prediction support means for generating prediction support information for supporting prediction of wind conditions at a prediction target position based on the wind condition information and information about a prediction target position for which wind conditions are to be predicted;
has
The prediction support means performs the prediction based on the appearance frequency for each wind direction of the value indicating the influence and the value indicating the wind speed calculated from the wind condition information, and information on the prediction target position. A wind forecast system characterized by generating support information . The prediction support means generates, as the prediction support information, information including at least a wind speed ratio for converting the wind speed at the observation position to the wind speed at the prediction target position,
The wind condition prediction system according to claim 1. The prediction support means includes one or more representative values indicating the influence, which are specified from the frequency of occurrence of each of the value indicating the influence and the value indicating the wind speed for each wind direction, and characterized by generating the prediction support information based on the information,
The wind condition prediction system according to claim 1 . The prediction support means generates the prediction support information based on an average value of the frequency of appearance of a plurality of representative values indicating the influence and information on the prediction target position,
The wind condition prediction system according to claim 3 . The value indicating the influence is indicated by a value of Richardson's number calculated based on information including at least the difference in elevation and temperature between the observation position and the ground surface, the wind speed at the observation position, and the gravitational acceleration. characterized by
The wind condition prediction system according to claim 1 . The value indicating the influence is indicated by a value obtained by changing the calculated Richardson number value according to the frequency of appearance of the value indicating the influence.
The wind condition prediction system according to claim 5 . The prediction support means divides the azimuth of the central angle of 360 degrees at the observation position into 16 wind directions, each of which is defined as one wind direction segment, and calculates from the wind condition information of each of the wind direction at the center and the wind direction at both ends in the one wind direction segment The prediction support information is generated based on the frequency of appearance of each of the value indicating the influence and the value indicating the wind speed, and information on the prediction target position,
The wind condition prediction system according to claim 1 . The prediction support means determines the central wind direction in the one wind direction segment when the arrangement of the one wind direction segment in the azimuth of the central angle of 360 degrees is changed while the size of the central angle of the one wind direction segment is maintained. and generating the prediction support information based on the observation data of each of the wind directions at both ends and the information on the prediction target position,
The wind condition prediction system according to claim 7 . a step of acquiring wind condition information comprising observation data for each predetermined wind direction at a wind condition observation position, including at least the effect of changes in temperature on the ground surface on atmospheric movement;
obtaining information about a location for which wind conditions are to be predicted;
a step of generating prediction support information for supporting the prediction of the wind conditions at the target position of the wind condition prediction, based on the wind condition information and the information on the target position of the wind condition prediction;
including
In the step of generating the prediction support information, the frequency of appearance for each wind direction of the value indicating the influence and the value indicating the wind speed, which are calculated from the wind condition information, are subject to prediction of the wind condition. generating the prediction support information based on positional information .

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