JP3226031B2 - Wind generator installation position determination method and wind power generation amount prediction method - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for determining a wind generator installation position and a method for estimating a wind power generation amount, and more particularly, to a method for determining an installation position of a wind generator which is predicted to generate maximum power, The present invention relates to a method for predicting the amount of power generated by an installed wind power generator.

[0002]

2. Description of the Related Art A wind power generator is being experimentally operated (for example, a wind power generator in Tatsuhizaki, Aomori Prefecture by Tohoku Electric Power Co., Inc.). In order to operate a wind power generator efficiently,
Needless to say, it is required to be installed in a place where strong winds are blowing continuously for a long time.

[0003] Further, when a wind power generator is installed at a certain place, it is required to predict the amount of power generated by the wind power generator and efficiently create a power supply plan. The installation position of the conventional wind generator can be determined by analogy with the wind direction and wind power in a narrow area based on knowledge of the wind speed in a wide area by experience and intuition, or by arbitrarily selecting a plurality of specific areas. The optimum location was selected by observing the wind speed in the area for a long time.

[0004] Conventionally, the amount of power generated by the installed wind power generator has not been predicted.

[0005]

There has been a problem that the optimum position cannot always be determined by simply determining the installation position based on experience and intuition. In addition, the method of arbitrarily selecting a plurality of specific areas and observing the wind speed in those areas for a long time to select an optimal place has a problem that the cost and time required for the observation are enormous.

Another problem is that an efficient power supply plan cannot be established unless the amount of power generated by the installed wind power generator is predicted. An object of the present invention is to perform a numerical simulation using an existing wide-area meteorological file describing the wind speed, so that the position where the predicted power generation amount by the wind power generator is the maximum is within the range of a rectangle on the order of several meters or less on one side. The purpose of the present invention is to provide a method for deciding.

Another object of the present invention is to calculate the amount of power generated by an already installed wind power generator using an existing wide-area weather file describing the wind speed, on the order of several meters or less on one side including the installation position. The present invention is to make predictions by calculating an airflow field within the rectangular range of, and efficiently create a power supply plan.

[0008]

In order to achieve the above object, a method for determining an installation position of a wind power generator provided by a first aspect of the present invention includes a first method for setting a calculation period and a calculation area of a predicted power generation amount. And the second step of, for each of the small calculation periods obtained by dividing the calculation period, for each of the mesh regions obtained by dividing the calculation region into meshes, calculating the predicted power generation amount and saving it in a file, A third step of selecting a mesh region indicating the maximum predicted power generation as a new calculation region among predicted power generation amounts within the calculation period calculated for each mesh region, and determining whether the selected new calculation region is a final calculation region A fourth step of determining and, if it is determined in the fourth step that the new calculation area is not the final calculation area, the second to fourth steps are repeatedly executed based on the new calculation area And steps, a new calculation area in the fourth step is determined to be the final calculation regions new computational domain and determining as the installation position of the wind power generator.

In the second step, an airflow field is calculated by a numerical calculation method for each mesh area obtained by dividing the calculation area into meshes, using an existing wide area file describing the air pressure and wind speed at each point. It is preferable to include a step of calculating and storing the electric energy based on the calculation result of the airflow field. In this method of determining the installation position of the wind turbine generator, the predicted power generation in the small calculation period in the new calculation area is set as the short-term predicted power generation, and the predicted power generation in the new calculation area in the calculation period is set as the long-term predicted power generation. Is preferred.

[0010] Even if the long-term predicted power generation is obtained as the sum of short-term predicted power generation in the new calculation area, the wind speed value in the new calculation area is read from a file for a predetermined period to determine the frequency distribution of the wind speed value. Alternatively, the power generation amount corresponding to the frequency distribution may be obtained by a statistical method. According to a second aspect of the present invention, there is provided a method for estimating the amount of power generated by an already installed wind power generator.

In this method, a first step of setting a calculation area including a calculation period of the predicted power generation amount and an installation position of the wind power generator, and each of a small calculation period obtained by dividing the calculation period in the calculation area A second step of calculating a predicted power generation amount and saving the file in a file; and, based on the predicted power generation amount calculated in the second step, the wind power generator for a desired large calculation period longer than the small calculation period. Calculating a predicted power generation amount at the installation position.

Also in this case, the second step is to calculate the wind speed by a numerical calculation method for each mesh area obtained by dividing the calculation area into meshes using an existing wide area file describing the pressure and wind speed at each point. It is preferable to include a step of calculating and storing an airflow field consisting of: and calculating and storing a predicted power generation amount based on a calculation result of the airflow field. Even if the predicted power generation during the large calculation period is the sum of the predicted power generation during the small calculation period in the calculation region, the wind speed value in the calculation region is read from the file over the large calculation period, and the frequency distribution of the wind speed value is calculated. And the power generation amount corresponding to the frequency distribution may be obtained by a statistical method.

[0013]

1 and 2 are flowcharts illustrating a method for determining a wind generator installation position and a method for estimating a wind power generation amount according to the present invention. FIG. 3 is a diagram showing a state where the calculation region is divided into meshes. 1 and 2, a calculation period N of the predicted power generation amount is set in step S11. The unit of the calculation period N is, for example, days. The N-day may be, for example, 365 days or 30 days, and is appropriately set as the cumulative number of days of the calculation result of the predicted power generation amount.

Next, in step S12, a maximum calculation area of the predicted power generation amount is set. As the maximum calculation area, for example,
For example, a calculation area of a square having a side of several hundred km as shown in FIG. Then in step S13, calculating the area of Figure 3 the mesh area, as shown in _{(a) M 11, M 12} , ... M 15, M 21, M 22,
... M _25, is divided into ... M _55. As shown in FIG. 3A, the mesh area obtained by the division has, for example,
It is a square of 0 km.

Next, in step S14, the number of days I
D is reset to 0, and the mesh area M
_{11, M 12, ... M 15} , M 21, M 22, ... M 25, ... stores the calculated storage device airflow field in each of the M _55. The calculation of the airflow field is described in detail later with reference to FIGS. 4 and 5.
Initial values and boundary values are created by interpolation using an existing wide-area file GPV issued by, for example, the Japan Meteorological Agency, which describes the wind speed, atmospheric pressure, and the like for each region. This is to calculate the wind speed in each mesh region by a numerical calculation method using LOCALS (registered trademark) by CRC Research Institute, Ltd.).

[0016] Then at step S16, based on the calculation result of the airflow field obtained by the above calculation, the mesh area _{M 11, M 12, ... M} 15, M 21, M 22, ... M 25, the ... M ₅₅ Calculate the short-term predicted power generation amount in each and store it in the auxiliary storage device 1
6 (FIG. 12) in the short-term power generation file. The short-term predicted power generation amount in each mesh region is calculated based on the wind speed in the mesh region, as will be described later in detail with reference to FIGS.

Next, the ID is incremented in step S17, and it is determined in step S18 whether the ID is larger than N. If ID is N, that is, when the short-term prediction power generation amount of each of the N-days to be computed and stored, mesh area M _11, M ₁₂ at step S19 in FIG. _{2, ... M 15, M 21} , M
_22, ... M _25, ... to calculate long-term prospective power generation amount of N-days in each of the M _55. The first method of calculating the long-term predicted power generation amount is a method of simply calculating the short-term predicted power generation amount for each mesh area. The second method of calculating the long-term predicted power generation amount is a statistical method described later in detail with reference to FIGS.

Next, in step S20, the mesh area M
_{11, M 12, ... M 15} , M 21, M 22, ... M 25, ... to the mesh area of the maximum expected power generation amount and the new calculation area among the long-term prospective power generation amount of M _55. In step S21, it is determined whether the new calculation area is the last calculation area. The final calculation area is predetermined as a minimum installation area to be obtained within the range of the computer's calculation ability. The minimum installation area is, for example, a square having a side of several meters.

If it is determined in step S21 that the new calculation area is not the minimum calculation area, steps S13 to S21 are repeated for the new calculation area, for example, a square area having a side of several tens km as shown in FIG. If the smaller new calculation area obtained in step S20 of the processing for this new calculation area is larger than the final calculation area in step S21, the new calculation area, for example, the side shown in FIG. Steps S13 to S21 are repeated for the square.

If it is determined in step S21 that the new calculation region is the minimum calculation region, the process proceeds to step S22, and the final new calculation region is determined as the installation position of the wind power generator. By the above-described processing, the installation position of the generator can be determined within a range of a square having several meters on each side. Then, in step S23, the generator characteristics to be described in detail later with reference to FIG. 11 are determined. The determination of the generator characteristics is performed by setting the parameters of the generator to an optimum value corresponding to the installation position.

FIG. 4 is a flowchart illustrating the calculation of the airflow field in step S15 of FIG. 1 in more detail. In the figure, in step S41, initial values and boundary values of the wind direction and the wind speed are created by interpolation using the wide area data file 41. The wide area data file 41 is, for example, an existing wide area file GP issued by the Japan Meteorological Agency.
There is V. The created initial value and boundary value are stored in the initial value / boundary value data file 42.

Next, in step S42, an airflow field is calculated based on the contents of the initial value / boundary value data file 42. In this calculation, the contents of the initial value / boundary value data file 42 are numerically calculated using a numerical simulation system (for example, LOCALS (registered trademark) by CRC Research Institute, Ltd.), and the wind direction and wind direction in each mesh area are calculated. Calculate wind speed. In this numerical simulation, the following basic formula and modeling are used.

1) Equation of motion: An equation that describes how the wind changes under the influence of pressure, topography, thermal influence, boundary conditions, and the like. 2) Equation of mass conservation: mass change in the calculation domain occurs only by the ingress and egress of air at the side and upper and lower boundaries. 3) Thermodynamic equation: An equation that describes the thermal effect on the air mass.

4) Modeling of turbulence: This is a model for evaluating the effect of fine turbulence that cannot be resolved by a discrete numerical model. The wind direction and wind speed (airflow field) in each mesh area calculated in this manner are stored in the narrow area data file 43 for each mesh.
Is stored in Next, in step S43, the contents of the narrow area data file 43 are stored in the database 44. FIG. 5 is a diagram for explaining a method of creating an initial value and a boundary value of a narrow area from the wide area data file 41 in step S41 of FIG. As shown in FIG. 5A, in a square wide area 51 having a side of several hundred km, the mesh interval is wide, but a mesh narrow area 52 of a square having a side of several tens km is narrow. As shown in FIG. 5B, a vertical line 53 and a horizontal line 54 passing through the position of the mesh value V (for example, the wind speed V) are divided into four small areas A, B, C, and D, and the area of each small area is divided. Is also represented by A, B, C, D,
Mesh values of the broad area _{51 (V A, V B,} V C, V D) mesh value V of the narrow region present in is determined by interpolation as follows.

[0025]

(Equation 1)

FIG. 6 is a flowchart illustrating the details of step S15 in FIG. 1, that is, step S42 in FIG. Since the numerical simulation itself is well known, only a brief description will be given. In FIG. 6, at step S611, the longitude, latitude, mesh interval, mesh number, and the like of the calculation area are read. In step S612, elevation data is read based on the terrain data. Step S6
In step 13, a coordinate system is created along the terrain of the calculation area and output to a file. In step S614, an initial value is read from the data file 42. Then, step S615
In step S626, a time integration loop is executed, for example, every 30 seconds to obtain a predicted value of the wind speed and the atmospheric pressure at the boundary of the calculation region.

In the time integration loop, predicted values of elements (wind speed, temperature, rain, water vapor, etc.) other than the atmospheric pressure are obtained in steps S616 to S620. The wind speed is a tentative forecast value. Step S621 to step S
In the loop 624, the atmospheric pressure equation is repeatedly calculated.
More specifically, in step S616, items other than pressure (wind speed, wind direction, temperature, rain, water vapor) are calculated by a numerical calculation method.
Calculate the advection term and the pressure gradient force term for each item in.
The advection term is a value reflecting the influence of the wind speed around the measurement point on the wind speed at the measurement point. The pressure gradient force term is a term that takes into account the fact that wind blows from a high pressure area to a low pressure area. In step S617, a Reynolds stress term, which is a frictional force, is calculated. Here, k is the energy of the turbulent flow, and ε represents the rate of disappearance of the turbulent energy. Calculate the eddy viscosity coefficient using k and ε, then calculate the Reynolds stress. In step S618, the wind speed
Time integration of values other than pressure, such as rain, temperature, water vapor, etc., is performed. At step S619, boundary values of values other than pressure, such as wind speed, rain, temperature, etc., in the calculation area are reset, and step S62 is performed.
At 0, the residual in the pressure equation is determined.

In steps S621 to S24, the atmospheric pressure equation is repeatedly calculated until the wind speed and the atmospheric pressure are balanced, and finally the predicted values of the wind speed and the atmospheric pressure are obtained.
That is, the residual is calculated in step S622, and
At 623, a pressure boundary value in the calculation area is set. Next, in step S625, the set values are stored in a file in the holding storage device 16 of FIG.

As a result, almost real time (for example, 3
The simulation value of the wind speed (every 0 seconds) is stored in the file. FIG. 7 is a flowchart illustrating details of the calculation of the short-term power generation amount in step S16 of FIG.
The calculation of the short-term power generation amount in step S16 of FIG. 1 is performed according to the flowchart of FIG. 7 based on the calculation result of the airflow field described in FIG. The calculation of the airflow field is performed at short time intervals, for example, every 30 seconds as described above. The amount of power generation may be calculated at the same time interval as the airflow field, but in the example of FIG. 7, an average value of the airflow field for, for example, 10 minutes is employed in order to reduce temporal fluctuation.

In FIG. 7, in step S71, a file of the output result of the narrow area in FIG. 4, that is, in step S71 in FIG.
For example, data obtained every 30 seconds obtained in 625 is read from the file, and for example, an average value of the wind speed every 30 seconds for 10 minutes is obtained. In steps S72 to S80, the predicted power generation amount is calculated every 10 minutes, and the calculation results are accumulated for one day, for example.

FIG. 8 is a graph showing the generator output when the parameters (cut-in wind speed, steady wind speed, and cut-out wind speed) that determine the output characteristics of the wind power generator are fixed. As shown in the figure, the generator output is 0 at a wind speed lower than the cut-in wind speed and at a wind speed higher than the cut-out wind speed.
Between the cut-in wind speed and the rated wind speed, the generator output is simply

[0032]

(Equation 2)

The generator output is a rated output between the rated wind speed and the cut-out wind speed. Using the generator output shown in FIG. 8, in step S73 of FIG. 7, if the wind speed V is smaller than the cut-in wind speed, the output is set to 0 in step S78.
At 74, the wind speed V is compared with the cut-out wind speed. If the wind speed V is equal to or higher than the cutout wind speed, the output is set to 0 in step S78.
Proceed to 75 and compare the wind speed with the rated wind speed. If the wind speed is equal to or higher than the rated wind speed, the output is made equal to the rated wind speed in step S77. If the wind speed is smaller than the rated wind speed, in step S76,
Simplified output = rated output x (V-cut-in wind speed) /
(Rated wind speed-cut-in wind speed).

Next, in step S79, step S7
The output obtained in step 6 is added to the sum of outputs up to the previous loop. Perform the above calculation for one day, for example,
The short-term forecast power generation for one day. The short-term predicted power generation obtained in this way is the basis for calculating the long-term predicted power generation described below.

According to the first method of calculating the long-term predicted power generation amount, it is obtained by simply summing the short-term predicted power generation amounts. That is, for example, the predicted power generation for one month is obtained by summing the predicted power generation for one day for 30 days. The second method of calculating the long-term predicted power generation is a statistical method. This will be described with reference to FIGS.

FIG. 9 is a graph showing a well-known Weibull distribution showing an example of the frequency of the wind speed v (wind speed distribution). This wind speed distribution is represented by the following equation representing a well-known frequency distribution.

[0037]

(Equation 3)

If the frequency distribution is known, the parameters c and k in the above equation can be obtained by the least square method or the like. Then, the amount of power generation E can be estimated by the well-known formula (Nei Yoneda, Taiichi Hayashi, “Evaluation of Wind Energy in Japan”, Weather, Vol. 26, No. 10, 583-594, October 1979)
Month, see).

[0039]

(Equation 4)

FIG. 10 is a flowchart for explaining the calculation of the long-term predicted power generation amount by the above-described statistical method. In the figure, in step S91, for example, the average value of the short-term predicted power generation amount at 10-minute intervals is accumulated over a long period of time, for example, one month. Next, in step S92, a frequency distribution as shown in FIG. 9 is calculated from the accumulation result. Next, in Step S93, parameters c and k are calculated from the frequency distribution. Next, in step S94, a long-term (one month in this case) predicted power generation amount E is calculated based on equation (3).

By the above processing, step S19 in FIG.
The long-term predicted power generation at is calculated. Then Figure 1
In steps S20 to S22, when the mesh area having the largest predicted power generation amount is determined as the installation position of the wind power generator, the characteristics of the wind power generator at the installation position are determined by optimizing the parameters.

FIG. 11 is a flowchart for explaining in detail the processing for determining the generator characteristics in step S23 of FIG. In the figure, parameters are set in step S111. As described with reference to FIG. 8, the parameters of the wind power generator include the cut-in wind speed, the cut-out wind speed, and the rated wind speed. First, a change range of each parameter is determined in advance, and how many times the parameter is changed within the change range is also determined in advance. Next, the process between steps S112a and S112b is repeated for each of the cut-out wind speeds for all the cut-in wind speeds and the rated wind speed. That is, first, the cut-out wind speed and the cut-in wind speed are fixed, and the process between steps S114a and S114b is repeated to change the rated wind speed little by little. Calculate the amount of power generation and store the calculation results in a file each time.

After storing the calculation results of the short-term predicted power generation amount for all of the changes in the rated wind speed, the cut-out wind speed is set as a fixed value, and steps S113a and S11 are executed.
3b, the cut-in wind speed is changed, and the rated wind speed is changed little by little for each cut-in wind speed.
The short-term predicted power generation amount shown in (1) is calculated, and the calculation result is stored in a file each time.

After storing the calculation results of the short-term predicted power generation amount for all of the changes in the cut-in wind speed and the rated wind speed, the process between steps S112a and S112b is repeated to thereby fix the cut-out wind speed fixed next. Is calculated again for all the combinations of the cut-in wind speed and the rated wind speed.
At 115, the short-term predicted power generation amount shown in FIG. 7 is calculated, and the calculation result is stored in a file each time.

In this way, the calculation results of the short-term predicted power generation amount for all combinations of the parameter change values are stored in the file. Next, in step S116, a combination of parameters indicating the largest predicted power generation amount among the predicted power generation amounts stored in the file is determined as an optimal parameter. In the above description, the method for determining the installation position of the wind power generator and the method for optimally setting the parameters of the installed wind power generator have been described. However, according to another aspect of the present invention, step S11 in FIG. A short-term predicted power generation amount is obtained by the processing from step S16 to step S16, and a long-term predicted power generation amount is obtained by the processing from step S11 to step S19 in FIG. Therefore, the short-term predicted power generation and / or the long-term predicted power generation for the already installed wind power generator can also be calculated. However, in this case, since the calculation area may be an area of a desired size including the position where the wind power generator is installed, the process of dividing into meshes in step 13 is unnecessary.

As a result, a future power generation amount such as a few minutes, a few hours, a few days, and a few months can be predicted for a desired area as needed, so that a power supply plan is efficiently created. be able to. FIG. 12 is a block diagram showing a known computer system for executing the above processing. In FIG. 12, a computer system includes a central processing unit (CPU) 12 and an input device 13.
, An output device 14, an input / output interface 15, and an auxiliary storage device 16. The CPU 12 includes a control device 121, a calculation device 122, and a main storage device 123. All the flowcharts described above are executed by the arithmetic unit 122. The file and database for storing the above-described calculation results are stored in the auxiliary storage device 16.

[0047]

As is apparent from the above description, according to the present invention, the optimum installation position of the wind power generator can be determined by numerical simulation. Further, according to the present invention, the amount of power generated by the already installed wind power generator can be predicted by numerical simulation, so that an efficient power supply plan can be created.

[Brief description of the drawings]

FIG. 1 is a part of a flowchart illustrating a method for determining a wind power generator installation position and a method for estimating a wind power generation amount according to the present invention.

FIG. 2 is another part of a flowchart illustrating a method for determining a wind generator installation position and a method for estimating a wind power generation amount according to the present invention.

FIG. 3 is a diagram showing a state where a calculation area is divided into meshes.

FIG. 4 is a flowchart illustrating the calculation of an airflow field in step S15 of FIG. 1 in further detail.

FIG. 5 is a diagram illustrating a method of creating an initial value and a boundary value of a narrow area from data of a wide area.

FIG. 6 is a flowchart illustrating details of step S15 in FIG. 1, that is, step S41 in FIG. 4;

FIG. 7 is a flowchart illustrating details of calculation of a short-term power generation amount in step S16 of FIG. 1;

FIG. 8 is a graph showing the generator output when parameters defining output characteristics of the wind generator are fixed.

FIG. 9 is a graph diagram of a well-known Weibull distribution showing an example of a wind speed distribution.

FIG. 10 is a flowchart illustrating a long-term power generation estimation process using a statistical method.

FIG. 11 is a flowchart illustrating in detail a generator characteristic determination process in step S23 of FIG. 1;

FIG. 12 is a block diagram showing a computer system for implementing the present invention.

[Explanation of symbols]

16: Auxiliary storage device S11, S12: First step of setting power generation amount calculation period and calculation area S15: Second step of calculating and storing power generation amount S20: New calculation of mesh area indicating maximum power generation amount step SM ₁₁ ~M ₅₅ determines the fourth step S22 ... new calculation area determines the third step S21 ... new computational domain if the last calculation area to be selected as the region as the installation position of the wind power generator ... mesh region

──────────────────────────────────────────────────続 き Continuing from the front page (72) Inventor Hiroyuki Okabe 2-7-5 Minamisuna, Koto-ku, Tokyo Inside CRC Research Institute (72) Inventor Hisashi Fukuda 2-7-5 Minamisuna, Koto-ku, Tokyo Within CRL Research Institute (58) Fields investigated (Int. Cl. ⁷ , DB name) F03D 9/00

Claims (9)

(57) [Claims] A first step of setting a calculation period and a calculation region of a predicted power generation amount; and a small calculation period obtained by dividing the calculation period for each mesh region obtained by dividing the calculation region into meshes. A second step of calculating a predicted power generation amount for each and saving the file in a file; and newly calculating a mesh region indicating a maximum predicted power generation amount among predicted power generation amounts within the calculation period calculated for each of the mesh regions. A third step of selecting as a region, a fourth step of determining whether the selected new calculation region is a final calculation region, and determining that the new calculation region is not a final calculation region in the fourth step Then, the steps from the second step to the fourth step are repeatedly executed based on the new calculation area, and the new calculation area is changed to a final calculation area in the fourth step. Comprising determining the new calculation area to be determined that as the installation position of the wind power generator, a wind power generator installed location method. 2. The method according to claim 2, wherein, using an existing wide area file describing the pressure and wind speed of each point, the calculation area is divided into meshes for each mesh area.
The method of claim 1, further comprising calculating and storing an airflow field by a numerical calculation method, and calculating and storing an electric energy based on a calculation result of the airflow field. 3. The predicted power generation amount in the new calculation area during the small calculation period is a short-term predicted power generation amount, and the predicted power generation amount in the new calculation region during the calculation period is a long-term predicted power generation amount. 2. The method for determining a wind generator installation position according to item 1. 4. The method according to claim 3, wherein the long-term predicted power generation amount is a sum of the short-term predicted power generation amounts in the new calculation area. 5. The long-term predicted power generation amount is obtained by reading a wind speed value in the new calculation area from the file over a predetermined period, obtaining a frequency distribution of the wind speed value, and statistically calculating a power generation amount corresponding to the frequency distribution. 3. The method according to claim 3, wherein the value is obtained by a statistical method.
The method for determining a wind power generator installation value according to the item. 6. A method for predicting the amount of power generation by an already installed wind power generator, comprising: a first step of setting a calculation period including a calculation period of the predicted power generation amount and an installation position of the wind power generator; A second step of calculating a predicted power generation amount and saving the calculated power generation amount in a file for each of the small calculation periods obtained by dividing the calculation period in the calculation area; and a prediction calculated in the second step. A third step of calculating a predicted power generation amount at the installation position of the wind power generator over a desired large calculation period longer than the small calculation period based on the power generation amount. 7. The method according to claim 7, wherein the second step includes: using an existing wide area file describing the pressure and wind speed at each point, dividing the calculation area into meshes for each mesh area;
The wind power generation amount according to claim 6, further comprising a step of calculating and storing an airflow field including a wind speed by a numerical calculation method, and calculating and storing the predicted power generation amount based on a calculation result of the airflow field. Forecasting method. 8. The wind power generation prediction method according to claim 6, wherein the predicted power generation amount in the large calculation period is a total of the predicted power generation amounts in the calculation region in the small calculation period. 9. The predicted power generation amount during the large calculation period is obtained by reading a wind speed value in the calculation region from the file over the large calculation period, obtaining a frequency distribution of the wind speed value, and corresponding to the frequency distribution. The wind power generation amount prediction method according to claim 6, wherein the power generation amount is obtained by a statistical method.