Wind turbine information processing device, wind turbine information processing method, and wind turbine information processing program

Abstract

The present invention provides a wind turbine information processing device that enables the optimal arrangement of wind condition observation equipment. [Solution] According to one embodiment, the wind turbine information processing device includes a simulation unit that simulates wind conditions in a first region and outputs first wind condition data including the calculation results of wind conditions at multiple locations within the first region. The device further includes a model construction unit that constructs a prediction model of wind conditions in the first region based on the first wind condition data. The device further includes a data acquisition unit that acquires second wind condition data including the calculation results of wind conditions at one or more wind turbine installation locations within the first region. The device further includes a placement determination unit that determines candidate locations where wind condition observation equipment is to be placed in the first region based on at least one of the first wind condition data, the second wind condition data, and the prediction model. The device further displays the candidate locations within the first region on a display unit.

Description

[Technical Field]

[0001] Embodiments of the present invention relate to a wind turbine information processing device, a wind turbine information processing method, and a wind turbine information processing program. [Background technology]

[0002] When designing a wind power generation facility that includes multiple wind turbines, it is desirable to place wind condition observation equipment around the locations where these turbines will be installed to conduct preliminary wind condition observations. Examples of such wind power generation facilities include wind farms installed on land or at sea. [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2023-069910 [Overview of the Initiative] [Problems that the invention aims to solve]

[0004] When deploying wind observation equipment, high ground surrounding the location where wind turbines are installed is often selected as the location for the equipment. This is because there are often fewer obstacles that obstruct wind flow around high ground.

[0005] However, if the wind conditions at the location where wind condition observation equipment is placed differ significantly from those at the location where the wind turbine will be installed, it may be impossible to properly observe the wind conditions in advance. For example, when designing a wind farm, it may become difficult to evaluate the validity of the wind condition observation data for wind farm certification.

[0006] Therefore, embodiments of the present invention provide a wind turbine information processing device, a wind turbine information processing method, and a wind turbine information processing program that can realize a suitable arrangement of wind condition observation equipment. [Means for solving the problem]

[0007] According to one embodiment, the wind turbine information processing device includes a simulation unit that simulates wind conditions in a first region and outputs first wind condition data including the calculation results of wind conditions at multiple locations within the first region. The device further includes a model construction unit that constructs a prediction model of wind conditions in the first region based on the first wind condition data. The device further includes a data acquisition unit that acquires second wind condition data including the calculation results of wind conditions at one or more wind turbine installation locations within the first region. The device further includes a placement determination unit that determines candidate locations where wind condition observation equipment is to be placed in the first region based on at least one of the first wind condition data, the second wind condition data, and the prediction model. The device further displays the candidate locations within the first region on a display unit. [Brief explanation of the drawing]

[0008] [Figure 1] This is a block diagram showing the configuration of the wind turbine information processing device according to the first embodiment. [Figure 2] This is a plan view showing an example of a wind condition simulation model according to the first embodiment. [Figure 3] This figure shows an example of the governing equations for the first embodiment. [Figure 4] This is a side view showing an example of a wind turbine according to the first embodiment. [Figure 5] This diagram illustrates a method for determining candidate locations for the wind condition observation equipment of the first embodiment. [Figure 6] This is a flowchart showing the flow of the wind turbine information processing method according to the first embodiment. [Modes for carrying out the invention]

[0009] Embodiments of the present invention will now be described with reference to the drawings. In Figures 1 to 6, identical components are denoted by the same reference numerals, and redundant descriptions are omitted.

[0010] (First Embodiment) Figure 1 is a block diagram showing the configuration of the wind turbine information processing device 1 according to the first embodiment.

[0011] The wind turbine information processing device 1 comprises an input unit 11, an information processing unit 12, and a display unit 13. The information processing unit 12 comprises a storage unit 21, a calculation unit 22, and a determination unit 23. The storage unit 21 comprises a pre-wind condition data storage unit 21a, a post-wind condition data storage unit 21b, a land data storage unit 21c, a social data storage unit 21d, and a set value storage unit 21e. The calculation unit 22 comprises a simulation unit 22a, a model construction unit 22b, a data acquisition unit 22c, and a placement determination unit 22d.

[0012] The wind turbine information processing device 1 is a device that processes information related to wind turbines. For example, when designing a wind power generation facility equipped with multiple wind turbines, the wind turbine information processing device 1 is used to select locations for placing wind condition observation equipment. The wind condition observation equipment of this embodiment is placed around the locations where these wind turbines will be installed (wind turbine installation locations) and is used to perform preliminary observations of wind conditions. Examples of wind power generation facilities include wind farms installed on land or at sea. The wind turbine information processing device 1 of this embodiment calculates and outputs appropriate locations for placing wind condition observation equipment based on wind conditions, land conditions, social conditions, etc., of the wind power generation facility.

[0013] Wind conditions include various factors related to wind. Examples of wind conditions include the annual energy production (AEP) obtained from the multiple wind turbines mentioned above, the wind updraft angle of the wind flowing into each turbine, and the wake effect that the leeward turbine receives from the windward turbine. Another example of wind conditions is the extreme wind speed V at the site of the wind power generation facility. ref , V e50 These include an index I indicating the turbulent state at the site, and an index indicating the change in wind speed in the vertical direction during a storm at the site. The wind conditions may also include various constraints related to wind.

[0014] The land conditions include, for example, various restrictive conditions regarding the land (site) where the wind power generation equipment is installed. Examples of land conditions are distance restrictions regarding the distance from buildings, roads, rivers, etc. to the windmill, and pollution restrictions regarding shading, noise, etc. caused by the windmill. Another example of land conditions is construction feasibility restrictions regarding the slope, ground, etc. where the windmill is installed, and rights restrictions regarding land rights, etc. The land conditions may further include various data regarding the topography and geography of the land (site) where the wind power generation equipment is installed.

[0015] The social conditions include, for example, various restrictive conditions socially imposed on the area where the wind power generation equipment is installed. Examples of social conditions are restrictions regarding protected areas for animals and plants, restrictions regarding landscape protection areas, and restrictions regarding cultural heritage protection areas.

[0016] The windmill information processing device 1 is, for example, a computer such as a PC (personal computer). The windmill information processing device 1 is realized, for example, by installing a computer program for information processing regarding the windmill on the computer. The installation may be performed by inserting a recording medium on which the computer program is recorded into the computer, or may be performed by downloading the computer program from a server to the computer via a network.

[0017] Hereinafter, referring to FIG. 1, the details of the windmill information processing device 1 will be described. In this description, other figures than FIG. 1 will also be referred to as appropriate.

[0018] The input unit 11 receives various input operations from the operator and outputs information corresponding to the input operations to the information processing unit 12. The input unit 11 is constituted, for example, by an input device such as a mouse or a keyboard.

[0019] The information processing unit 12 performs various information processing. The information processing unit 12 comprises a storage unit 21 for storing various data and programs, an arithmetic unit 22 for performing various calculations, and a determination unit 23 for performing various determinations. The storage unit 21 is composed of memory and storage such as ROM (Read Only Memory), RAM (Random Access Memory), HDD (Hard Disk Drive), and SSD (Solid State Drive). On the other hand, the arithmetic unit 22 and the determination unit 23 are composed of processors such as CPU (Central Processing Unit) and ASIC (Application Specific Integrated Circuit). The information processing unit 12 may also be equipped with a communication device for controlling communication between the wind turbine information processing device 1 and other devices, and a memory port for attaching external memory to the wind turbine information processing device 1.

[0020] The display unit 13 displays various information output from the information processing unit 12 on its screen. The display unit 13 is composed of a display device such as a liquid crystal display. The information from the information processing unit 12 may be displayed locally on the display unit 13 of the wind turbine information processing device 1, or it may be displayed remotely on the display unit of a device other than the wind turbine information processing device 1.

[0021] The preceding wind condition data storage unit 21a stores wind condition data showing the calculation results (simulation results) of wind conditions when the simulation unit 22a performs a wind condition simulation. On the other hand, the subsequent wind condition data storage unit 21b stores wind condition data acquired by the data acquisition unit 22c.

[0022] The land data storage unit 21c stores data related to the land on which the wind power generation facility will be installed, such as the land conditions mentioned above. The social data storage unit 21d stores data related to the social aspects of the area on which the wind power generation facility will be installed, such as the social conditions mentioned above. The setting value storage unit 21e stores various setting values ​​used by the information processing unit 12 when performing information processing.

[0023] In this embodiment, before the information processing unit 12 performs information processing, the operator inputs the data and settings necessary for information processing in advance through the input unit 11. The data and settings input from the input unit 11 are stored in the land data storage unit 21c, social data storage unit 21d, setting value storage unit 21e, etc., as shown in Figure 1. Note that instead of the operator manually inputting the above data and settings into the wind turbine information processing device 1, the wind turbine information processing device 1 may automatically acquire them.

[0024] Next, we will describe the details of the functional blocks such as the simulation unit 22a, the model construction unit 22b, the data acquisition unit 22c, the placement determination unit 22d, and the judgment unit 23. These functional blocks are realized, for example, by the processor in the wind turbine information processing device 1 executing a computer program for processing information about wind turbines. The program in question is an example of a wind turbine information processing program.

[0025] [Simulation section 22a] The simulation unit 22a simulates wind conditions in the analysis domain and outputs the simulation results of the wind conditions in the analysis domain. The simulation unit 22a simulates wind conditions in the analysis domain using wind condition analysis software such as MASCOT® or RIAM-COMPACT®. The analysis domain is a computational domain that corresponds to the real-world area (study area) where the placement of wind turbines is being considered. An example of a study area is the area within the site of a wind power generation facility. The simulation unit 22a stores wind condition data showing the simulation results of the wind conditions in the pre-wind condition data storage unit 21a. This wind condition data is an example of first wind condition data. The wind condition simulation performed by the simulation unit 22a is also called wind condition analysis.

[0026] In this embodiment, the simulation unit 22a simulates wind conditions in the above-mentioned analysis domain and outputs simulation results of wind conditions at multiple locations within the analysis domain. Figure 5 shows domain R as an example of the analysis domain. The left side of Figure 5 shows how wind conditions are simulated at multiple grid points P1 within domain R. The simulation unit 22a stores the wind condition data showing the simulation results of wind conditions at these grid points P1 in the preceding wind condition data storage unit 21a. Domain R is an example of the first domain, and grid points P1 are examples of multiple locations within the first domain. Further details of Figure 5 will be described later.

[0027] Alternatively, the simulation unit 22a may simulate wind conditions at multiple points on one or more contour lines of the terrain within the analysis domain, instead of simulating wind conditions at multiple grid points within the analysis domain. Points on contour lines are also examples of multiple locations within the first domain.

[0028] Furthermore, the wind turbine information processing device 1 of this embodiment may be used to optimize the wind turbine arrangement when designing a wind power generation facility equipped with multiple wind turbines. In this case, the simulation unit 22a samples the position coordinates of various wind turbine arrangements of multiple wind turbines, for example, using random numbers (quasi-random numbers). The simulation unit 22a further samples from among the various wind turbine arrangements the wind turbine arrangement that maximizes the total power generated by all wind turbines, using a greedy method or the like. Alternatively, the simulation unit 22a samples from among the various wind turbine arrangements the wind turbine arrangement with the smallest difference from the current wind turbine arrangement. When sampling various wind turbine arrangements, the type of each wind turbine may be changed to various types.

[0029] Figure 2 is a plan view showing an example of the wind condition simulation model 2 of the first embodiment.

[0030] In Figure 2, the wind condition simulation model 2 includes an analysis center 31, a minimum analysis grid range 32, a target region 33, an analysis region 34, an additional region 35, an upstream buffer region 41, a downstream buffer region 42, a lateral buffer region 43, and a lateral buffer region 44. Figure 2 further shows the wind turbine position P and the inflow wind W. The simulation unit 22a of this embodiment simulates wind conditions using the wind condition simulation model 2 shown in Figure 2.

[0031] Figure 2 further shows the X, Y, and Z directions, which are perpendicular to each other. In this embodiment, the +Z direction is upward, the -Z direction is downward, and the XY plane is the horizontal plane. In this embodiment, the -Z direction coincides with the direction of gravity, but it may be inclined from the direction of gravity.

[0032] The wind turbine position P is the location where the wind turbine is placed. The incoming wind W is the wind flowing into the wind turbine from the windward side. The analysis center 31 is the central position of the analysis of the wind condition simulation model 2. The minimum analysis grid range 32 is the region of the smallest constituent unit of the target region 33 of the wind condition simulation. The analysis region 34 is the region that encloses the target region 33 in a ring shape. The additional region 35 is a region provided on the windward side of the analysis region 34 and added to the analysis region 34. Note that the above-mentioned "analysis region" in which the simulation unit 22a simulates wind conditions may be the same as the analysis region 34, or it may be different from the analysis region 34.

[0033] The upstream buffer region 41 is the region adjacent to the additional region 35 on the upwind side of the additional region 35. The downstream buffer region 42 is the region adjacent to the analysis region 34 on the downwind side of the analysis region 34. The lateral buffer regions 43 and 44 are the regions adjacent to the sides of the analysis region 34 and the additional region 35. In Figure 2, the lateral buffer region 43 is located in the +Y direction of the analysis region 34 and the additional region 35, and the lateral buffer region 44 is located in the -Y direction of the analysis region 34 and the additional region 35.

[0034] In this embodiment, the operator pre-specifies the above-mentioned study area using the input unit 11 before the wind condition simulation. The operator further inputs topographic data of the region including this study area from the input unit 11. The operator further inputs wind inflow conditions such as wind direction, wind speed, and turbulence intensity, as well as wind turbine information such as wind turbine shape and number of wind turbines, from the input unit 11. The operator further inputs other data such as wind conditions, land conditions, and social conditions from the input unit 11. The data thus input by the operator is used in the wind condition simulation. For example, the specification of the study area and the content of the topographic data are reflected in each region of the wind condition simulation model 2.

[0035] Figure 3 shows an example of the governing equations in the first embodiment.

[0036] The simulation unit 22a of this embodiment generates a wind condition simulation model 2 for calculating predetermined physical quantities based on governing equations. The governing equations of this embodiment are the Navier-Stokes equations, as shown in Figure 3. In the wind condition simulation of this embodiment, the Navier-Stokes equations are adopted as the governing equations that express the physical laws within the mesh model in mathematical equations.

[0037] In Figure 3, ρ represents the fluid density, μ represents the fluid viscosity, and ν represents the fluid kinematic viscosity. In this embodiment, the fluid is air. The Navier-Stokes equations shown in Figure 3 include a time term, a pressure term, an advection term, and a viscosity term, as well as an external force term derived from the external force F from the wind turbine rotor. When the Navier-Stokes equations are expressed as three equations for the X, Y, and Z directions, the external force term is the X component F of the external force F. X , Y component F Y , and Z component F Z This represents a vector quantity expressed as follows:

[0038] Figure 4 is a side view showing an example of the wind turbine 3 of the first embodiment.

[0039] The wind turbine 3 shown in Figure 4 comprises a tower 51, a nacelle 52, a hub 53, and a plurality of blades 54.

[0040] The tower 51 extends in the Z direction from its lower end on the ground side to its upper end on the nacelle 52 side. The nacelle 52 is attached to the upper end of the tower 51 and houses a generator (not shown). The hub 53 is attached to the rotor of the generator. Each blade 54 is attached to the hub 53.

[0041] In Figure 4, when the multiple blades 54 rotate due to wind power, the rotation of these blades 54 is transmitted to the generator via the hub 53 and the rotating shaft. As a result, the generator is driven by wind power and generates an alternating current voltage.

[0042] The explanation of the wind turbine information processing device 1 will now resume, again referring to Figure 1. Other figures will also be referenced as appropriate during this explanation.

[0043] [Model Construction Section 22b] The model building unit 22b constructs a prediction model of the wind conditions in the above-mentioned analysis domain based on the wind condition data output by the simulation unit 22a. The model building unit 22b constructs the prediction model using, for example, regression analysis methods such as Gaussian process regression. The model building unit 22b may also construct the prediction model using a neural network, random forest, or support vector regression.

[0044] The wind condition prediction model in this embodiment is a model that uses the position coordinates of one wind turbine as an explanatory variable. Examples of wind conditions handled by the prediction model include the aforementioned AEP, updraft angle, wake effect, and extreme wind speed V. ref , V e50 These include an index I representing the state of turbulence and an index of wind speed change during storms. The wind conditions handled by the prediction model are called wind condition parameters. The model construction unit 22b constructs a prediction model using, for example, the wind condition data stored in the preceding wind condition data storage unit 21a and the wind conditions input from the input unit 11.

[0045] In FIG. 5, the model construction unit 22b constructs a prediction model of the wind conditions in the region R based on the simulation results of the wind conditions at a plurality of grid points P1 within the region R. This is shown in the central figure in FIG. 5. For example, the model construction unit 22b predicts the extreme wind speeds V ref , V e50 and constructs a prediction model for predicting them. Further details of FIG. 5 will be described later.

[0046] [Data acquisition unit 22c] The data acquisition unit 22c acquires wind condition data including the calculation results of the wind conditions at one or more wind turbine installation sites within the above analysis region. This wind condition data is an example of the second wind condition data. The right figure in FIG. 5 shows three wind turbine installation sites P2 within the region R as examples of one or more wind turbine installation sites within the analysis region. FIG. 5 further shows three wind turbines 3 located at these wind turbine installation sites P2.

[0047] The data acquisition unit 22c may acquire the wind condition data of the wind turbine installation site based on the wind condition data output by the simulation unit 22a, or may acquire the wind condition data of the wind turbine installation site based on the prediction model constructed by the model construction unit 22b. In the former case, for example, the data acquisition unit 22c acquires the wind condition data of a predetermined wind turbine installation site P2 by acquiring the wind condition data of the grid point P1 corresponding to the predetermined wind turbine installation site P2 from the front-stage wind condition data storage unit 21a. The data acquisition unit 22c may acquire the wind condition data stored in the front-stage wind condition data storage unit 21a via the model construction unit 22b. On the other hand, in the latter case, for example, the data acquisition unit 22c acquires the wind condition data of a predetermined wind turbine installation site P2 as the output data of the prediction model. The data acquisition unit 22c stores the acquired wind condition data in the back-stage wind condition data storage unit 21b.

[0048] [Arrangement determination unit 22d] The placement determination unit 22d determines candidate locations for the placement of wind condition observation equipment in the above-mentioned analysis domain based on at least one of the wind condition data output by the simulation unit 22a, the wind condition data acquired by the data acquisition unit 22c, and the prediction model constructed by the model construction unit 22b. The number of candidate locations may be one or two or more. The right-hand diagram in Figure 5 shows the three candidate locations P3 in domain R where the wind condition observation equipment 4 will be placed, indicated by dashed circles. The wind condition observation equipment 4 is an instrument that observes the wind conditions at the location where the wind condition observation equipment 4 is placed. In Figure 5, the wind condition observation equipment 4 is placed at one of these candidate locations P3.

[0049] In this embodiment, the placement determination unit 22d acquires wind condition data for multiple grid points P1 within region R from the upstream wind condition data storage unit 21a, and acquires wind condition data for one or more wind turbine installation locations P2 within region R from the downstream wind condition data storage unit 21b. Then, the placement determination unit 22d determines one or more candidate locations P3 based on the wind condition data for multiple grid points P1 within region R, the wind condition data for one or more wind turbine installation locations P2 within region R, and a prediction model for region R. For example, when the placement determination unit 22d determines whether to determine a predetermined grid point P1 as a candidate location P3, it determines whether the wind condition data for the predetermined grid point P1 is similar to the wind condition data for the one or more wind turbine installation locations P2. In this case, if the placement determination unit 22d determines that the wind condition data for the predetermined grid point P1 is similar to the wind condition data for these wind turbine installation locations P2, it determines the predetermined grid point P1 as a candidate location P3. Thus, the placement determination unit 22d may determine a predetermined grid point P1 as a candidate site P3 based on the similarity between the wind condition data of a predetermined grid point P1 and the wind condition data of these wind turbine installation sites P2.

[0050] The similarity can be determined by any method. For example, when determining whether wind condition data for one grid point P1 is similar to wind condition data for one wind turbine installation site P2, the difference between the value for the former's wind condition data and the value for the latter's wind condition data can be calculated, and the similarity can be determined based on whether the absolute value of this difference is smaller than a threshold. Alternatively, when determining whether wind condition data for one grid point P1 is similar to wind condition data for multiple wind turbine installation sites P2, the absolute value can be calculated for each wind turbine installation site P2, the average value of these absolute values ​​can be calculated for multiple wind turbine installation sites P2, and the similarity can be determined based on the magnitude of this average value. Furthermore, when determining three candidate sites P3 from multiple grid points P1, the three grid points P1 with the highest similarity can be selected as the three candidate sites P3.

[0051] Furthermore, when determining similarity, the placement determination unit 22d may use the output data of the prediction model instead of the wind condition data of grid point P1. Also, the placement determination unit 22d may determine candidate locations P3 based on criteria other than similarity.

[0052] The placement determination unit 22d determines candidate locations P3 within region R based on, for example, the wind conditions of region R. An example of wind conditions is the extreme wind speed V. ref , V e50 The arrangement determination unit 22d determines the extreme wind speed V predicted by the prediction model. ref , V e50 Similarity may be determined based on this.

[0053] The placement determination unit 22d may determine candidate locations P3 within region R based on the wind conditions of region R and the land and / or social conditions of region R. In one example, candidate locations P3 for the wind condition observation equipment 4 are determined by considering not only the wind conditions but also the land condition that the wind turbine 3 is installed at wind turbine installation site P2, which is sufficiently far from the fishing port. In this case, the land conditions stored in the land data storage unit 21c are used for placement determination. In another example, candidate locations P3 are determined by considering not only the wind conditions but also the social condition that the wind turbine 3 is installed at wind turbine installation site P2, which is sufficiently far from the flora and fauna protection area. In this case, the social conditions stored in the social data storage unit 21d are used for placement determination. For example, candidate locations P3 are determined to be in a location that satisfies the land and / or social conditions for wind turbine installation site P2, similar to wind turbine installation site P2.

[0054] The placement determination unit 22d may determine candidate site P3 based on the wind conditions and topography of grid point P1 and the wind conditions and topography of wind turbine installation site P2. For example, the placement determination unit 22d may determine candidate site P3 to be a grid point P1 having wind conditions and topography similar to those of wind turbine installation site P2. In this case, information regarding the wind conditions of grid point P1 and wind turbine installation site P2 is obtained, for example, using wind condition data, and information regarding the topography of grid point P1 and wind turbine installation site P2 is obtained, for example, using land conditions. The topography used as the criterion for similarity determination is, for example, topography complexity, roughness classification, elevation, etc.

[0055] [Judgment section 23] The determination unit 23 determines whether each candidate location within the analysis area satisfies predetermined conditions. This makes it possible to determine whether each candidate location is appropriate. Examples of predetermined conditions include constraints related to wind conditions, land conditions, and social conditions. For example, it is determined whether each candidate location is appropriate in terms of constraints related to wind conditions, such as "the wind must not be too weak" or "the wind must not be too strong." In this case, it may also be determined whether constraints related to fishing ports are met, and / or whether constraints related to flora and fauna protection areas are met.

[0056] The determination unit 23 displays candidate locations that it has determined satisfy predetermined conditions as candidate locations within the above-mentioned analysis area on the display unit 13. For example, if the three candidate locations P3 shown in the right-hand diagram in Figure 5 satisfy the predetermined conditions, the area R shown in the right-hand diagram in Figure 5 will be displayed on the display unit 13 along with the three candidate locations P3. This allows the operator to select a suitable location for the wind condition observation equipment 4 by selecting one candidate location P3 from the three candidate locations P3. The process of selecting one candidate location P3 from the three candidate locations P3 may be performed automatically by the wind turbine information processing device 1 instead of being performed manually by the operator. For example, the determination unit 23 may select the most desirable candidate location P3 and display the selection result of the most desirable candidate location P3 on the display unit 13 in the form of displaying the wind condition observation equipment 4 on this candidate location P3 as shown in Figure 5. The most desirable candidate location P3 is, for example, the location among the three candidate locations P3 where the cost and effort of placing the wind condition observation equipment 4 are minimized. For example, candidate site P3, which has few trees in the surrounding area, is a location where it takes less effort to install wind condition observation equipment 4.

[0057] The determination unit 23 may also display candidate locations that it has determined do not satisfy the predetermined conditions on the display unit 13. In this case, each candidate location may be displayed on the display unit 13 along with information on whether or not each candidate location satisfies the predetermined conditions. Furthermore, the process of displaying candidate locations may be performed by a functional block other than the determination unit 23, for example, by the placement determination unit 22d.

[0058] If a candidate location does not satisfy the predetermined conditions, the placement determination unit 22d may perform the processing again for that candidate location. This makes it possible to change the position of the candidate location so that it satisfies the predetermined conditions.

[0059] As described above, the wind turbine information processing device 1 of this embodiment determines candidate locations for wind condition observation equipment based on wind condition data at the wind turbine installation site. This makes it possible to determine candidate locations that have wind conditions similar to those at the wind turbine installation site. According to this embodiment, by placing wind condition observation equipment at such candidate locations, it becomes possible to appropriately perform pre-monitoring of wind conditions for wind power generation facilities.

[0060] Generally, wind condition observations are conducted over a long period (e.g., one year) by placing wind condition observation equipment at a predetermined location. Wind condition observations often measure wind speed and wind direction at that location. Since wind condition observations are conducted over a long period, it is desirable to avoid repeating the observations. According to this embodiment, by placing the wind condition observation equipment at a suitable location, the possibility of having to repeat wind condition observations can be reduced.

[0061] Generally, even after determining candidate locations for wind condition observation equipment, it is difficult to determine whether the wind conditions at these candidate locations are similar to those at the wind turbine installation sites. According to this embodiment, by determining candidate locations using wind condition simulations and prediction models, it becomes possible to easily and precisely determine whether the wind conditions at candidate locations are similar to those at the wind turbine installation sites, even if the wind conditions are complex.

[0062] The candidate locations for the placement of wind condition observation equipment may be determined and / or indicated in a manner that identifies the exact location where the wind condition observation equipment will be placed, or they may be determined and / or indicated in a manner that identifies the area in which the wind condition observation equipment will be placed. In the former case, the location where the wind condition observation equipment will be placed can be determined, for example, by coordinates representing the location, or indicated by a point representing the location. In the latter case, the area in which the wind condition observation equipment will be placed can be determined, for example, by coordinates representing a point on the outline of the area, or indicated by a shape (for example, a circle or a rectangle) representing the area.

[0063] The following describes in more detail the information processing performed by the wind turbine information processing device 1 with reference to Figures 5 and 6. The reference numerals shown in Figure 1 will also be used as appropriate in this description.

[0064] Figure 5 is a diagram illustrating the method for determining candidate locations for the wind condition observation equipment 4 of the first embodiment.

[0065] Figure 5 shows region R as an example of an analysis region. The left-hand diagram in Figure 5 shows the simulation of wind conditions at multiple grid points P1 within region R. The simulation unit 22a outputs wind condition data including the simulation results of wind conditions at these grid points P1.

[0066] In this embodiment, the model building unit 22b constructs a prediction model of the wind conditions in region R based on the wind condition data of these grid points P1. The data acquisition unit 22c acquires wind condition data for one or more wind turbine installation sites P2 (Figure 5) within region R based on the wind condition data from the simulation unit 22a or the prediction model from the model building unit 22b. The placement determination unit 22d determines one or more candidate locations P3 (Figure 5) where the wind condition observation equipment 4 will be placed, based on the wind condition data of multiple grid points P1 within region R, the wind condition data of one or more wind turbine installation sites P2 within region R, and at least one of the prediction model for region R. For example, region R shown in the right-hand diagram in Figure 5 is displayed on the display unit 13 after determination by the determination unit 23.

[0067] Figure 6 is a flowchart showing the flow of the wind turbine information processing method according to the first embodiment. The wind turbine information processing method shown in Figure 6 is performed by the wind turbine information processing device 1 of this embodiment. For the sake of clarity, the following explanation will use the region R, grid point P1, wind turbine installation location P2, and candidate location P3 shown in Figure 5.

[0068] First, the simulation unit 22a sets various conditions based on information input by the operator from the input unit 11 (step S1). For example, the operator inputs information about the area under consideration for placing wind turbines, and the various information mentioned above that is stored in the memory unit 21.

[0069] Next, the simulation unit 22a performs a wind condition simulation in region R and outputs wind condition data including the simulation results for multiple grid points P1 within region R (step S2). As a result, the wind condition data for these grid points P1 is stored in the preceding wind condition data storage unit 21a. The simulation by the simulation unit 22a is performed using the conditions set in step S1. The grid points P1 from which to acquire simulation results are selected, for example, by sampling using random numbers (quasi-random numbers).

[0070] Next, the model building unit 22b constructs a prediction model of the wind conditions in region R based on the wind condition data at these grid points P1 (step S3). The prediction model is constructed, for example, using the wind condition data stored in the preceding wind condition data storage unit 21a.

[0071] Next, the data acquisition unit 22c acquires wind condition data for one or more wind turbine installation sites P2 within region R based on the wind condition data from the simulation unit 22a or the prediction model from the model construction unit 22b (step S4). As a result, the wind condition data for these wind turbine installation sites P2 is stored in the downstream wind condition data storage unit 21b.

[0072] Next, the placement determination unit 22d outputs one or more candidate locations P3 where the wind condition observation equipment 4 will be placed, based on the wind condition data of these wind turbine installation locations P2 (step S5). Step S5 is performed, for example, using wind condition data stored in the downstream wind condition data storage unit 21b. For example, if the placement determination unit 22d determines that the wind condition data of a predetermined grid point P1 is similar to the wind condition data of these wind turbine installation locations P2, it outputs the predetermined grid point P1 as a candidate location P3. In step S5, the placement determination unit 22d calculates, for example, the error between the wind condition at grid point P1 and the wind condition at wind turbine installation locations P2, and outputs N1 grid points P1 (where N1 is an integer of 1 or more) with the smallest error as candidate locations P3.

[0073] Next, the placement determination unit 22d outputs one or more candidate locations P3 where the wind turbine observation equipment 4 will be placed, based on the land data of these wind turbine installation sites P2 (step S6). In step S6, the placement determination unit 22d outputs candidate locations P3 selected from the candidate locations P3 output in step S5. Examples of land data include land conditions related to the terrain within the region R, such as terrain complexity, roughness classification, and elevation. In step S6, the placement determination unit 22d calculates, for example, the error between the terrain of grid point P1 and the terrain of wind turbine installation site P2, and outputs N2 grid points P1 (where N2 is an integer from 1 to N1) with the smallest error as candidate locations P3.

[0074] In steps S5 and S6, the placement determination unit 22d determines a grid point P1 having wind conditions and topography similar to those of the wind turbine installation site P2 as a candidate site P3. Note that the error minimization in steps S5 and S6 may be performed using, for example, a genetic algorithm, an evolutionary computation method, or Bayesian optimization. Alternatively, in steps S5 and S6, the weighted sum of errors in wind conditions and topography may be minimized, and one or more grid points P1 may be output as candidate sites P3 based on this minimization.

[0075] Next, the determination unit 23 determines whether each candidate location P3 output in step S6 satisfies predetermined conditions (step S7). Examples of predetermined conditions include constraints related to wind conditions, constraints related to land conditions, and constraints related to social conditions. If the determination result in step S7 is No, the process returns to step S5. If the determination result in step S7 is Yes, the candidate locations P3 that satisfy the predetermined conditions are displayed on the display unit 13.

[0076] As described above, the wind turbine information processing device 1 of this embodiment determines candidate locations for wind condition observation equipment based on wind condition data at the wind turbine installation site. This makes it possible to determine candidate locations that have wind conditions similar to those at the wind turbine installation site. According to this embodiment, by placing wind condition observation equipment at such candidate locations, it becomes possible to appropriately perform pre-observation of wind conditions for wind power generation facilities. Thus, according to this embodiment, it is possible to achieve a suitable arrangement of wind condition observation equipment.

[0077] Although several embodiments have been described above, these embodiments are presented only as examples and are not intended to limit the scope of the invention. The novel apparatus, methods, and programs described herein can be implemented in a variety of other forms. Furthermore, various omissions, substitutions, and modifications can be made to the forms of apparatus, methods, and programs described herein, without departing from the spirit of the invention. The appended claims and equivalents are intended to include such forms and modifications that are included in the scope and spirit of the invention. [Explanation of Symbols]

[0078] 1: Wind turbine information processing device, 2: Wind condition simulation model, 3: Wind turbines, 4: Wind condition observation equipment, 11: Input unit, 12: Information processing unit, 13: Display unit, 21: Memory unit, 21a: Pre-stage wind condition data storage unit, 21b: Lower wind condition data storage unit, 21c: Land data storage unit, 21d: Social data storage unit, 21e: Setting value storage unit, 22: Calculation unit, 22a: Simulation unit, 22b: Model building unit, 22c: Data acquisition unit, 22d: Placement determination unit, 23: Judgment unit, 31: Analysis center, 32: Minimum analysis grid range, 33: Target area, 34: Analysis area, 35: Additional area, 41: Upstream buffer area, 42: Downstream buffer area, 43: Side buffer area, 44: Side buffer area, 51: Tower, 52: Nacelle, 53: Hub, 54: Blade

Claims

1. A simulation unit that simulates wind conditions in a first region and outputs first wind condition data including the calculation results of wind conditions at multiple locations within the first region, A model building unit constructs a prediction model of the wind conditions in the first region based on the first wind condition data, A data acquisition unit that acquires second wind condition data including the calculation results of wind conditions at one or more wind turbine installation sites within the first region, The system includes a placement determination unit that determines candidate locations in the first region where wind condition observation equipment is to be placed, based on at least one of the first wind condition data, the second wind condition data, and the prediction model. A wind turbine information processing device that displays the candidate locations within the first region on a display unit.

2. The wind turbine information processing device according to claim 1, wherein the data acquisition unit acquires the second wind condition data based on the first wind condition data or the prediction model.

3. The wind turbine information processing device according to claim 1, wherein the placement determination unit determines the predetermined location as the candidate location based on the first wind condition data of a predetermined location among the plurality of locations and the second wind condition data of one or more wind turbine installation locations.

4. The wind turbine information processing device according to claim 3, wherein the placement determination unit determines the predetermined location as the candidate location based on the similarity between the first wind condition data of the predetermined location and the second wind condition data of one or more wind turbine installation locations.

5. The wind turbine information processing device according to claim 1, wherein the placement determination unit determines the candidate locations within the first region based on the wind conditions of the first region and the land conditions and / or social conditions of the first region.

6. The system further includes a determination unit that determines whether or not the candidate location within the first region satisfies predetermined conditions. The wind turbine information processing device according to claim 1, wherein the candidate locations determined to satisfy the predetermined conditions within the first region are displayed on the display unit.

7. The wind turbine information processing device according to claim 6, wherein the predetermined conditions include constraints relating to the wind conditions in the first region.

8. The wind turbine information processing device according to claim 7, wherein the predetermined conditions further include constraints relating to land conditions and / or social conditions of the first region.

9. The wind turbine information processing device according to claim 1, wherein the simulation unit simulates wind conditions in the first region using wind condition analysis software.

10. The wind turbine information processing device according to claim 1, wherein the model construction unit constructs the prediction model for the first region using a regression analysis method.

11. The system simulates wind conditions in a first region and outputs first wind condition data including the calculation results of wind conditions at multiple locations within the first region. Based on the first wind condition data, a prediction model for the wind conditions in the first region is constructed. Second wind condition data is obtained, which includes the calculation results of wind conditions at one or more wind turbine installation sites within the first region. Based on at least one of the first wind condition data, the second wind condition data, and the prediction model, candidate locations for wind condition observation equipment to be placed in the first region are determined. The candidate locations within the first region are displayed on the display unit. A wind turbine information processing method that includes the following.

12. The system simulates wind conditions in a first region and outputs first wind condition data including the calculation results of wind conditions at multiple locations within the first region. Based on the first wind condition data, a prediction model for the wind conditions in the first region is constructed. Second wind condition data is obtained, which includes the calculation results of wind conditions at one or more wind turbine installation sites within the first region. Based on at least one of the first wind condition data, the second wind condition data, and the prediction model, candidate locations for wind condition observation equipment to be placed in the first region are determined. The candidate locations within the first region are displayed on the display unit. A wind turbine information processing program that causes a computer to execute a wind turbine information processing method that includes the following.

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