JP7066374B2 - Turbulence evaluation device, turbulence evaluation method and program - Google Patents

Description

The present invention relates to a turbulence evaluation device, a turbulence evaluation method and a program, and more particularly to a turbulence evaluation device for evaluating a turbulent flow of natural energy at a candidate site.

In recent years, wind turbine accidents have occurred frequently. As a result of the accident investigation, "metal fatigue" is reported to be the main cause of the accident.

The inventors have researched and developed wind power generation and put it into practical use (see, for example, Patent Document 1). The wind turbine is generally designed based on the IEC standard (see, for example, Non-Patent Document 1). Further, the turbulent flow intensity is known as a value for evaluating the turbulent flow (local wind condition) of the wind turbine. Turbulence intensity is generally defined as the ratio of the standard deviation of the wind turbine to the average wind speed (see page 195 of Non-Patent Document 2).

Japanese Unexamined Patent Publication No. 2016-186253

New Energy and Industrial Technology Development Organization, Annex A (Reference) "Design conditions for wind power generators according to IEC standards", [online], [Search on November 7, 2016], Internet <URL: http //www.nedo.go.jp/content/100107253.pdf ＞ New Energy and Industrial Technology Development Organization, Wind Power Generation Introduction Guidebook, [online], February 2008, Revised 9th Edition, [Search on November 7, 2016], Internet <URL: http: / /www.nedo.go.jp/content/100079735.pdf>

At this time, there are no reports that turbulence causes metal fatigue. Therefore, it is said that there is no problem in installing the current wind turbine in any place as long as it complies with the IEC standard and the like.

However, the inventors noted that turbulence may have an effect on wind turbine accidents and failures. Even if the wind turbine satisfies the IEC standard, etc., it may not be possible to install the wind turbine at the candidate installation site depending on the turbulent flow conditions at the candidate installation site.

Here, it is also conceivable to determine whether or not a wind turbine may be installed at the candidate site based on the turbulent flow intensity. However, the turbulent flow intensity is evaluated using the standard deviation and average wind speed of the wind at a certain height, for example, the hub height of a wind turbine. Therefore, it may not be possible to sufficiently evaluate the wind conditions at the candidate sites.

Therefore, an object of the present invention is to provide a turbulence evaluation device or the like suitable for determining whether or not a wind turbine or the like may be installed at a candidate point by a new evaluation standard different from the turbulence intensity or the like. And.

The first aspect of the present invention is a turbulence evaluation device for evaluating the turbulence of natural energy at a candidate point, and is a boundary input for storing the boundary input condition of the natural energy in the candidate space including the candidate point. The condition storage means, the simulation means for calculating the change of the natural energy in the candidate space under the boundary input condition, the change of the natural energy in the candidate space calculated by the simulation means, and the boundary input condition. The turbulence evaluation index calculation means for calculating the turbulence evaluation index at the candidate point using the boundary input condition stored in the storage means, and the turbulence evaluation index when the turbulence evaluation index exceeds the evaluation reference value, the candidate point It is provided with a determination means for determining that the turbulence of the natural energy is large.

The second aspect of the present invention is the turbulence evaluation device of the first aspect, the change of the natural energy is the speed at which the natural energy changes, and the boundary input condition is the candidate space. A standard deviation calculation means for calculating the standard deviation of the change speed of the natural energy at the evaluation points included in the candidate space, including the maximum speed of the change of the natural energy in a part or all of the boundary, is provided. The random number evaluation index calculation means calculates the turbulence evaluation index as a ratio of the standard deviation at the evaluation point to the maximum speed.

The third aspect of the present invention is the turbulence evaluation device of the first or second aspect, in the natural energy at the evaluation point obtained by actual measurement or obtained by the simulation means. When there is a direction in which the average of the changes per unit time exceeds the determination reference value, the boundary input condition can cause the change of the natural energy corresponding to the determination reference value at the evaluation point. The simulation means calculates the change of the natural energy in the candidate space under the boundary input condition, and the turbulence evaluation index calculation means changes the natural energy in a direction exceeding the determination reference value. On the other hand, the turbulence evaluation index is calculated.

The fourth aspect of the present invention is a turbulence evaluation device for evaluating the turbulence of natural energy at a candidate point, and is a boundary input for storing the boundary input condition of the natural energy in the candidate space including the candidate point. The condition storage means, the simulation means for calculating the change of the natural energy in the candidate space under the boundary input condition, the change of the natural energy in the candidate space calculated by the simulation means, and the boundary input condition. Design of a turbulence evaluation index calculation means for calculating a turbulence evaluation index at the candidate point using the boundary input condition stored in the storage means, and a power generation device for generating power using the natural energy at the candidate point. A design DEL storage means for storing a fatigue line, a cumulative fatigue calculation means for calculating the accumulated fatigue of the power generation device using a plurality of fatigue load equations, and a life evaluation means for obtaining a time point when the accumulated fatigue exceeds the designed fatigue line. The turbulence evaluation index calculation means calculates the turbulence evaluation index at the candidate point for the natural energy from each of a plurality of directions, and the fatigue load formula is at least the turbulence. The first fatigue load equation for calculating the accumulated fatigue due to the natural energy from the direction in which the evaluation index exceeds the evaluation reference value, and the natural energy from the direction in which the turbulence evaluation index does not exceed the evaluation reference value. The accumulated fatigue calculation means includes the second fatigue load formula for calculating the accumulated energy, and unlike the first fatigue load formula and the second fatigue load formula, the accumulated fatigue calculation means has the disturbance for each of a plurality of directions. The accumulated energy is calculated by selecting one of the plurality of fatigue load equations according to the value of the flow evaluation index.

The fifth aspect of the present invention is the turbulence evaluation device of the fourth aspect, and the fatigue load type is the rate of change of the natural energy and the speed of change of the natural energy in the power generation device. It was obtained by linear approximation to the standard deviation.

A sixth aspect of the present invention is a turbulence evaluation method in a turbulence evaluation device for evaluating turbulence of natural energy at a candidate point, wherein the turbulence evaluation device is in a candidate space including the candidate point. A simulation means in which the boundary input condition storage means for storing the boundary input condition of the natural energy is provided and the simulation means provided in the turbulence evaluation device calculates the change of the natural energy in the candidate space under the boundary input condition. The step and the change of the natural energy in the candidate space calculated by the turbulence evaluation index calculation means calculated by the turbulence evaluation device and the boundary input condition stored by the boundary input condition storage means. When the turbulence evaluation index calculation step for calculating the turbulence evaluation index at the candidate point and the determination means provided in the turbulence evaluation device exceed the evaluation reference value, the candidate point It includes a determination step for determining that the turbulence of the natural energy is large.

The seventh aspect of the present invention is a program for realizing the turbulence evaluation method of the sixth aspect in a computer. The invention of the present application may be regarded as a computer-readable recording medium for recording the program of the seventh aspect.

According to each aspect of the present invention, the turbulence of natural energy at the candidate site can be evaluated by using the data of natural energy obtained by the simulation and using a new standard called the turbulence evaluation index. Here, the turbulence evaluation index is different from the conventional turbulence intensity. The turbulent flow intensity is a value obtained by the standard deviation and the average velocity of the wind speed at a fixed point such as the height of the hub. On the other hand, the turbulence evaluation index is a boundary input condition conversion value, and is obtained by using the boundary input condition used in the simulation and the standard deviation in the hub height or the like. Then, as will be shown later, the inventors use this turbulence evaluation index to determine whether or not the turbulence at the candidate site can cause the failure of the power generation device using natural energy. It was clarified by an experiment that it can be judged whether or not.

Further, according to the second aspect of the present invention, for example, when the evaluation point is the hub height of the wind turbine and the maximum wind speed U _in (boundary wind speed) at the altitude of the top of the wind turbine under the boundary input condition. It can be obtained by the formula "turbulence evaluation index = σ _u (hub height wind speed standard deviation) / U _in (boundary wind speed)".

Further, according to the third aspect of the present invention, the turbulence evaluation index is calculated and the turbulence is evaluated in the time zone in which the change is large, such as the time zone in which the wind speed is large. In this way, the dangerous direction and the time zone thereof can be specified and evaluated by the turbulence evaluation index.

Further, according to the fourth aspect of the present invention, the life of the power generation device can be predicted by using the fatigue load formula corresponding to the turbulence evaluation index. In particular, according to the fifth viewpoint, for example, in the case of wind power generation, the turbulence index can be obtained from the ratio of the wind speed to the wind speed standard deviation and the wind speed as in the second viewpoint, and further, the inventors Using the fact that the found wind speed and wind speed standard deviation can be linearly approximated to accumulated fatigue, the fatigue load formula obtained by linearly approximating the wind speed and wind speed standard deviation for those that exceed and do not exceed the evaluation standard value. By using, it is possible to predict the life with high accuracy.

It is a block diagram which shows an example of the structure of the turbulence evaluation apparatus which concerns on the example of the Embodiment of this invention. It is a flow chart which shows an example of the operation of the turbulence evaluation apparatus 1 of FIG. It is a figure for demonstrating the turbulence evaluation index newly introduced in this application. It is a figure which shows the situation which (a) the strain sensor was installed in the actual wind turbine, and (b)-(d) strain measurement data. It is a figure which shows the analysis of the wind condition and strain measurement data at the time of the east wind, and the wind turbine fatigue load evaluation. It is a figure which shows the data obtained by the wind condition simulation. It is a block diagram which shows an example of the structure of the turbulence evaluation apparatus which concerns on another example of embodiment of this invention. It is a flow chart which shows an example of the operation of the turbulence evaluation apparatus 21 of FIG. The analysis results of the wind speed, the wind speed standard deviation, and the fatigue (DEL) for the east and north directions are shown. The blade life evaluation performed using the past actual measurement data is shown. The blade life evaluation performed using the turbulence evaluation index obtained by simulation in addition to the past actual measurement data is shown.

Hereinafter, examples of the present invention will be described with reference to the drawings. The invention of the present application is not limited to the following examples.

FIG. 1 is a block diagram showing an example of the configuration of a turbulence evaluation device according to an example of the embodiment of the present invention. FIG. 2 is a flow chart showing an example of the operation of the turbulence evaluation device 1 of FIG. An example of the configuration and operation of the turbulence evaluation device 1 will be described with reference to FIGS. 1 and 2.

Here, it is assumed that the turbulence evaluation device 1 determines whether or not a wind power generation device (wind turbine) that generates power using wind as natural energy may be installed at a candidate point. Further, the candidate space is assumed to be a space in which a wind turbine is installed. The highest point of the candidate space is the altitude of the highest point of the wind turbine (usually the height of the blade tip). The evaluation point is the hub height of the wind turbine.

The conventionally known turbulent intensity is expressed as "turbulent intensity = σ _u (hub height standard deviation of wind speed) / U (hub height average wind speed)" at a constant height determined by the wind turbine. Use only wind data. This is widely used because it can be measured with a wind turbine. However, the turbulence intensity is trying to evaluate the candidate site by a part of the sample, so to speak, the wind at the hub height. Therefore, the wind power generation company cannot evaluate the wind turbine as a whole depending on the turbulence intensity.

On the other hand, the inventors can obtain wind data under arbitrary conditions by using a high-precision simulation device that they have researched and developed. The newly introduced turbulence evaluation index is "turbulence evaluation index = σ _u (hub height wind speed standard deviation) / U _in (boundary wind speed)", and refer to the boundary input conditions used in the simulation. It is obtained as a boundary wind speed conversion value. Therefore, the turbulence evaluation device 1 evaluates the turbulence at the candidate point by using the wind data obtained by the simulation under the boundary input condition and using the turbulence evaluation index in consideration of the boundary input condition. be able to. Therefore, the wind power generation company can use the simulation to determine whether or not the wind turbine may be installed at the candidate site, assuming that the wind turbine is installed at the candidate site.

As described above, the turbulence evaluation index newly introduced by the present application can evaluate the space where the wind turbine is installed at the candidate point. Furthermore, since each wind direction can be evaluated with high accuracy, for wind power generation companies, for example, the wind direction at risk of failure can be known in advance, and when that wind direction is reached, power generation is stopped to avoid failure, and other wind directions. In this case, by performing appropriate power generation control such as power generation, it is possible to avoid stoppage due to a failure and efficiently obtain electricity. In this way, the evaluation of candidate points changes depending on whether or not countermeasures to prevent failures are possible. According to the present invention, usage modes such as control according to the direction can also be considered.

With reference to FIG. 1, the turbulence evaluation device 1 includes a terrain data storage unit 3 (an example of the “topography data storage means” according to the present claim) and a boundary input condition storage unit 5 (“boundary input condition” according to the present claim). An example of "storage means"), a reference value storage unit 7, a turbulence evaluation index storage unit 9, a simulation unit 11 (an example of "simulation means" in the claims of the present application), a control unit 12, and a standard deviation calculation unit. 13 (an example of the "standard deviation calculation means" of the present claim), a turbulence evaluation index calculation unit 15 (an example of the "turbulence evaluation index calculation means" of the present claim), and a determination unit 17 (an example of the present application claim). An example of a "determining means") and a display unit 19 (an example of the "display means" according to the claim of the present application) are provided.

The terrain data storage unit 3 stores terrain data for specifying the terrain of the area including the candidate point. The boundary input condition storage unit 5 stores the boundary input condition. In this embodiment, it is assumed that the boundary input condition includes the boundary wind speed. Here, the boundary wind speed is assumed to be the maximum wind speed at the altitude of the blade tip height of the wind turbine. In the following, the boundary wind speed is 10 m / s. The reference value storage unit 7 stores the reference value of the determination process. In this embodiment, the judgment reference value and the evaluation reference value are stored. The turbulence evaluation index storage unit 9 stores the turbulence evaluation index calculated by the turbulence evaluation index calculation unit 15.

An example of the operation of each configuration of the turbulence evaluation device 1 of FIG. 1 will be described with reference to FIG.

First, the simulation unit 11 refers to the terrain data stored in the terrain data storage unit 3 under the boundary input condition stored in the boundary input condition storage unit 5, and at the evaluation point (hub height) in the evaluation period. Obtain wind data (step ST1).

Next, the control unit 12 is divided into, for example, 45 °, and 8 of east (wind blowing from a range of 45 ° centered on the east; the same applies hereinafter), southeast, south, southwest, west, northwest, north, and northeast. The wind direction is divided into a plurality of parts so as to be divided into one, and one of them is selected (step ST2). In addition, the upper and lower parts may be added and divided three-dimensionally.

The control unit 12 obtains time-dependent data of the wind speed of the wind in the wind direction set in step ST2 by using the wind direction in the wind data obtained by the simulation unit 11 (step ST3). The wind speed data obtained in step ST3 over time shall be for one or more periods. Wind data belonging to continuous periods is called a "wind speed group". The criteria for dividing the period are, for example, one wind speed group from another wind direction to the set wind direction and changing to another wind direction, or even if the wind direction is the same, the wind speed changes from less than a predetermined value to more than a predetermined value. One wind speed group may be formed until the value becomes less than a predetermined value, or a combination thereof may be used as a wind speed group.

The control unit 12 selects one wind speed group (step ST4). Then, it is determined whether or not the average wind speed in the selected wind speed group for a unit time exceeds the determination reference value (step ST5). In this embodiment, the unit time is 10 minutes and the determination reference value is 9.0 m / s. If the average wind speed in a unit time exceeds the determination reference value, the process proceeds to step ST6. If the average wind speed for the unit time does not exceed the determination reference value, the process proceeds to step ST10.

In step ST6, the standard deviation calculation unit 13 calculates the standard deviation of the wind speed at the hub height. Then, the turbulence evaluation index calculation unit 15 calculates the turbulence evaluation index at the candidate point by using the standard deviation of the wind speed calculated by the standard deviation calculation unit 13 and the boundary speed stored by the boundary input condition storage unit 5. (Step ST7).

The determination unit 17 determines whether or not the turbulence evaluation index exceeds the evaluation reference value (step ST9). Here, the evaluation reference value is 0.2. If the turbulence evaluation index does not exceed the evaluation reference value, the determination unit 17 proceeds to step ST10. If the turbulence evaluation index exceeds the evaluation reference value, the determination unit 17 determines that the wind turbulence at the candidate point is large, and the wind direction and the turbulence evaluation index determine the evaluation reference value for the display unit 19. It is displayed that the excess is exceeded (step ST9), and the process proceeds to step ST10.

The control unit 12 determines whether or not the processing has been performed for all the wind speed groups (step ST10). If there is a wind speed group that has not been processed, the process returns to step ST4, and one wind speed group that has not been processed is selected. If the treatment is performed for all the wind speed groups, it is determined whether or not the treatment is performed for all the wind directions (step ST11). If all the wind directions have not been processed, the process returns to step ST2 and one wind direction that has not been processed is selected. When the processing has been performed for all the wind directions, the processing shown in FIG. 2 is terminated.

The experiments conducted by the inventors will be described with reference to FIGS. 3 to 6.

FIG. 3 is a diagram for explaining a turbulence evaluation index newly introduced in the present application.

FIG. 3A shows the wind speed distribution of the ideal laminar flow in the vertical direction of the wind turbine. By smoothly increasing from the ground surface and evenly distributed in the blades, the force acts evenly on each blade, and the rotation speed becomes almost the same. Therefore, the stress applied to the roots of the three blades is almost the same. The wind conditions for which the wind turbine performance is defined are as shown in FIG. 3 (a).

However, for example, at a point where there is a mountain on the windward side, as shown in FIG. 3 (b), the wind speed and the wind cycle near the ground surface are disturbed due to the change in topography. As shown in FIG. 3 (c), the wind turbulence deviates from the ideal wind speed distribution in FIG. 3 (a). In FIG. 3C, when the wind speed at the lower part of the wind receiving surface is decelerated due to the influence of turbulence, the rotation speeds of the three blades and the stress applied to the roots are different. In particular, since the wind cycle becomes smaller due to the influence of turbulence, cyclic stress is generated at the base of the blade, and the stress accumulates, which may eventually lead to crisis damage. As a result, metal fatigue and the like progress, and the possibility of failure or accident increases. FIG. 3D shows the state of turbulence based on the data obtained in the later simulation. The vertical axis shows the height from the ground surface, and the horizontal axis shows the velocity distribution. Arrows indicate the width of the hub height decelerated from the ideal wind speed distribution.

Here, even if metal fatigue occurs under the wind conditions peculiar to complicated terrain, the wind turbine can be installed on the terrain as long as the structural strength of the wind turbine can sufficiently withstand it. Therefore, in the experiment, the wind speed data input to the actually measured wind turbine equipment and the wind turbine blade strain data are measured, and the wind conditions peculiar to complicated terrain and the influence on the structural strength of the wind turbine are identified and then complicated. Based on the reproduction results of wind conditions on the terrain (wind condition analysis results by Liam Compact), we will quantify the optimum placement criteria for recommending wind turbine accidents from the numerical wind condition side. By using this optimum placement standard, it is possible to support the optimum placement plan.

In the experiment, first, in an actual wind turbine, the synchronized measurement data of the wind condition and the wind turbine behavior were compared, and the wind direction in which the strain data fluctuation amount (amplitude) was large was identified. Here, the wind conditions were analyzed for wind speed and wind direction fluctuations using a nacelle anemometer and wind direction meter. For the wind turbine behavior, strain cages were installed at the root roots of the three blades, and strain fluctuations were analyzed.

Then, the blade bending fatigue load was evaluated for the specified wind direction, and the effect on wind turbine fatigue in complicated terrain was grasped. The blade bending fatigue load for 20 years was calculated from the strain data, and the blade bending fatigue damage was evaluated (blade bending fatigue damage = fatigue load calculated from strain data (20 years) / design allowable fatigue load (20 years)). If the blade bending fatigue damage exceeds 1, fatigue fracture will occur before the end of the useful life of 20 years.

FIG. 4A shows a situation in which a strain sensor is installed in an actual wind turbine. This wind turbine has a blade tip height of 100 m, a blade diameter of 80 m, and a hub height of 60 m. The roots of the three blades (root part: about 1.3 m from the hub joint surface) are places that can be retrofitted to existing equipment, and strain sensors are installed. The strength evaluation of the blade root (blade bending load evaluation) is important because the wind energy is input through the blade.

4 (b) to 4 (d) show strain measurement data. (B) In the easterly wind, a large distortion was measured from 8:00 to 10:00 on November 13. (C) In the north wind, a large distortion was measured from 17:00 to 22:00 on November 9. (D) In the southerly wind, a large distortion was measured from 2:00 to 5:00 on November 14.

Analyzing the wind speed and strain measurement data for each wind direction, the strain fluctuation (fluctuation) becomes maximum when the wind speed rises to a maximum of about 9 / s in the east wind, the north wind, and the south wind. The east wind, north wind, and south wind rose to almost the same wind speed during the time when the large distortion occurred, but the distortion fluctuation was the largest in the east wind. The fatigue damage was 2.03 for the east wind, 0.95 for the north wind, and 0.93 for the south wind. Since the east wind exceeds 1, it is expected that fatigue rupture will occur before the useful life of 20 years has passed.

With reference to FIG. 5, the analysis of wind conditions and strain measurement data in the case of an east wind and the evaluation of wind turbine fatigue load will be specifically described. With reference to FIG. 5A, a concrete analysis is made from 8:00 to 13:00 on November 13, when the strain fluctuation is large. Here, the sampling period is 50 Hz (0.02 s). Analyzing the time-series data of wind speed and wind direction in this time zone, eastern winds are continuously generated, and the wind cycle is shortened due to the influence of turbulence. With reference to FIG. 5 (b), the maximum fatigue damage is 2.03 when the wind speed is 9.7 m / s (10-minute average). The standard deviation of the wind speed is about 2.4 m / s. Fatigue damage is about 2 from 8:00 to 10:00 when the east wind occurs continuously. After that, it moved to the southeast and became less than 1. Therefore, for example, by controlling according to the wind direction, such as stopping power generation when the wind is easterly and restarting power generation when the wind shifts to the southeast, continuous power generation can be realized while avoiding failures. Can be done.

Subsequently, the data obtained by the wind condition simulation will be described with reference to FIG. Here, in order to evaluate the effect of turbulence due to the terrain, we compared the time when there was an upwind mountain in the easterly wind (without elevation correction) and the time when there was no mountain (with elevation correction).

FIG. 6A compares the easterly wind with and without elevation correction. When there was no altitude correction, the change in wind speed was larger than when there was altitude correction. The change in wind speed with elevation correction was similar to the change in wind speed in north and south winds with no mountains upwind.

Comparing the measured wind condition data and the wind condition simulation result, in the case of the east wind (around 90 deg of the wind direction), the same periodic fluctuation (period 6 to 7 s) was observed in both wind direction fluctuation periods, and the wind speed fluctuation was large. .. In addition, the standard deviations of the wind speeds were about 2.4 m / s (U component in the simulation) in both cases, and tended to be almost the same. Therefore, it is considered that turbulence occurred in the actual machine, as obtained from the simulation results.

As shown in FIG. 3D, the wind speed given as the boundary input condition is decelerated (turbulent) on the blade surface in the actual machine. According to the simulation results, it is considered that the average wind speed decreases toward the lower part of the wind receiving surface and turbulence is generated due to the influence of the topography.

Regarding the turbulence evaluation, in the case of actual measurement, the easterly wind speed was 9.7 m / s, the standard deviation was 2.4, and the turbulence intensity was 25%. With a fatigue damage of 2.03 in the easterly wind, the planned value of the design fatigue load was reached in 5.88.

According to the simulation results, the turbulence evaluation index (boundary wind speed (10 m / s) conversion value) newly proposed by the present application for easterly wind is 0.236 (= hub height standard deviation 2.36 m / s / boundary wind speed 10 m / s). became. The turbulent flow intensity was 64% (hub height standard deviation 2.36 m / s / average wind speed 3.71 m / s). On the other hand, in the north wind and the south wind, the turbulence evaluation indexes are 0.099 and 0.111, and the turbulence intensity is 0.11 and 0.09, respectively. From this, the placement criterion that the turbulence evaluation index does not exceed 0.2 (that is, the criterion that the upper limit of the turbulence evaluation index is 0.2) is appropriate, and in this experiment, the turbulence evaluation index 0.236 was used. , Fatigue damage was 2.03, which could be evaluated quantitatively.

Summarizing the above, the layout that can reduce wind turbine accidents can be considered as follows. First, for example, when the wind speed exceeds 9 m / s based on the wind condition observation data, it is confirmed whether or not there is an obstacle (topography / feature) that causes turbulence in the wind direction. Next, simulate the wind direction caused by the obstacle and confirm that the turbulence evaluation index is within 0.2. That is, in this experiment, when the turbulence evaluation index exceeded 0.2, the fatigue damage was 1 or more.

FIG. 7 is a block diagram showing an example of the configuration of the turbulence evaluation device according to another example of the embodiment of the present invention. FIG. 8 is a flow chart showing an example of the operation of the turbulence evaluation device 21 of FIG. An example of the configuration and operation of the turbulence evaluation device 21 will be described with reference to FIGS. 7 and 8.

It is assumed that the turbulence evaluation device 21 determines whether or not a wind power generation device (wind turbine) that generates power using wind as natural energy may be installed at a candidate point.

With reference to FIG. 7, the turbulence evaluation device 21 includes a topographical data storage unit 3 (an example of the “topographical data storage means” of the present application claim) and a boundary input condition storage unit 5 (“boundary input condition” of the present application claim). An example of "storage means"), a reference value storage unit 7, a turbulence evaluation index storage unit 9, a simulation unit 11 (an example of "simulation means" according to the present invention), a control unit 12, and a standard deviation calculation unit. 13 (an example of the "standard deviation calculation means" of the present application claim) and a turbulence evaluation index calculation unit 15 (an example of the "turbulence evaluation index calculation means" of the present application claim) are provided. Each of these units operates in the same manner as that of the turbulence evaluation device 1 of FIG. 1 with the same reference numerals, and the turbulence evaluation index calculation unit 15 calculates the turbulence evaluation index in each direction.

The turbulence evaluation device 21 further includes an actually measured value storage unit 23, a design DEL storage unit 25 (an example of the “design DEL storage means” in the claims of the present application), a fatigue load type calculation unit 27, and a cumulative fatigue calculation unit 29. (An example of the "accumulated fatigue calculation means" of the present claim) and a life evaluation unit 31 (an example of the "life evaluation means" of the present claim) are provided.

With reference to FIG. 8, the simulation unit 11 refers to the terrain data stored in the terrain data storage unit 3 under the boundary input condition stored in the boundary input condition storage unit 5, and evaluates the evaluation points in the evaluation period ( Obtain wind data at hub height) (step STJ1).

Next, the turbulence evaluation index calculation unit 15 determines the standard deviation of the wind velocity calculated by the standard deviation calculation unit 13 and the boundary speed stored in the boundary input condition storage unit 5 for each direction divided into 16 directions. It is used to calculate the turbulence evaluation index at the candidate point (step STJ2).

Specifically, steps STJ1 and STJ2 can be calculated in the same manner as in FIG. 1 in which steps ST8 and ST9 are omitted.

The fatigue load type calculation unit 27 performs linear approximation for a part or all of each direction and calculates the fatigue load type (step STJ3).

The accumulated fatigue calculation unit 29 selects a fatigue load formula according to the value of the turbulence evaluation index in each direction (step STJ4), and accumulates fatigue using the measured data for a certain period stored in the measured value storage unit 23. Calculate (step STJ5). If there is no actual measurement data, the value obtained by simulation or the like may be used instead.

If the fatigue load type calculation unit 27 calculates the fatigue load formula for all directions, the accumulated fatigue calculation unit 29 may select the fatigue load formula corresponding to each direction and calculate the accumulated fatigue.

When the fatigue load formula calculation unit 27 calculates the fatigue load formula for some directions, the fatigue load formula is calculated for at least one of the directions in which the turbulence evaluation index exceeds the evaluation reference value and accumulated. The fatigue calculation unit 29 selects one of the fatigue load equations obtained from the direction in which the turbulence evaluation index exceeds the evaluation reference value for the direction in which the turbulence evaluation index exceeds the evaluation reference value. The fatigue load type calculation unit 27 calculates the fatigue load formula for at least one direction in which the turbulence evaluation index does not exceed the evaluation reference value, and the accumulated fatigue calculation unit 29 uses the turbulence evaluation index as the evaluation reference value. For the orientation that does not exceed, select one of the fatigue load equations obtained from the orientation in which the turbulence evaluation index does not exceed the evaluation reference value.

In FIGS. 9 to 11, the fatigue load type calculation unit 27 sets the turbulence evaluation index to be more than 0.2, not more than 0.2 and more than 0.1, and 0.1. One direction is selected from those that do not exceed each, and the fatigue load formula is calculated. The accumulated fatigue calculation unit 29 indicates that the turbulence evaluation index exceeds the evaluation reference value of 0.2 and exceeds the evaluation reference value of 0.2. Accumulated fatigue is calculated by selecting the corresponding fatigue load equations for the directions exceeding 0.1 and the directions not exceeding 0.1, respectively.

The life evaluation unit 31 obtains a time when the accumulated fatigue calculated by the accumulated fatigue calculation unit 29 increases with the passage of time and exceeds the design fatigue line of the wind turbine stored in the design DEL storage unit 25. Evaluate the life (step STJ6).

A specific example will be described with reference to FIGS. 9 to 11.

FIG. 9 shows the analysis results for the east direction (turbulence evaluation index 0.236) and the north direction (turbulence evaluation index 0.099). As a result of analyzing the mutual data relationship using the measured data of wind speed, wind speed standard deviation, turbulence intensity and fatigue (DEL) for the east and north directions, the following two points were found. That is, the relationship between fatigue (DEL) and wind speed can be linearly approximated. The relationship between fatigue (DEL) and wind speed standard deviation (σ) can be linearly approximated.

9 (a) and 9 (b) are graphs showing the relationship between the wind speed (m / s) and the wind speed standard deviation (m / s) for 10 minutes in the east and north directions, respectively. The horizontal axis is the wind speed (m / s), and the vertical axis is the wind speed standard deviation (m / s). In the straight line approximation, the east direction has a slope a = 0.23 and the north direction has a slope a = 0.14. In the case of the east direction, the slope of the wind speed standard deviation is larger than that of the north direction, and the larger the wind speed is, the larger the wind speed standard deviation is.

FIG. 9C shows the relationship between wind speed and fatigue. The horizontal axis is wind speed (m / s), and the vertical axis is fatigue (DEL). In the straight line approximation, the east direction has a slope a = 0.15, and the north direction has a slope a = 0.08. FIG. 9D shows the relationship between the wind speed standard deviation and fatigue. The horizontal axis is the wind speed standard deviation (m / s), and the vertical axis is fatigue (DEL). In the straight line approximation, the east direction has a slope a = 0.41 and the north direction has a slope a = 0.46. Therefore, it was found that the larger the wind speed standard deviation (σ), the larger the slope of the wind speed and fatigue (DEL).

In Fig. 10, the stress (accumulated fatigue) for 20 years is integrated using the measured data of the past wind speed and direction (for one year), and the life of the blade is evaluated by comparing with the design fatigue line of 20 years, which is the useful life. Was done.

FIG. 10A shows each of the 12 azimuths. FIG. 10B is a graph showing measured fatigue (DEL) lines in each direction. The horizontal axis is wind speed (m / s), and the vertical axis is fatigue (DEL). FIG. 10C shows the actual measurement DEL and the design DEL obtained by integrating the time corresponding to the wind speed in the wind direction in each direction in the actual measurement data. The accumulated fatigue of the measured DEL and the design DEL for one year is 13,976 and 20,425, respectively. The 20-year accumulated fatigue is 279,524 and 408,496, respectively. The stress (accumulated fatigue) ratio is defined as the measured DEL / design DEL. The life (year) is 20 (year, useful life) / stress ratio, and 20 / 0.68 = 29 (rounded to the first decimal place).

FIG. 11 shows a case where the accumulated fatigue is calculated using the turbulence evaluation index. The simulation is performed in 16 directions while the measured data is in 12 directions.

In this example, the direction 4 (east) in 12 directions is defined as the direction in which the turbulence evaluation index exceeds 0.2, and the direction 12 in 12 directions is defined as 0.1 as the direction not exceeding 0.2 but exceeding 0.1. Direction 1 (north) in 12 directions is selected as the direction that does not exceed, and the fatigue load equation is calculated by linear approximation. The fatigue load equations corresponding to the directions 4, 12, and 1 are obtained from the measured data and have slopes of 0.1527, 0.0945, and 0.0782, and intercepts of -0.4089 and -0.2304, respectively. -0.1458. FIG. 11A shows these fatigue load equations and the design DEL line. The horizontal axis is wind speed (m / s), and the vertical axis is fatigue (DEL).

FIG. 11B shows a turbulence evaluation index in each direction. For the direction 5 in 16 directions exceeding 0.2, the fatigue load equation obtained for the direction 4 in 12 directions is used. Direction 2, 4, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16 in 16 orientations not exceeding 0.2 but exceeding 0.1 are obtained for orientation 12 in 12 orientations. Use the fatigue load type. For the directions 1, 3, and 11 in 16 directions that do not exceed 0.1, the fatigue load equation obtained for the direction 1 in 12 directions is used. FIG. 11C shows the actual measurement DEL and the design DEL obtained by integrating the time corresponding to the wind speed in the wind direction in each direction in the actual measurement data. The accumulated fatigue of the measured DEL and the design DEL for one year is 13,184 and 20,425, respectively. The 20-year accumulated fatigue is 263,684 and 408,496, respectively. The stress (accumulated fatigue) ratio is defined as the measured DEL / design DEL. The life (year) is 20 (year, useful life) / stress ratio, and 20 / 0.65 = 31 (rounded to the first decimal place).

As a result of comparing FIGS. 10 and 11 and predicting the lifetime using the turbulence evaluation index, the lifetime was 31 years. It was almost the same as the result of life prediction (lifetime 29 years) using the measured fatigue (DEL) lines in 12 directions.

From the above, it was confirmed that the wind speed and the standard deviation of the wind speed are closely related to the wind turbine stress (accumulated fatigue). Furthermore, by performing wind condition simulation, wind condition data, and analysis of operation data, it is possible to identify a wind direction in which wind turbine stress (accumulated fatigue) is large. Furthermore, the blade life can be predicted by the fatigue load formula corresponding to the turbulence evaluation index obtained from the measured wind speed and the wind condition simulation result.

Based on this example, an example of a method for analyzing the influence of turbulence on a wind turbine generator will be described. Wind power generators usually acquire wind condition data. Therefore, the past wind speed, wind direction, and wind speed standard deviation can be obtained. In addition, ANN, power generation output, acceleration, etc. can be obtained as past operation data. By using these, wind conditions and operation data can be analyzed. According to this embodiment, in addition to this, a wind condition simulation can be performed to obtain a turbulence evaluation index for each of a plurality of directions, and past wind condition data can be used as a turbulence evaluation index. Based on this, the fatigue load type can be selected to predict the life of the wind turbine. Then, the influence of turbulence can be determined by the wind condition / operation data analysis and the life of the wind turbine, and it can be determined whether the current maintenance should be continued or a new maintenance / operation is proposed.

1,21 Turbulence evaluation device, 3 Topography data storage unit, 5 Boundary input condition storage unit, 7 Reference value storage unit, 9 Turbulence evaluation index storage unit, 11 Simulation unit, 12 Control unit, 13 Standard deviation calculation unit, 15 Random number evaluation index calculation unit, 17 judgment unit, 19 display unit, 23 actual measurement value storage unit, 25 design DEL storage unit, 27 fatigue load type calculation unit, 29 accumulated fatigue calculation unit, 31 life evaluation unit

Claims (6)

It is a turbulence evaluation device for evaluating the turbulence of wind energy that causes accumulated fatigue of the wind power generation device at a candidate site where it is considered to install a wind power generation device that generates power using wind energy.
Boundary input condition storage means for storing the boundary input condition which is the maximum wind speed in a part or all of the boundary of the candidate space used in the wind condition simulation of the wind energy in the candidate space including the candidate point.
Under the boundary input condition, a simulation means for calculating the wind speed changing in time series of the wind energy in the candidate space, and
A turbulence evaluation index at the candidate point is calculated using the wind speed that changes in time series of the wind energy in the candidate space calculated by the simulation means and the boundary input condition stored by the boundary input condition storage means. Turbulence evaluation index calculation means and
A determination means for determining that the turbulence of the wind energy at the candidate point is large when the turbulence evaluation index exceeds the evaluation reference value is provided .
A standard deviation calculation means for calculating the standard deviation of the wind speed changing in the time series at the evaluation points included in the candidate space is provided.
The turbulence evaluation index calculation means is a turbulence evaluation device that calculates the turbulence evaluation index as a boundary wind speed conversion value represented by the ratio of the standard deviation at the evaluation point to the maximum wind speed . In the wind energy at the evaluation point obtained by actual measurement or obtained by the simulation means, when there is a direction in which the average wind speed per unit time exceeds the judgment reference value, the direction thereof. Against
The simulation means calculates a wind speed that changes in a time series of the wind energy in the candidate space under the boundary input condition.
The turbulence evaluation device according to claim 1 , wherein the turbulence evaluation index calculation means calculates a turbulence evaluation index for a wind speed changing in a time series of the wind energy in a direction exceeding the determination reference value. It is a turbulence evaluation device for evaluating the turbulence of wind energy that causes accumulated fatigue of the wind power generation device at a candidate site where it is considered to install a wind power generation device that generates power using wind energy.
Boundary input condition storage means for storing the boundary input condition which is the maximum wind speed in a part or all of the boundary of the candidate space used in the wind condition simulation of the wind energy in the candidate space including the candidate point.
Under the boundary input condition, a simulation means for calculating the wind speed changing in time series of the wind energy in the candidate space, and
A turbulence evaluation index calculation means for calculating a turbulence evaluation index at the candidate point using a wind speed that changes in time series of the wind energy in the candidate space calculated by the simulation means.
A design DEL storage means for storing the design fatigue line of the wind power generator at the candidate point,
Accumulated fatigue calculation means for calculating the accumulated fatigue of the wind power generation device using a plurality of fatigue load equations, and
A life evaluation means for calculating the time point at which the accumulated fatigue crosses the design fatigue line is provided.
A standard deviation calculation means for calculating the standard deviation of the wind speed changing in the time series at the evaluation points included in the candidate space is provided.
The turbulence evaluation index calculation means calculates the turbulence evaluation index as a boundary wind speed conversion value represented by the ratio of the standard deviation at the evaluation point to the maximum speed.
The turbulence evaluation index calculation means calculates the turbulence evaluation index at the candidate point for the wind energy from each of the plurality of directions.
The fatigue load type is at least
The first fatigue load formula for calculating the accumulated fatigue due to the wind energy from the direction in which the turbulence evaluation index exceeds the evaluation reference value, and
The second fatigue load equation for calculating the accumulated fatigue due to the wind energy from the direction in which the turbulence evaluation index does not exceed the evaluation reference value is included.
Unlike the first fatigue load type and the second fatigue load type,
The accumulated fatigue calculation means calculates the accumulated fatigue by selecting one of the plurality of fatigue load equations according to the value of the turbulence evaluation index for each of the plurality of directions. Evaluation device.
The fatigue load equation is obtained by linearly approximating the wind speed of the wind energy and the standard deviation of the wind speed changing in the time series of the wind energy in the wind power generation device, according to claim 3 . Turbulence evaluation device. Turbulence evaluation in a turbulence evaluation device for evaluating the turbulence of wind energy that causes accumulated fatigue of the wind power generation device at a candidate site where consideration is being given to installing a wind power generation device that generates power using wind energy. It ’s a method,
The turbulence evaluation device stores a boundary input condition that is the maximum wind speed in a part or all of the boundary of the candidate space used in the wind condition simulation of the wind energy in the candidate space including the candidate point. Equipped with storage means
The simulation means provided in the turbulence evaluation device includes a simulation step of calculating a wind speed changing in a time series of the wind energy in the candidate space under the boundary input condition.
The turbulence evaluation index calculation means included in the turbulence evaluation device has the wind velocity changing in time series of the wind energy in the candidate space calculated by the simulation means, and the boundary input condition stored in the boundary input condition storage means. The turbulence evaluation index calculation step for calculating the turbulence evaluation index at the candidate point, and
The determination means provided in the turbulence evaluation device includes a determination step of determining that the turbulence of the wind energy at the candidate point is large when the turbulence evaluation index exceeds the evaluation reference value.
A standard deviation calculation means for calculating the standard deviation of the wind speed changing in the time series at the evaluation points included in the candidate space is provided.
In the turbulence evaluation index calculation step, the turbulence evaluation index calculation means calculates the turbulence evaluation index as a boundary wind velocity conversion value represented by the ratio of the standard deviation at the evaluation point to the maximum speed. Turbulence evaluation method . A program for realizing the turbulence evaluation method according to claim 5 in a computer.

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