TWI729349B - Wind power generation device and wind power generation system - Google Patents

Abstract

The present invention provides a wind power generation device and a wind power generation system capable of accurately estimating a wind cut as a wind speed distribution with a simple structure. The wind power generation device of the present invention includes: a wind power generation device 2 having at least an impeller 25, a nacelle 22, and a tower 21 rotatably supporting the nacelle 22; and a control device 31 that controls the wind power generation device 2; and a control device 31 is equipped with a wind condition estimating device 32, which has: a load measuring unit 13 which measures the load attached to the wind power generator 2; and a memory unit 16 which stores a wind shear function 33 that defines the relationship between the load and the wind shear ; And the wind shear estimation unit 18, which calculates the wind shear based on the load and the wind shear function 33.

Description

Wind power generation device and wind power generation system

The present invention relates to a wind power generation device and a wind power generation system with the function of estimating the wind conditions around the wind power generation device.

Due to the increasing interest in the use of renewable energy, the expansion of wind power generation devices in the world market is predicted. As a one-million-watt wind power generation device, the following components are frequently used: an impeller formed by radially installing blades on a rotating hub, a nacelle supporting the impeller via a main shaft, and allowing yaw rotation and support from below The tower of the engine room. Wind power generation devices use wind that changes all the time as an energy source to generate electricity. Therefore, when the wind speed and turbulence of the wind actually flowing into the wind power generation device are more severe than the design conditions, the load on the wind power generation device may increase, and the damage of the component parts may be accelerated. When an unexpected failure occurs due to the acceleration of the damage, in addition to the time required for the replacement of the failed parts, the preparation of replacement parts or the preparation of engineering components and operators also takes time, so it is better than the implementation plan In terms of the replacement of parts, there is a concern that the operation stop time of the wind power generation device will increase and the power generation will decrease. As this countermeasure, there is a method of estimating damage to the component parts of the wind power generation device by estimating and measuring the inflow wind that becomes an energy source, or a method of controlling in a manner that reduces the load. For example, Patent Document 1 discloses a device which is based on the wind speed, power generation or blade pitch angle data that can be obtained by a simple device configuration, and uses pre-made wind speed, power generation or pitch angle, and A table that correlates wind condition parameters and a table that correlates wind condition parameters with the fatigue load attached to the wind power generation device is used to estimate the life of the component parts of the wind power generation device and output maintenance information. On the other hand, Patent Document 2 discloses a method that installs a microwave or radar wave transmitter generally called Doppler Lidar in the nacelle or hub of a wind power generation device, which is opposed to the wind power. The wind speed distribution in front and behind the power generation device is measured, and the pitch angle of the blades is controlled in a way that maximizes the power generation efficiency or minimizes the load of the wind power generation device. [Prior Technical Documents] [Patent Documents]

[Patent Document 1] Japanese Patent Application Publication No. 2015-117682 [Patent Document 2] Japanese Patent Application Publication No. 2015-519516

[The problem to be solved by the invention]

However, in the configuration disclosed in Patent Document 1, since the power generation amount or pitch angle is controlled to be approximately a unique value with respect to the wind speed, it is difficult to accurately estimate the wind cut as the wind speed distribution based on the wind speed, power generation amount, and pitch angle. , Also worried about the impact on the life estimation accuracy of the component parts. In addition, in the configuration disclosed in Patent Document 2, although it is possible to accurately measure the wind speed distribution by Doppler Lidar, this type of measuring equipment is expensive, so it is necessary for all of the wind power plant (in the wind farm). The installation of such machines in wind power plants is not realistic in terms of cost.

Therefore, the present invention provides a wind power generation device and a wind power generation system capable of accurately estimating a wind cut as a wind speed distribution with a simple structure. [Technical means to solve the problem]

In order to solve the above-mentioned problems, the wind power generation device of the present invention is characterized by including: a wind power generation device having at least an impeller, a nacelle, and a tower that rotatably supports the nacelle; and a control device that controls the wind power generation device; and The control device is equipped with a wind condition estimating device, which has: a load measuring unit that measures the load attached to the wind power generation device; a memory unit that stores the wind shear function that defines the relationship between the load and the wind shear; and the wind speed distribution The calculation unit calculates the wind shear based on the load and the wind shear function. In addition, the wind power generation system of the present invention is characterized by having at least one wind power generation device, a control device for controlling the wind power generation device, an electronic terminal with a display device, and a communication network that connects them in a way that can communicate with each other; And the control device is equipped with a wind condition estimating device, the wind condition estimating device having: a load measuring unit that measures the load attached to the wind power generation device; a memory unit that stores a wind shear function that defines the relationship between the load and the wind shear; and The wind speed distribution calculation unit calculates the wind shear based on the above-mentioned load and wind shear function. In addition, another wind power generation system of the present invention is characterized by having at least one wind power generation device, a control device for controlling the wind power generation device, an electronic terminal with a display device, and a communication network that connects them in a way that can communicate with each other. And the control device has a load measuring unit that measures the load attached to the wind power generation device; the electronic terminal has a wind condition estimating device, the wind condition estimating device has: a memory unit that stores the wind defining the relationship between the load and the wind shear Tangent function; and a wind speed distribution calculation unit, which calculates the wind shear based on the load input from the load measuring unit via the communication network and the wind shear function stored in the memory unit. [Effects of Invention]

According to the present invention, there is provided a wind power generation device and a wind power generation system capable of accurately estimating a wind cut as a wind speed distribution with a simple configuration. The problems, constitutions, and effects other than those described above will be clarified by the description of the following embodiment.

Fig. 1 is an overall schematic configuration diagram of a wind power generation system according to an embodiment of the present invention. As shown in Figure 1, the wind power generation system 1 includes a wind power generation device 2 and an electronic terminal 4 or a server not shown in the operation management center 3, which are connected via a communication network 5 in a way that can communicate with each other. . Furthermore, the communication network 5 may be wired or wireless.

In addition, the wind power generator 2 includes a blade 24 that receives wind and rotates, a hub 23 that supports the blade 24, a nacelle 22, and a tower 21 that rotatably supports the nacelle 22. The nacelle 22 is provided with a main shaft 26 which is connected to the hub 23 and rotates with the hub 23; a speed increaser 27 which is connected to the main shaft 26 and increases the speed of rotation; and a generator 28 which increases the speed of the rotor by The engine 27 rotates at an increased speed to perform power generation operation. The part that transmits the rotational energy of the blade 24 to the generator 28 is called a power transmission part. In this embodiment, the main shaft 26 and the speed increaser 27 are included in the power transmission part. In addition, the speed increaser 27 and the generator 28 are held on the main frame 29. In addition, the blade 24 and the hub 23 constitute an impeller 25. As shown in Figure 1, the bottom (lower part) of the tower 21 is equipped with a power converter 30 that converts the frequency of power, a switch for switching current, a transformer, etc. (not shown), and a control device 31 and so on. As the control device 31, for example, a control panel or SCADA (Supervisory Control And Data Acquisition) is used.

In addition, the wind power generator 2 shown in FIG. 1 shows an example in which the impeller 25 is formed by three blades 24 and a hub 23, but it is not limited to this. The impeller 25 may also be formed by the hub 23 and at least one blade 24. Hereinafter, the embodiments of the present invention will be described using drawings. [Example 1]

Fig. 2 is a diagram showing the structure of a wind power generation device of Example 1 which is an embodiment of the present invention. In FIG. 2, the structure of the wind speed distribution 11 in the height direction of the wind power generator 2 and its surroundings of this embodiment is shown. In addition, in FIG. 2, the state where the wind power generator 2 is viewed from the side is shown, and the wind is assumed to be blowing from the left side to the right side of the paper. As shown in FIG. 2, the wind power generation device 2 includes: an impeller 25, which is formed by radially mounting blades 24 on a rotating hub 23; a nacelle 22, which allows the rotation of the impeller 25 and supports the hub 23 laterally; And the tower 21, which supports the nacelle 22 rotatably with respect to the vertical axis from the bottom. Regarding the wind power generation device 2, FIG. 2 shows a downwind type wind power generation device in which the impeller 25 is located on the wind side below the tower 21, but it can also be an upwind type wind power generation device in which the impeller 25 is located on the wind side above the tower 21 .

The wind power generation device 2 includes a strain sensor 7 installed on a tower 21. The strain sensor 7 is not limited to the tower 21, and can also be installed in the nacelle 22 or the hub 23. For example, other load sensors such as acceleration sensors can also be used instead of the strain sensor 7. In addition, the wind power generator 2 may also include a pitch angle control mechanism 6 for controlling the pitch angle of the blades 24, an anemometer 8 installed in the upper part of the nacelle 22, and a thermometer 9 and a barometer 10 installed in the nacelle 22. Furthermore, the anemometer 8, the thermometer 9, and the barometer 10 can also be installed in other positions of the wind power generation device 2. As long as they are near the wind power generation device 2, they can also be installed outside the wind power generation device 2. In addition, with regard to the thermometer 9 and the barometer 10, public observation data used for weather forecasting and the like may be used instead of measurement.

The wind speed distribution 11 usually changes along the height direction (Z direction), and generally has a tendency to increase the wind speed as it goes to the upper altitude according to the boundary layer of the atmosphere. The change in wind speed in the height direction (Z direction) is called wind shear. If the power index representing its strength is set as α _WS , the wind speed distribution in the height direction (Z direction) can be assumed as in the following formula (1).

[Number 1]

Here, V(z) is the wind speed at height z from the surface, z _ref represents the height defined as the reference wind speed, and V(z _ref ) represents the wind speed as the reference. As shown in Figure 3, the _{greater the power exponent α WS} becomes, the greater the change in wind speed due to altitude becomes. For example, when using the anemometer 8 to measure the wind speed as the reference, by using the measured wind speed as the V(z _ref ) of formula (1), and using the height of the anemometer 8 from the ground as the z _ref , and as long as Knowing a certain power exponent α _WS can obtain the wind speed distribution in the height direction. That is, when the wind speed distribution is assumed as in equation (1), the problem of estimating the wind speed distribution finally returns to the problem of estimating the power exponent α _WS . Furthermore, in this embodiment, the wind speed distribution of equation (1) is assumed, and the power exponent α _WS representing the strength of the wind shear is estimated. However, the assumption of wind speed distribution is not limited to equation (1), and logarithms or polynomials can also be used Etc., multiple parameters can also be used to assume the wind speed distribution.

FIG. 4 is a functional block diagram of the control device 31 constituting the wind power generation device 2 of this embodiment. As shown in Fig. 4, the control device 31 includes a wind speed measuring unit 12, a load measuring unit 13, a temperature measuring unit 14, a barometric pressure measuring unit 15, a memory unit 16 storing a wind shear function 33, an atmospheric density calculating unit 17, and wind shear estimation The section 18, the wind speed distribution calculation section 19, the input I/F 34, the output I/F 35, and the communication I/F 36 are connected in such a way that they can be mutually accessed using the internal bus 37. The wind speed measurement unit 12, the load measurement unit 13, the temperature measurement unit 14, the air pressure measurement unit 15, the memory unit 16 storing the wind shear function 33, the atmospheric density calculation unit 17, the wind shear estimation unit 18, and the wind speed distribution calculation unit 19 not only estimate _{The power exponent α WS} that defines the strength of the wind shear, and also obtains the actual wind speed distribution, constitutes the wind condition estimating device 32. Furthermore, if only the power exponent α _WS needs to be estimated, the wind speed measurement unit 12, the load measurement unit 13, the temperature measurement unit 14, the air pressure measurement unit 15, the storage unit 16 storing the wind shear function 33, and the atmospheric density calculation unit can also be used 17. The wind shear estimating unit 18 constitutes a wind condition estimating device 32. Furthermore, when a reduction in estimation accuracy is allowed and only the power exponent α _WS is estimated, it is also possible to use only the load measuring unit 13, the memory unit 16 storing the wind shear function 33, and the wind shear estimating unit 18 to form the wind condition estimating device 32 . The wind speed measuring unit 12, the load measuring unit 13, the temperature measuring unit 14, the air pressure measuring unit 15, the atmospheric density calculating unit 17, the wind shear estimating unit 18, and the wind speed distribution calculating unit 19 constituting the wind condition estimating device 32 are, for example, by The CPU (Central Processing Unit, central processing unit) and other processors shown in the figure, ROM (Read Only Memory) for storing various programs, RAM (Random Access Memory) for temporarily storing data in the calculation process ), an external memory device and other memory devices, and the CPU and other processors read and execute various programs stored in the ROM, and store the calculation result as the execution result in the RAM or external memory device. Hereinafter, the details of each part of the control device 31 will be described.

The wind speed measuring unit 12 calculates the time series data of wind speed and the average wind speed obtained by averaging at a specific time based on the wind speed measured by the anemometer 8 and input via the input I/F 34 and the internal bus 37. Then, the wind speed measurement unit 12 transmits the average wind speed to the wind cut estimating unit 18 via the internal busbar 37 and transmits the time series data of the wind speed to the wind speed distribution calculation unit 19. Furthermore, in the averaging process, for example, the average wind speed may be calculated every 10 minutes, or the average wind speed may be continuously output by using a moving average.

The load measuring part 13 inputs the strain of the tower 21 measured by the strain sensor 7 via the input I/F 34 and the internal bus 37, and multiplies the measured value of the strain of the input tower 21 by the measurement position The section factor is thereby converted into bending moment. Furthermore, the bending moment is subjected to averaging processing for a specific time, and is transmitted to the wind shear estimation unit 18 via the internal bus 37. When the wind direction at the construction location of the wind power generation device 2 is approximately one direction, the strain sensor 7 can be installed in one part, but when the wind direction changes, in order to calculate the wind power generation device 2 along the nacelle 22 The bending moment component of the falling direction of the tower 21 is preferably provided with strain sensors 7 at two or more locations at the same height of the tower 21. In addition, the position in the height direction where the strain sensor 7 is installed is ideally near the top of the tower 21, but since even if the top torque is not directly measured, it can be corrected based on the wind speed and the thrust coefficient of the impeller 25, so there is no need to measure The location is limited to the top.

The temperature measurement unit 14 inputs the temperature measured by the thermometer 10 through the input I/F 34 and the internal bus 37, and calculates the averaged temperature for a specific time. The temperature measurement unit 14 transmits the calculated averaged temperature to the atmospheric density calculation unit 17 via the internal busbar 37. The air pressure measurement unit 15 inputs the air pressure measured by the barometer 11 through the input I/F 34 and the internal bus 37, and calculates the averaged air pressure at a specific time. The air pressure measurement unit 15 transmits the calculated averaged air pressure to the atmospheric density calculation unit 17 via the internal busbar 37. The atmospheric density calculation unit 17 calculates the atmospheric density based on the temperature and the pressure and uses the gas state equation, for example, transmits the average value of the atmospheric density to the wind shear estimation unit 18 via the internal busbar 37 every 10 minutes. Furthermore, as long as the atmospheric density can be calculated, other methods can also be used.

The wind shear estimating unit 18 inputs the bending moment transmitted from the load measuring unit 13, the average wind speed transmitted from the wind speed measuring unit 12, and the average value of the atmospheric density transmitted from the atmospheric density calculating unit 17, and defines these The value of the wind shear function 33 is related to the power exponent α _WS representing the strength of the wind shear, and the estimated value of the _{power exponent α WS is output every specific time used for averaging.} In this embodiment, the average value of the bending moment, average wind speed, and atmospheric density is used as the input to the wind shear estimation unit 18. However, when the estimation accuracy of the _{power exponent α WS can be tolerated, the self-load} The bending moment transmitted by the measuring unit 13 is used as an input, and one of the bending moment, the average wind speed or the average value of the atmospheric density may also be used. Also, other physical quantities that change in accordance with the wind speed may be used instead of the average wind speed. For example, the amount of power generation or pitch angle, the number of revolutions of the impeller, etc. can be used.

The wind shear function 33 stored in the memory 16 stores a function that can uniquely output the power exponent α _WS with respect to the average value of the bending moment, average wind speed, and atmospheric density. The storage method of the function is not particularly limited. In addition to the response surface or neural network, it can also be a number such as a polynomial, or a data table formed by dividing each variable by a bin. The method of making the function is not particularly limited. For example, there is a method of temporarily installing Doppler Lidar on the upper part of the nacelle 22 that constitutes the wind power generation device 2, and the wind speed distribution measured by the least square method. Calculate the power exponent α _WS , and create the response surface with the _{design variable and the power exponent α WS} as the objective function for the average value of bending moment, average wind speed, and atmospheric density. As another method, numerical simulation can also be used to calculate _{the bending moment when the power exponent α WS} , the average wind speed, and the average value of the atmospheric density change, and the neural network can learn the calculation result to estimate the power exponent α _WS .

The wind speed distribution calculation unit 19 calculates based on _{the estimated value of the power exponent α WS} obtained in the wind shear estimation unit 18 and the time series data of the wind speed transmitted from the wind speed measurement unit 12 via the internal bus 37, using the above formula (1) to calculate Time series data of wind speed distribution. _{Furthermore, the height z ref of the} anemometer 8 from the ground surface is set to be known. The output I/F 35 outputs the time series data of the wind speed distribution calculated by the wind speed distribution calculation unit 19 and transmitted via the internal bus 37 to a display unit not shown. The communication I/F 36 sends the time series data of the wind speed distribution calculated by the wind speed distribution calculation unit 19 and transmitted via the internal bus 37 via the communication network 5 to the electronic terminal 4 set in the operation management center 3 or a servo not shown in the figure. Device.

Next, the principle of estimating the wind shear based on the wind condition estimating device 32 will be described. It is assumed that the wind speed flowing into the impeller 25 adopts a distribution like the above-mentioned equation (1) due to the wind shear. The aerodynamic force (thrust) T acting on the wind direction of the blade 24 can be expressed by equation (2).

[Number 2]

Here, b is the length of the blade 24, ρ is the atmospheric density, C _t is the local thrust coefficient of the blade 24 at a distance r from the center of the hub 23, and V is the distance between the blade 24 and the center of the hub 23 The local wind speed at a distance r, c is the chord length of the blade 24 at a distance r from the center of the hub 23. Among them, b and c are inherent values of the blade 24, and are fixed regardless of operating conditions. In addition, C _t is also a value inherent to the blade 24, but it changes according to the pitch angle, wind speed, and number of revolutions. Here, for the sake of simplicity, it is assumed that the wind speed has the distribution of the above formula (1) in the height direction but does not change with time, and the pitch angle and the number of rotations are fixed. In addition, it is assumed that the impeller 25 does not have an inclination angle or a taper angle and rotates in a vertical plane. At this time, since the angle of attack of the blade 24 increases as the wind speed increases within the range where the blade 24 does not stall, the C _t also increases monotonically. Therefore, as can be seen from the above equation (2), when the local wind speed V increases, as C _t V ² increases, the thrust T also increases.

It is currently known that if the atmospheric density and the wind speed at the center of the hub 23 are assumed to be constant, then z _ref in Figure 3 represents the height of the hub 23. As the power exponent α _WS increases, the wind speed above the hub 23 increases. The wind speed below 23 decreases. Therefore, as shown in FIG. 5, the thrust T also increases above the hub 23 and decreases below the hub 23 _{as the power exponent α WS increases.} Here, it can be seen that if the torque at the center of the hub 23 that causes the wind power generator 2 to fall along the direction of the nacelle 22 is considered, when the blade 24 is located at any position in the rotation plane, the torque increases with the power exponent α _WS It increases and monotonically increases. Therefore, the average value of the torque at the center of the hub 23 during one revolution of the impeller 25 also increases monotonously as shown in FIG. 6 _{as the power exponent α WS increases.} Therefore, when the atmospheric density and the wind speed at the center of the hub 23 are constant, the power exponent α _WS can be estimated from the moment at the center of the hub 23. Furthermore, the graph shown in FIG. 6 for explaining the relationship between the power exponent and the torque at the center of the hub is generated by simulating the model of an ordinary wind power generation device. In the actual wind power generation device 2, since the wind speed and the atmospheric density at the center of the hub 23 also change, the torque also increases monotonously by the increase (FIG. 7 and FIG. 8). Therefore, in order to estimate the power exponent α _WS with high accuracy, in addition to measuring the torque, it is also necessary to measure the wind speed and atmospheric density at a certain location. If you know the wind speed and the atmospheric density, you can select the relational expressions that are consistent with the wind speed and the atmospheric density from _{the plurality of torque-power exponent α WS relational expressions shown in Figs. 7 and 8, and the power exponent α WS can} be estimated from the torque. However, the change in the torque caused by the change in atmospheric density shown in Fig. 8 _{is relatively small compared to the change in the power exponent α WS and the wind speed shown in Fig. 7, so the power exponent α WS} can be estimated even if the atmospheric density is not used. In addition, in the case where the variation of wind speed is small or _{when the estimation accuracy of the power exponent α WS} can be tolerated, the wind speed and atmospheric density may not be used, and only the power exponent α _WS may be estimated from the torque.

Since it is actually difficult to measure the torque at the rotating hub 23, the following behaviors can be performed: substitute the torque at the tower 21 measured by the strain sensor 7; insert in the height direction of the tower 21 Calculate the torque at the center of the hub 23 from the moments measured at the two locations. Regarding the wind speed and atmospheric density, it is not necessary to use the value of the center of the hub 23, as long as it is measured in the vicinity of the wind power generator 2. In addition, although the pitch angle and the number of revolutions are assumed to be fixed, they are generally determined by the control corresponding to the wind speed. Therefore, when the power exponent α _WS is estimated using the wind speed, even if the pitch angle and the number of revolutions change, the estimation The impact of accuracy is also small. The inclination angle and the cone angle are inherent values of the wind power generator 2 and do not depend on the operating conditions, but are fixed, so they have no influence on the estimation accuracy.

Furthermore, in this embodiment, as shown in FIG. 4, the memory unit 16, the wind shear estimating unit 18, and the wind speed distribution calculating unit 19 that constitute the wind condition estimating device 32 and storing the wind shear function 33 are installed in the control device. The situation within 31 is explained as an example, but it is not limited to this. For example, it may be configured as follows, that is, the storage unit 16, the wind shear estimation unit 18, and the wind speed distribution calculation unit 19 storing the wind shear function 33 are installed in the operation management center 3 shown in FIG. 1 In the electronic terminal 4 or the server not shown in the figure.

As described above, according to the present embodiment, it is possible to provide a wind power generation device and a wind power generation system capable of accurately estimating a wind cut as a wind speed distribution with a simple configuration. [Example 2]

FIG. 9 is a functional block diagram of the control device 31a of the wind power generation device of Embodiment 2 constituting another embodiment of the present invention. The difference between this embodiment and the first embodiment is that the reliability evaluation device 40 is provided in the control device, and the reliability evaluation device 40 uses the wind shear estimating part 18 and the wind speed distribution calculation part shown in the first embodiment. 19 estimated wind shears are used to evaluate the reliability of the wind power generation device 2. The same reference numerals are given to the same constituent elements as those of the first embodiment, and the overlapping description with the first embodiment is omitted below. Furthermore, for convenience of explanation, as shown in FIG. 9, only the input I/F 34, the wind shear estimation unit 18, the output I/F 35, the communication I/F 36, and the internal bus 37 are shown as the same configuration as the first embodiment. Elements.

As shown in FIG. 9, the control device 31a of this embodiment includes an input I/F 34, a wind shear estimation unit 18, an output I/F 35, a communication I/F 36, an operating condition acquisition unit 41, a load calculation unit 42, and a storage design The storage unit 16a, the reliability evaluation unit 44, and the information output unit 45 of the information 43 are connected in such a way that they can be mutually accessed using the internal bus 37. The operating condition acquisition unit 41, the load calculation unit 42, the memory unit 16 a storing the design information 43, the reliability evaluation unit 44, and the information output unit 45 constitute the reliability evaluation device 40. Furthermore, the reliability evaluation device 40 may also be configured to not have the information output unit 45. The wind shear estimation unit 18, the operating condition acquisition unit 41, the load calculation unit 42, the reliability evaluation unit 44, and the information output unit 45 are, for example, a processor such as a CPU (Central Processing Unit) not shown, and a ROM storing various programs. , It is realized by RAM, external memory device and other memory devices that temporarily store the data of the calculation process, and the CPU and other processors read and execute various programs stored in the ROM, and store the calculation result as the execution result in RAM or external In the memory device.

Hereinafter, the reliability evaluation device 40 will be described by taking the reliability evaluation of the blade 24 of the wind turbine generator 2 as an example. Furthermore, the application object of the reliability evaluation device 40 does not need to be limited to the blade 24, as long as it is a part where the wind shear affects the reliability, it can also be other components of the wind power generation device 2, such as the nacelle 22 or the tower 21.

The operating condition acquiring unit 41 acquires time history data of the operating conditions of the wind power generator 2 related to the load acting on the blade 24. The operating conditions include, for example, the wind speed or direction at the anemometer 8, the pitch or azimuth angle of the blade 24, the rotation speed of the impeller 25, the azimuth angle of the nacelle 22, and the power generation of the wind power generator 2 and so on. When a load sensor such as a strain sensor or an acceleration sensor is installed in the wind power generation device 2, the time history data thereof may also be included. In addition, when SCADA is used as the control device 31a, for example, the operating conditions may be obtained from the SCADA.

The load calculation unit 42 uses the operating conditions sent from the operating condition acquisition unit 41, the power exponent α _WS sent from the wind shear estimation unit 18, and the design information 43 of the blade 24 to calculate the time history of the load acting on the blade 24. As a method of calculating the load, for example, there is a method of _{calculating the wind speed distribution (wind cut) flowing into the impeller 25 based on the wind speed at the anemometer 8 and the power exponent α WS} using the above formula (1), and the wind speed distribution and operation The conditional time history data is used as input for aeroelastic simulation based on Blade Element Momentum Theory or Multibody Dynamics. The design information 43 stored in the memory 16a is, for example, the size or mass distribution of the blade 24 and the tower 21, the rigidity distribution, the aerodynamic coefficient, the inclination or cone angle of the impeller 25, the size or mass distribution of the nacelle 22, the aerodynamic coefficient, Design data such as the control program of the wind power generation device 2. Furthermore, the design information 25 stored in the memory 16a includes data related to the reliability of the constituent parts of the blade 24 as reliability information, such as the dimensions of the constituent parts, modulus of elasticity, section coefficient, stress concentration factor, SN Line diagram (stress endurance diagram, stress repetition diagram), etc.

The reliability evaluation unit 44 uses the time history of the load acting on the blade 24 and the above-mentioned reliability information output from the load calculation unit 42 to perform reliability evaluation of the components of the blade 24. As a reliability evaluation, calculation of fatigue damage degree, remaining life, and failure probability of constituent parts is performed. For example, when calculating the fatigue damage degree based on the time history data of the load, there are the following methods. First, the time history of the stress acting on the component parts is calculated based on the load acting on the blade 24. Secondly, apply the rain flow method to the stress time history data and convert it into the frequency distribution of the stress amplitude. According to the frequency distribution of the stress amplitude obtained and the SN line diagram of the material of the component stored in the reliability information, use Line cumulative damage law to calculate the fatigue damage degree in the time history.

The information output unit 45 displays the evaluation results sent from the reliability evaluation unit 44 via the internal bus 37 in the form of a table, a graph, or a contour map. Furthermore, the data output from the operating condition acquisition unit 41, the wind shear estimation unit 18, and the load calculation unit 42 may also be displayed. For example, the wind speed of the anemometer 8 output from the operating condition acquiring unit 41 and the power exponent α _WS output from the wind shear estimating unit 18 may be used to express the wind speed distribution flowing into the impeller 25 by the above formula (1). Furthermore, this embodiment is configured as a configuration in which the reliability evaluation device 40 is installed in the control device 31a, but it is not limited to this, and it can also be installed as an electronic device installed in the operation management center 3 shown in FIG. Configuration in terminal 4 or server not shown.

As described above, according to this embodiment, in addition to the effects of Embodiment 1, the reliability evaluation device 40 can also be used to estimate the wind power based on the operating conditions of the wind power generation device and the load of the wind power generation device. All time history data is used to evaluate the reliability of wind power generation equipment. [Example 3]

FIG. 10 is a functional block diagram of the control device 31b of the wind power generation device of Embodiment 3 constituting another embodiment of the present invention. This embodiment is different from Embodiment 1 in that the wind shear estimated by the wind shear estimation unit 18 and the wind speed distribution calculation unit 19 shown in Embodiment 1 is used to control the wind power generator 2. The same reference numerals are given to the same constituent elements as those of the first embodiment, and the overlapping description with the first embodiment is omitted below. Furthermore, for the convenience of description, as shown in FIG. 10, only the input I/F 34, the wind shear estimation unit 18, the output I/F 35, the communication I/F 36, and the internal bus 37 are shown as the same configuration as the first embodiment. Elements.

As shown in FIG. 10, the control device 31b of this embodiment includes an input I/F 34, a wind shear estimation unit 18, an output I/F 35, a communication I/F 36, an operating condition acquisition unit 41, a control amount calculation unit 51, and storage The memory portion 16b of the control information 52 is connected in such a way that they can be accessed mutually using the internal bus 37. The wind shear estimation unit 18, the operating condition acquisition unit 41, and the control amount calculation unit 51 are implemented by, for example, a processor such as a CPU (Central Processing Unit) (not shown), a ROM that stores various programs, a RAM that temporarily stores data of the calculation process, It is realized by a memory device such as an external memory device, and a processor such as a CPU reads and executes various programs stored in the ROM, and stores the calculation result as the execution result in a RAM or an external memory device.

The operating condition acquisition unit 41 acquires the operating conditions of the wind turbine generator 2 in the same manner as in the above-mentioned second embodiment. The control amount calculation unit 51 uses the operating conditions transmitted from the operating condition acquisition unit 41 via the internal bus 37, the power exponent α _WS transmitted from the wind shear estimation unit 18 via the internal bus 37, and the control information 52, for example, to determine the pitch of the blade 24 The angle or the rotation speed of the impeller 25, etc., and the control amount is determined in such a way as to achieve them. The pitch angle of the blade 24 or the rotation speed of the impeller 25 can be determined, for example, by maximizing the power generation and minimizing the load variation of the blade 24. Furthermore, the pitch angle may also be changed during one rotation of the impeller 25. This kind of control can be realized by the following way, that is, according to the wind speed at the anemometer 8 and the power exponent α _{WS, the} above formula (1) is used to calculate the wind speed distribution flowing into the impeller 4, and the inflow is estimated with high accuracy relative to any impeller speed. The distribution of wind speed and wind direction to blade 24. The memory 16b stores constants used for control or the aerodynamic characteristics of the blade 24 as the control information 52. The above-mentioned control variable output from the control variable calculation unit 51 is output to the generator 28 or the pitch angle control mechanism 6 and the like via the internal bus 37 and the output I/F 35.

As mentioned above, according to this embodiment, in addition to the effect of embodiment 1, the wind power generation device can also be controlled based on the operating conditions of the wind power generation device and the time history data of the wind shear estimated from the load of the wind power generation device. , And realize the maximization of the power generation or the minimization of the load change of the blades. [Example 4]

Fig. 11 is a diagram showing the structure of a wind power generator according to a fourth embodiment of another embodiment of the present invention. The difference between this embodiment and the first embodiment is that the wind power condition estimating device 32 of the wind power generation device 2 of the first embodiment is used to estimate the wind shear in the horizontal direction. The same reference numerals are given to the same constituent elements as those of the first embodiment, and the overlapping description with the first embodiment is omitted below.

In FIG. 11, the structure of the wind speed distribution 61 in the horizontal direction of the wind power generator 2 and its surroundings is shown. In FIG. 11, the state where the wind power generator 2 is viewed from above is shown, and the wind is assumed to be blowing from the left side to the right side of the paper. In addition, the wind turbine generator 2 has the same configuration as that of the first embodiment described above.

The wind speed distribution 61 in the horizontal direction shown in FIG. 11 changes in the horizontal direction. If the coefficient representing the strength of the wind shear in the horizontal direction is set as β _WS , the wind speed distribution 61 in the horizontal direction can be assumed as in the following equation (3).

[Number 3]

Here, V(y) is the wind speed at the position y in the direction orthogonal to the wind speed vector on the horizontal plane, y _ref represents the position defined as the reference wind speed, and V(y _ref ) represents the wind speed as the reference. As can be seen from equation (3), the _{larger the coefficient β WS} becomes, the larger the change in the wind speed in the horizontal direction becomes. For example, in the case of using an anemometer 8 to measure the wind speed as the reference, by setting V(y _ref ) of formula (3) to the measured wind speed, setting y _ref to 0 (origin), and using y The distance in the y-axis direction from the anemometer 8 in Fig. 11, and the wind speed distribution 61 in the horizontal direction can be obtained _{as long as a certain coefficient β WS is known.} That is, when the wind speed distribution is assumed as in equation (3), the problem of estimating the wind speed distribution eventually returns to the problem of estimating the coefficient β _WS . _{Furthermore, in this embodiment, the coefficient β WS} representing the strength of the wind shear in the horizontal direction is estimated by considering the wind speed distribution of the assumed equation (3), but the assumption of the wind speed distribution does not need to be limited to equation (3), and multiple Parameters to assume the wind speed distribution.

The structure of the wind condition estimating device 32 of the wind power generation device 2 in this embodiment for _{estimating the coefficient β WS} that defines the strength of the wind shear in the horizontal direction is the same as that of the first embodiment. Hereinafter, the details of the wind force condition estimating device 32 will be described differently from the first embodiment. In this embodiment, in the load measuring part 13 (not shown), the strain sensor 7 is used to measure the shear strain of the tower 21, and the surface active moment of inertia at the measurement position and the radius of the tower 21 are used to measure the shear strain of the tower 21. Converted into torque. Furthermore, the torque is subjected to averaging processing for a specific time and output. The torque acts evenly in the cross-section of the tower 21, so the strain sensor 7 can also be arranged in one position, and the position in the height direction does not need to be particularly limited.

In the wind shear estimating part 18 (not shown), by inputting the average value of torque, wind speed, and atmospheric density, the relationship between these _{values and the coefficient β WS representing the strength of the wind shear in the horizontal direction is used.} The wind shear function 33 outputs the estimated value of the _{coefficient β WS every specific time used for averaging.} In this embodiment, torque, wind speed, and atmospheric density are used as the input to the wind shear estimating unit 18. However, when _{the estimation accuracy of the allowable coefficient β WS} is reduced, only the torque may be used as the input, or the torque may be used. Moment, wind speed or atmospheric density. In addition, other physical quantities that change in accordance with the wind speed may be used instead of the wind speed. For example, power generation, pitch angle, impeller revolution, etc. can be used. Furthermore, since the torque is also generated due to the deviation of the nacelle 22 called the yaw error from the wind direction, by adding the yaw error to the input of the wind shear estimating unit 18, high accuracy can be achieved.

The wind shear function 33 is defined as a function that can uniquely output the coefficient β _WS with respect to the input values of torque, wind speed, and atmospheric density. The storage method and production method of the function are not particularly limited, and the same method as the above-mentioned embodiment 1 can be used. In the wind speed distribution calculation unit 19, based on _{the estimated value of the coefficient β WS} obtained in the wind shear estimation unit 18 and the time series data of the wind speed obtained in the wind speed measurement unit 12, the above formula (3) is used to calculate the wind speed distribution Time series data.

The principle of estimating the wind shear in the horizontal direction based on the wind condition estimating device 32 is the same as that of the first embodiment except for the following points. That is, the moment acting on the center of the hub 23 by the wind shear in the horizontal direction is generated in the direction that causes the nacelle 22 to rotate in the horizontal plane. Therefore, the torque acts on the tower 21, so it is necessary to measure the torque for estimating the _{coefficient β WS.} Furthermore, by simultaneously measuring the bending moment and torque of the tower 21, and simultaneously estimating the wind shear in the height direction (Z direction) and the horizontal direction (y direction) of Example 1 and Example 4, it is also possible to measure the bending moment and torque of the tower 21 at the same time. The estimated wind shear in the horizontal direction is used as the input of the reliability evaluation device 40 of the second embodiment and the control device 31b of the third embodiment.

As described above, according to this embodiment, by measuring the load of the wind power generator, the wind shear in the horizontal direction can be estimated with high accuracy with a simple structure. [Example 5]

Fig. 12 is a diagram showing the structure of a wind power generator according to a fifth embodiment of another embodiment of the present invention. The difference between this embodiment and the first embodiment is that the strain sensor 7 installed on the tower 21 shown in the above-mentioned embodiment 1 is installed on the blade 24. The same reference numerals are given to the same constituent elements as those of the first embodiment, and the overlapping description with the first embodiment is omitted below.

Fig. 12 shows the structure of the wind power generation device 2 of this embodiment and the wind speed distribution 11 in the height direction around it. In FIG. 12, the state where the wind power generator 2 is viewed from the side is shown, and the wind is assumed to be blowing from the left side to the right side of the paper. The wind power generator 2 has the same configuration as that of the first embodiment, and also has a strain sensor 7 on the blade 24 instead of on the tower 21. The strain sensor 7 only needs to be installed on at least one blade 24 constituting the impeller 25, and other load sensors such as an acceleration sensor can also be used instead of the strain sensor 7.

The structure of the wind condition estimating device 32 of the wind power generation device 2 of the present embodiment for _{estimating the power index α WS} that defines the strength of the wind shear is the same as that of the first embodiment. Hereinafter, the details of the wind force condition estimating device 32 will be described differently from the first embodiment. In this embodiment, in the load measuring part 13, the strain sensor 7 is used to measure the strain of the blade 24 and multiply it by the profile factor at the measurement position, thereby converting it into a bending moment. Furthermore, statistical processing is performed on the bending moment and the statistical value is output. As the statistical value, for example, the standard deviation of the bending moment at a specific time, or the difference between the maximum value and the minimum value (maximum amplitude), etc. are used. In addition, it is also possible to divide the azimuth angle by divisions and use the average value of each division. It is also possible to install strain sensors 7 on all the blades 24 constituting the impeller 25, and obtain the calculation based on the bending moment of each blade 24. The torque at the center of the hub 23 is obtained, and the calculated value is used. The strain sensor 7 can be installed in one location, but in order to calculate the moment component that causes the blade 24 to bend in the wind direction, it is better to install the strain sensor 7 at two or more locations at the same position in the length direction of the blade 24 . In addition, the strain sensor 7 is preferably installed near the root of the blade 24, but there is no need to limit the measurement position to the vicinity of the root of the blade.

The wind shear estimating unit 18 takes the statistics of the bending moment of the blade 24, the average value of the wind speed, and the atmospheric density as input, and uses the wind shear function 33 that relates these _{values to the power index α WS representing the strength of the wind shear.} , And output the estimated value of the _{power exponent α WS at regular intervals.} In this embodiment, the bending moment, wind speed, and atmospheric density are used as the input to the wind shear estimating unit 18. However, when _{the estimation accuracy of the power exponent α WS} can be tolerated, the bending moment can also be used as the input. One of bending moment, wind speed or atmospheric density can be used. In addition, other physical quantities that change in accordance with the wind speed may be used instead of the wind speed. For example, power generation, pitch angle, impeller revolution, etc. can be used.

The principle of estimating the wind shear based on the wind condition estimating device 32 is the same as that of the first embodiment except for the following points. That is, the thrust acting on the blade 24 by the wind shear changes according to the azimuth angle as shown in FIG. 5, and therefore the bending moment measured by the strain sensor 7 also changes according to the azimuth angle. Therefore, by using the standard deviation or the maximum amplitude to express the variation range of the bending moment acting on the blade 24 during one revolution of the impeller 25, the power exponent α _WS can be estimated. Moreover, even if the variation range of the bending moment under one rotation is not used, the power exponent α _{WS can} be estimated based on the value of the bending moment under a certain azimuth angle. For example, as shown in FIG. 5, when the blade 24 is located directly above the hub 23, the bending moment or thrust _{increases monotonically with the increase of the power index α WS , so the power index α WS} can be estimated based on this value. Furthermore, when the strain sensor 7 is installed on all the blades 24 constituting the impeller 25, and the moment at the center of the hub 23 is obtained by calculation based on the bending moment of each blade 24, the same can be used with the embodiment 1 The same principle is used to estimate wind shear.

Furthermore, if the bending moment when the blade 24 becomes horizontal is used, the wind shear in the horizontal direction can be estimated, and the wind shear in the height direction and the horizontal direction can also be estimated at the same time. In addition, the estimated wind shear can also be used as the input of the reliability evaluation device 40 of the second embodiment and the control device 31b of the third embodiment.

As described above, according to this embodiment, it is also possible to estimate the wind shear with a simple structure with high accuracy by measuring the load of the wind power generator.

Furthermore, the present invention is not limited to the embodiments described above, and includes various modifications. For example, the above-mentioned embodiments are explained in detail in order to easily understand the present invention, and are not necessarily limited to those having all the constitutions explained. In addition, a part of the configuration of a certain embodiment may be replaced with a configuration of another embodiment, and the configuration of another embodiment may be added to the configuration of a certain embodiment.

1‧‧‧Wind power generation system2‧‧‧Wind power generation device3‧‧‧Operation management center4‧‧‧Electronic terminal5‧‧‧Communication network6‧‧‧Pitch angle control mechanism7‧‧‧Strain sensor 8 ‧‧‧Anemometer 9‧‧‧Temperature 10‧‧‧Barometer 11‧‧‧Wind speed distribution 12‧‧‧Wind speed measuring part 13‧‧‧Load measuring part 14‧‧‧Temperature measuring part 15‧‧‧Air pressure measuring part 16‧‧‧Memory part 16a‧‧‧Memory part 16b‧‧‧Memory part 17‧‧‧Atmospheric density calculation part 18‧‧‧Wind shear estimation part 19‧‧‧Wind speed distribution calculation part 21‧‧‧Tower 22‧ ‧‧Engine room 23‧‧‧Wheel 24‧‧‧Blade 25‧‧‧Impeller 26‧‧‧Main shaft 27‧‧‧Speed increaser 28‧‧‧Generator 29‧‧‧Main frame 30‧‧‧Power converter 31 ‧‧‧Control device 31a‧‧‧Control device 31b‧‧‧Control device 32‧‧‧Wind condition estimation device 33‧‧‧Wind shear function 34‧‧‧Input I/F35‧‧‧Output I/F36‧‧‧ Communication I/F37‧‧‧Internal bus 40‧‧‧Reliability evaluation device 41‧‧‧Operating condition acquisition unit 42‧‧‧Load calculation unit 43‧‧‧Design information 44‧‧‧Reliability evaluation unit 45‧‧ ‧Information output unit 51‧‧‧Control amount calculation unit 52‧‧‧Control information 61‧‧‧Horizontal wind speed distribution T‧‧‧Aerodynamic force (thrust) y‧‧‧Horizontal direction z‧‧‧Height direction

Fig. 1 is an overall schematic configuration diagram of a wind power generation system according to an embodiment of the present invention. Fig. 2 is a diagram showing the structure of a wind power generation device of Example 1 which is an embodiment of the present invention. FIG. 3 is a diagram for explaining the wind cut in Example 1. FIG. Fig. 4 is a functional block diagram of the control device constituting the wind power generation device of the first embodiment. Fig. 5 is a diagram for explaining the principle of the wind condition estimating device constituting the control device shown in Fig. 4. Figure 6 is a diagram used to illustrate the relationship between the power exponent and the moment at the center of the hub. Figure 7 is a diagram used to illustrate the influence of wind speed in the relationship between the power exponent and the torque at the center of the hub. Figure 8 is a diagram used to illustrate the influence of air density in the relationship between the power exponent and the torque at the center of the hub. Fig. 9 is a functional block diagram of the control device of the wind power generation device of embodiment 2 constituting another embodiment of the present invention. Fig. 10 is a functional block diagram of the control device of the wind power generation device of embodiment 3 constituting another embodiment of the present invention. Fig. 11 is a diagram showing the structure of a wind power generator according to a fourth embodiment of another embodiment of the present invention. Fig. 12 is a diagram showing the structure of a wind power generator according to a fifth embodiment of another embodiment of the present invention.

5‧‧‧Communication network

7‧‧‧Strain sensor

8‧‧‧Anemometer

9‧‧‧Thermometer

10‧‧‧Barometer

12‧‧‧Wind Speed Measurement Department

13‧‧‧Load Measurement Department

14‧‧‧Temperature Measurement Department

15‧‧‧Barometric pressure measurement department

16‧‧‧Memory Department

17‧‧‧Atmospheric Density Calculation Department

18‧‧‧Wind Shear Estimation Department

19‧‧‧Wind speed distribution calculation department

31‧‧‧Control device

32‧‧‧Wind condition estimation device

33‧‧‧Wind shear function

34‧‧‧Input I/F

35‧‧‧Output I/F

36‧‧‧Communication I/F

37‧‧‧Internal bus

Claims (15)

A wind power generation device, characterized in that it has at least an impeller, a nacelle, and a tower that rotatably supports the nacelle; and includes: a control device that controls the wind power generation device; and the control device includes a wind condition estimating device The wind condition estimating device has: a wind speed measurement unit that calculates the average wind speed; a load measurement unit that measures the load attached to the wind power generation device; a memory unit that stores the wind shear function that defines the relationship between the load and the wind shear; And a wind shear estimation unit that calculates the wind shear based on the average wind speed, the load, and the wind shear function. The wind power generation device of claim 1, wherein the wind shear estimating unit calculates the wind shear as the wind speed distribution in the height direction based on the wind shear function stored in the memory unit and the load input from the load measuring unit. The wind power generation device of claim 1, wherein the wind shear estimating unit calculates the wind shear as the wind speed distribution in the horizontal direction based on the wind shear function stored in the memory unit and the load input from the load measuring unit. The wind power generation device of claim 2, wherein the control device has a reliability evaluation device that uses the wind cut as the wind speed distribution in the height direction to evaluate the reliability of the wind power generation device. The wind power generation device of claim 2 or 3, wherein the load measuring unit measures the load attached to the tower. The wind power generation device of claim 2 or 3, wherein the load measuring unit measures strain or acceleration as a load added to the wind power generation device. A wind power generation system, which is characterized by having at least one wind power generation device, a control device for controlling the wind power generation device, an electronic terminal with a display device, and a communication network connecting them in a mutually communicable manner; and the above-mentioned control The device is equipped with a wind condition estimating device, which has: a wind speed measuring unit that calculates the average wind speed; a load measuring unit that measures the load added to the wind power generation device; a memory unit that stores the definition of the load and wind cut The wind shear function of the relationship; and the wind shear estimation part, which calculates the wind shear based on the above average wind speed, the above load and the wind shear function. Such as the wind power generation system of claim 7, wherein the wind shear estimation unit calculates the wind speed distribution in the height direction based on the wind shear function stored in the memory unit and the load input from the load measuring unit via the communication network Wind cut. Such as the wind power generation system of claim 7, where The wind shear estimating unit calculates the wind shear as the wind speed distribution in the horizontal direction based on the wind shear function stored in the memory unit and the load input from the load measuring unit via the communication network. The wind power generation system of claim 8, wherein the control device has a reliability evaluation device, and the reliability evaluation device uses the wind cut as the wind speed distribution in the height direction to evaluate the reliability of the wind power generation device. The wind power generation system of claim 8 or 9, wherein the load measurement unit measures the load attached to the tower of the wind power generation device. The wind power generation system of claim 8 or 9, wherein the load measuring unit measures strain or acceleration as a load added to the wind power generation device. A wind power generation system, which is characterized by having at least one wind power generation device, a control device for controlling the wind power generation device, an electronic terminal with a display device, and a communication network connecting them in a mutually communicable manner; and the above-mentioned control The device has: a wind speed measurement unit that calculates the average wind speed and a load measurement unit that measures the load attached to the wind power generation device; the electronic terminal is equipped with a wind condition estimating device, and the wind condition estimation device has a memory unit that stores the defined load and wind The wind shear function of the relation of the wind shear; and the wind shear estimation part, its basis The wind shear is calculated from the average wind speed input from the wind speed measuring unit via the communication network, the load input from the load measuring unit, and the wind shear function stored in the memory unit. Such as the wind power generation system of claim 13, wherein the wind shear estimation unit calculates the wind speed distribution in the height direction based on the wind shear function stored in the memory unit and the load input from the load measurement unit via the communication network Wind cut. Such as the wind power generation system of claim 13, wherein the wind shear estimating unit calculates the wind speed distribution in the horizontal direction based on the wind shear function stored in the memory unit and the load input from the load measuring unit via the communication network Wind cut.

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