JP7009237B2 - Wind power generation equipment and wind power generation system - Google Patents

Description

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

The growing interest in renewable energy utilization is expected to expand the global market for wind power plants. Megawatt-class wind power generators are equipped with a rotor that is radially attached to a hub that rotates blades, a nacelle that supports the rotor via a spindle, and a tower that allows and supports yaw rotation from below. Is frequently used.
Wind power generators generate electricity using the ever-changing wind as an energy source. Therefore, if the wind speed or turbulence of the wind that actually flows into the wind power generation device is stricter than the design conditions, the load on the wind power generation device may increase and the damage to the components may be accelerated. If an unexpected failure occurs due to accelerated damage, it will take time to arrange replacement parts, construction equipment, and workers in addition to the time required to replace the failed parts, so planned parts replacement There is a concern that the downtime of the wind power generation equipment will increase and the amount of power generation will decrease compared to the case of implementing.
As a countermeasure, there are a method of estimating damage to the components of the wind power generation device by estimating and measuring the inflow wind as an energy source, and a method of controlling so as to reduce the load. For example, in Patent Document 1, a table that associates the wind speed, the amount of power generation, or the pitch angle created in advance from the data of the wind speed, the amount of power generation, or the pitch angle of the blade, which can be obtained with a simple device configuration, with the wind condition parameter. A device that estimates the life of the components of the wind power generation device and outputs maintenance information using a table that associates the wind condition parameters with the fatigue load applied to the wind power generation device has been proposed.
On the other hand, in Patent Document 2, a microwave or radar wave launcher generally called a Doppler lidar is attached to a nacelle or hub of a wind power generation device, and the wind speed distribution in front of and behind the wind power generation device is measured to improve power generation efficiency. Methods have been proposed to control the pitch angle of the blades to maximize or minimize the load on the wind turbine.

JP-A-2015-117682 Japanese Patent Application Laid-Open No. 2015-591516

However, in the configuration disclosed in Patent Document 1, since the power generation amount and the pitch angle are controlled so as to be substantially unique values with respect to the wind speed, the wind shear which is the wind speed distribution from the wind speed, the power generation amount, and the pitch angle is obtained. It is difficult to estimate with high accuracy, and there is concern about the influence on the life estimation accuracy of components. Further, in the configuration disclosed in Patent Document 2, although the wind speed distribution can be accurately measured by the Doppler lidar, such a measuring device is expensive, so that it can be used for all wind power generation devices in a wind power plant (in a wind farm). Installation 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 estimating wind shear, which is a wind speed distribution, with high accuracy with a simple configuration.

In order to solve the above problems, the wind power generation device according to the present invention includes at least a wind power generation device having a rotor, a nacelle, and a tower that rotatably supports the nacelle, and a control device for controlling the wind power generation device. The control device has a load measuring unit that measures the load applied to the wind power generator, a storage unit that stores the wind shear function that defines the relationship between the load and the wind shear, and a gas state equation from temperature and pressure. A wind condition having an air density calculation unit that calculates the air density using the wind shear and obtains the average value of the air density, and a wind speed distribution calculation unit that calculates the wind shear based on the load, the average value of the air density, and the wind shear function. It is characterized by being provided with an estimation device.
Further, the wind power generation system according to the present invention includes at least one wind power generation device, a control device for controlling the wind power generation device, an electronic terminal having a display device, and a communication network connecting these to each other so as to be communicable. The control device includes a load measuring unit that measures the load applied to the wind power generator, a storage unit that stores a wind shear function that defines the relationship between the load and the wind shear, and a gas from temperature and pressure. An air density calculation unit that calculates the air density using the state equation and obtains the average value of the air density, and a wind speed distribution calculation unit that calculates the wind shear based on the load, the average value of the air density, and the wind shear function. It is characterized by being provided with a wind condition estimation device.
Further, another wind power generation system according to the present invention is a communication that connects at least one wind power generation device, a control device for controlling the wind power generation device, and an electronic terminal having a display device so as to be communicable with each other. Equipped with a network, the control device has a load measuring unit that measures the load applied to the wind power generator , and the atmosphere that calculates the air density from the temperature and pressure using the gas state equation and obtains the average value of the air density. The electronic terminal has a density calculation unit, a storage unit for storing a wind shear function that defines a relationship between a load and a wind power, and the load input from the load measurement unit via the communication network. A wind condition estimation device including an average value of the air density input from the air density calculation unit and a wind speed distribution calculation unit for calculating wind power based on the wind shear function stored in the storage unit. And.

According to the present invention, it is possible to provide a wind power generation device and a wind power generation system capable of estimating wind shear, which is a wind speed distribution, with high accuracy with a simple configuration.
Issues, configurations and effects other than those described above will be clarified by the following description of the embodiments.

It is an overall schematic block diagram of the wind power generation system which concerns on one Embodiment of this invention. It is a figure which shows the structure of the wind power generation apparatus of Example 1 which concerns on one Example of this invention. It is a figure for demonstrating the wind shear in Example 1. FIG. It is a functional block diagram of the control device which constitutes the wind power generation device of Example 1. FIG. It is a figure for demonstrating the principle of the wind condition estimation apparatus which constitutes the control apparatus shown in FIG. It is a figure for demonstrating the relationship between the exponentiation and the moment at the center of a hub. It is a figure for demonstrating the influence of the wind speed on the relationship between the exponent and the moment at the center of the hub. It is a figure for demonstrating the influence of the air density on the relationship between the exponent and the moment at the center of the hub. It is a functional block diagram of the control device which constitutes the wind power generation device of Example 2 which concerns on another Example of this invention. It is a functional block diagram of the control device which constitutes the wind power generation device of Example 3 which concerns on another Example of this invention. It is a figure which shows the structure of the wind power generation apparatus of Example 4 which concerns on another Example of this invention. It is a figure which shows the structure of the wind power generation apparatus of Example 5 which concerns on another Example of this invention.

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 FIG. 1, the wind power generation system 1 includes a wind power generation device 2 and an electronic terminal 4 or a server (not shown) installed in an operation management center 3, which enable a communication network 5 to communicate with each other. Connected via. The communication network 5 may be wired or wireless.

Further, the wind power generation device 2 includes a blade 24 that rotates in response to wind, a hub 23 that supports the blade 24, a nacelle 22, and a tower 21 that rotatably supports the nacelle 22. In the nacelle 22, a spindle 26 connected to the hub 23 and rotating together with the hub 23, a speed increasing machine 27 connected to the spindle 26 to increase the rotation speed, and a rotor at a rotation speed increased by the speed increasing machine 27. It is equipped with a generator 28 that is rotated to generate power. The portion that transmits the rotational energy of the blade 24 to the generator 28 is referred to as a power transmission unit, and in the present embodiment, the main shaft 26 and the speed increaser 27 are included in the power transmission unit. The speed increaser 27 and the generator 28 are held on the main frame 29. Further, the rotor 25 is composed of the blade 24 and the hub 23. As shown in FIG. 1, at the bottom (lower part) in the tower 21, a power converter 30 that converts the frequency of electric power, a switch and a transformer for switching that switches and switches current (not shown), and a control are provided. The device 31 and the like are arranged. As the control device 31, for example, a control panel or SCADA (Supervision Control And Data Acquisition) is used.

The wind power generation device 2 shown in FIG. 1 shows an example in which the rotor 25 is composed of three blades 24 and a hub 23, but the rotor 25 is not limited to this, and the rotor 25 includes a hub 23 and at least one blade 24. May be configured.
Hereinafter, examples of the present invention will be described with reference to the drawings.

FIG. 2 is a diagram showing a configuration of a wind power generation device according to a first embodiment of the present invention. FIG. 2 shows the configuration of the wind power generation device 2 according to the present embodiment and the wind speed distribution 11 in the height direction around the wind power generator 2. Further, FIG. 2 shows a state in which the wind power generation device 2 is viewed from the side, and it is assumed that the wind is blowing from the left to the right of the paper. As shown in FIG. 2, the wind power generation device 2 includes a rotor 25 radially attached to a hub 23 that rotates the blade 24, a nacelle 22 that allows the rotor 25 to rotate and supports the hub 23 from the lateral direction, and a nacelle. A tower 21 that rotatably supports the 22 from the lower part with respect to the vertical axis is provided. The wind power generation device 2 shows a downwind type wind power generation device in which the rotor 25 is located on the leeward side of the tower 21 in FIG. 2, but the rotor 25 is an upwind type wind power generation device located on the windward side of the tower 21. It may be a device.

The wind power generator 2 includes a strain sensor 7 attached to the tower 21. The strain sensor 7 may be installed not only in the tower 21 but also in the nacelle 22 or the hub 23, and instead of the strain sensor 7, another load sensor such as an acceleration sensor may be used. Further, the wind power generator 2 includes a pitch angle control mechanism 6 for controlling the pitch angle of the blade 24, an anemometer 8 installed above the nacelle 22, a thermometer 9 installed in the nacelle 22, and a barometer 10. May be equipped. The anemometer 8, the thermometer 9, and the barometer 10 may be installed at other positions of the wind power generation device 2, or may be installed outside the wind power generation device 2 if they are in the vicinity of the wind power generation device 2. good. Further, the thermometer 9 and the barometer 10 may not be measured, and public observation data used for weather prediction or the like may be used.

The wind speed distribution 11 usually changes in the height direction (Z direction), and generally, the wind speed tends to increase toward the sky depending on the boundary layer of the atmosphere. This change in wind speed in the height direction (Z direction) is called wind shear, and if the index representing the strength is α _WS , the wind speed distribution in the height direction (Z direction) is as shown in the following equation (1). You can assume.

Here, V (z) is the wind speed at the height z from the ground surface, z _ref is the height that defines the reference wind speed, and V (z _ref ) is the reference wind speed. As shown in FIG. 3, the larger the exponent α _WS , the larger the change in wind speed depending on the height. For example, when the reference wind speed is measured by the anemometer 8, the measured wind speed is used for V (z _ref ) in the equation (1), and the height from the ground surface of the anemometer 8 is used for z _ref . If the α _WS is known, the wind speed distribution in the height direction can be obtained. That is, when the wind speed distribution is assumed as in the equation (1), the problem of estimating the wind speed distribution results in the problem of estimating the exponent α _WS . In this embodiment, it is considered to estimate the wind shear index α _WS representing the strength of the wind shear by assuming the wind speed distribution of the equation (1), but the assumption of the wind speed distribution is not limited to the equation (1). A logarithm, a polynomial, or the like may be used, or a plurality of parameters may be used to assume a 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 storage unit 16 for storing a wind shear function 33, an atmospheric density calculation unit 17, and a window. A shear estimation unit 18, a wind speed distribution calculation unit 19, an input I / F34, an output I / F35, and a communication I / F36 are provided, and these are connected to each other so as to be accessible by an internal bus 37. The wind speed measurement unit 12, the load measurement unit 13, the temperature measurement unit 14, the barometric pressure measurement unit 15, the storage unit 16 for storing the wind shear function 33, the air density calculation unit 17, the wind shear estimation unit 18, and the wind speed distribution calculation unit 19 , The wind condition estimation device 32 is configured to obtain not only the estimation of the barometric pressure index α _WS that defines the strength of the wind shear but also the actual wind speed distribution. If only the estimation of the exponentiation α _WS is performed, the wind condition estimation device 32 is a storage unit 16 that stores the wind speed measuring unit 12, the load measuring unit 13, the temperature measuring unit 14, the barometric pressure measuring unit 15, and the wind shear function 33. , The atmospheric density calculation unit 17, and the wind shear estimation unit 18 may be configured. Furthermore, when only the exponent α _WS is estimated by allowing the estimation accuracy to decrease, the wind condition is determined only by the load measuring unit 13, the storage unit 16 that stores the wind shear function 33, and the wind shear estimation unit 18. The estimation device 32 may be configured.
The wind speed measurement unit 12, the load measurement unit 13, the temperature measurement unit 14, the pressure measurement unit 15, the air density calculation unit 17, the wind shear estimation unit 18, and the wind speed distribution calculation unit 19 constituting the wind condition estimation device 32 are, for example,. , A processor such as a CPU (Central Processing Unit) (not shown), a ROM for storing various programs, a RAM for temporarily storing data of an arithmetic process, a storage device such as an external storage device, and a processor such as a CPU. Reads and executes various programs stored in the ROM, and stores the calculation result, which is the execution result, in the RAM or an external storage device. The details of each part of the control device 31 will be described below.

The wind speed measuring unit 12 calculates the time-series data of the wind speed and the average wind speed averaged at a predetermined time from 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 measuring unit 12 transfers the average wind speed to the wind shear estimation unit 18 via the internal bus 37, and transfers the time series data of the wind speed to the wind speed distribution calculation unit 19. In the averaging process, for example, the average wind speed may be calculated every 10 minutes, or the average value may be continuously output using a moving average.

The load measuring unit 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 the input measured value of the strain of the tower 21 is measured at the measurement position. By multiplying by the section modulus, it is converted into a bending moment. Further, the bending moment is averaged in a predetermined time and transferred to the wind shear estimation unit 18 via the internal bus 37. If the wind direction at the construction position of the wind power generation device 2 is generally unidirectional, the strain sensor 7 may be installed at one place, but if the wind direction changes, wind power is generated along the direction of the nacelle 22. It is desirable to install strain sensors 7 at two or more locations at the same height point of the tower 21 in order to calculate the bending moment component in the direction in which the device 2 is overturned. Further, the position in the height direction in which the strain sensor 7 is attached is preferably near the top of the tower 21, but correction can be made from the wind speed and the thrust coefficient of the rotor 25 without directly measuring the moment at the top. Therefore, it is not necessary to limit the measurement position to the top.

The temperature measuring unit 14 inputs the temperature measured by the thermometer 10 via the input I / F 34 and the internal bus 37, and calculates the average temperature in a predetermined time. The temperature measuring unit 14 transfers the calculated averaged temperature to the atmospheric density calculation unit 17 via the internal bus 37. The barometric pressure measuring unit 15 inputs the barometric pressure measured by the barometer 11 via the input I / F 34 and the internal bus 37, and calculates the average barometric pressure at a predetermined time. The atmospheric pressure measuring unit 15 transfers the calculated averaged atmospheric pressure to the atmospheric density calculation unit 17 via the internal bus 37.
The atmospheric density calculation unit 17 calculates the atmospheric density from the temperature and the atmospheric pressure using the gas state equation, and transfers the average value of the atmospheric density to the Windsia estimation unit 18 via the internal bus 37 every 10 minutes, for example. do. If the atmospheric density can be calculated, another method may be used.

The wind shear estimation unit 18 inputs the bending moment transferred from the load measurement unit 13, the average wind speed transferred from the wind speed measurement unit 12, and the average value of the air density transferred from the air density calculation unit 17 as inputs. By using the wind shear function 33 that defines the relationship between the value of wind shear and the power index α _WS representing the strength of the wind shear, the estimated value of the power index α _WS is output at predetermined time intervals used for averaging. In this embodiment, the average values of bending moment, average wind speed, and atmospheric density are used as inputs to the wind shear estimation unit 18, but if a decrease in the estimation accuracy of the exponential α _WS can be tolerated, the load measurement unit Only the bending moment transferred from 13 may be used as an input, and either the average wind speed or the average value of the atmospheric density may be used in addition to the bending moment. Further, instead of the average wind speed, another physical quantity that changes in response to the wind speed may be used. For example, the amount of power generation, the pitch angle, the rotor rotation speed, and the like can be used.

The wind shear function 33 stored in the storage unit 16 stores a function that can uniquely output the index α _WS with respect to the average value of the bending moment, the average wind speed, and the atmospheric density. The storage method of the function is not particularly limited, and may be a response surface, a neural network, a mathematical formula such as a polynomial, or a data table in which each variable is separated by a bin. The method of creating the function is also not particularly limited, but for example, a Doppler lidar is temporarily attached to the upper part of the nacelle 22 constituting the wind power generator 2, and the exponentiation α _WS is calculated from the measured wind speed distribution by the least squares method or the like. Then, there is a method of creating a response curved surface by using the average values of bending moment, average wind speed, and atmospheric density as design variables and exponentiation α _WS as an objective function. Another method is to use a numerical simulation to calculate the bending moment when the average value of the exponent α _WS , mean wind velocity, and atmospheric density is changed, and let the neural network learn the calculation result to learn the exponent α. _WS can also be estimated.

The wind speed distribution calculation unit 19 uses the above equation (from the estimated value of the wind shear index α _WS obtained by the wind shear estimation unit 18 and the time series data of the wind speed transferred from the wind speed measurement unit 12 via the internal bus 37. Calculate the time series data of the wind speed distribution using 1). It is assumed that the height _zref of the anemometer 8 from the ground surface is known.
The output I / F 35 is calculated by the wind speed distribution calculation unit 19, and outputs the time series data of the wind speed distribution transferred via the internal bus 37 to a display unit (not shown).
The communication I / F 36 is an electronic terminal 4 installed in the operation management center 3 via the communication network 5 for the time series data of the wind speed distribution calculated by the wind speed distribution calculation unit 19 and transferred via the internal bus 37. Alternatively, it is sent to a server (not shown).

Next, the principle of wind shear estimation by the wind condition estimation device 32 will be described. It is assumed that the wind speed flowing into the rotor 25 has a distribution as shown in the above equation (1) due to the wind shear. The aerodynamic force (thrust force) T acting on the blade 24 in the wind direction can be expressed by the equation (2).

Here, b is the length of the blade 24, ρ is the air density, Ct is the local thrust coefficient at the position of the distance _r from the center of the hub 23 of the blade 24, and V is the position of the distance r from the center of the hub 23 of the blade 24. The local wind speed, c, is the chord length at a distance r from the center of the hub 23 of the blade 24. Of these, b and c are values unique to the blade 24 and are constant regardless of operating conditions. Further, C _t is also a value peculiar to the blade 24, but changes depending on the pitch angle, the wind speed, and the rotation speed. Here, for the sake of simplicity, it is assumed that the wind speed has the distribution of the above equation (1) in the height direction, but does not change with time, and the pitch angle and the rotation speed are constant. Further, it is assumed that the rotor 25 does not have a tilt angle and a cornering angle and rotates in a vertical plane. At this time, as long as the blade 24 does not stall, the angle of attack of the blade 24 increases as the wind speed increases, so that _Ct also increases monotonically. Therefore, as can be seen from the above equation (2), when the local wind speed V increases, the thrust force T also increases as the C _t V ² increases.

Assuming that the air density and the wind speed at the center of the hub 23 are constant, _zref represents the height of the hub 23 in FIG. 3, and the wind speed is higher above the hub 23 as the exponent α _WS increases. It can be seen that the wind speed increases and the wind speed decreases below the hub 23. Therefore, as shown in FIG. 5, the thrust force T also increases above the hub 23 and decreases below the hub 23 as the exponent α _WS increases. Here, considering the moment in the direction of overturning the wind turbine generator 2 along the direction of the nacelle 22 at the center of the hub 23, the exponentiation α _WS increases when the blade 24 is at an arbitrary position in the rotation plane. It can be seen that the moment increases monotonically with this. Therefore, the average value of the moments at the center of the hub 23 during one rotation of the rotor 25 also monotonically increases as the exponent α _WS increases, as shown in FIG. Therefore, when the atmospheric density and the wind speed at the center of the hub 23 are constant, the exponent α _WS can be estimated from the moment at the center of the hub 23. The figure for explaining the relationship between the exponent and the moment at the center of the hub shown in FIG. 6 is generated by simulation with respect to a model of a general wind power generation device. In the actual wind power generation device 2, the wind speed and the atmospheric density at the center of the hub 23 also change, and the moment increases monotonically due to these increases (FIGS. 7 and 8). Therefore, in order to estimate the exponential α _WS with high accuracy, it is necessary to measure the wind speed and atmospheric density at a certain position in addition to the moment. Once the wind speed and air density are known, select a relational expression suitable for the wind speed and air density from a plurality of moment-exponentiation α _WS relational expressions as shown in FIGS. 7 and 8, and the exponentiation α from the moment. _WS can be estimated. However, since the change in moment due to the change in air density shown in FIG. 8 is smaller than the change in power index α _WS and wind speed shown in FIG. 7, it is possible to estimate the power index α _WS without using the air density. Is. Further, when the fluctuation range of the wind speed is small or when the estimation accuracy of the exponentiation α _WS can be reduced, the exponentiation α _WS may be estimated only from the moment without using the wind speed and the atmospheric density.

Since it is actually difficult to measure the moment with the rotating hub 23, the moment measured at two points in the height direction of the tower 21 is used as a substitute for the moment measured by the strain sensor 7, and the hub 23 is externally mounted. You may calculate the moment at the center of. It is not necessary to use the values at the center of the hub 23 for the wind speed and the atmospheric density, and the values may be measured in the vicinity of the wind power generation device 2. In addition, although the pitch angle and the number of revolutions are assumed to be constant, these are generally determined by control according to the wind speed, so when estimating the exponent α _WS using the wind speed, the pitch angle Even if the rotation speed changes, the effect on the estimation accuracy is small. Since the tilt angle and the cornering angle are values peculiar to the wind power generation device 2 and are constant regardless of the operating conditions, there is no influence on the estimation accuracy.

In this embodiment, as shown in FIG. 4, the control device 31 is a storage unit 16 for storing the wind shear function 33, a wind shear estimation unit 18, and a wind speed distribution calculation unit 19 that constitute the wind condition estimation device 32. The case of implementing within is described as an example, but the present invention is not limited to this. For example, the storage unit 16 storing the wind shear function 33, the wind shear estimation unit 18, and the wind speed distribution calculation unit 19 can be installed in the electronic terminal 4 installed in the operation management center 3 shown in FIG. 1 or a server (not shown). It may be a configuration to be implemented.

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 estimating wind shear, which is a wind speed distribution, with high accuracy with a simple configuration.

FIG. 9 is a functional block diagram of the control device 31a constituting the wind power generation device of the second embodiment according to another embodiment of the present invention. In this embodiment, the control device controls the reliability evaluation device 40 for evaluating the reliability of the wind power generation device 2 using the wind shear estimated by the wind shear estimation unit 18 and the wind speed distribution calculation unit 19 shown in the first embodiment. The point provided inside is different from the first embodiment. The same components as those in the first embodiment are designated by the same reference numerals, and the description overlapping with the first embodiment will be omitted below. For convenience of explanation, as shown in FIG. 9, only the input I / F34, the wind shear estimation unit 18, the output I / F35, the communication I / F36, and the internal bus 37 are used as the same components as in the first embodiment. show.

As shown in FIG. 9, the control device 31a according to the present embodiment has an input I / F34, a wind shear estimation unit 18, an output I / F35, a communication I / F36, an operating condition acquisition unit 41, and a load calculation unit. 42, a storage unit 16a for storing design information 43, a reliability evaluation unit 44, and an information output unit 45 are provided, and these are connected to each other so as to be accessible by an internal bus 37. The reliability evaluation device 40 is composed of an operating condition acquisition unit 41, a load calculation unit 42, a storage unit 16a for storing design information 43, a reliability evaluation unit 44, and an information output unit 45. The reliability evaluation device 40 may be configured not to 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 ROM for storing a processor such as a CPU (Central Processing Unit) (not shown) and various programs. , A RAM that temporarily stores data in the calculation process, a storage device such as an external storage device, and a processor such as a CPU that reads and executes various programs stored in the ROM, and is the calculation result that is the execution result. Is stored in a RAM or an external storage device.

Hereinafter, the reliability evaluation device 40 will be described by taking the reliability evaluation of the blade 24 of the wind power generation device 2 as an example. The application destination of the reliability evaluation device 40 does not have to be limited to the blade 24, and if the wind shear affects the reliability, other configurations of the wind power generation device 2 such as the nacelle 22 and the tower 21 It may be a part.

The operating condition acquisition unit 41 acquires time history data of the operating conditions of the wind power generation device 2 related to the load acting on the blade 24. The operating conditions include, for example, the wind speed and direction of the anemometer 8, the pitch angle and azimuth angle of the blade 24, the rotation speed of the rotor 25, the azimuth angle of the nacelle 22, and the amount of power generated by the wind power generation device 2. When a load sensor such as a strain sensor or an acceleration sensor is attached to the wind power generator 2, the time history data thereof may be included. Further, when, for example, SCADA is used as the control device 31a, the operating conditions may be acquired from this SCADA.

The load calculation unit 42 uses the operating conditions transferred from the operating condition acquisition unit 41, the exponentiation α _WS transferred from the wind shear estimation unit 18, and the design information 43 of the blade 24 to act on the blade 24. Calculate the time history of. As a method of calculating the load, for example, the wind speed distribution (wind shear) flowing into the rotor 25 is calculated from the wind speed in the anemometer 8 and the aerodynamic index α _WS using the above equation (1), and the wind speed distribution and operating conditions are used. There is a method of inputting the time history data of the above into an aeroelastic simulation based on the wind shear momentum theory or multibody dynamics.
The design information 43 stored in the storage unit 16a is, for example, the dimensions and mass distribution of the blade 24 and the tower 21, the rigidity distribution, the aerodynamic coefficient, the tilt angle and cornering angle of the rotor 25, the dimensions and mass distribution of the nacelle 22, and the aerodynamic coefficient. , Design data such as a control program for the wind power generator 2. The design information 25 stored in the storage unit 16a includes data on the reliability of the components of the blade 24 as reliability information, for example, the dimensions of the components, the elastic modulus, the section modulus, the stress concentration coefficient, and S-. N-ray diagram and the like are included.

The reliability evaluation unit 44 evaluates the reliability of the components of the blade 24 by using the time history of the load acting on the blade 24 output from the load calculation unit 42 and the reliability information. For reliability evaluation, the degree of fatigue damage, remaining life, and fracture probability of components are calculated. For example, when calculating the degree of fatigue damage from the time history data of the load, there are the following methods. First, the time history of the stress acting on the component is calculated from the load acting on the blade 24. Next, the rainflow method is applied to the stress time history data to convert it into the appearance frequency distribution of the stress amplitude, and the S- of the component material stored in the obtained stress amplitude appearance frequency distribution and reliability information. From the N diagram, the degree of fatigue damage in the time history is calculated using the linear cumulative damage degree rule.

The information output unit 45 displays the evaluation results transferred from the reliability evaluation unit 44 via the internal bus 37 as a table, a graph, or a contour diagram. The data output from the operating condition acquisition unit 41, the wind shear estimation unit 18, and the load calculation unit 42 may be displayed. For example, the wind speed distribution in the rotor 25 by the above equation (1) using the wind speed in the anemometer 8 output from the operating condition acquisition unit 41 and the exponentiation α _WS output from the wind shear estimation unit 18. May be displayed.
In this embodiment, the reliability evaluation device 40 is provided in the control device 31a, but the present invention is not limited to this, and the electronic terminal 4 installed in the operation control center 3 shown in FIG. 1 or not shown. It may be configured to be implemented on the server.

As described above, according to the present embodiment, in addition to the effect of the first embodiment, by using the reliability evaluation device 40, the time history data of Windsia estimated from the operating conditions of the wind power generation device and the load of the wind power generation device. Based on the above, it is possible to evaluate the reliability of the wind power generation device.

FIG. 10 is a functional block diagram of a control device 31b constituting the wind power generation device of the third embodiment according to another embodiment of the present invention. This embodiment is different from the first embodiment in that the wind shear generator 2 is controlled by using the wind shear estimated by the wind shear estimation unit 18 and the wind speed distribution calculation unit 19 shown in the first embodiment. The same components as those in the first embodiment are designated by the same reference numerals, and the description overlapping with the first embodiment will be omitted below. For convenience of explanation, as shown in FIG. 10, only the input I / F34, the wind shear estimation unit 18, the output I / F35, the communication I / F36, and the internal bus 37 are used as the same components as in the first embodiment. show.

As shown in FIG. 10, the control device 31b according to the present embodiment has an input I / F34, a wind shear estimation unit 18, an output I / F35, a communication I / F36, an operating condition acquisition unit 41, and a control amount calculation unit. 51, a storage unit 16b for storing control information 52 is provided, and these are connected to each other so as to be accessible by an internal bus 37. The wind shear estimation unit 18, the operating condition acquisition unit 41, and the control amount calculation unit 51 temporarily store, for example, a processor such as a CPU (Central Processing Unit) (not shown), a ROM for storing various programs, and data of an arithmetic process. It is realized by a storage device such as a RAM or an external storage device, and a processor such as a CPU reads and executes various programs stored in the ROM, and stores the calculation result which is the execution result in the RAM or the external storage device.

The operating condition acquisition unit 41 acquires the operating conditions of the wind power generation device 2 in the same manner as in the second embodiment described above. The control amount calculation unit 51 includes an operating condition transferred from the operating condition acquisition unit 41 via the internal bus 37, a wind shear _estimation unit 18 transferred via the internal bus 37, and a control information 52. For example, the pitch angle of the blade 24 and the rotation speed of the rotor 25 are determined by using and, and the control amount is determined so as to realize these. The pitch angle of the blade 24 and the rotation speed of the rotor 25 can be determined, for example, by maximizing the amount of power generation and minimizing the load fluctuation of the blade 24. The pitch angle may change during one rotation of the rotor 25. In such control, the wind speed distribution flowing into the rotor 4 is calculated from the wind speed of the anemometer 8 and the index α _WS using the above equation (1), and the wind speed flows into the blade 24 for an arbitrary rotor rotation speed. This can be achieved by estimating the distribution of wind speed and direction with high accuracy.
The storage unit 16b stores constants used for control and aerodynamic characteristics of the blade 24 as control information 52. The above-mentioned control amount output from the control amount calculation unit 51 is output to the generator 28, the pitch angle control mechanism 6, and the like via the internal bus 37 and the output I / F 35.

As described above, according to the present embodiment, in addition to the effect of the first embodiment, the wind power generation device is controlled based on the operating conditions of the wind power generation device and the time history data of Windsia estimated from the load of the wind power generation device. , It is possible to maximize the amount of power generation and minimize the load fluctuation of the blade.

FIG. 11 is a diagram showing a configuration of a wind power generation device according to a fourth embodiment according to another embodiment of the present invention. This embodiment differs from the first embodiment in that the wind shear in the horizontal direction is estimated by using the wind condition estimation device 32 of the wind power generation device 2 of the above-mentioned embodiment 1. The same components as those in the first embodiment are designated by the same reference numerals, and the description overlapping with the first embodiment will be omitted below.

FIG. 11 shows the configuration of the wind power generation device 2 and the horizontal wind speed distribution 61 around it. FIG. 11 shows a state in which the wind power generation device 2 is viewed from above, and it is assumed that the wind is blowing from the left to the right of the paper. The wind power generation device 2 has the same configuration as that of the first embodiment described above.

The horizontal wind velocity distribution 61 shown in FIG. 11 changes in the horizontal direction, and if the coefficient representing the strength of the horizontal wind shear is β _WS , the horizontal wind velocity distribution 61 is given by the following equation (3). Can be assumed as follows.

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 is the position that defines the reference wind speed, and V (y _ref ) is the reference wind speed. There is. As can be seen from the equation (3), the larger the coefficient β _WS , the larger the change in the horizontal wind speed. For example, when the reference wind speed is measured by the anemometer 8, y is the wind speed measured by V (y _ref ) in the equation (3), y _ref is 0 (origin), and y is y from the anemometer 8 in FIG. By using the axial distance, a horizontal wind speed distribution 61 can be obtained if a certain coefficient β _WS is known. That is, when the wind speed distribution is assumed as in the equation (3), the problem of estimating the wind speed distribution results in the problem of estimating the coefficient β _WS . In this embodiment, it is considered to estimate the coefficient β _WS representing the strength of the wind shear in the horizontal direction by assuming the wind speed distribution in the equation (3), but the assumption of the wind speed distribution is limited to the equation (3). It is not necessary to do so, and the wind speed distribution may be assumed using a plurality of parameters.

The configuration of the wind condition estimation 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 condition estimation device 32 will be described as different from those of the first embodiment.
In this embodiment, the load measuring unit 13 (not shown) measures the shear strain of the tower 21 using the strain sensor 7, and twists using the moment of inertia of area at the measurement position and the radius of the tower 21. Convert to moment. Further, the twisting moment is averaged in a predetermined time and output. Since the twisting moment acts uniformly within the cross section of the tower 21, the strain sensor 7 may be installed at only one place, and the position in the height direction does not need to be particularly limited.

The wind shear estimation unit 18 (not shown) takes the average values of the twisting moment, wind speed, and atmospheric density as inputs, and defines the relationship between these values and the coefficient β _WS that represents the strength of the horizontal wind shear. By using the function 33, the estimated value of the coefficient β _WS is output at predetermined time intervals used for averaging. In this embodiment, the twisting moment, the wind speed, and the atmospheric density are used as the inputs to the wind shear estimation unit 18, but if the estimation accuracy of the coefficient β _WS can be reduced, only the twisting moment may be input. , Either wind speed or atmospheric density may be used in addition to the twisting moment. Further, instead of the wind speed, another physical quantity that changes in response to the wind speed may be used. For example, the amount of power generation, the pitch angle, the rotor rotation speed, and the like can be used. Since the twisting moment is also generated by the deviation between the nacelle 22 and the wind direction, which is called a yaw error, high accuracy can be achieved by adding the yaw error to the input of the wind shear estimation unit 18.

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 the twisting moment, the wind speed, and the atmospheric density. The method of saving and creating the function is not particularly limited, and the same method as in Example 1 of fulfillment may be used.
In the wind speed distribution calculation unit 19, the wind speed distribution is performed using the above equation (3) from the estimated value of the coefficient β _WS obtained by the wind shear estimation unit 18 and the time series data of the wind speed obtained by the wind speed measurement unit 12. Calculate series data.

The principle of estimating the horizontal wind shear by the wind condition estimation 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 horizontal wind shear is generated in the direction of rotating the nacelle 22 in the horizontal plane. Therefore, since the twisting moment acts on the tower 21, it is necessary to measure the twisting moment in order to estimate the coefficient β _WS . By simultaneously measuring the bending moment and the twisting moment of the tower 21, the wind shears in the height direction (Z direction) and the horizontal direction (y direction) of Examples 1 and 4 may be estimated at the same time. The estimated horizontal wind shear may be used as an input for the reliability evaluation device 40 of Example 2 and the control device 31b of Example 3 described above.

As described above, according to the present embodiment, by measuring the load of the wind power generation device, it is possible to estimate the wind shear in the horizontal direction with high accuracy with a simple configuration.

FIG. 12 is a diagram showing a configuration of a wind power generation device according to a fifth embodiment according to another embodiment of the present invention. This embodiment is different from the first embodiment in that the strain sensor 7 installed in the tower 21 shown in the first embodiment is installed on the blade 24. The same components as those in the first embodiment are designated by the same reference numerals, and the description overlapping with the first embodiment will be omitted below.

FIG. 12 shows the configuration of the wind power generation device 2 according to the present embodiment and the wind speed distribution 11 in the height direction around the wind power generator 2. FIG. 12 shows a state in which the wind power generation device 2 is viewed from the side, and it is assumed that the wind is blowing from the left to the right of the paper. In addition to the same configuration as in the first embodiment, the wind power generation device 2 includes a strain sensor 7 on the blade 24 instead of the tower 21. The strain sensor 7 may be attached to at least one blade 24 constituting the rotor 25, and another load sensor such as an acceleration sensor may be used instead of the strain sensor 7.

The configuration of the wind condition estimation device 32 of the wind power generation device 2 according to the present embodiment for estimating the exponential 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 condition estimation device 32 will be described as different from those of the first embodiment.
In this embodiment, the load measuring unit 13 measures the strain of the blade 24 using the strain sensor 7 and converts it into a bending moment by multiplying it by the cross-sectional coefficient at the measurement position. Further, the bending moment is statistically processed and the statistical value is output. As the statistical value, for example, the standard deviation of the bending moment at a predetermined time, the difference between the maximum value and the minimum value (maximum amplitude), and the like are used. Further, the azimuth angle may be divided by bins and the average value for each bin may be used, or the strain sensors 7 may be attached to all the blades 24 constituting the rotor 25, and the bending moment of each blade 24 may be used at the center of the hub 23. You may use the value obtained by the calculation of the moment of. The strain sensor 7 may be installed at one place, but it is desirable to install the strain sensor 7 at two or more places at the same position in the longitudinal direction of the blade 24 in order to calculate the moment component that bends the blade 24 in the wind direction. Further, although it is desirable that the strain sensor 7 is attached near the blade root, it is not necessary to limit the measurement position to the vicinity of the blade root.

The wind shear estimation unit 18 takes the statistics of the bending moment of the blade 24, the wind speed, and the average value of the air density as inputs, and defines the relationship between these values and the power index α _WS representing the strength of the wind shear. By using 33, the estimated value of the wind shear index α _WS is output at predetermined time intervals. In this embodiment, the bending moment, the wind speed, and the atmospheric density are used as the inputs to the wind shear estimation unit 18, but if the estimation accuracy of the exponent α _WS can be reduced, only the bending moment may be input. At best, either wind speed or atmospheric density may be used in addition to the bending moment. Further, instead of the wind speed, another physical quantity that changes according to the wind speed may be used. For example, the amount of power generation, the pitch angle, the rotor rotation speed, and the like can be used.

The principle of wind shear estimation by the wind condition estimation device 32 is the same as that of the first embodiment except for the following points. That is, as shown in FIG. 5, the thrust force acting on the blade 24 by the wind shear changes according to the azimuth angle, so that the bending moment measured by the strain sensor 7 also changes according to the azimuth angle. Therefore, the exponent α _WS can be estimated by expressing the fluctuation range of the bending moment acting on the blade 24 during one rotation of the rotor 25 by using the standard deviation and the maximum amplitude. Further, it is also possible to estimate the exponent α _WS from the magnitude of the value of the bending moment at a certain azimuth angle without using the fluctuation range of the bending moment in one rotation. For example, as shown in FIG. 5, the bending moment and the thrust force when the blade 24 is located directly above the hub 23 increase monotonically with the increase of the exponent α _WS , and therefore, from these values, the exponent α _WS Can be estimated. When the strain sensor 7 is attached to all the blades 24 constituting the rotor 25 and the moment at the center of the hub 23 is calculated from the bending moment of each blade 24, the window is based on the same principle as in the first embodiment. Shear can be estimated.

By using the bending moment when the blade 24 becomes horizontal, the wind shear in the horizontal direction can be estimated, and the wind shear in the height direction and the horizontal direction may be estimated at the same time. Further, the estimated wind shear may be used as an input for the reliability evaluation device 40 of the above-mentioned Example 2 and the control device 31b of the third embodiment.

As described above, also in this embodiment, by measuring the load of the wind power generation device, it is possible to estimate the wind shear with high accuracy with a simple configuration.

The present invention is not limited to the above-described embodiment, and includes various modifications. For example, the above-described embodiment has been described in detail in order to explain the present invention in an easy-to-understand manner, and is not necessarily limited to the one including all the described configurations. Further, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment.

1 ... Wind power generation system 2 ... Wind power generation device 3 ... Operation management center 4 ... Electronic terminal 5 ... Communication network 6 ... Pitch angle control mechanism 7 ... Strain sensor 8 ... Anemometer 9 ... Thermometer 10 ... Pressure gauge 11 ... Wind speed distribution 12 ... Wind speed measurement unit 13 ... Load measurement unit 14 ... Temperature measurement unit 15 ... Pressure measurement unit 16, 16a, 16b ... Storage unit 17 ... Atmospheric density calculation unit 18 ... Wind shear estimation unit 19 ... Wind speed distribution calculation unit 21 ... Tower 22 ... Nacelle 23 ... Hub 24 ... Blade 25 ... Rotor 26 ... Main shaft 27 ... Accelerator 28 ... Generator 29 ... Main frame 30 ... Power converters 31, 31a, 31b ... 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 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 direction Wind speed distribution

Claims (15)

It comprises at least a wind power generator having a rotor and a nacelle and a tower that rotatably supports the nacelle, and a control device for controlling the wind power generator.
The control device is
A load measuring unit that measures the load applied to the wind power generator, a storage unit that stores the wind shear function that defines the relationship between the load and the wind shear, and an atmospheric density using a gas state equation from temperature and pressure. A wind shear estimation device having an atmospheric density calculation unit for calculating the average value of the atmospheric density and a wind shear estimation unit for calculating the wind shear based on the load, the average value of the atmospheric density, and the wind shear function. A wind shear device that is characterized by that. In the wind power generation device according to claim 1,
The wind shear estimation unit is characterized in that a wind shear function stored in the storage unit and wind shear, which is a wind speed distribution in the height direction, are calculated based on the load input from the load measuring unit. Power generator. In the wind power generation device according to claim 1,
The wind shear estimation unit calculates wind shear, which is a horizontal wind speed distribution, based on the wind shear function stored in the storage unit and the load input from the load measuring unit. Device. In the wind power generation device according to claim 2,
The control device is
A wind power generation device comprising a reliability evaluation device for evaluating the reliability of the wind power generation device using wind shear which is a wind speed distribution in the height direction. In the wind power generation device according to claim 2 or claim 3.
The load measuring unit is a wind power generator that measures the load applied to the tower. In the wind power generation device according to claim 2 or claim 3.
The load measuring unit is a wind power generation device that measures strain or acceleration as a load applied to the wind power generation device. It is provided with at least one wind power generation device, a control device for controlling the wind power generation device, an electronic terminal having a display device, and a communication network for connecting these to each other so as to be communicable.
The control device is
A load measuring unit that measures the load applied to the wind power generator, a storage unit that stores the wind shear function that defines the relationship between the load and the wind shear, and an atmospheric density using a gas state equation from temperature and pressure. A wind shear estimation device having an atmospheric density calculation unit for calculating the average value of the atmospheric density and a wind shear estimation unit for calculating the wind shear based on the load, the average value of the atmospheric density, and the wind shear function. A wind shear system characterized by that. In the wind power generation system according to claim 7.
The wind shear estimation unit calculates wind shear, which is a wind speed distribution in the height direction, based on the wind shear function stored in the storage unit and the load input from the load measuring unit via the communication network. A wind power generation system characterized by that. In the wind power generation system according to claim 7.
The wind shear estimation unit calculates wind shear, which is a horizontal wind speed distribution, based on the wind shear function stored in the storage unit and the load input from the load measuring unit via the communication network. A wind power generation system featuring. In the wind power generation system according to claim 8,
The control device is
A wind power generation system comprising a reliability evaluation device for evaluating the reliability of the wind power generation device by using the wind shear which is the wind speed distribution in the height direction. In the wind power generation system according to claim 8 or 9.
The load measuring unit is a wind power generation system characterized by measuring a load applied to a tower of the wind power generation device. In the wind power generation system according to claim 8 or 9.
The load measuring unit is a wind power generation system characterized by measuring strain or acceleration as a load applied to the wind power generation device. It is provided with at least one wind power generation device, a control device for controlling the wind power generation device, an electronic terminal having a display device, and a communication network for connecting these to each other so as to be communicable.
The control device includes a load measuring unit that measures the load applied to the wind power generation device, and an atmospheric density calculation unit that calculates the atmospheric density from the temperature and pressure using the equation of state of the gas and obtains the average value of the atmospheric density. , Has,
The electronic terminal is input from a storage unit that stores a wind shear function that defines a relationship between a load and a wind shear, and a load input from the load measurement unit and an atmospheric density calculation unit via the communication network. A wind power generation system including a wind shear estimation device having a wind shear estimation unit that calculates wind shear based on an average value of atmospheric densities and a wind shear function stored in the storage unit. In the wind power generation system according to claim 13,
The wind shear estimation unit calculates wind shear, which is a wind speed distribution in the height direction, based on the wind shear function stored in the storage unit and the load input from the load measuring unit via the communication network. A wind power generation system characterized by that. In the wind power generation system according to claim 13,
The wind shear estimation unit calculates wind shear, which is a horizontal wind speed distribution, based on the wind shear function stored in the storage unit and the load input from the load measuring unit via the communication network. A wind power generation system featuring.

Images