An intelligent fuzzy variable frequency yaw control system and method

Abstract

An intelligent fuzzy variable frequency yaw control system comprises a power supply module, a rectifier module, an inverter module, an LC filter module and a yaw motor module which are electrically connected in sequence, and also comprises a control core board and a data acquisition module, wherein the data acquisition module is electrically connected to the control core board, and the control core board is electrically connected to the inverter module; the present invention provides an intelligent fuzzy variable frequency yaw control system and method, which realizes an intelligent variable frequency and variable speed yaw function, and can output a corresponding frequency value according to the current wind direction and yaw angular velocity, thereby controlling the yaw speed of the wind turbine, and this control method realizes that the output frequency value changes with the change of yaw displacement angle and yaw angular velocity. It changes with the wind. When the yaw displacement angle is large, the variable frequency yaw is performed at a higher speed to face the wind, which greatly improves the efficiency of wind energy utilization. At the same time, as the yaw displacement angle becomes smaller, the yaw speed of the motor will also decrease accordingly, realizing the "soft landing" function. At the same time, if the displacement angle is large and the yaw angular velocity is zero or small, it will not start at a large speed, realizing the "soft start" function. This method has less vibration for the unit and will not cause the vibration of the fan to affect the equipment. At the same time, it can yaw to face the wind in an intelligent variable frequency manner, which increases the power generation, improves the wind energy utilization rate, and improves the power generation efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power, and in particular to an intelligent fuzzy variable frequency yaw control system and a control method. Background Art

[0002] At present, the most commonly used method in the yaw-to-wind system of a wind turbine is to control the yaw of the yaw motor by directly attracting a weak-current control contactor. In order to solve the problem of slow yaw speed of the wind turbine, some types of wind turbines use variable frequency and variable speed yaw control to improve the yaw speed of the wind turbine. Although this method can improve the yaw efficiency of the wind turbine, it will cause a large speed change rate when the wind turbine starts and stops, which will cause vibration of the equipment and blades in the cabin, and seriously affect the operation of the equipment and the unit. Therefore, this patent designs an intelligent variable frequency control technology with the goal of improving the yaw efficiency of the yaw motor while realizing "soft start" and "soft landing" functions. This patent introduces intelligent fuzzy control logic to realize intelligent control. This method can make the frequency change with the change of the yaw angle difference and the yaw angular velocity, so as to obtain the corresponding suitable frequency and realize the intelligent yaw effect. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide an intelligent fuzzy variable frequency yaw control system and control method, which improves the yaw efficiency of the unit to the wind and solves the frequent yaw system failures caused by defects in the yaw control algorithm.

[0004] To solve the above technical problems, the technical solution adopted by the present invention is: an intelligent fuzzy variable frequency yaw control system, comprising a power module, a rectifier module, an inverter module, an LC filter module and a yaw motor module electrically connected in sequence, and also comprising a control core board and a data acquisition module, wherein the data acquisition module is electrically connected to the control core board, and the control core board is electrically connected to the inverter module;

[0005] The data acquisition module uses current transformers and voltage transformers to collect current and voltage values. The purpose of collecting data is to realize the CLark and Park transformation (conversion from three-phase coordinate system to two-phase rotating coordinate system). Its purpose is to improve the control effect of the motor, so that the three-phase motor has the control effect similar to that of a DC motor.

[0006] The control core board uses the DSP28335 motor-specific control chip, which performs 3 / 2 conversion and then burns it into the control chip. Its carrier and modulation waves are also completed through the control core board. Its output PWM wave is input to the power module to control the motor.

[0007] The power module provides three-phase AC power, which is converted into DC power through the rectifier module. The purpose of AC-DC conversion is to realize the input of the control algorithm. The control logic algorithm is introduced in the inverter module to output a discrete three-phase sine wave. The LC filter module is used to realize the tuning of the discrete sine wave to a continuous sine wave. The yaw motor module is the control object.

[0008] The rectifier module rectifies the collected three-phase voltage and current in order to add control logic to the inverter module to achieve better control effects.

[0009] The inverter module converts DC power into AC power, and controls the motor through the PWM wave generated by the control core board.

[0010] The LC filter module converts the equivalent three-phase sine wave generated by the inverter into a sine waveform, thereby improving the quality of the sine wave.

[0011] Preferably, the control core board adopts DSP28355 control chip.

[0012] An intelligent fuzzy variable frequency yaw control method comprises the following steps:

[0013] S1. Collect the three-phase voltage of the motor input and convert the three-phase stationary coordinate system into a two-phase rotating coordinate system through 3 / 2 equivalent transformation to achieve control performance close to that of a DC motor.

[0014] S2. The collected three-phase line voltage is equivalently transformed to obtain Ud and Uq. Uq is phase-locked through a PI phase-locked loop. The PI control adopts an incremental PI control method to output w, which is multiplied by t to obtain the angle θ. The phase is locked to make Uq = 0. PI control: Piout = Kp (Err - Erro) + Ki × Err, Err = DF - FB;

[0015] S3, the switching frequency is set to 10kHz, and the switching frequency is used as the sampling frequency;

[0016] S4, lock Uq=0 through the phase-locked loop, and get Ud= Um, as the amplitude of the sinusoidal modulation wave, the sinusoidal modulation wave is: U=Umsin((2Πf)t), and the output frequency and waveform quality are adjusted by adjusting the modulation wave frequency. The triangular wave frequency is the switching frequency set to 10kHz;

[0017] S5. By collecting the yaw displacement angle and yaw angular velocity, taking them as the logical input values of the second-order fuzzy control logic, and then performing fuzzy logic analysis to obtain the fuzzy output value, variable frequency and variable speed yaw to wind direction can be achieved;

[0018] S6. The obtained fuzzy output frequency is further processed inside the DSP as the frequency of the modulation wave to obtain a three-phase PWM wave. The power drive module controls the three-phase inverter bridge and then controls the rotation of the motor, realizing intelligent variable frequency control of the yaw motor.

[0019] Preferably, step S5 uses the collected yaw angular displacement and yaw angular velocity data as two input reference quantities for fuzzy control. The system internally adopts Mamdani fuzzy algorithm and center of gravity defuzzification. The yaw angular displacement and yaw angular velocity collected by the sensor are used as fuzzy inputs of fuzzy rules. Fuzzy rules are established and a suitable output frequency is obtained through a membership function. The membership function judgment is based on the angular displacement and angular velocity of the existing motor collected by the sensor, thereby realizing intelligent control of the motor.

[0020] The present invention provides an intelligent fuzzy variable frequency yaw control system and method, which realizes an intelligent variable frequency and variable speed yaw function, can output a corresponding frequency value according to the current wind direction and yaw angular velocity, and then control the yaw speed of the wind turbine. This control method realizes that the output frequency value changes with the change of the yaw displacement angle and the yaw angular velocity. When the yaw displacement angle is large, the variable frequency yaw is performed at a higher speed to the wind, which greatly improves the wind energy utilization efficiency. At the same time, as the yaw displacement angle decreases, the yaw speed of the motor will also decrease accordingly, realizing a "soft landing" function. At the same time, if the displacement angle is large and the yaw angular velocity is zero or small, it will not be started at a high speed, realizing a "soft start" function. This method has less vibration for the unit and will not cause the vibration of the wind turbine to affect the equipment. At the same time, it can yaw the wind in an intelligent variable frequency manner, thereby increasing the power generation, improving the wind energy utilization rate, and improving the power generation efficiency.

[0021] Compared with the traditional yaw motor's uniform yaw, this solution has better yaw-to-wind efficiency and realizes intelligent variable-frequency yaw-to-wind effect, thus improving the efficiency of wind energy utilization and the power generation of the wind turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The present invention will be further described below with reference to the accompanying drawings and examples:

[0023] Figure 1 It is a structural schematic diagram of the present invention;

[0024] Figure 2 is a flow chart of the method of the present invention;

[0025] Figure 3 Inputting the yaw displacement angle for the present invention;

[0026] Figure 4 Input yaw rate for the present invention;

[0027] Figure 5 Outputs the yaw motor frequency for the present invention. DETAILED DESCRIPTION

[0028] like Figure 1-2 As shown, an intelligent fuzzy variable frequency yaw control system includes a power module, a rectifier module, an inverter module, an LC filter module and a yaw motor module electrically connected in sequence, and also includes a control core board and a data acquisition module, the data acquisition module is electrically connected to the control core board, and the control core board is electrically connected to the inverter module;

[0029] The data acquisition module uses current transformers and voltage transformers to collect current and voltage values. The purpose of collecting data is to realize the CLark and Park transformation (conversion from three-phase coordinate system to two-phase rotating coordinate system). Its purpose is to improve the control effect of the motor, so that the three-phase motor has the control effect similar to that of a DC motor.

[0030] The control core board uses the DSP28335 motor-specific control chip, which performs 3 / 2 conversion and then burns it into the control chip. Its carrier and modulation waves are also completed through the control core board. Its output PWM wave is input to the power module to control the motor.

[0031] The power module provides three-phase AC power, which is converted into DC power through the rectifier module. The purpose of AC-DC conversion is to realize the input of the control algorithm. The control logic algorithm is introduced in the inverter module to output a discrete three-phase sine wave. The LC filter module is used to realize the tuning of the discrete sine wave to a continuous sine wave. The yaw motor module is the control object.

[0032] The rectifier module rectifies the collected three-phase voltage and current in order to add control logic to the inverter module to achieve better control effects.

[0033] The inverter module converts DC power into AC power, and controls the motor through the PWM wave generated by the control core board.

[0034] The LC filter module converts the equivalent three-phase sine wave generated by the inverter into a sine waveform, thereby improving the quality of the sine wave.

[0035] Preferably, the control core board adopts DSP28355 control chip.

[0036] An intelligent fuzzy variable frequency yaw control method comprises the following steps:

[0037] S1. Collect the three-phase voltage of the motor input and convert the three-phase stationary coordinate system into a two-phase rotating coordinate system through 3 / 2 equivalent transformation to achieve control performance close to that of a DC motor.

[0038] S2. The collected three-phase line voltage is equivalently transformed to obtain Ud and Uq. Uq is phase-locked through a PI phase-locked loop. The PI control adopts an incremental PI control method to output w, which is multiplied by t to obtain the angle θ. The phase is locked to make Uq = 0. PI control: Piout = Kp (Err - Erro) + Ki × Err, Err = DF - FB;

[0039] S3, the switching frequency is set to 10kHz, and the switching frequency is used as the sampling frequency;

[0040] S4, lock Uq=0 through the phase-locked loop, and get Ud= Um, as the amplitude of the sinusoidal modulation wave, the sinusoidal modulation wave is: U=Umsin((2Πf)t), and the output frequency and waveform quality are adjusted by adjusting the modulation wave frequency. The triangular wave frequency is the switching frequency set to 10kHz;

[0041] S5. By collecting the yaw displacement angle and yaw angular velocity, taking them as the logical input values of the second-order fuzzy control logic, and then performing fuzzy logic analysis to obtain the fuzzy output value, variable frequency and variable speed yaw to wind direction can be achieved;

[0042] S6. The obtained fuzzy output frequency is further processed inside the DSP as the frequency of the modulation wave to obtain a three-phase PWM wave. The power drive module controls the three-phase inverter bridge and then controls the rotation of the motor, realizing intelligent variable frequency control of the yaw motor.

[0043] Preferably, step S5 uses the collected yaw angular displacement and yaw angular velocity data as two input reference quantities for fuzzy control. The system internally adopts Mamdani fuzzy algorithm and center of gravity defuzzification. The yaw angular displacement and yaw angular velocity collected by the sensor are used as fuzzy inputs of fuzzy rules. Fuzzy rules are established and a suitable output frequency is obtained through a membership function. The membership function judgment is based on the angular displacement and angular velocity of the existing motor collected by the sensor, thereby realizing intelligent control of the motor.

[0044] As shown in the table below, the fuzzy control is designed as seven fuzzy subsets and seven fuzzy outputs. The system uses the Mamdani fuzzy algorithm and centroid defuzzification. The input and output quantities use the triangular membership function as shown in the following example: Figure 3 、 Figure 4 、 Figure 5 As shown, the ordinate is the degree of membership, and the abscissas are the yaw angle displacement, yaw angle velocity, and output frequency respectively.

[0045] Table 1 Fuzzy control logic

[0046]

[0047] Figure 4The unit of yaw angular velocity is (degrees / second), positive and negative represent the direction. Figure 3 The yaw displacement angle is 180° on each side, and the positive and negative values represent the positive and negative semicircles. Figure 5 Represents the output yaw motor frequency.

[0048] The PI phase-locked loop control process is to perform phase locking at Uq=0 through the continuously accumulated θ and the continuously updated wt, so as to further obtain the modulated sine wave.

[0049] In the first step, this patent first converts the collected voltage information into a two-phase rotating coordinate system through equivalent transformation, and obtains the Ud value by using the PI phase-locked loop and the Uq=0 control mode. Um, and further obtain the system modulation wave.

[0050] The second step is to collect the motor yaw displacement angle and yaw angular velocity, and use them as the input value of the second-order fuzzy control logic. Through fuzzy logic analysis, a fuzzy output value is obtained. By controlling the motor frequency, the yaw motor speed is controlled. Then, the speed is changed by the speed gearbox, so that the motor can intelligently change the frequency and speed of yaw.

[0051] The present invention realizes intelligent variable frequency yaw control by introducing fuzzy logic control as the frequency control method of variable frequency control; the second-order fuzzy control method realizes the control function without increasing the amount of calculation, takes the yaw displacement angle and yaw angular velocity as fuzzy input, and derives the fuzzy control output frequency value through fuzzy logic to realize intelligent yaw variable frequency control.

[0052] The present invention can change the frequency of the motor as the yaw displacement angle changes, realizes intelligent frequency conversion control, and implements soft start and soft landing functions, thereby avoiding fan vibration problems and not causing vibration problems of the unit equipment.

Claims

1. An intelligent fuzzy variable frequency yaw control method, characterized by: The following steps are involved: S1. Collect the three-phase voltage of the motor input and convert the three-phase stationary coordinate system into a two-phase rotating coordinate system through 3 / 2 equivalent transformation to achieve control performance close to that of a DC motor. S2. The collected three-phase line voltage is equivalently transformed to obtain Ud and Uq. Uq is phase-locked through a PI phase-locked loop. The PI control adopts an incremental PI control method to output w, which is multiplied by t to obtain the angle θ. The phase is locked to make Uq = 0. PI control: Piout = Kp (Err - Erro) + Ki × Err, Err = DF - FB; S3, the switching frequency is set to 10kHz, and the switching frequency is used as the sampling frequency; S4, lock Uq=0 through the phase-locked loop, and get Ud= Um, as the amplitude of the sinusoidal modulation wave, the sinusoidal modulation wave is: U=Umsin((2Πf)t), and the output frequency and waveform quality are adjusted by adjusting the modulation wave frequency. The triangular wave frequency is the switching frequency set to 10kHz; S5. By collecting the yaw displacement angle and yaw angular velocity, taking them as the logical input values of the second-order fuzzy control logic, and then performing fuzzy logic analysis to obtain the fuzzy output value, variable frequency and variable speed yaw to wind direction can be achieved; S6. The obtained fuzzy output frequency is further processed inside the DSP as the frequency of the modulation wave to obtain a three-phase PWM wave. The power drive module controls the three-phase inverter bridge and then controls the rotation of the motor, realizing intelligent variable frequency control of the yaw motor.

2. The intelligent fuzzy variable frequency yaw control method according to claim 1, characterized in that: In step S5, the collected yaw angular displacement and yaw angular velocity data are used as two input reference quantities for fuzzy control. The system internally adopts the Mamdani fuzzy algorithm and center of gravity defuzzification. The yaw angular displacement and yaw angular velocity collected by the sensor are used as fuzzy inputs of the fuzzy rules. The fuzzy rules are established and the appropriate output frequency is obtained through the membership function. The membership function judgment is based on the angular displacement and angular velocity of the existing motor collected by the sensor, thereby realizing intelligent control of the motor.

3. A system for implementing the intelligent fuzzy variable frequency yaw control method according to claim 1 or 2, characterized in that: It includes a power module, a rectifier module, an inverter module, an LC filter module and a yaw motor module which are electrically connected in sequence, and also includes a control core board and a data acquisition module, wherein the data acquisition module is electrically connected to the control core board, and the control core board is electrically connected to the inverter module; The data acquisition module uses current transformers and voltage transformers to collect current and voltage values and implement CLark and Park transformations; The control core board performs 3 / 2 conversion and then burns it into the control chip. Its carrier and modulation waves are also completed through the control core board. Its output PWM wave is input to the power module to control the motor. The power module is used to provide three-phase AC power, which is converted into DC power through the rectifier module. The control logic algorithm is introduced into the inverter module to output a discrete three-phase sine wave. The LC filter module is used to realize the tuning of the discrete sine wave to a continuous sine wave. The yaw motor module is the control object; Rectifier module, which rectifies the collected three-phase voltage and current; The inverter module converts DC power into AC power, and controls the motor through the PWM wave generated by the control core board. The LC filter module converts the equivalent three-phase sine wave generated by the inverter into a sine waveform.

4. The system for implementing an intelligent fuzzy variable frequency yaw control method according to claim 3, characterized in that: The control core board adopts DSP28355 control chip.

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