Emergency control method, device and equipment based on PMSG wind turbine and medium

Abstract

The application belongs to the technical field of wind power control, and specifically discloses an emergency control method, device, equipment and medium based on a PMSG wind turbine, which comprises the following steps: acquiring error data of a wind turbine operating state and a rated state, inputting the error data into a variable pitch control system, the variable pitch control system having a multi-feedback compensation control mode; determining a feedback compensation control mode from the multi-feedback compensation control mode according to the error data; the variable pitch control system comprising a fuzzy PID controller; the fuzzy PID controller outputting a pitch angle according to error data corresponding to the determined feedback compensation mode; and the variable pitch control system adjusting output power of the wind turbine according to the pitch angle output by the fuzzy PID controller. The application can improve the control speed of the wind turbine and ensure the pitch angle regulation precision.

Description

Technical Field

[0001] This invention belongs to the field of wind power control technology, specifically relating to an emergency control method, device, equipment and medium based on PMSG wind turbine generators. Background Technology

[0002] Unlike traditional thermal power generation, wind power, as a form of renewable energy, is highly susceptible to external weather factors, resulting in intermittent and fluctuating power output. Under normal weather conditions, numerical weather prediction can provide relatively accurate forecasts of renewable energy output, and weather fluctuations have a relatively small impact on power grid operation. In recent years, however, with the intensification of global warming and the increasing frequency of extreme weather events, extreme weather events have posed serious challenges to renewable energy and even the safe operation of the power system.

[0003] Based on the aerodynamic characteristics of wind turbines, grid-connected PMSG (permanent magnet synchronous wind turbine) units can exceed their rated power output during strong winds, causing fluctuations in power system operation. Existing solutions address this issue by controlling the pitch angle using classical or intelligent algorithms. However, classical algorithms, including graph theory and heuristics, are computationally intensive, inefficient, and unsuitable for large-scale systems. Many intelligent algorithms suffer from numerous parameters, are difficult to operate, and are prone to getting trapped in local optima, making them unsuitable for adoption. Existing pitch angle control strategies are slow and often use a fixed set of parameters, making it difficult to precisely adjust the pitch angle when wind speed changes, thus hindering effective power control under extreme conditions. Summary of the Invention

[0004] The purpose of this invention is to provide an emergency control method, device, equipment and medium based on PMSG wind turbines to solve the technical problems of slow control speed and low pitch angle control accuracy of wind turbines.

[0005] To achieve the above objectives, the present invention employs the following technical solution:

[0006] According to one aspect of the present invention, an emergency control method based on a PMSG wind turbine is provided, comprising the following steps:

[0007] The system acquires error data between the operating status and rated status of the wind turbine, inputs the error data into the pitch control system, which has multiple feedback compensation control modes; and determines the feedback compensation control mode from the multiple feedback compensation control modes based on the error data.

[0008] The variable pitch control system includes a fuzzy PID controller; the fuzzy PID controller outputs the pitch angle based on the error data corresponding to the determined feedback compensation mode.

[0009] The variable pitch control system adjusts the output power of the wind turbine based on the pitch angle output by the fuzzy PID controller.

[0010] The above technical solution addresses a microgrid system where permanent magnet direct-drive wind turbines are connected to the grid via back-to-back converters. By employing virtual synchronous machine control technology and utilizing feedback on the rate of frequency change, the virtual inertia coefficient is flexibly adjusted, thereby achieving active frequency control of the system. A feedback compensation control mode is determined based on the actual power error during wind turbine operation, thus adjusting the wind turbine pitch angle according to different output power levels, improving the speed of pitch angle control. The use of a fuzzy PID controller, with adaptive correction of PID parameters, enables more precise pitch angle adjustment control.

[0011] According to one embodiment of the present invention, the step of determining a feedback compensation control mode from multiple feedback compensation control modes based on error data includes:

[0012] Determine the power error from the error data, and determine the feedback compensation control mode based on the power error;

[0013] Among them, the power error is the deviation between the rated power and the output power of the wind turbine.

[0014] Furthermore, the multi-feedback compensation control mode includes single power feedback compensation mode and power-speed joint feedback compensation mode;

[0015] When the input power of the wind turbine is less than or equal to 1.1 times the rated power, it is in single power feedback compensation mode;

[0016] When the input power of the wind turbine is greater than 1.1 times the rated power, it adopts the power-speed joint feedback compensation mode.

[0017] Furthermore, the error data includes the error and rate of change between the rated power and output power of the wind turbine, as well as the error and rate of change between the rated speed and actual speed of the wind turbine.

[0018] The error data corresponding to the single power feedback compensation mode includes the error between the rated power and output power of the wind turbine and the error change rate.

[0019] The error data corresponding to the power-speed joint feedback compensation mode includes the error and error change rate between the rated power and output power of the wind turbine, as well as the error and error change rate between the rated speed and actual speed of the wind turbine.

[0020] According to one embodiment of the present invention, the step of the fuzzy PID controller outputting the pitch angle based on the error data corresponding to the determined feedback compensation mode includes:

[0021] The error data is input into the fuzzy controller corresponding to the feedback compensation control mode, and the fuzzy controller outputs the PID parameter adjustment amount.

[0022] The PID controller corrects the parameters based on the PID parameter adjustment and outputs the pitch angle based on the error data.

[0023] The steps involved in inputting error data into the fuzzy controller corresponding to the feedback compensation control mode, and the fuzzy controller outputting the PID parameter adjustment, include:

[0024] Fuzzy description involves defining the discrete universe of discourse for the input variables and processing the error data based on the discrete universe of discourse to obtain the error fuzziness quantity.

[0025] Establish fuzzy rules and determine the values ​​of proportional, integral, and derivative parameters in the fuzzy PID controller based on the error fuzzy quantity obtained from the fuzzy description;

[0026] Fuzzy inference establishes fuzzy relation equations based on the values ​​of proportional, integral, and differential parameters determined by fuzzy rules, obtains the output fuzzy control quantity using the error fuzzy quantity, establishes a fuzzy control table based on all possible output fuzzy control quantities, and uses the table lookup method to determine the corresponding output fuzzy control quantity.

[0027] Defuzzification is performed by adjusting the output fuzzy control quantity using a weighted average method to obtain the defuzzified output control quantity. Based on the defuzzified output control quantity, the adjustment amounts of the proportional, integral, and derivative parameters in the fuzzy PID controller are obtained. The PID parameters are then corrected based on the adjustment amounts of the proportional, integral, and derivative parameters.

[0028] According to one embodiment of the present invention, the whale algorithm is used to optimize the parameters of the fuzzy PID controller, including the error parameter, error rate of change parameter, proportional parameter, integral parameter and derivative parameter in the fuzzy PID controller;

[0029] In the whale algorithm, the error parameters, error rate of change parameters, proportional parameters, integral parameters, and derivative parameters of the fuzzy PID controller are correlated with the position of the whale.

[0030] The whale algorithm has advantages such as fewer parameter settings, simple operation, easy implementation, and strong optimization ability. Based on the fuzzy PID controller, the whale algorithm is added to optimize the parameters in the fuzzy controller. By utilizing the global search capability of the whale algorithm, the accuracy and speed of pitch angle adjustment are further improved.

[0031] Furthermore, in the whale algorithm, the ITAE metric, which measures the performance of the control system, is used as the fitness function.

[0032] According to one aspect of the present invention, an emergency control method apparatus based on a PMSG wind turbine is provided, comprising:

[0033] The data acquisition module is used to obtain error data between the operating status and the rated status of the wind turbine.

[0034] The feedback compensation module is used to input error data into the pitch control system, which has multiple feedback compensation control modes. The feedback compensation control mode is determined from the multiple feedback compensation control modes based on the error data. The pitch control system includes a fuzzy PID controller. The fuzzy PID controller outputs the pitch angle based on the error data corresponding to the determined feedback compensation mode.

[0035] The control and execution module is used by the pitch control system to adjust the output power of the wind turbine according to the pitch angle output by the fuzzy PID controller.

[0036] According to one aspect of the present invention, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the emergency control method based on a PMSG wind turbine according to any of the above embodiments.

[0037] According to one aspect of the present invention, a computer-readable storage medium is provided, which stores a computer program that, when executed by a processor, implements the emergency control method for PMSG wind turbines according to any of the above embodiments.

[0038] Compared with the prior art, the present invention has at least the following beneficial effects:

[0039] 1. This invention determines the feedback compensation control mode based on the actual power error during wind turbine operation, thereby adjusting the wind turbine pitch angle according to different output power and improving the control speed of the pitch angle. The use of a fuzzy PID controller to adaptively correct the PID parameters enables more precise pitch angle adjustment control.

[0040] 2. Based on the fuzzy PID controller, this invention incorporates the whale algorithm to optimize the parameters in the fuzzy controller. By utilizing the global search capability of the whale algorithm, the accuracy and speed of pitch angle adjustment are further improved. Attached Figure Description

[0041] The accompanying drawings, which form part of this specification, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0042] Figure 1The ideal output power curves of the grid-type PMSG wind turbine under different wind speeds are provided for the emergency control method of the grid-type PMSG wind turbine under strong winds proposed in Example 1.

[0043] Figure 2 This is a control block diagram of the pitch control system for a grid-type PMSG wind turbine in Example 1.

[0044] Figure 3 This is a control block diagram of the pitch control system for the grid-type PMSG wind turbine in Example 2;

[0045] Figure 4 To optimize the iterative curve of the fuzzy PID controller using the whale algorithm in Example 2;

[0046] Figure 5 Example 3 presents a control block diagram of the pitch control system for a grid-type PMSG wind turbine.

[0047] Figure 6 The pitch angle variation curves are shown for three different variable pitch control systems in Examples 1-3.

[0048] Figure 7 The output power variation curves are shown for three different variable pitch control systems in Examples 1-3. Detailed Implementation

[0049] The present invention will now be described in detail with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0050] The following detailed description is exemplary and intended to provide further detailed explanation of the invention. Unless otherwise specified, all technical terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this invention is for describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention.

[0051] Example 1

[0052] An emergency control method based on PMSG wind turbines includes the following steps:

[0053] The system acquires error data between the operating status and rated status of the wind turbine, inputs the error data into the pitch control system, which has multiple feedback compensation control modes; and determines the feedback compensation control mode from the multiple feedback compensation control modes based on the error data.

[0054] The variable pitch control system includes a fuzzy PID controller; the fuzzy PID controller outputs the pitch angle based on the error data corresponding to the determined feedback compensation mode.

[0055] The variable pitch control system adjusts the output power of the wind turbine based on the pitch angle output by the fuzzy PID controller.

[0056] The above technical solution addresses a microgrid system where permanent magnet direct-drive wind turbines are connected to the grid via back-to-back converters. By employing virtual synchronous machine control technology and utilizing feedback on the rate of frequency change, the virtual inertia coefficient is flexibly adjusted, thereby achieving active frequency control of the system. A feedback compensation control mode is determined based on the actual power error during wind turbine operation, thus adjusting the wind turbine pitch angle according to different output power levels, improving the speed of pitch angle control. The use of a fuzzy PID controller, with adaptive correction of PID parameters, enables more precise pitch angle adjustment control.

[0057] like Figure 1 The figure shows the ideal output power curves of a grid-connected PMSG wind turbine under different wind speeds. When the wind speed is greater than the cut-in wind speed but less than or equal to the rated wind speed, the grid-connected PMSG wind turbine outputs power according to MPPT (Maximum Power Point Tracking). When the wind speed is greater than the rated wind speed but less than the cut-out wind speed, if the output power is still output according to MPPT, the output will be overloaded. In windy weather, the wind speed is often quite high, and the output power overload is quite serious. If not controlled, it will cause instability in the power system. Therefore, it is desirable for the output power of the grid-connected PMSG wind turbine to remain at the rated power in this case. When the wind speed is greater than the cut-out wind speed, considering the safety of the grid-connected PMSG wind turbine, the unit is cut off, and the output power is 0.

[0058] Build as Figure 2 The pitch control system of the grid-connected PMSG wind turbine shown includes a fuzzy PID controller. Based on the fact that the wind turbine can operate continuously at 110% of its rated current (i.e., 1.1 times its rated power) for extended periods, a pitch control system with multiple feedback compensation modes is established. When the wind turbine's output power is 1.1 times or less of its rated power, a single power feedback compensation mode is used; when the output power exceeds 1.1 times its rated power, a combined power-speed feedback compensation mode is used. Different feedback compensation control modes correspond to different input data for the pitch control system.

[0059] The input data to the pitch control system is the error data between the obtained operating state and rated state of the PMSG wind turbine. This error data includes the error and rate of change between the rated power and output power of the wind turbine, as well as the error and rate of change between the rated speed and actual speed of the wind turbine. When using the single-power feedback compensation mode, the rated power of the PMSG wind turbine is... P refWith output power P m error e 1 and error change rate ec 1 is used as the input to the fuzzy controller in the single power feedback compensation mode to obtain the PID parameter adjustment; when the power-speed joint feedback compensation mode is adopted, the rated power of the PMSG wind turbine is used. P ref With output power P m error e 2 and the rate of change of error ec 2 serves as the input to the fuzzy controller for power feedback compensation control in the power-speed joint feedback compensation mode; the rated speed of the PMSG wind turbine is used as the input. w ref Compared with actual speed w r error e 3 and error change rate ec 3 serves as the input to the fuzzy controller for speed feedback compensation control in the power-speed joint feedback compensation mode. After undergoing steps such as fuzzification description, fuzzy rule establishment, fuzzy inference, and defuzzification, the fuzzy controller obtains the PID parameter adjustment quantities for power feedback control and speed feedback control, respectively. The PID controller then corrects the PID parameters based on the PID parameter adjustment quantities to achieve better pitch angle adjustment.

[0060] In the above process, the step of the fuzzy controller outputting the PID parameter adjustment amount based on the corresponding input error data specifically includes the following steps:

[0061] S1. Fuzzy Description

[0062] Define the discrete universe of discourse for the input variables, and process the error data based on the discrete universe of discourse to obtain the error ambiguity.

[0063] Specifically, the input to the pitch control system is determined to be the rated power of the wind turbine corresponding to the single-power feedback compensation mode. P ref With output power P m error e 1 and error change rate ec 1. Or the rated power of the wind turbine corresponding to the power-speed joint feedback compensation mode. P ref With output power P m error e 2 and the rate of change of error ec 2 and the rated speed of the wind turbine w ref Compared with actual speedw r error e 3 and error change rate ec 3.

[0064] The fuzzy controller outputs PID parameters and proportional parameters based on the above error data. k p Integral parameters k i and differential parameters k d adjustment amount , and Define input variables e 1, e 2, e 3, ec 1, ec 2, ec The discrete universe of discourse for 3 is {-3, -2, -1, 0, 1, 2, 3}, where the deviation is... e 1, e 2, e The fundamental domain of 3 is [-30, 30], and the quantization factor is... K e =0.1.

[0065] S2. Establish fuzzy rules

[0066] The values ​​of proportional, integral, and derivative parameters in the fuzzy PID controller are determined based on the error fuzziness quantity obtained from the fuzzy description.

[0067] Specifically, in the deviation value e 1, e 2, e When 3 is relatively large, a larger value can be selected. k p To accelerate the system's response speed, if the system's integral action is not limited, integral saturation will occur, leading to excessive overshoot. Therefore, a value of [value missing] is generally chosen. To avoid this situation;

[0068] In deviation value e 1, e 2, e 3 and the rate of change of deviation value ec 1, ec 2, ec 3. For medium-sized items, you can choose the smaller one. k p Value, moderate k i Value and k dThis value ensures that the system response has a small overshoot while maintaining the system's response speed.

[0069] In deviation value e 1, e 2, e When the value of 3 is low and approaching the set value, it can be increased. k p and k i The value, and k d The value of is particularly important for the system's ability to effectively control disturbances, especially in the case of the rate of change of the deviation. ec 1, ec 2, ec When 3 is larger, the smaller value should be selected. k d Value, in the rate of change of deviation value ec 1, ec 2, ec When 3 is smaller, a larger value should be chosen. k d value.

[0070] , and The fuzzy rule tables are shown in Tables 1-3 respectively.

[0071] Table 1 Fuzzy rule table

[0072]

[0073] Table 2 Fuzzy rule table

[0074]

[0075] Table 3 Fuzzy rule table

[0076]

[0077] S3. Fuzzy Reasoning

[0078] A fuzzy relation equation is established based on the values ​​of the proportional, integral, and differential parameters determined by the fuzzy rules. The output fuzzy control quantity is obtained using the error fuzzy quantity. A fuzzy control table is established based on all possible output fuzzy control quantities, and the corresponding output fuzzy control quantity is determined by the table lookup method.

[0079] Based on the fuzzy input of the fuzzy adaptive PID controller, and the set fuzzy relation equation, the output fuzzy control quantity is obtained. The above operation is repeated to obtain all possible output values ​​and establish a fuzzy control table. Then, the corresponding output value can be determined by looking up the table. This method is called the CRI lookup table method, which has the advantages of simple operation and good real-time performance.

[0080] S4. Deblurring

[0081] The weighted average method is used to adjust the output fuzzy control quantity to obtain the defuzzified output control quantity. Based on the defuzzified output control quantity, the adjustment amounts of the proportional, integral, and derivative parameters in the fuzzy PID controller are obtained. The PID parameters are then corrected based on the adjustment amounts of the proportional, integral, and derivative parameters.

[0082] After fuzzy inference, a fuzzy control table is obtained. The control information in the fuzzy control table is complex, and to obtain a precise and clear control quantity, it needs to be defuzzified. This embodiment uses the weighted average method, which considers multiple elements in the fuzzy control table and improves the system's response characteristics by adjusting the weighting coefficients. This method offers greater flexibility and better control performance.

[0083] By obtaining the defuzzified output control quantity, the proportional parameter can be obtained. k p Integral parameters k i Differential parameters k d Adjustment amount:

[0084] ;

[0085] ;

[0086] ;

[0087] In the formula, , , They are , , The initial value can be used to adjust the fuzzy adaptive PID parameters in real time based on the adjustment amount.

[0088] When using single-power feedback compensation mode, the corrected PID controller compares the output power with the rated power to output the pitch angle. When using the power-speed joint feedback compensation mode, the corrected PID controller can obtain the pitch angle by comparing the output power with the rated power. By comparing the actual rotational speed with the rated rotational speed, the pitch angle can be obtained. . Figure 2 The pitch control system of the grid-type PMSG wind turbine shown can adjust the output power of the wind turbine according to the pitch angle of the corresponding feedback compensation control mode, and realize emergency control of the PMSG wind turbine in strong wind conditions.

[0089] The emergency control method based on PMSG wind turbines in this embodiment uses a switching feedback control compensation strategy for the pitch control system, which can adjust the pitch angle control method according to different output power, resulting in faster control speed. For the PID parameters in the pitch angle control, a fuzzy controller is used to adaptively correct the PID parameters, which can make the pitch angle adjustment more accurate. This solves the problem of fixed parameters in traditional PID controllers.

[0090] Example 2

[0091] An emergency control method and device based on a PMSG wind turbine differs from Embodiment 1 in that:

[0092] Build as Figure 3 The pitch control system of the grid-connected PMSG wind turbine shown includes a fuzzy PID controller, and the whale algorithm is used to optimize the parameters of the fuzzy PID controller, including the error parameters of the fuzzy PID controller. k e Error change rate parameter k ec proportional parameters k p Integral parameters k i Differential parameters k d ;

[0093] In the whale algorithm, the error parameters in the fuzzy PID controller are... k e Error change rate parameter k ec proportional parameters k p Integral parameters k i Differential parameters k d Corresponding to the location of the whale.

[0094] The speed and accuracy of regulation are improved after adding fuzzy control to the traditional PID controller. The whale algorithm is used to optimize the parameters in the fuzzy PID controller, which can further improve the regulation effect.

[0095] The whale algorithm is similar to intelligent optimization algorithms, and it has the advantages of few parameter settings, simple operation, easy implementation, and strong optimization ability. Its steps are as follows:

[0096] Set the initial population size and maximum number of iterations; and adjust the error parameters in the fuzzy PID controller. k e Error change rate parameter k ec proportional parameters k p Integral parameters k i Differential parameters k d Corresponding to the location of the whale;

[0097] Set the upper and lower bounds of the parameter;

[0098] The fitness function is determined by using the ITAE index, which measures the performance of the control system, as the fitness function. Its expression is as follows: In the formula, It represents the value of the fitness function; t represents time. This is the absolute error;

[0099] Run the whale optimization algorithm and output the 5 optimized parameters (which are respectively ( k e , k ec , k p0 , k i0 , k d0 The value of ); through sim The function inputs the values ​​of the five parameters obtained by the whale algorithm into the simulation model of the wind turbine generator system, and evaluates the optimized parameters through the fitness function; if the maximum number of iterations is reached, the global optimal solution is output.

[0100] In this embodiment, the whale algorithm is set to a population size of 10, a maximum number of iterations of 20, and a population dimension of 5; the optimization range of the parameters is set as follows: , , , , See also Figure 4 The iteration curve of the fuzzy PID controller was optimized for the Whale Algorithm. After simulation, the iteration curve showed that the fitness value of WOA converged and reached the optimum after 7 iterations.

[0101] The optimal solution obtained by the whale algorithm is input into the fuzzy controller in the fuzzy PID controller. Based on this, the fuzzy controller obtains the PID parameter adjustment amount according to the error data of the corresponding feedback compensation control mode. The PID controller corrects the PID parameter based on the PID parameter adjustment amount, and the corrected PID controller outputs the pitch angle corresponding to the feedback compensation control mode. The variable pitch control system adjusts the output power of the wind turbine according to the pitch angle output by the fuzzy PID controller to realize emergency control of the PMSG wind turbine in high wind conditions.

[0102] Example 3

[0103] Build as Figure 5 The pitch control system of the grid-connected PMSG wind turbine shown is based on the fact that the wind turbine can operate continuously at 110% of its rated current for a long time, that is, at 1.1 times its rated power. A pitch control system with multiple feedback compensation control modes is established. When the output power of the wind turbine is 1.1 times the rated power or less, a single power feedback compensation mode is adopted. When the output power is greater than 1.1 times the rated power, a power-speed combined feedback compensation mode is adopted. The pitch control system of different feedback compensation control modes corresponds to different input data.

[0104] When using a single-power feedback compensation mode, the pitch angle can be obtained by comparing the output power and the rated power. When using a power-speed combined feedback compensation mode, the pitch angle can be obtained by comparing the output power and the rated power. By comparing the actual rotational speed with the rated rotational speed, the pitch angle can be obtained. When the output power of the wind turbine is different, different pitch angle control methods can be switched, which has a faster adjustment speed than the traditional pitch angle control strategy.

[0105] Pitch angle , and Calculate according to the following formulas respectively:

[0106] ;

[0107] ;

[0108] ;

[0109] in, , and This is the proportionality coefficient; , and The integral coefficient; This refers to the output power of the wind turbine generator; This refers to the rated power of the wind turbine generator set; This refers to the actual rotational speed of the wind turbine. This refers to the rated speed of the wind turbine.

[0110] When the output power of the wind turbine is different, different pitch angle control methods can be switched, which has a faster adjustment speed than the traditional pitch angle control strategy.

[0111] Simulation Example

[0112] Based on the emergency control methods for PMSG wind turbines described in Examples 1-3, simulation models of the wind turbine system were established. The simulation models included wind speed jumps at 6s and 11s to simulate strong winds encountered by grid-connected PMSG wind turbines. From 0s to 6s, the wind speed was 11m / s; from 6s to 11s, it was 14m / s; and from 11s to 16s, it was 25m / s. The rated wind speed of the grid-connected PMSG wind turbine is 11m / s, the cut-off wind speed is 25m / s, and the rated power is 2MW.

[0113] The output power of the wind turbine base can be obtained using wind speed, calculated according to the following formula:

[0114] ;

[0115] in: This refers to the power output of the fan. air density (kg / m³) 3 ); The area swept by the wind turbine (m²) 2 ); v The actual wind speed (m / s); C p Wind energy utilization coefficient; As an intermediate variable; The tip speed ratio; The pitch angle is (°). R t The radius of the wind turbine blade is (m). The blade rotational angular velocity is ω (rad / s).

[0116] Therefore, the ratio of the output power to the rated power of the wind turbine can be determined based on the actual wind speed and the rated wind speed. In other words, the feedback compensation control mode of the pitch control system can be determined based on the actual wind speed and the rated wind speed.

[0117] The pitch angle remains relatively stable at 3° between 1s and 6s. At 6s, the wind speed jumps to 14m / s, exceeding the rated wind speed. Based on the relationship between wind speed and output power, the wind turbine's output power is greater than 1.1 times the rated power. Pitch angle control aims to maintain the output power at the rated power; therefore, the pitch angle is increased. (See [reference needed]). Figure 6 Under the three different control strategies in Examples 1-3, the pitch angle first increases and then decreases. It can be seen that the variable pitch control system in Example 2, under the fuzzy PID control based on the improved whale algorithm, has a small overshoot of pitch angle and is more accurate and faster. In the variable pitch control system in Example 1, the speed of the fuzzy PID control increasing and then decreasing is also faster than that of the traditional PID control in Example 3, and finally stabilizes at about 6.2°. At the 11th second, the wind speed jumps to 25m / s, which is the cutoff wind speed. At this time, the wind turbine should cut off and the output power is 0. At this time, the pitch angle control system no longer works, so it remains unchanged at the original angle.

[0118] See Figure 7 The output power variation curves of the grid-type PMSG wind turbine under three different variable pitch control systems in Examples 1-3 are shown.

[0119] The output power of the grid-connected PMSG wind turbine basically stabilizes at 2MW between 1s and 6s. At 6s, the wind speed jumps to 14m / s, which exceeds the rated wind speed. After pitch angle control, the output power should continue to be maintained at the rated power. Therefore, the output power is reduced by increasing the pitch angle. Under the three different variable pitch control systems, the variation law of the grid-connected PMSG wind turbine is different. In Example 2, the variable pitch control system under the fuzzy PID control based on the whale algorithm shows a slight fluctuation in output power, which is basically around 2MW. In Example 1, the variable pitch control system under the fuzzy PID control first increases and then decreases. The overshoot is smaller than that of the traditional PID control strategy, and the speed when it recovers to 2MW is faster than that of the traditional PID control strategy in Example 3. Finally, it stabilizes at 2MW, which takes about 2.2s. At 11s, the wind speed jumps to 25m / s, which is the cutoff wind speed. The wind turbine should cut off and the output power is 0. It can be seen that the output power is also 0 at this time, and the wind turbine has successfully cut off.

[0120] Example 4

[0121] An emergency control method device based on PMSG wind turbine, comprising:

[0122] The data acquisition module is used to obtain error data between the operating status and the rated status of the wind turbine.

[0123] The feedback compensation module is used to input error data into the pitch control system, which has multiple feedback compensation control modes. The feedback compensation control mode is determined from the multiple feedback compensation control modes based on the error data. The pitch control system includes a fuzzy PID controller. The fuzzy PID controller outputs the pitch angle based on the error data corresponding to the determined feedback compensation mode.

[0124] The control and execution module is used by the pitch control system to adjust the output power of the wind turbine according to the pitch angle output by the fuzzy PID controller.

[0125] Example 5

[0126] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the emergency control method based on PMSG wind turbines described in Embodiment 1 or Embodiment 2 above.

[0127] Example 6

[0128] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the emergency control method based on a PMSG wind turbine as described in Embodiment 1 or Embodiment 2 above.

[0129] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An emergency control method based on PMSG wind turbine generators, characterized in that, Includes the following steps: Obtain error data between the operating status and rated status of the wind turbine; Error data is input into the pitch control system, which has multiple feedback compensation control modes. These modes include a single power feedback compensation mode and a power-speed combined feedback compensation mode. When the wind turbine's input power is less than or equal to 1.1 times its rated power, the single power feedback compensation mode is used; when the wind turbine's input power is greater than 1.1 times its rated power, the power-speed combined feedback compensation mode is used. The power error is determined from the error data, and the feedback compensation control mode is determined based on this power error. The power error is the deviation between the wind turbine's rated power and output power. The error data also includes the error rate of change between the wind turbine's rated power and output power, as well as the error and error rate of change between the wind turbine's rated speed and actual speed. The error data corresponding to the single power feedback compensation mode includes the error and error rate of change between the wind turbine's rated power and output power; the error data corresponding to the power-speed combined feedback compensation mode includes the error and error rate of change between the wind turbine's rated power and output power, as well as the error and error rate of change between the wind turbine's rated speed and actual speed. The pitch control system includes a fuzzy PID controller; The fuzzy PID controller outputs the propeller pitch angle based on the error data corresponding to the determined feedback compensation mode. The variable pitch control system adjusts the output power of the wind turbine based on the pitch angle output by the fuzzy PID controller.

2. The emergency control method based on PMSG wind turbine according to claim 1, characterized in that, The step of the fuzzy PID controller outputting the propeller pitch angle based on the error data corresponding to the determined feedback compensation mode includes: The error data is input into the fuzzy controller corresponding to the feedback compensation control mode, and the fuzzy controller outputs the PID parameter adjustment amount. The PID controller corrects the parameters based on the PID parameter adjustment and outputs the pitch angle based on the error data.

3. The emergency control method based on PMSG wind turbine according to claim 1, characterized in that, The parameters of the fuzzy PID controller are optimized using the whale algorithm. These parameters include the error parameter, error rate of change parameter, proportional parameter, integral parameter, and derivative parameter of the fuzzy PID controller. In the whale algorithm, the error parameters, error rate of change parameters, proportional parameters, integral parameters, and derivative parameters of the fuzzy PID controller are correlated with the position of the whale.

4. The emergency control method based on PMSG wind turbine according to claim 3, characterized in that, In the whale algorithm, the ITAE metric, which measures the performance of the control system, is used as the fitness function.

5. An emergency control method and device based on PMSG wind turbine generators, characterized in that, include: The data acquisition module is used to obtain error data between the operating status and the rated status of the wind turbine. A feedback compensation module is used to input error data into the pitch control system, which has multiple feedback compensation control modes. These modes include a single power feedback compensation mode and a power-speed combined feedback compensation mode. When the wind turbine input power is less than or equal to 1.1 times its rated power, the single power feedback compensation mode is used; when the wind turbine input power is greater than 1.1 times its rated power, the power-speed combined feedback compensation mode is used. The module determines the power error from the error data and then determines the feedback compensation control mode based on this error. The power error is the deviation between the wind turbine's rated power and its output power. The error data also includes... The error data includes the rate of change between the rated power and output power of the wind turbine, as well as the error and rate of change between the rated speed and actual speed of the wind turbine; the error data corresponding to the single power feedback compensation mode includes the error and rate of change between the rated power and output power of the wind turbine; the error data corresponding to the power-speed joint feedback compensation mode includes the error and rate of change between the rated power and output power of the wind turbine, as well as the error and rate of change between the rated speed and actual speed of the wind turbine; the variable pitch control system includes a fuzzy PID controller; the fuzzy PID controller outputs the pitch angle according to the error data corresponding to the determined feedback compensation mode; The control and execution module is used by the variable pitch control system to adjust the output power of the wind turbine according to the pitch angle output by the fuzzy PID controller.

6. An electronic device, characterized in that, It includes a processor and a memory, the processor being used to execute a computer program stored in the memory to implement the emergency control method based on a PMSG wind turbine as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction, which, when executed by a processor, implements the emergency control method based on a PMSG wind turbine as described in any one of claims 1 to 4.

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