CN202545109U - Wind generating set optimal control system - Google Patents

Abstract

The utility model discloses an optimal control system of a wind power generating set, which comprises a wind power generating set signal processing subsystem, an optimal control signal execution subsystem and a system state updating subsystem, a wind power generating set signal processing subsystem, an optimal control signal The execution subsystem and the system status update subsystem are connected sequentially. Adopting the technical scheme of the utility model, replacing the PID controller, directly inputting the optimal control signal to the wind turbine, realizing the stability of the system and the tracking of the target reference curve by the system output, and improving the control performance of the wind turbine control system There's important meaning.

Description

An Optimal Control System for Wind Power Generating Sets

technical field

The utility model relates to the technical field of wind power generation, in particular to an optimal control system of a wind power generating set. the

Background technique

The wind turbine control system is the core of the whole wind turbine, which directly affects the performance, efficiency and power quality of the whole wind power system. Wind turbines will be affected by the uncertainty of wind speed and load disturbance during the operation process. For the control system of wind turbines, the controller needs to meet the stability requirements of the control system to achieve a satisfactory control effect, and It can track the target reference curve to make the system achieve the ideal electric power output. the

At present, the control system of wind turbine mainly includes torque control system and pitch control system. These two systems mainly use PID controller, which compares the data observed by the system with a preset reference value, and then The difference obtained after the comparison uses the control algorithm to calculate a new input value, and this new input value can make the output of the system reach the target value. the

应用比例K_P,积分K_I和微分K_D三种控制规律，根据系统状态和参考值状态的差值来调整输入值 得到预期的控制效果。  PID controller:

Three control laws of proportional K _P , integral _KI and differential K _D are applied, and the input value is adjusted according to the difference between the system state and the reference value state to obtain the expected control effect.

For the PID controller in the wind turbine control system, engineering designers need to adjust and design the controller parameters. Enlarging the ratio link will make the system move quickly, respond quickly, and reduce the steady-state error, but if the ratio is too large, the system will increase the number of oscillations, lengthen the adjustment time, and even become unstable. The integral link can eliminate the steady-state error of the system and improve the invariance of the system, but it will slow down the response speed of the system. The differential link can improve the dynamic characteristics of the system, reflect the variation trend of the deviation signal, and introduce an effective early correction signal into the system before the deviation signal becomes too large, thereby speeding up the action speed of the system and reducing the adjustment time. the

To adjust these parameters, it is necessary to consider the dynamic and static requirements of the system and adjust them step by step. There are generally two types of PID parameter adjustment methods: one is the theoretical calculation tuning method, which is mainly based on the mathematical model of the system to determine the controller parameters according to the logarithmic frequency characteristics or root locus characteristics. The second is the engineering setting method, which mainly relies on engineering experience and is carried out directly in the test of the control system. These PID controller parameter adjustment methods have always required repeated adjustments and modifications in actual engineering applications. The workload is heavy and time-consuming, and there is no precise and direct numerical correspondence between parameters and graphics, and most of them need to rely on engineering design. Personnel use their own experience to adjust, and there are certain errors and uncertainties, which bring inconvenience and difficulty to the design of the control system of the wind turbine. the

Utility model content

The purpose of this utility model is to propose an optimal control system for wind power generators, which can directly input optimal control signals to the wind turbines, realize system stability and track the system output to the target reference curve, and improve the control of the wind power generator control system performance. the

For this purpose, the utility model adopts the following technical solutions:

An optimal control system for a wind power generator, including a signal processing subsystem for a wind power generator, an execution subsystem for an optimal control signal, and a system state update subsystem, a signal processing subsystem for a wind power generator, an execution subsystem for an optimal control signal, and a system The status update subsystem is connected sequentially, where,

The wind turbine signal processing subsystem further includes a wind turbine signal measurement sensor and a linearization model processor,

The optimal control signal execution subsystem further includes an optimal control input calculator, a converter and a pitch motor,

The system status update subsystem further includes a status updater,

The output end of the wind turbine signal measurement sensor is connected to the input end of the linearization model processor, the output end of the linearization model processor is connected to the input end of the optimal control input calculator, and the output end of the optimal control input calculator is respectively connected to Converter, pitch motor and status updater connections. the

Adopting the technical scheme of the utility model, replacing the PID controller, directly outputting the optimal control signal to the wind turbine, realizing the stability of the system and the tracking of the target reference curve by the system output, and improving the control performance of the wind turbine control system There's important meaning. the

Description of drawings

Fig. 1 is the structure schematic diagram of the optimal control system of wind power generating set in the specific embodiment of the present invention. the

Fig. 2 is a schematic diagram of an optimal control input calculator in a specific embodiment of the present invention. the

Detailed ways

The technical scheme of the utility model will be further described below in conjunction with the accompanying drawings and through specific embodiments. the

Fig. 1 is a schematic structural diagram of an optimal control system for a wind power generating set in a specific embodiment of the present invention. As shown in FIG. 1 , the wind turbine optimal control system includes a wind turbine signal processing subsystem 1 , an optimal control signal execution subsystem 2 and a system state update subsystem 3 . the

The wind turbine signal processing subsystem, the optimal control signal execution subsystem and the system status update subsystem are connected in sequence. the

Wherein, the signal processing subsystem of the wind power generation unit further includes a wind power generator signal measurement sensor 101 and a linearization model processor 102, and the optimal control signal execution subsystem further includes an optimal control input calculator 201, a converter 202 and a pitch Motor 203 , the system status update subsystem further includes a status updater 301 . the

The output end of the wind power generator signal measurement sensor is connected to the input end of the linearization model processor, the output end of the linearization model processor is connected to the input end of the optimal control input calculator, and the output end of the optimal control input calculator is respectively connected to Converter, pitch motor and status updater connections. the

In the specific embodiment of the utility model, the signal processing subsystem of the wind power generating set is first to install a wind power generator signal measurement sensor on the wind generator to measure and record the rotating speed and the pitch angle signal of the wind power generator. The measured signal is transmitted to the linearization model processor. Through the built-in simulation calculation software, the system parameters are set according to the specific wind turbine, and the model of the wind turbine is linearized to obtain the linearization of the wind turbine within the wind speed range. Model. The structure and dynamic characteristics of each part of the wind turbine are complex, including wind energy characteristics, aerodynamic characteristics of the wind rotor, transmission chain system characteristics, generator characteristics, etc. The entire wind turbine is a high-order nonlinear system, which directly affects the nonlinear It is difficult to design the controller of the system. Through the wind turbine signal measurement sensor and the linearization model processor, the linearization model can be established, and then the optimal control input signal can be obtained. the

y＝Cx+Du表示的风力发电机组线性系统，控制器的性能指标函数可表示为系统状态和控制输入的线性二次型函数。该线性二次函数的最优解可以表示成最小化性能指标函数的解析表达式，实现求解过程的规范化，并可以计算出最优控制参数K和最优控制输入u=Kx，然后将最优输入信号传递给变流器进行转矩控制或者传递给变桨电机进行桨距的控制，构成闭环控制系统，能够兼顾系统稳定性和对目标参考曲线的快速跟踪等多项性能指标，而且主要的数学软件都为该控制器的实验和仿真提供了平台，为实现控制器的参数优化设计提供了方便。  The optimal control signal execution subsystem is first passed through the optimal control input calculator. According to the optimal control theory, for the state space form

For the linear system of the wind power generating set represented by y=Cx+Du, the performance index function of the controller can be expressed as a linear quadratic function of the system state and control input. The optimal solution of the linear quadratic function can be expressed as an analytical expression that minimizes the performance index function, and the solution process can be standardized, and the optimal control parameter K and the optimal control input u=Kx can be calculated, and then the optimal The input signal is transmitted to the converter for torque control or to the pitch motor for pitch control, forming a closed-loop control system that can take into account multiple performance indicators such as system stability and fast tracking of the target reference curve, and the main Mathematics software provides a platform for the experiment and simulation of the controller, and provides convenience for realizing the parameter optimization design of the controller.

The system state update subsystem first transmits the optimal control input signal calculated according to the initial state to the system at the current moment. At the next moment, use the system state updater to use the built-in software to update the state at the next moment as the initial state, and then calculate the optimal control input at the next moment and pass it to the system, and so on, forming a state Feedback closed loop system. the

In the wind turbine signal processing subsystem, the wind turbine signal measurement sensor measures the motor speed and pitch angle signal of the wind turbine, and then the linearization model processor sets it according to the specific parameters of the wind turbine, and at the same time according to the torque The control system and the pitch control system are linearized within the wind speed range, and the state space model of the linear system at each wind speed is obtained:

$\stackrel{\·}{x}=\mathrm{Ax}+\mathrm{Bu},$ y=Cx+Du

The input quantity u of these state space models is the wind speed, the pitch angle control quantity and the generator torque control quantity, the output quantity y is the generator speed and the pitch angle, x is the system state of the wind turbine, A, B, C and D is the system state matrix. the

In the optimal control signal execution subsystem, the state space model of the linear system established by the optimal control input calculator defines a quadratic function

$\mathrm{<span\; class="notranslate">\; J</span>}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; \&Integral;</span>}_{\mathrm{<span\; class="notranslate">\; 0</span>}}^{<span\; class="notranslate">\; \&infin;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; u</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}\mathrm{<span\; class="notranslate">\; Ru</span>}<span\; class="notranslate">\; )</span>$

As a performance index function, the purpose is to calculate the optimal control input through the performance index function to reduce the system output error, so as to achieve the goal of comprehensive optimization of system error and control energy. The first item y ^T y in the performance index function J represents the requirements and restrictions on the system output vector y during the system working process, which is used to constrain the error in the control process and ensure the rapid response of the control system and the accuracy of the terminal output state . The second item u ^T Ru in the performance index function J represents the constraints and requirements on the input of control variables in the dynamic process of the system, where T in y ^T and u ^T represents the transposition of the matrix of y and u, and u is the optimal control Input, the matrix R is a positive definite matrix set according to the control input requirements, and its value is used to reflect the input requirements for adjusting the output to the reference target and the input size of the required control amount. This item can be used to limit the amplitude and smoothness of u , to ensure the safe operation of the system, and also play an important role in limiting the energy consumption of the control process, thereby ensuring the energy efficiency of the system. The goal of optimal control input design is to calculate an optimal control input u to minimize the performance index function J, so as to constrain and limit the output y and the control variable u, obtain the optimal control input, and achieve the stability of the control system Requirements for convergence and tracking of target reference curves. The optimal control input can be expressed as the function of minimizing the performance index:

$\underset{\mathrm{<span\; class="notranslate">\; u</span>}}{\mathrm{<span\; class="notranslate">\; min</span>}}\mathrm{<span\; class="notranslate">\; J</span>}<span\; class="notranslate">\; =</span>{<span\; class="notranslate">\; \&Integral;</span>}_{\mathrm{<span\; class="notranslate">\; 0</span>}}^{<span\; class="notranslate">\; \&infin;</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}\mathrm{<span\; class="notranslate">\; the\; y</span>}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; u</span>}}^{\mathrm{<span\; class="notranslate">\; T</span>}}\mathrm{<span\; class="notranslate">\; Ru</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; .</span>$

When the system is controllable, since the time range included in the performance index function is from zero time to infinity, according to the Bellman optimality theory, the optimal control input exists and is unique, and the optimal control input is:

u=Kx. the

The optimal control parameter K at this time can be obtained by the formula

K=-(B ^T SB+R) ^-1 B ^T SA

Calculated, where S is the Riccati equation:

A ^T SA-SA ^T SB(B ^T SB+R) ^-1 B ^T SA+C ^T C=0

The only positive definite symmetric solution of . The optimal control input u includes the optimal control input at the current moment and the estimation of the optimal control input at the future moment at the current moment. the

Then the optimal control input signal is transmitted to the converter for torque control or to the pitch motor for pitch control to achieve the control effect, as shown in Figure 2. the

In the system state update subsystem, in practical application, according to the initial state x at the current moment and the calculated controller parameter value K, the optimal control input at the current moment is obtained. At the next moment, use the system state updater to update the initial state at the next moment, and then calculate the optimal control input at the next moment, and so on, forming a state feedback closed-loop system. The closed-loop system using the optimal control input is stable and convergent, the dynamic response is fast, and the system output can accurately reach the reference target value. the

需要对三个参数K_P，K_I，K_D进行反复的逐个调节，而本实用新型具体实施方式所设计的最优控制器可以直接给风机输出最优控制信号，执行转矩或者桨距控制，并且能够满足控制系统稳定性和对目标曲线的准确跟踪，保证了风力发电机组控制系统在各个风速下的控制效果。  PID controllers currently used in wind turbines

It is necessary to repeatedly adjust the three parameters K _P , _KI , and K _D one by one, but the optimal controller designed in the specific embodiment of the utility model can directly output the optimal control signal to the fan to perform torque or pitch control , and can meet the stability of the control system and the accurate tracking of the target curve, ensuring the control effect of the wind turbine control system at various wind speeds.

The above is only a preferred embodiment of the utility model, but the scope of protection of the utility model is not limited thereto, any person familiar with the technology can easily think of it within the technical scope disclosed in the utility model Changes or replacements should fall within the protection scope of the present utility model. Therefore, the protection scope of the present utility model should be based on the protection scope of the claims. the

Claims (1)

1. wind power generating set optimal control system; It is characterized in that; Comprise wind power generating set signal processing subsystem, optimal control signal executive subsystem and system mode renewal subtense angle; Wind power generating set signal processing subsystem, optimal control signal executive subsystem and system mode are upgraded subtense angle and are connected successively, wherein

The wind power generating set signal processing subsystem further comprises wind-driven generator signal measurement sensor and linearized model processor,

Optimal control signal executive subsystem further comprises optimal control input calculator, current transformer and change oar motor,

System mode is upgraded subtense angle and is further comprised the state renovator,

Wind-driven generator signal measurement sensor output terminal is connected with the input end of linearized model processor; The output terminal of linearized model processor is connected with the input end of optimal control input calculator, and the output terminal of optimal control input calculator is connected with the state renovator with current transformer, change oar motor respectively.

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