CN108678902A - The straight disturbance sensing control method for driving PMSM wind generator systems MPPT - Google Patents

Abstract

Aiming at the problem that the traditional PID is difficult to set the parameters, the various improved PIDs have a large amount of calculation and the problem of poor anti-disturbance ability, the problem of high-frequency chattering in the sliding mode control (SMC) and the calculation amount in the active disturbance rejection control (ADRC) Too large, too many gain parameters, etc., the present invention proposes a "disturbance-aware control method for direct-drive PMSM wind power generation system MPPT". The controller parameter of the present invention has a large margin, and not only has the characteristics of small calculation amount, high control precision, strong anti-disturbance ability, etc., but also has the characteristic of global asymptotic stability. Especially when the external environment changes drastically, there is no need for online stabilization gain parameters, which completely subverts the control strategies of classical control theory and modern control theory. The invention has great theoretical significance and application value for realizing the MPPT control of the direct-drive PMSM wind power generation system.

Description

Disturbance-aware control method for direct-drive PMSM wind power generation system MPPT

technical field

Wind power generation system, motor operation and control.

Background technique

Wind energy, as one of the green energy with the most economic value in today's society, has been widely concerned and vigorously developed by countries all over the world. With the increasing installed capacity of permanent magnet direct drive wind power generation systems, how to reliably and effectively utilize wind energy has become a research hotspot in wind power generation technology. Large-scale machine and intelligent control technology are two major development trends of wind power generation system today. Maximum power point tracking (MPPT) is the most widely used technology for wind turbine control. At present, regarding the maximum power point tracking control, scholars at home and abroad have successively proposed algorithms such as the optimal tip speed ratio method, the power signal feedback method, the hill-climbing search method, the optimal torque method, and related improved algorithms, but these algorithms are not used in engineering applications. There are varying degrees of defects. In actual engineering, most operating units still use the optimal torque method based on the maximum power curve, that is, according to the set power curve of the unit (or made into a discrete table), the speed is used to control the unit. This control algorithm has a simple structure and is easy to operate. Stable, high reliability, more suitable for the current large-scale wind turbines. However, it is not easy to obtain the relevant curve of the actual unit accurately, and at the same time, changes in external environmental factors can easily change the actual operating curve to a large extent, which will affect the output power of the unit and reduce the power generation efficiency of the unit. Therefore, it is urgent to construct a new tracking control method with simple structure, easy parameter stabilization, good dynamic quality and strong anti-disturbance ability. This method determines the expected angular velocity of the fan with the best blade tip speed ratio and wind speed, or determines the expected angular velocity of the fan through the actual operating power of the PMSM, and obtains the q-axis command current by controlling the fan speed Then the command voltage is obtained through the current control link and In order to realize MPPT control.

Contents of the invention

Under the rated wind speed, first determine the expected speed of the fan according to the optimal blade tip speed ratio and wind speed, or determine the expected speed of the fan through the actual operating power of the PMSM (which can be calculated), and obtain q through the control of the fan speed Shaft command current Then the command voltage is obtained through the current control link and In order to realize the tracking control of the maximum power point. The outstanding advantages of the "disturbance-aware control method for MPPT of a direct-drive PMSM wind power generation system" of the present invention mainly include: (1) global asymptotic stability; (2) parameter-free stabilization; (3) simple structure and large amount of calculation Small size, good real-time performance; (4) Dynamic qualities such as fast response, no chattering, and strong anti-disturbance ability.

Description of drawings

Figure 1 Expected speed tracking differentiator (Tracking Differentiator, TDm)

Fig.2 DOm of speed loop disturbance observer

Figure 3 Disturbance Perception Controller (Disturbance Perception Controller, DPC), (a) speed loop disturbance perception controller (DPCm), (b) d-axis stator current disturbance perception controller (DPCd), (c) q-axis stator current disturbance Perception Controller (DPCq)

Fig. 4 Direct drive PMSM wind turbine MPPT disturbance perception controller (MPPT-DPC)

Fig. 5 Schematic diagram of MPPT control system of direct-drive PMSM wind turbine

Fig. 6 Simulation results of MPPT control of direct-drive PMSM wind turbine at a wind speed of 7 m/s, (a) speed tracking control curve, (b) q-axis stator current i _q change curve, (c) wind turbine output torque T _m and Generator electromagnetic torque T _e change curve, (d) wind energy utilization coefficient C _p curve

Fig. 7 At the time of 2.5s, when the wind speed drops from 7m/s to 6m/s, the MPPT control simulation results of PMSM wind turbines, (a) speed tracking control curve, (b) q-axis stator current i _q change curve, (c ) change curve of wind turbine output torque T _m and generator electromagnetic torque T _e , (d) wind energy utilization coefficient C _p curve

Figure 8 In the case of rated random wind speed, when there is an extreme situation of wind speed mutation, the control simulation results of direct drive PMSM wind turbine MPPT, (a) random wind speed curve of wind speed mutation, (b) speed tracking control curve, (c) q-axis stator current i _q change curve, (d) wind turbine output torque and generator electromagnetic torque change curve, (e) wind energy utilization coefficient curve

Detailed ways

1. How to obtain the expected speed of the wind turbine

(1) Wind turbine output characteristics

The mechanical energy output by the wind turbine is

P _m =0.5ρπR ² C _p v ³ (1)

C _p =0.5176(116/β-0.4θ-5)exp(-21/β)+0.0068λ (2)

In the formula, P _m is the power of the wind turbine; C _p is the wind energy utilization coefficient; λ is the tip speed ratio; θ is the pitch angle; v is the wind speed. Define the tip speed ratio λ as

In the formula, ω _m is the rotor speed of the wind turbine (rad/s); R is the radius of the blade of the wind turbine.

It can be seen from formula (2) that C _p is a nonlinear function about λ and θ, and at the rated wind speed, θ=0 is usually set, therefore, C _p is only related to λ. It can be known by calculation that when λ=λ _opt =8.1, C _p =C _pmax =0.488. At this time, the maximum power obtained by the wind turbine is:

P _max ＝0.5ρπR ² C _pmax v ³ (5)

From the definition of the tip speed ratio in formula (4), it can be seen that when the optimal tip speed ratio λ=λ _opt =8.1, the desired speed of the wind turbine is:

Therefore, theoretically, the maximum output mechanical torque T _m of the wind turbine is

or

(2) MPPT control of direct drive PMSM wind power system

When the wind power generation system is running, it is necessary to control the speed of the wind turbine, that is, when the electromagnetic torque T _e , mechanical torque T _m and viscous friction torque Bω _m satisfy the condition: T _m -T _e -Bω _m =0, the wind power system into steady state. When ignoring the viscous friction moment _Bωm , the expected speed of the wind turbine can be defined as

in, (constant), and

T _e ＝1.5p _n i _q [i _d (L _d -L _q )+ψ _f ] (10)

Under the synchronous rotating coordinate system d-q, the mathematical model of PMSM is:

The physical meaning of each parameter: u _d , u _q are the dq-axis components of the stator voltage; id and i _q are the _dq -axis components of the stator current; L _d , L _q are the dq-axis inductance components (H); R _s is the stator resistance; ψ _f is the flux linkage of the rotor permanent magnet (Wb); ω _m is the mechanical angular velocity of the fan (rad/s), and the electrical angular velocity ω _e of the motor is ω _e = p _n ω _m ; p _n is the pole Logarithm; T _m is the fan torque (Nm); B is the damping coefficient (Nms); J is the moment of inertia (kgm ² ).

It can be seen from formula (10) and formula (11) that the direct-drive PMSM wind turbine is a typical MIMO nonlinear strong coupling object. Among them, u _d and u _q are the control input of the system, T _m is the external wind energy disturbance input; i _d , i _q and ω _m are the state output of the system respectively. For the convenience of theoretical analysis, the constant parameter is defined as: b ₀ =-1.5p _n ψ _f /J, and the related disturbance components are: d ₁ = (p _n L _q i _q ω _m -R _s i _d )/L _d , d ₂ =-(p _n L _d i _d ω _m +p _n ψ _f ω _m +R _s i _q )/L _q , d ₃ =[T _m -Bω _m -1.5p _n i _d (L _d -L _q )]/J, the system (11) can be defined as a disturbance system:

Wherein, |d ₁ |<∞, |d ₂ |<∞, |d ₃ |<∞.

Considering that there are measurement errors in the state quantities of PMSM, there are uncertainties in the disturbance components d ₁ , d ₂ and d ₃ , therefore, how to apply effective control to the disturbance system (12) is the core technology of the present invention, that is, the MPPT Disturbance-aware control technology.

2. Tracking Differentiator (TD)

When the wind speed changes randomly at the rated wind speed, in order to realize the maximum power point tracking of wind energy, the expected speed of the fan is required to respond quickly, or in other words, the expected speed of the fan is required to be able to follow the change of the wind speed. Since the expected speed of the fan is a time-varying physical quantity, and the differential information of the expected speed needs to be obtained when controlling the fan speed. Considering that the specific mathematical model of the fan's expected speed cannot be known with certainty, it is difficult to obtain the differential information of the expected speed through traditional methods. For this reason, the present invention uses the tracking differentiator technology to obtain the tracking signal and its differential signal of the expected speed of the fan. On the one hand, it can effectively solve the difficult problem of obtaining the differential information of the expected speed of the fan. The contradiction between rapidity and overshoot. The specific method is as follows:

(1) Tracking differentiator technology

Let the expected angular velocity of the fan be and v ₁ and v ₂ are respectively The tracking signal and differential signal of , define the tracking error as Then the corresponding tracking differentiator (TDm) model is:

Among them, z _v >0 is the gain coefficient of TDm, as shown in Fig. 1 .

(2) Stability analysis of tracking differentiator

Theorem 1. Assume that the expected acceleration of the wind turbine is bounded: Then if and only if z _v >0, the desired rotational speed tracking differentiator (13) is globally asymptotically stable.

Proof: According to the speed tracking error And combined with (13), we can get: Therefore there are

Assume Take the Lass transform of formula (14), that is:

Considering: V ₂ (s) = sV ₁ (s), therefore, Substituting into formula (15), we get: which is

Since the system (16) is a rotation speed signal at the desired speed The error dynamic system under excitation, according to the signal and system complex frequency domain analysis theory, when z _v >0, the error dynamic system (16) is globally asymptotically stable, therefore, as long as Then there are: Therefore, it is expected that the rotational speed tracking differentiator (13) is globally asymptotically stable. Depend on It can be seen that when t→∞, there are: Figure 1.

3 Speed loop disturbance state estimation

(1) Speed loop state observer

The rotational speed ω _m and the disturbance d ₃ are estimated using z ₃₁ and z ₃₂ , respectively. Suppose the observation error is: e _zm = z ₃₁ -ω _m , then the corresponding disturbance observer DOm is:

Wherein, z _o >0, so that z ₃₁ ≈ω _m , z ₃₂ ≈d ₃ , as shown in FIG. 2 .

(2) Stability analysis of speed loop state observer

Theorem 2. Assuming that the disturbance state of the speed loop is bounded: |d ₃ |<∞, then the disturbance observer (17) is globally asymptotically stable if and only if zo>0.

Proof: According to the third formula of formula (17) and formula (12), the state observation error system can be obtained as:

Assume Take the Lass transform of formula (19) and sort it out, we get

The perturbed observation error system shown in Eq. (20) is an observation error dynamical system excited by the perturbed state d ₃ , if the perturbed state is bounded: |d ₃ |<∞, then if and only if z _o >0 When , the error system (20) is globally asymptotically stable, and The disturbance observer (17) is thus globally asymptotically stable.

4. Design of Disturbance Perception Controller (MPPT-DPC) for MPPT

For the control problem of direct-drive PMSM wind turbines, the outer loop is set for speed control, the inner loop is for current control, and the expected current of the d-axis of the inner loop is usually set to zero, that is,

(1) Design of speed loop disturbance-aware controller (DPCm)

Suppose the actual mechanical angular velocity of the direct-drive PMSM wind power system is ω _m , since the expected angular velocity of the wind turbine is a time-varying physical quantity, the present invention uses TD to estimate the expected angular velocity To track and obtain the corresponding differential information, namely Therefore, the fan angular velocity tracking control error can be expressed as:

e _m =v ₁ -z ₃₁ (21)

According to the third formula of system (12), the differential signal with tracking error is:

Obviously, formula (22) is a first-order disturbance error system (Disturbance Error dynamics System, DEDS). Taking the state quantity i _q (q-axis current) of the third formula in the disturbance system (12) as the virtual control quantity of the speed control link, in order to make DEDS globally asymptotically stable, define the expected command of the q-axis current i _q for:

Among them, z _m > 0, z _o > 0, e _zm = z ₃₁ −ω _m . The speed loop disturbance-aware controller (DPCm), as shown in Figure 3(a).

because and The dq-axis current expectation commands are provided for the PMSM inner-loop current control link respectively, thus laying a theoretical foundation for the design of the inner-loop current controller, which are introduced as follows:

(2) Design of d-axis current disturbance sensing controller (DPCd)

Set the d-axis current tracking control error of the inner ring as: Combined with the first formula of system (12), the differential signal of the error is:

Obviously, formula (24) is a first-order disturbance error system (DES). The d-axis disturbance-aware control law is defined as:

Among them, z _d > 0, The d-axis current disturbance sensing controller (DPCd), as shown in Figure 3(b).

(3) Design of q-axis current disturbance sensing controller (DPCq)

Set the inner ring q-axis current tracking control error as:

Combined with the second formula of system (12), the differential signal of the error is:

The q-axis current disturbance-aware control law is defined as:

Among them, z _q > 0, The q-axis current disturbance sensing controller (DPCq), as shown in Figure 3(c).

TDm, DPCm, DPCd and DPCq are integrated together to form a direct-drive PMSM wind turbine MPPT disturbance-aware controller (MPPT-DPC), as shown in Figure 4.

5. Stability analysis of disturbance-aware control system

In order to ensure the stability of the direct-drive PMSM wind power control system, the speed loop disturbance-aware controller (DPCm), the d-axis current disturbance-aware controller (DPCd) and the q-axis current disturbance-aware controller (DPCq) are all required to be stable. In the following, the stability of the three disturbance-aware controllers is analyzed theoretically.

(1) Stability analysis of the d-axis current disturbance sensing controller (DPCd)

Theorem 3. Assuming that the disturbance d ₁ is bounded: |d ₁ |<∞, then if and only if z _d >0, the d-axis current disturbance-aware controller (DPCd) shown in equation (25):

is globally asymptotically stable. Among them, tracking control error _{ed = -i d ,} L _d is the d-axis inductance component.

Proof: substituting the d-axis current disturbance-aware control law (25) into the disturbance error system (DES) shown in formula (24), that is:

Assume considering Taking the Lass transformation of formula (29) and sorting it out, we get

Equation (30) is an error dynamical system excited by _a disturbance d1. Obviously, as long as |d ₁ |<∞, the error dynamic system (30) is globally asymptotically stable if and only if z _d >0, namely: Therefore, the d-axis current disturbance-aware controller (DPCd) shown in equation (25) is globally asymptotically stable, and the proof is completed.

(2) Stability analysis of q-axis current disturbance sensing controller (DPCq)

Theorem 4. Assuming that the differential of the q-axis desired current is bounded: And the disturbance d ₂ is bounded: |d ₂ |<∞, then if and only if the gain parameter z _q >0, the q-axis current disturbance-aware controller (DPCq) shown in equation (28):

is globally asymptotically stable.

in, L _q is the q-axis inductance component.

Proof: Substituting the q-axis current disturbance-aware control law u _q (28) into the disturbance error system (DES) shown in equation (27), we get:

Assume if then there is reset considering Taking the Lass transformation of formula (31) and sorting it out, we get

Equation (32) is a bounded disturbance Excited error dynamics system. Obviously, as long as |d ₂ |<∞, so that Then if and only if z _q >0, the error dynamical system (32) is globally asymptotically stable, namely: Therefore, the q-axis current disturbance-aware controller (DPCq) shown in equation (28) is globally asymptotically stable, and the proof is completed.

(3) Stability analysis of the speed loop disturbance-aware controller (DPCm)

Theorem 5. Assumption |d ₂ |<∞, then if and only if z _m >0, the speed loop disturbance-aware controller (DPCm) shown in equation (23):

is globally asymptotically stable. Among them, em = _{v 1} -z ₃₁ , v ₁ is the expected angular velocity of the fan The tracking signal of v ₂ is The differential tracking information of , z ₃₂ is the state estimation value of the disturbance d ₃ , that is, z ₃₂ ≈d ₃ .

Proof: Since the state quantity i _q (q-axis current) of the third formula in the disturbance system (12) is used as the virtual control quantity of the speed control link, the goal of its control is to make the q-axis current i _q track the desired command current From Theorem 4, we can see that as long as and |d ₂ |<∞, then the q-axis current disturbance-aware controller (DPCq) shown in equation (28) is globally asymptotically stable if and only if z _q >0, namely: Therefore, by It can be seen that when t→∞, Substituting it into the disturbance-aware error system shown in equation (22), we get:

Assuming that the initial state of the speed error is: e _m (0)≠0, then the solution of formula (33) is:

and

Obviously, as long as |d ₂ |<∞, then if and only if z _m >0, and It shows that the speed error can approach the origin from any initial point that is not zero, that is Moreover, the larger z _m is, the faster the speed error approaches the origin from any initial point that is not zero. Therefore, the speed loop disturbance-aware controller (DPCm) shown in equation (23) is globally asymptotically stable, Certificate completed.

6. Gain parameter stabilization method of direct drive PMSM wind power MPPT control system

Since the direct-drive PMSM wind power MPPT control system includes not only the speed-loop disturbance-aware controller (DPCm) and the current-loop disturbance-aware controllers DPCd and DPCq, but also includes functional components such as tracking differentiator and speed-loop disturbance observer, so a total of 5 A gain parameter needs to be stabilized. Although Theorem 1~Theorem 5 respectively prove that: when z _v >0, the tracking differentiator of the expected speed is globally asymptotically stable; when z _o >0, the speed loop disturbance observer is globally asymptotically stable; when When |d _i |<∞(i=1,2,3), and z _d >0, z _q >0, z _m >0, both the current loop controller and the speed loop controller are globally asymptotically stable, This shows that the relevant gain parameters of the patent of the present invention have a large adjustment margin. However, in addition to ensuring global asymptotic stability, it is also required that the tracking differentiator, disturbance observer, current loop controller and speed loop controller all have fast response speed and high tracking accuracy, or high observation accuracy, or high tracking control accuracy. Therefore, the relevant five parameters are required to be selected within the optimal range, too small will reduce the response speed, and too large will cause oscillation. Let h be the integral step size, and the relevant gain parameters are set as follows:

(1) z _d =z _q =z _m =z _c , where, 700≤z _c ≤1000;

(2) _{100≤zv≤500} ;

(3) z _o =1/(2h).

7. Simulation experiment and analysis of direct-drive PMSM wind power control system

In order to verify the effectiveness of the "disturbance-aware control method for direct-drive PMSM wind power generation system MPPT" of the present invention, the following simulation experiments are carried out. The schematic diagram of the MPPT control system of the direct-drive PMSM wind turbine is shown in Figure 5, and the influence of the PWM inverter is ignored in the simulation experiment. The relevant simulation conditions are set as follows:

(1) Three-phase PMSM related parameters

p _n = 40, L _d = L _q = 5mH, R _s = 0.01Ω, ψ _f = 0.175Wb, J = 0.05kgm ² , B = 0.008Nms;

(2) Fan related parameters

Blade radius R=5m, air density ρ=1.29kg/m ³ , pitch angle β=0;

(3) Related parameters of the disturbance-aware control system

Assuming the integration step size h=1/4000, z _d =z _q =z _m =850; z _v =300; z _o =1/(2h).

Example 1. When the wind speed is 7m/s, the curves of permanent magnet synchronous generator speed ω _m , quadrature axis current i _q , wind turbine output torque T _m , generator electromagnetic torque T _e , and wind energy utilization coefficient C _p are shown in the figure 6. Fig. 6 shows that the control method of the present invention not only has fast response speed and high steady-state tracking accuracy, but also the maximum wind energy utilization coefficient C _pmax of the wind turbine reaches 0.483.

Example 2. At the moment of 2.5s, when the wind speed suddenly drops from 7m/s to 6m/s, the permanent magnet synchronous generator speed ω _m , quadrature axis current i _q , wind turbine output torque T _m and generator electromagnetic torque T _e , wind energy utilization coefficient C _p and other curves are shown in Figure 7. Fig. 7 further shows that the control method of the present invention not only has fast response speed, but also has high steady-state tracking precision, and the maximum wind energy utilization coefficient C _pmax of the wind turbine reaches about 0.483. Fig. 7 verifies that the MPPT control method of the present invention has fast tracking performance and high tracking accuracy in extreme cases of sudden wind speed changes.

Example 3. In the extreme case of rated random wind speed and sudden change of wind speed, random wind speed v, permanent magnet synchronous generator speed ω _m , quadrature axis current i _q , wind turbine output torque T _m and generator electromagnetic torque T _e . Curves such as wind energy utilization coefficient _Cp are shown in Figure 8. Fig. 8 further shows that the control method of the present invention not only has fast response speed and high steady-state tracking precision, but also the maximum wind energy utilization coefficient C _pmax of the wind turbine can reach 0.478-0.488. Fig. 8 verifies that the MPPT control method of the present invention has fast tracking performance and high tracking accuracy in the extreme case of random wind speed mutation.

8. Conclusion

PID controller, sliding mode controller (SMC) and active disturbance rejection controller (ADRC) based on cybernetics strategy (elimination of error based on error) are the three mainstream controllers widely used in the field of control engineering. However, the gain parameters of the traditional PID controller change with the change of the working condition, lack of anti-disturbance ability, so there is difficulty in parameter stabilization; and the strong anti-disturbance ability of the sliding mode controller (SMC) is achieved by sacrificing the dynamic quality of the system Therefore, there is an irreconcilable contradiction between the anti-disturbance ability and high-frequency chattering; although the ADRC has a strong anti-disturbance ability, however, the controller involves many parameters, and some Some nonlinear smooth functions have the problem of large amount of calculation. The disturbance-aware controller (DPC) of the present invention combines the respective advantages of the three mainstream controllers, and not only has the characteristics of fast response speed, high control precision, good robustness and stability, and strong anti-disturbance ability, but also has a simple structure, The calculation amount is small, the gain parameter has a large adjustment margin, and in the extreme case of a sudden change in the working condition, there is no need to re-stabilize the gain parameter. The simulation results of three examples show that under the working conditions of completely different wind speeds, the disturbance-aware controller (DPC) with the same gain parameters has realized the effective control of the direct drive PMSM wind power generation system MPPT, thus verifying the theoretical analysis of the present invention correctness.

The invention has important theoretical and practical significance for realizing the MPPT control of the direct drive type PMSM.

Claims (1)

1. The invention relates to a disturbance perception control method of a direct-drive PMSM wind power generation system MPPT, which is characterized by comprising the following steps:

1) since the desired angular velocity of the wind turbine is a time-varying physical quantity, the invention uses TDm for the desired angular velocity of the wind turbinePerforming tracking and obtaining corresponding differential information, i.e.And (3) performing disturbance estimation on the actual angular speed of the wind turbine by using a disturbance observer Dom, so that the tracking control error of the angular speed of the wind turbine can be expressed as: e.g. of the type_m＝v₁-z₃₁And defining the desired command for q-axis current as:

wherein, z is more than or equal to 700_m≤1000、z_o＝1/(2h)，e_zm＝z₃₁-ω_m。

2) Obtaining a desired command for q-axis current according to 1)Then, a q-axis current tracking error is established asAnd defining the q-axis current disturbance sensing controller as:

wherein, z is more than or equal to 700_q≤1000，L_qIs the q-axis inductance component;

3) according to d-axis current desired valueMay establish a tracking error of e_d＝-i_dDefining the d-axis current disturbance sensing controller as follows:

wherein, z is more than or equal to 700_d≤1000，L_dIs the d-axis inductance component;

4) obtaining desired voltages of d-axis and q-axis from 3) and 2), respectivelyAndthen, according to inverse Park transformation, the synchronous rotation coordinate system can be realizedAndconversion to stationary coordinate systemAndand are provided withAndenergizing the SVPWM to generate a desired pulse width modulated signal; or synchronously rotating the coordinate system according to the inverse Park transformation and the inverse Clark transformationAndv converted to three-phase natural coordinate ABC_a、V_bAnd V_cAnd with V_a、V_bAnd V_cTo excite SVPWM to generate the desired pulse width modulation signal;

5) and 4) after obtaining an expected pulse width modulation signal generated by SVPWM, driving the expected pulse width modulation signal to an inverter so as to obtain the maximum output power from the direct-drive PMSM, thereby realizing the disturbance perception control method of the MPPT of the direct-drive PMSM wind power system.