CN103603767B - A kind of extremum search controling parameters self-adapting regulation method based on sliding formwork - Google Patents

Abstract

The present invention relates to an adaptive adjustment method of extreme value search control parameters based on sliding mode, including the following steps: (1) collecting the actual output power p _s at time t (current time) from the generator output terminal every sampling period Δt (t), get the current wind speed from the wind speed measurement device; (2) derive the optimal speed at the current wind speed; (3) calculate the adjustment coefficient γ; (4) adjust the parameters of the extreme value search control based on the sliding mode, if |p _s (t)-p _wmax (t)|>ξ, ξ is a small threshold, then set Z ₀ =Z ₀ ×γ, U ₀ =U ₀ ×γ; otherwise, keep Z ₀ and U ₀ unchanged, t =t+Δt and go to step ②; (5) The control system quickly adjusts the generator speed ω _r to its optimal speed ω _ref through sliding mode motion; (6) Make the output power curve closest to the optimal power curve. The invention automatically adjusts the parameters of the control system according to the current wind speed environment, makes the output power curve closer to the optimal curve, and restores the wind energy utilization coefficient C _p to the maximum value.

Description

A method for adaptive adjustment of control parameters based on sliding mode extreme value search

technical field

The invention belongs to the technical field of double-fed variable-speed constant-frequency wind power generation systems, in particular to an adaptive adjustment method for extreme value search control parameters based on sliding mode.

Background technique

In the past ten years, wind power generation technology has achieved rapid development in the world. The power of a single wind power system has increased from several thousand W in the 1990s to the current 5-6MW. How to maximize the utilization of wind energy within the effective wind speed range and improve the efficiency of wind farms, that is, the problem of tracking and adjusting the maximum wind energy of the wind power system, has always been a hot issue in the regulation and control of wind farm output.

Regarding the problem of tracking the maximum wind energy of wind power systems, researchers at home and abroad have proposed many meaningful algorithms and strategies. The optimal tip speed ratio method is used to achieve maximum wind energy tracking. This method has a simple control principle, but requires real-time and accurate measurement of wind speed, which reduces the control accuracy. The so-called hill-climbing method is used to realize the maximum wind energy tracking of the unit, but the disadvantage of this method is that the accuracy of the controller needs to be further improved. Combining the WRBFN neural network with the hill-climbing algorithm solves the shortcomings of the hill-climbing algorithm's control accuracy, but it can only be applied to direct-drive permanent magnet variable-speed constant-frequency wind power systems. The so-called power feedback method to obtain the optimal output curve corresponding to the given wind speed curve based on the simulation test is used to realize the maximum wind energy tracking control. Since the wind speed curve changes randomly, how to quickly obtain effective wind speed curves for different wind speed curves with very complicated changes? The representative optimal power wind speed control curve is the difficulty that this method needs to overcome. The optimal wind energy tracking method based on the sliding mode variable structure control strategy has the characteristics of no error tracking and fast response, but its disadvantage is that oscillation may occur near the maximum power point. Based on the maximum wind energy tracking strategy of fuzzy control strategy, the biggest advantage of this method is that it does not need to accurately model the controlled object, but the control accuracy of the controller is relatively low. The wind power maximum output tracking method based on perturbation extremum search does not need to establish an accurate model for the control object. Increased the complexity of the control system. Based on sliding mode extreme value search control, this control method not only does not need the mathematical model of the control object, but also has a simple control principle and good control effect. The disadvantage is that this control method has three parameters. If the parameters are not set properly, the control quality will be greatly reduced. , while the traditional method is to use the simulation method to repeatedly adjust the artificial parameters to obtain parameters with better control quality. When the system structure changes, it needs to be adjusted accordingly, so it is very cumbersome. It can be seen that the current maximum wind energy tracking control methods for wind power have their own advantages, but there are also certain problems.

Contents of the invention

The purpose of the present invention is to overcome the deficiencies of the prior art and provide a sliding mode based extreme value search control parameter adaptive adjustment method, which can automatically Adjust the three parameters of ρ, Z ₀ , and U ₀ of the sliding mode-based extreme value search control (SM-ESC), so as to maintain the best control quality of SM-ESC, and finally improve the utilization rate of wind energy and realize the maximum value of the wind power system. The purpose of wind energy tracking. .

The present invention solves its technical problem and realizes by taking the following technical solutions:

A method for adaptive adjustment of control parameters based on sliding mode extremum search, comprising the following steps:

(1) Every sampling period Δt, the actual output power p _s (t) at time t (current moment) is collected from the output terminal of the generator, and the current wind speed is obtained from the wind speed measuring device;

(2) Deriving the best rotational speed under the current wind speed;

(3) Calculate the adjustment coefficient γ;

(4) Parameter adjustment of extreme value search control based on sliding mode, if |ps (t)-p _wmax ( _t )|>ξ, ξ is a small threshold, then let Z ₀ =Z ₀ ×γ, U ₀ =U ₀ ×γ; otherwise, keep Z ₀ and U ₀ unchanged, t=t+Δt and go to step ②;

(5) When p _s (t)=p _wmax (t), the parameters Z ₀ and U ₀ in the extreme value search control structure based on sliding mode are the optimal parameters of the control system, and the control system moves quickly through the sliding mode Adjust the generator speed ω _r to its optimum speed ω _ref ;

(6) Through the wind energy conversion system, the wind turbine operating at the optimal speed ω _ref outputs the maximum power p _wmax under the current wind speed, and finally obtains a set of optimal parameters through parameter adjustment, so that the output power curve is closest to the optimal power curve.

Moreover, the specific method for deriving the optimal rotational speed under the current wind speed in the step (2) is as follows: the wind energy utilization rate C _p takes the maximum value of 0.475, according to the formula Calculate the maximum power p _wmax (t) at the wind speed v at time t, and the speed corresponding to the maximum power is the optimal speed ω _ref at the current wind speed.

Moreover, the formula used to calculate the adjustment coefficient γ in the step (3) is: according to the formula Computes the adjustment factor γ.

Advantage and positive effect of the present invention are:

The present invention improves the extremum search control based on sliding mode, adds a parameter self-adaptive adjustment module, and applies it to a double-fed variable-speed constant-frequency wind power generation system. It can automatically adjust the control system parameters according to the current wind speed environment, so that the control quality is the best. In order to make the output power curve closer to the optimal curve; in the maximum wind energy tracking effect, after the wind speed changes, the speed can be quickly adjusted to keep the tip speed ratio λ at its optimal value, so that the wind energy utilization coefficient C _p can be restored to the maximum value.

Description of drawings

Figure 1 is a structural block diagram of the extreme value search control based on sliding mode applied to wind power;

Fig. 2 Control strategy block diagram of doubly-fed generator rotor side PWM based on sliding mode extremum search control;

Fig. 3 is a comparison chart of the optimal wind power output curve obtained with parameter adaptive adjustment and without parameter adjustment;

Figure 4 adds a block diagram of the control structure based on sliding mode extreme value search for parameter adaptive adjustment;

Fig. 5 is the wind speed model used when the effect verification of the present invention;

Fig. 6 The comparison effect between this patent method and the SM-ESC without parameter adaptive adjustment, the optimal tip speed ratio method and the perturbation-based ESC method ω _r ;

Fig. 7 The comparison effect diagram of the patented method and the SM-ESC without parameter adaptive adjustment, the optimal tip speed ratio method and the perturbation-based ESC method p _s .

detailed description

The embodiments of the present invention will be described in further detail below in conjunction with the accompanying drawings. It should be emphasized that the following embodiments are illustrative, not restrictive, and should not be used as limitations of the present invention.

A sliding mode based extreme value search control parameter adaptive adjustment method, the system includes: a sliding mode based extreme value search control system including a parameter adaptive adjustment module, the system outputs an optimal generator speed reference value ω _ref , the wind energy conversion system outputs the maximum power by tracking the speed reference value, and the output power is fed back to the extreme value search control system based on the sliding mode with the parameter adaptive adjustment module. Such a feedback system can ensure that the wind power system can be adjusted at any time Its speed thus maximizes the output power.

Proceed as follows:

(1) Every sampling period Δt, the actual output power p _s (t) at time t (current moment) is collected from the output terminal of the generator, and the current wind speed is obtained from the wind speed measuring device; the maximum value of wind energy utilization C _p is 0.475, according to Mode Calculate the maximum power p _wmax (t) under the wind speed v at time t, as shown in Figure 1, the speed corresponding to the maximum power is the best speed ω _ref under the current wind speed;

(2) According to the formula $\mathrm{\γ}=\frac{|p_{w\max }\left(t\right)-p_{w\max }(t-\mathrm{\Δt})|}{|p_{\mathrm{the\; s}}\left(t\right)-p_{\mathrm{the\; s}}(t-\mathrm{\Δt})|}$ Calculate the adjustment factor γ;

(3) As shown in Figure 2, the parameter adjustment module of the extremum search control based on sliding mode, if |ps (t)-p _wmax ( _t )|>ξ, ξ is a relatively small threshold, then let Z ₀ =Z ₀ ×γ, U ₀ =U ₀ ×γ; otherwise, keep Z ₀ and U ₀ unchanged. t=t+Δt and go to step ②;

(4) When p _s (t)=p _wmax (t), the parameters Z ₀ and U ₀ in the extreme value search control structure based on sliding mode are the optimal parameters of the control system, and the control system can move through the sliding mode Quickly adjust the generator speed ω _r to its optimum speed ω _ref ;

(5) Through the wind energy conversion system, the wind turbine operating at the optimal speed ω _ref outputs the maximum power p _wmax under the current wind speed, as shown in Figure 3, and finally obtains a set of optimal parameters through parameter adjustment, so that the output power The curve is closest to the optimal power curve.

In order to verify the effect of the above-mentioned improved sliding mode-based extreme value search control method on maximum wind energy tracking and mechanical torque control, this patent builds a control model of variable-speed constant-frequency wind turbines on the PSCAD/EMTDC simulation platform. The parameters of the DFIG are shown in Table 1, and the parameters of the wind turbine are shown in Table 2.

Table 1 Parameters of doubly-fed asynchronous generator

Rated Capacity Rated voltage is 1 frequency 5MVA 10KV 50HZ

Table 2 Wind turbine parameters

The initial parameters ρ, Z ₀ , U ₀ are: 0.015, 1.125, 0.077 respectively; Δt is taken as 0.1s. Figure 4 shows the random wind speed curve with an average value of 8m/s used in the simulation, and the duration is 3000 seconds; Figure 5 shows the change curve of the blade tip speed ratio λ and the wind energy utilization coefficient _Cp . It can be seen from Figure 5 that λ fluctuates around the optimal value of 7, and C _p fluctuates at the maximum value of 0.475 and below, the fluctuation range is not large, and can quickly return to the maximum value after being reduced, indicating that the control strategy in this paper can It is guaranteed that the wind turbine operates near λ _opt and C _pmax in most cases, and realizes the purpose of tracking the maximum wind energy.

In order to more intuitively observe the control effect of the maximum wind energy tracking based on the sliding mode extreme search control, this patent respectively builds the models of the optimal tip speed ratio method and the perturbation based extreme value search method and the extreme value search method based on the sliding mode. When the wind speed suddenly increases from 9m/s to 10m/s, the changes of rotor speed ω _r and stator output active power p _s of the three methods are shown in Figure 6 and Figure 7, which can be It can be seen that the extreme value search control based on sliding mode is closer to the optimal curve than the other two methods, so the improved extreme value search method not only has advantages in the control principle (the only input variable required by this method is the generator output Active power, which avoids the complex problems of many traditional methods, such as fast and accurate measurement of wind speed, requirements for wind turbine models and parameters, and the need for gradient sensors, etc.), and the control effect is better than other methods.

In summary, the invention patent improves the extreme value search control based on sliding mode, adds a parameter adaptive adjustment module, and applies it to double-fed variable-speed constant-frequency wind turbines to maintain the best control quality of SM-ESC , and finally achieve the purpose of improving the utilization rate of wind energy and realizing the maximum wind energy tracking of the wind power system.

Claims (2)

1. A sliding mode-based extreme value search control parameter adaptive adjustment method is characterized in that comprising steps as follows: (1) Every sampling period Δt, collect the actual output power p _s (t) at the current moment t from the output terminal of the generator, and obtain the current wind speed from the wind speed measuring device; (2) Deriving the best rotational speed under the current wind speed; (3) Calculate the adjustment coefficient γ; the formula used to calculate the adjustment coefficient γ is: according to the formula Calculate the adjustment factor γ; (4) Parameter adjustment of extremum search control based on sliding mode, if |ps (t)-p _wmax ( _t )|>ξ, ξ is a small threshold, then let Z ₀ =Z ₀ ×γ, U ₀ =U ₀ ×γ; otherwise, keep Z ₀ and U ₀ unchanged, t=t+Δt and go to step (2); (5) When p _s (t)=p _wmax (t), the parameters Z ₀ and U ₀ in the extremum search control structure based on sliding mode are the optimal parameters of the control system, and the control system moves quickly through the sliding mode Adjust the generator speed ω _r to its optimum speed ω _ref ; (6) Through the wind energy conversion system, the wind turbine operating at the optimal speed ω _ref outputs the maximum power p _wmax under the current wind speed, and finally obtains a set of optimal parameters through parameter adjustment, so that the output power curve is closest to the optimal power curve. 2. the extreme value search control parameter adaptive adjustment method based on sliding mode according to claim 1, is characterized in that: the specific method of described step (2) deriving the optimal rotating speed under the current wind speed is: wind energy utilization rate C _p takes the maximum value of 0.475, according to the formula Calculate the maximum power p _wmax (t) at the wind speed v at time t, and the speed corresponding to the maximum power is the optimal speed ω _ref at the current wind speed.