CN102427323B - Start control and MPPT (Maximum Power Point Tracking) control method for switched reluctance wind power system - Google Patents

Abstract

The invention discloses a start control and MPPT (Maximum Power Point Tracking) control method for a switched reluctance wind power system, wherein a switched reluctance motor is controlled to be operated in an electromotor state at the start period of the system so that the switched reluctance motor works with a wind turbine to drive the system to accelerate; when reaching a rated rotation speed in the accelerating of the system, the switched reluctance motor is switched into a power generation operation control state; and the rotation speed closed loop control method of the switched reluctance generator (SRG) based on a single neuron adaptive PID (Proportion Integration Differentiation) algorithm is adopted to implement the MPPT. The start control and MPPT (Maximum Power Point Tracking) control method for switched reluctance wind power system effectively solves the problem of the start control and MPPT nonlinear control of low-power switched reluctance wind power systems, and can be applied to the design of the control algorithmof the low-power switched reluctance wind power systems.

Description

Switching magnetic-resistance wind power system starting control and MPPT control method

Technical field

The present invention relates to small-power varying speed switch magnetic resistance wind generator system field, relate in particular to a kind of adaptive neurotic element control method that realizes Switched Reluctance GeneratorUsed in Wind Energy Converter System starting control and maximal power tracing.

Background technology

SRG (switched reluctance generator, switch reluctance generator) firm in structure, simple, cost is low, efficient is high, allow temperature rise higher, be applicable to the abominable occasion of environment, power inverter is unipolar, and phase winding is connected with main switch, margin of safety is larger, is a kind of novel synchronous generator that has development prospect in the variable speed wind turbine system.At present, the main method of Switched Reluctance GeneratorUsed in Wind Energy Converter System maximal power tracing control is: during system initial work, by external force SRG is dragged to certain rotating speed first, then access wind energy conversion system, adopting one of wind speed tracking, Feedback of Power, these 3 kinds of control methods of maximum power search to carry out the SRG rotational speed regulation changes to follow the tracks of wind speed, make the wind wheel tip speed ratio remain on optimum value, realize maximal wind-energy tracking (MPPT) control, wherein the conventional proportion integration differentiation pid algorithm of the many employings of closed loop controller.But because the Switched Reluctance GeneratorUsed in Wind Energy Converter System physical presence is non-linear and uncertain, there is parameter tuning difficulty, poor robustness, is difficult to when wind speed, load change, obtain the shortcoming of desirable dynamic and static state performance on a large scale and significantly based on the MPPT control of conventional pid algorithm.On the other hand, during system initial work, provide mechanical external force to drive SRG by the method for static starting to certain rotating speed by additional power device (such as the additional electrical motivation), increased the cost of system and the complexity of control.If when the initial work of system, utilize the self-starting performance that wind wheel has and do not assist SRG is dragged to certain rotating speed by other external force, but though this simplied system structure, reduce cost, most of wind wheels only surpassing under the condition of certain wind speed, just possess the self-starting ability.For from the competitive small power switch magnetic resistance of net type wind-powered electricity generation unit wind generator system, its operating air velocity is generally lower, the low wind speed section in its operating air velocity scope, wind wheel self-starting difficulty or can not self-starting.

Starting control and the MPPT nonlinear Control of small power switch magnetic resistance wind generator system are in its commercialization process key issue to be solved to be arranged.

Summary of the invention

Technical problem to be solved by this invention is for the starting control of the small power switch magnetic resistance wind generator system of mentioning in the background technology and the problem of MPPT nonlinear Control, proposes a kind of adaptive neurotic element control method that realizes Switched Reluctance GeneratorUsed in Wind Energy Converter System starting control and maximal power tracing.

The present invention is for solving the problems of the technologies described above by the following technical solutions:

A kind of switching magnetic-resistance wind power system starting control and MPPT control method comprise the switched reluctance machines starting control step of electric operation, the switched Reluctance Motor Control step of generator operation;

Wherein, described switched reluctance machines starting control step is specific as follows:

Steps A, at system's start-up period, the kinetic moment of electricity generation system starting is provided jointly by the switched reluctance machines of wind energy conversion system and electric operation, switched reluctance motor is operated under the current chopping control model, the corresponding turn-on angle of switched reluctance machines chopper current threshold value and electric operation directly is set within the specific limits, closes angle of rupture fixed value, and turn-on angle, that the setting of closing the angle of rupture should make the conducting of adjacent phase winding have is suitably overlapping in order to avoid the starting dead band occurs;

Step B, when switched reluctance machines by the static rated speed that is dragged to, starting control step finishes, and switches to the switched Reluctance Motor Control step of generator operation;

The switched Reluctance Motor Control step of described generator operation is as follows:

Step C when the storage capacitor terminal voltage of power inverter main circuit is less than or equal to auxiliary DC power supply voltage, adopts auxiliary DC power supply to provide electric energy for switch reluctance generator phase winding excitation;

Step D, when storage capacitor terminal voltage during greater than auxiliary DC power supply voltage, the excision auxiliary DC power supply switches to the electric energy excitation of being sent by switch reluctance generator self;

Switch reluctance generator is operated under the current chopping control model, the corresponding turn-on angle of switched reluctance machines generator operation directly is set, closes angle of rupture fixed value, switched reluctance machines chopper current threshold value is then obtained by MPPT single neure adaptive PI D control algolithm, and concrete steps are as follows:

If

Be switched reluctance machines angular speed optimum instruction value, it is corresponding to the wind energy conversion system optimum tip-speed ratio, namely

(1)

In the formula, jBe the gear box no-load voltage ratio; λ _Opt Optimum tip-speed ratio for wind energy conversion system; RBe the wind wheel radius, VBe wind speed;

Definition switched reluctance machines actual angular speed Follow the tracks of optimum instruction

Error be

(2)

The input signal of single neure adaptive PI D-algorithm

,

Carry out following state transformation, namely

（3）

The output increment of single neure adaptive PI D-algorithm and being output as

（4）

In the formula, Δ I _Chop Increment for switched reluctance machines chopper current threshold value; I _Chop Be the switched reluctance machines chopper current threshold value of trying to achieve; KProportionality coefficient for single neure adaptive PI D control; W _i Be state variable shown in the formula (3) x _i Weights, i=1,2,3;

Adjust online the weights of state variable by the Hebb learning algorithm that supervision is arranged shown in the formula (5) W _i , namely

（5）

In the formula,

,

With

Be respectively weights W ₁, W ₂With W ₃The learning efficiency factor.

Further, a kind of switching magnetic-resistance wind power system starting control of the present invention and MPPT control method, the scope of the switched reluctance machines chopper current threshold value setting of the described electric operation of steps A refers to 1～2.5 times of rated current scope.

The present invention adopts above technical scheme compared with prior art, has following technique effect:

Starting control and MPPT neural network adaptive control method that the present invention proposes, can in the operating air velocity scope, stablize, Fast starting and can realize MPPT with good dynamic and static performance, and system can keep good MPPT performance when wind speed, load change on a large scale and significantly, has good robustness.

Description of drawings

Fig. 1 is based on Switched Reluctance GeneratorUsed in Wind Energy Converter System starting and the MPPT integral control system schematic diagram of single neure adaptive PI D-algorithm.

Fig. 2 is SRG speed closed loop single neure adaptive PI D control principle block diagram.

Fig. 3 is that wind energy conversion system power coefficient and tip speed ratio concern schematic diagram.

Fig. 4 power schematic diagram that to be wind energy conversion system catch under different angular speed and different wind speed.

Fig. 5 is the distribution character schematic diagram of threephase switch reluctance motor phase inductance under out-of-phase current, rotor position angle.

Fig. 6 is three-phase SRG asymmetrical half-bridge main circuit topology figure under the self-excitation mode of operation.

Fig. 7 is based on the starting of switching magnetic-resistance wind turbine generator and the MPPT integral control system simulation model figure of single neure adaptive PI D-algorithm.

Fig. 8 is Switched Reluctance GeneratorUsed in Wind Energy Converter System starting control and MPPT single neure adaptive PI D control program flow chart.

System's starting and MPPT performance simulation figure when Fig. 9 is constant wind speed V=5m/s; Wherein figure (a) is SRG angular speed, (b) catches power for wind energy conversion system.

System's starting and MPPT performance simulation figure when Figure 10 is constant wind speed V=7m/s; Wherein figure (a) is SRG angular speed, (b) catches power for wind energy conversion system.

Figure 11 is the system MPPT performance simulation figure under the wind speed step situation of change; Wherein figure (a) is SRG angular speed, (b) catches power for wind energy conversion system.

Figure 12 is the system MPPT performance simulation figure in the wind speed gradual change situation; Wherein figure (a) is SRG angular speed, (b) catches power for wind energy conversion system.

Figure 13 is wind speed system MPPT performance simulation figure under the DC load resistance step situation of change when being 6.9 m/s; Wherein figure (a) is SRG angular speed, (b) catches power for wind energy conversion system.

Embodiment

Below in conjunction with accompanying drawing technical scheme of the present invention is described in further detail:

As shown in Figure 1, the essential composition structure of step-up gear, inverter, AC load or electrical network and nonsystematic; In inverter, AC load (or electrical network) when existing, DC load then and the essential composition structure of nonsystematic.The power inverter main circuit is the self-excitation pattern, auxiliary DC power supply wherein provides electric energy at system's start-up period for the switched reluctance machines of electric operation, and at switched reluctance machines generator operation initial period, when storage capacitor C terminal voltage is not more than auxiliary DC power supply voltage, auxiliary DC power supply provides electric energy for SRG phase winding excitation, when storage capacitor C terminal voltage during greater than auxiliary DC power supply voltage, auxiliary DC power supply is then cut, and system switches to the electric energy excitation of being sent by SRG self; No matter be the electric operation of start-up period, or the generator operation in MPPT control stage, switched reluctance machines all is operated under current chopping control (CCC) pattern, the commutation control of phase winding is based on the rotor-position detection signal, and the turn-on angle of phase current, the pass angle of rupture and current chopping threshold value are obtained by starting control and MPPT single neure adaptive PI D control algolithm.

The kinetic moment of Switched Reluctance GeneratorUsed in Wind Energy Converter System starting is provided jointly by the switched reluctance machines of wind energy conversion system and electric operation.Switched reluctance machines starting control and MPPT single neure adaptive PI D control algolithm are made of two large branched programs:

One, when the initial work of system, the fixed value of switched reluctance machines CCC mode chopper current threshold value and the corresponding turn-on angle of electric operation, the pass angle of rupture directly is set in 1～2.5 times of rated current scope, and it is suitably overlapping that the setting of turn-on angle, the pass angle of rupture should make the conducting of adjacent phase winding have, in order to avoid the starting dead band occurs.Until, starting control by the static rated speed that is dragged to, finishes switched reluctance machines.

Its two, after starting control finishes, switch to the SRG generator operation control based on the single neure adaptive PI D-algorithm, to realize MPPT.In this branched program, SRG directly is set with the corresponding turn-on angle of CCC mode generator operation, pass angle of rupture definite value, the chopper current threshold value is then by the deviation of SRG angular speed actual value and optimum instruction value, obtains through as shown in Figure 2 single neure adaptive PI D control algolithm:

Among Fig. 2,

Be SRG angular speed optimum instruction, it is corresponding to the wind energy conversion system optimum tip-speed ratio, namely

(1)

In the formula, jBe the gear box no-load voltage ratio; λ _Opt Optimum tip-speed ratio for wind energy conversion system; RBe the wind wheel radius, VBe wind speed.

Definition SRG actual angular speed Follow the tracks of optimum instruction

Error be

(2)

The input signal of single neure adaptive PI D-algorithm

,

Be transformed to through state transformation link shown in Figure 2

（3）

And the output increment of single neure adaptive PI D-algorithm and being output as

（4）

In the formula, I _Chop , Δ I _Chop Be respectively SRG phase current current chopping threshold value and increment thereof; KProportionality coefficient for single neure adaptive PI D control; Be state variable shown in the formula (3) x _iWeights ( i=1,2,3), it is adjusted online by the Hebb learning algorithm that supervision is arranged shown in the formula (5), namely

（5）

In the formula,

, With

Be respectively weights W ₁, W ₂With W ₃The learning efficiency factor.

Embodiment:

The starting control that the present invention is proposed and MPPT single neure adaptive PI D control algolithm are carried out simulation modeling and simulation analysis take certain 750W, 1500r/min three-phase (6/4 utmost point) SRG wind generator system as application example of the present invention under the MATLAB environment.

Fig. 7 is the simulation model that starts control and MPPT single neure adaptive PI D control integral control system based on the switching magnetic-resistance wind turbine generator that MATLAB sets up.

Parameter among Fig. 7 is as follows:

Wind mill wind wheel radius R=1.6 m, its power coefficient C _P Provided by formula (6), namely

（6）

In the formula,

Be tip speed ratio.The optimum tip-speed ratio of this wind energy conversion system is 6.3, and corresponding power coefficient maximum is 0.4382.

The air dynamic behaviour of wind energy conversion system is seen Fig. 3～Fig. 4; Fig. 3 is that propeller pitch angle is 0 o'clock, and wind energy conversion system power coefficient and tip speed ratio relation curve, ordinate are power coefficient CP, and abscissa is tip speed ratio λ.Fig. 3 shows that when tip speed ratio kept optimum value 6.3, power coefficient was maximum 0.4382.Fig. 4 is that propeller pitch angle is 0 o'clock, the relation curve of the wind energy conversion system capturing wind energy of wind wheel radius R=1.6m and angular speed, wind speed.Fig. 4 shows when tip speed ratio keeps optimum value 6.3, under different wind speed V=4m/s, 5 m/s, 6 m/s, 6.5 m/s, 7 m/s, 7.5 m/s, 8 m/s, the maximum power that wind energy conversion system is caught is about respectively 140.97W, 275.33 W, 475.77 W, 604.90 W, 755.50 W, 929.24 W, 1127.7W.

Fig. 5 is the relation curve of three-phase (stator 6 utmost points, rotor 4 utmost points) 750W switched reluctance machines phase inductance and rotor position angle, phase current.Its rated speed is 1500r/min, and phase winding resistance is 1.27 Ω.Rotor position angle is that the corresponding rotor in 0 place does not line up the position; Rotor position angle is 45 ° and locates corresponding rotor aligned position.

Fig. 6 is the power inverter asymmetrical half-bridge main circuit topology that three-phase (6/4 utmost point) SRG adopts the self-excitation mode of operation.Among the figure, U _SBe auxiliary DC power supply; C _SBe storage capacitor; R _LBe the Equivalent DC load; Diode D _SEffect be to work as C _STerminal voltage is greater than U _SThe time, blocking-up U _SSupply access, system switches to the electric energy that sent by SRG to the phase winding excitation.In the present embodiment, storage capacitor C _S=470 μ f, auxiliary DC power supply U _S=120V, the gearratio j=6 of step-up gear, mechanical system moment of inertia J=0.0017kgm2, coefficient of friction are 0.00813Nms.

Fig. 8 is for realizing the program flow diagram of Switched Reluctance GeneratorUsed in Wind Energy Converter System starting control and MPPT single neure adaptive PI D control algolithm.Switched reluctance machines all is operated under current chopping control (CCC) pattern, and the control parameter arranges as follows:

At start-up period, switched reluctance machines electric operation, and the common drive system raising speed of wind energy conversion system.Start-up period, phase winding turn-on angle are set to 0 °, close the angle of rupture and are set to 40 °, and the current chopping threshold value setting is 10A.

After starting control finishes, switched reluctance machines switches to generator operation, enter the MPPT control flow, turn-on angle, the pass angle of rupture are set to respectively 38 °, 67 °, and the chopper current threshold value is then obtained through single neure adaptive PI D control algolithm by the deviation of SRG angular speed actual value and optimum instruction value.According to current wind speed V (m/s), SRG angular speed optimum instruction value is provided by formula (7), namely

(7)

SRG angular speed tracking error according to this sampling acquisition

, the proportionality coefficient of neuron control KBy formula (8) subsection setup, namely

(8)

According to formula (3) SRG angular speed tracking error is converted to state variable, then carries out the state variable weights according to formula (5) W ₁, W ₂With W ₃Adjustment and make amplitude limiting processing, wherein, W ₁, W ₂With W ₃The learning efficiency factor

,

With Be taken as respectively 0.0001,0.01 and 0.01; Then calculate chopper current threshold value increment, chopper current threshold value and make amplitude limiting processing according to formula (4).

Finishing to upgrade preservation relevant variable (see figure 8) before this calls single neure adaptive PI D control algolithm.

Based on Fig. 7 simulation model, carry out respectively the system emulation under different constant wind speed, the variation of wind speed step, wind speed gradual change, the DC load step situation of change, simulation result such as Fig. 9-shown in Figure 13.

Fig. 9～Figure 10 is under constant wind speed V=5m/s, V=7 m/s, the starting performance of system and MPPT performance simulation result, simulation result shows: under V=5m/s, V=7 m/s wind speed, system's starting time all is no more than 0.05s, the error of stable state MPPT all is no more than 0.3%, and visible system can Fast starting also can be realized MPPT with good dynamic and static performance.

Figure 11 is under the wind speed step situation of change that obtains based on Fig. 7 simulation model, system MPPT performance simulation result, and its corresponding wind speed step situation of change is: the wind speed during system initial work is 7.2 m/s; Wind speed is reduced to 5.5 m/s by 7.2 m/s steps when 1.2 s; Wind speed is upgraded to 6.7 m/s by 5.5 m/s steps when 2.2 s.As seen from Figure 11: no matter the wind speed step rises or step decline, and SRG angular speed is energy tenacious tracking optimal corner speed command all, makes system realize MPPT with good dynamic and static performance.

Figure 12 is in the wind speed gradual change situation that obtains based on Fig. 7 simulation model, system MPPT performance simulation result, and its corresponding wind speed gradual change situation is: the wind speed during system initial work is 5m/s; Wind speed is with 1.5 m/s when 1s ²Acceleration gradually rise, rise to 6.5m/s during to 2s and remain unchanged.As seen from Figure 12, when the wind speed gradual change, system still can the tenacious tracking optimum instruction, realizes MPPT with good precision

The Equivalent DC load resistance R of Figure 13 for obtaining based on Fig. 7 simulation model _LUnder the step situation of change, system MPPT performance simulation result, its corresponding operating mode is: wind speed is constant to be 6.9 m/s; R during system initial work _LBe 10k Ω, R during 1s _LReduce to 0.196 k Ω by 10k Ω step.As seen from Figure 13, the load current step that system can adapt to certain amplitude changes, and keeps MPPT with good precision and dynamic characteristic.

Above simulation example shows: the starting control and the MPPT neural network adaptive control method that adopt the present invention to propose in Switched Reluctance GeneratorUsed in Wind Energy Converter System, can in the operating air velocity scope, stablize, Fast starting and can realize MPPT with good dynamic and static performance, and system can keep good MPPT performance when wind speed, load change on a large scale and significantly, has good robustness.The present invention has effectively overcome the shortcoming of current small power switch magnetic resistance wind generator system starting control and MPPT control existence, can be used for the small power switch magnetic resistance wind generator system Control System Design of high performance-price ratio.

Claims (2)

1. a switching magnetic-resistance wind power system starting is controlled and the MPPT control method, it is characterized in that: comprise the switched reluctance machines starting control step of electric operation, the switched Reluctance Motor Control step of generator operation;

Wherein, described switched reluctance machines starting control step is specific as follows:

Steps A, at system's start-up period, the kinetic moment of electricity generation system starting is provided jointly by the switched reluctance machines of wind energy conversion system and electric operation, switched reluctance motor is operated under the current chopping control model, directly arrange within the specific limits switched reluctance machines chopper current threshold value and the corresponding turn-on angle of electric operation fixed value, close the fixed value of the angle of rupture, and turn-on angle, that the setting of closing the angle of rupture should make the conducting of adjacent phase winding have is suitably overlapping in order to avoid the starting dead band occurs;

Step B, when switched reluctance machines by the static rated speed that is dragged to, starting control step finishes, and switches to the switched Reluctance Motor Control step of generator operation;

The switched Reluctance Motor Control step of described generator operation is as follows:

Step C when the storage capacitor terminal voltage of power inverter main circuit is less than or equal to auxiliary DC power supply voltage, adopts auxiliary DC power supply to provide electric energy for switch reluctance generator phase winding excitation;

Step D, when storage capacitor terminal voltage during greater than auxiliary DC power supply voltage, the excision auxiliary DC power supply switches to the electric energy excitation of being sent by switch reluctance generator self;

Switch reluctance generator is operated under the current chopping control model, the fixed value of the corresponding turn-on angle of switched reluctance machines generator operation, the fixed value of the pass angle of rupture directly are set, switched reluctance machines chopper current threshold value is then obtained by MPPT single neure adaptive PI D control algolithm, and concrete steps are as follows:

If

Be switched reluctance machines angular speed optimum instruction value, it is corresponding to the wind energy conversion system optimum tip-speed ratio, namely

${\mathrm{\ω}}_{\mathrm{SRG}}^{*}=j\frac{{\mathrm{\λ}}_{\mathrm{opt}}}{R}V---\left(1\right)$

In the formula, j is the gear box no-load voltage ratio; λ _OptOptimum tip-speed ratio for wind energy conversion system; R is the wind wheel radius, and V is wind speed;

Definition switched reluctance machines actual angular speed ω _SRGFollow the tracks of optimum instruction

Error be

$e\left(k\right)={\mathrm{\ω}}_{\mathrm{SRG}}\left(k\right)-{\mathrm{\ω}}_{\mathrm{SRG}}^{*}\left(k\right)---\left(2\right)$

The input signal of single neure adaptive PI D-algorithm

ω _SRGCarry out following state transformation, namely

$\left\{\begin{array}{c}{x}_1\left(k\right)=e\left(k\right)\\ x_2\left(k\right)=e\left(k\right)-e(k-1)\\ x_3\left(k\right)=e\left(k\right)-2e(k-1)-e(k-2)\end{array}---\left(3\right)\right.$

The output increment of single neure adaptive PI D-algorithm and being output as

$\left\{\begin{array}{c}{\mathrm{\ΔI}}_{\mathrm{chop}}\left(k\right)=K\underset{i=1}{\overset{3}{\mathrm{\Σ}}}\frac{W_i\left(k\right)x_i\left(k\right)}{\left|W_1\left(k\right)\right|+\left|W_2\left(k\right)\right|+\left|W_3\left(k\right)\right|}\\ I_{\mathrm{chop}}\left(k\right)=I_{\mathrm{chop}}(k-1)+{\mathrm{\ΔI}}_{\mathrm{chop}}\left(k\right)\end{array}---\left(4\right)\right.$

In the formula, Δ I _ChopIncrement for switched reluctance machines chopper current threshold value; I _ChopBe the switched reluctance machines chopper current threshold value of trying to achieve; K is the proportionality coefficient of single neure adaptive PI D control; W _iBe state variable x shown in the formula (3) _iWeights, i=1,2,3; Adjust online the weights W of state variable by the Hebb learning algorithm that supervision is arranged shown in the formula (5) _i, namely

$\left\{\begin{array}{c}{W}_1\left(k\right)=W_1(k-1)+{\mathrm{\η}}_{I}e\left(k\right)I_{\mathrm{chop}}(k-1)x_1\left(k\right)\\ W_2\left(k\right)=W_2(k-1)+{\mathrm{\η}}_{P}e\left(k\right)I_{\mathrm{chop}}(k-1)x_2\left(k\right)\\ W_3\left(k\right)=W_3(k-1)+{\mathrm{\η}}_{D}e\left(k\right)I_{\mathrm{chop}}(k-1)x_3\left(k\right)\end{array}---\left(5\right)\right.$

In the formula, η _I, η _PAnd η _DBe respectively weights W ₁, W ₂And W ₃The learning efficiency factor.

2. a kind of switching magnetic-resistance wind power system starting according to claim 1 is controlled and the MPPT control method, and it is characterized in that: the scope of the switched reluctance machines chopper current threshold value setting of the described electric operation of steps A refers to 1～2.5 times of rated current scope.

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