CN101604848B - Modified fuzzy sliding mode controlling method of monopole three-phase photovoltaic grid-connected system - Google Patents

Abstract

The invention relates to a modified fuzzy sliding mode controlling method of a monopole three-phase photovoltaic grid-connected system, belonging to the control technical application field of a photovoltaic grid-connected system; the method has the advantages of strong robustness, good stability and rapid dynamic response speed; the method comprises the following steps particularly: firstly, feedforward compensation is led in to rapidly compensate the coupling part of d, q shaft current id and iq which are output by an inverter, thereby realizing rapid dynamic decoupling between id and iq; secondly, by controlling reaching law of lead-in index of an integral sliding mode controller, the dynamic performance of a sliding mode controlling system is improved, the response speed of the system at the initial starting stage is accelerated, and a system state trajectory is ensured to rapidly and smoothly enter in a sliding mode surface to move, wherein the sliding mode surface has good robustness to system interference; finally, a fuzzy control is led in to weaken the buffeting of common sliding mode control in the sliding mode surface, the output of the sliding mode controller is softened, and the stability of the system is improved.

Description

The modified fuzzy sliding mode controlling method of monopole three-phase photovoltaic grid-connected system

Technical field

The present invention relates to a kind of modified fuzzy sliding mode controlling method of monopole three-phase photovoltaic grid-connected system, belong to photovoltaic generating system control technology application.

Background technology

For photovoltaic parallel in system, topmost problem is how to improve the generating efficiency and the whole system operation stability of system.The stage photovoltaic single grid-connected system is owing to have only an energy conversion link, and system has simple structure, and higher efficient and stability have become the domestic and international research focus.Generally, its control system adopts many ring controls, and promptly at first by MPPT maximum power point tracking MPPT method, the disturbance observation as commonly used at present provides photovoltaic array maximum power point reference voltage U _Ref, control the photovoltaic array output voltage U by the double closed-loop control system of being formed by voltage PI controller and synchronous vector current PI controller again _PvFollow the tracks of U _RefBut, because the nonlinear characteristic of uncertainty, photovoltaic array variation of temperature and the photovoltaic array power output-voltage response of solar irradiation intensity, make the current inner loop control of photovoltaic parallel in system become a very complicated problems, the robustness of the general synchronous vector current PI controller that adopts is relatively poor, and when external environment condition sharply changes, dynamic response performance is slower, can produce over control simultaneously.

Find through literature search prior art, I 1-Song Kim is at " Robust maximum power point tracker using sliding mode controller for the three-phase grid-connected photovoltaic system " (the robust MPPT maximum power point tracking device that is used for the use sliding mode controller of three-phase photovoltaic grid-connected system, derive from periodical Solar Energy, in March, 2007, the 81st the 3rd phase of volume, 405 pages-414 pages) in the literary composition, a kind of integral form sliding-mode control has been proposed for the current inner loop controller of monopole three-phase photovoltaic grid-connected system.Sliding-Mode Control Based is a kind of non linear robust control method, be mainly used in and handle because the coarse problem of system modelling that external disturbance and the perturbation of internal system parameter etc. cause, advantage is just: even the model inaccuracy, its also can be good the stability and the robustness of the system that keeps, this is very suitable for grid-connected this strongly non-linear system.

But also there is shortcoming in Sliding-Mode Control Based self, is mainly:

Shi Ji System with Sliding Mode Controller since the influence of factor such as diverter switch is imperfect make sliding mode produce high frequency and buffet, peculiar in the System with Sliding Mode Controller that Here it is " buffeting " phenomenon.When external disturbance or inner parameter perturbation increasing, guarantee system stability, just must use bigger controlled quentity controlled variable, and this will aggravate further to buffet;

2. the response time of system's initial start up phase is directly connected to the dynamic response performance of system, generally, the motion of sliding formwork in chronological sequence can be divided into two stages in proper order in the sliding mode controller, phase I is the convergence stage, it is the system mode track arrives sliding-mode surface from initial condition the convergence stage, second stage is a sliding phase, after promptly the system mode track arrives sliding-mode surface, and the sliding phase on sliding-mode surface.The time in convergence stage is extremely important, because have only when sliding formwork quick arrival on the sliding-mode surface in finite time, when on sliding-mode surface, sliding, the robustness of Sliding-Mode Control Based just can fully show, and the integral form sliding mode controller is in system's initial start up phase, and promptly the response time in convergence stage is still waiting further improvement.

Summary of the invention

The objective of the invention is to propose the modified fuzzy sliding mode controlling method of the monopole three-phase photovoltaic grid-connected system of a kind of strong robustness, good stability and rapid dynamic response speed at above-mentioned deficiency of the prior art.

This method at first by introducing feedforward compensation, compensates d, the q shaft current i of inverter output fast _d, i _qBetween the part that intercouples, realize i _dWith i _qBetween quick dynamic decoupling; Then, by the integral form sliding mode controller being introduced the control of index convergence rule, improve the dynamic property of System with Sliding Mode Controller, the response speed of quickening system initial start up phase, guarantee that the system mode track in the short as far as possible time, quickly and smoothly enters the sliding formwork in-plane moving that system interference is had good robust performance; At last, introduce the fuzzy control chattering phenomenon that general Sliding-Mode Control Based exists that weakens in sliding-mode surface, the output of softening sliding mode controller improves the steady-state behaviour of system.

The present invention is achieved through the following technical solutions:

(1) A, B, the C three-phase voltage signal of detection utility grid are obtained line voltage vector anglec of rotation θ by the phase-locked loop pll method, utilize anglec of rotation θ and electrical network A, B, C three-phase voltage signal to calculate d, the q axle DC component e of line voltage simultaneously _d, e _q

(2) detect inverter output end A, B, C three-phase current signal, utilize the anglec of rotation θ in the step (1) to carry out the conversion of dq rotating vector, rotated the direct current component i under the dq axis coordinate system synchronously _d, i _q

(3) detect the photovoltaic array output voltage U _PvAnd electric current I _Pv, adopt MPPT maximum power point tracking MPPT method---disturbance observation commonly used, try to achieve the photovoltaic array maximum power point reference voltage U under the current environment condition _Ref

(4) the photovoltaic array output voltage U that obtains by step (3) _PvWith the U that obtains by step (3) _RefDifference through obtaining the d axle reference current i of inverter output behind the proportional integral pi regulator ^* _d,, the q axle reference current i of inverter output is set for making inverter output current and line voltage same-phase ^* _q=0, again according to step

(2) current i that obtains _dAnd i _q, obtain the sliding formwork s of the d shaft current of inverter output by formula (1) ₁Sliding formwork s with the q shaft current ₂, c in the formula (1) ₁And c ₂Be respectively the integral coefficient of sliding formwork of d, the q shaft current of inverter output, t is the time;

$\left\{\begin{array}{c}{\mathrm{<figure-callout\; id="1"\; label="s"\; filenames="H2009100320140E00031.png,H2009100320140E00041.png"\; state="\{\{state\}\}">s</figure-callout>}}_1=i_d^{*}-i_d+{\mathrm{<figure-callout\; id="1"\; label="c"\; filenames="H2009100320140E00031.png,H2009100320140E00041.png"\; state="\{\{state\}\}">c</figure-callout>}}_1{\&Integral;}_0^t(i_d^{*}-i_d)\mathrm{<figure-callout\; id="2"\; label="dt\; s"\; filenames="H2009100320140E00031.png"\; state="\{\{state\}\}">dt</figure-callout>}& \\ s_{}{}_2=i_q^{*}-i_q+{\mathrm{<figure-callout\; id="2"\; label="c"\; filenames="H2009100320140E00031.png"\; state="\{\{state\}\}">c</figure-callout>}}_2{\&Integral;}_0^t(i_q^{*}-i_q)\mathrm{dt}\end{array}\right.---\left(1\right)$

(5) make i=1,2, the s that step (4) is obtained ₁And s ₁Derivative

As the input of first fuzzy controller, pass through obfuscation, fuzzy reasoning and reverse gelatinization successively after, obtain the output variable p of first fuzzy controller ₁, the s that step (4) is obtained ₂And s ₂Derivative

As the input of second fuzzy controller, pass through obfuscation, fuzzy reasoning and reverse gelatinization successively after, obtain the output variable p of second fuzzy controller ₂, s wherein _i,

And p _iFuzzy set all be taken as 7, be expressed as that { NB=is negative big, during NM=is negative, NS=is negative little, and ZE=zero, and PS=is just little, PM=center, PB=is honest }, 49 fuzzy rules that 49 fuzzy rules that first fuzzy controller is adopted and second fuzzy controller are adopted are shown in the following table:

(6) e that obtains according to step (1), (2), (4) and (5) _d, e _q, i _d, i _q, i ^* _d, i ^* _q, p ₁And p ₂, wherein, i ^* _q=0, try to achieve the d axle reference voltage u that inverter is exported by formula (2) ^* _dWith q axle reference voltage u ^* _q, L and R are respectively the inductance and the resistance of inverter outlet side reactor, k in the formula (2) ₁And k ₂Be respectively the exponential damping coefficient of the sliding formwork of inverter output d, q shaft current, k _cBe the feedforward compensation coefficient;

$\left\{\begin{array}{c}{u}_d^{*}={Ri}_d+e_d+c_{1}L(i_d^{*}-i_d)+k_1{\mathrm{<figure-callout\; id="1"\; label="s"\; filenames="H2009100320140E00031.png,H2009100320140E00041.png"\; state="\{\{state\}\}">s</figure-callout>}}_1+p_1\\ u_q^{*}=k_c{i}_d^{*}+{\mathrm{Ri}}_q+e_q+c_{2}L(i_q^{*}-i_q)+k_2{\mathrm{<figure-callout\; id="2"\; label="s"\; filenames="H2009100320140E00031.png"\; state="\{\{state\}\}">s</figure-callout>}}_2+p_2\end{array}\right.---\left(2\right)$

(7) anglec of rotation θ that utilizes step (1) to obtain u that step (6) is obtained ^* _dAnd u ^* _qCarry out Parker Park inverse transformation, obtain the u under the two-phase rest frame ^* _αAnd u ^* _β, adopt space vector pulse width modulation SVPWM method then, handle obtaining 6 road pulse-width modulation PWM pulses through digital signal processor DSP.

The present invention compared with prior art has following beneficial effect:

1) strong robustness.Sliding-Mode Control Based is a kind of non linear robust control method, and it is mainly used in the inexactness of handling modeling, though its model inaccuracy, the robustness of the system that keeps that also can be good; Simultaneously, the maximum characteristics of fuzzy control are that the experience and knowledge with the expert is expressed as language rule and is used for control, do not rely on the mathematical models of controlled device, can overcome the non-linear factor influence, the parameter that is conditioned object had stronger robustness, therefore, fuzzy control will more can improve the robustness of grid-connected control system with combining of Sliding-Mode Control Based;

2) good stability.Because fuzzy control does not rely on the mathematical models of controlled device, can overcome the non-linear factor influence, the parameter that is conditioned object had stronger robustness, therefore, replace switch amount of switched in the general Sliding-Mode Control Based with the output variable of fuzzy controller, promptly utilize the output variable of fuzzy algorithmic approach softening sliding mode controller, alleviate the chattering phenomenon of general Sliding-Mode Control Based greatly.Simultaneously, owing to have integral in the sliding formwork that is adopted, as the formula (1), therefore, can effectively eliminate d, the q shaft current i of inverter output _d, i _qRespectively to its reference current i ^* _d, i ^* _qThe steady-state error of following the tracks of;

3) rapid dynamic response speed.K in the formula (2) _iS is the control component that index law changes, i.e. index convergence rule control, when the system mode track from sliding formwork line s _iWhen=0 distance was far away more, controlled quentity controlled variable is exponential ground to be increased fast, greatly shortens the response time of system's initial start up phase, and works as the system mode track from sliding formwork line s _iWhen=0 distance was near more, then controlled quentity controlled variable was the decay fast of exponential ground again, and enter the sliding-mode surface that system interference is had a good robust performance (is sliding formwork line s with guaranteeing the system mode smooth trajectory _iNear=0) interior motion; Simultaneously, use d, the q shaft current i that feedforward compensation compensates inverter output fast _d, i _qBetween the part that intercouples, realize i _dWith i _qBetween quick dynamic decoupling.

Description of drawings

Fig. 1 is monopole three-phase photovoltaic grid-connected system topological structure and control block diagram.

Fig. 2 is the modified fuzzy sliding mode controlling method block diagram.

Fig. 3 (a) and (b) and the input variable s that (c) is respectively fuzzy controller _i,

And output variable p _iMembership function.

Fig. 4 (a) is the intensity of illumination change curve, (b) the d shaft current i that exports for inverter _dAnd reference current i ^* _dChange curve, (c) be the q shaft current i of inverter output _qAnd reference current i ^* _qChange curve, (d) be the sliding formwork s of the d shaft current of inverter output ₁Movement locus, be 600W/m (e) for intensity of illumination ²The time, the sliding formwork s of the d shaft current of inverter output ₁Movement locus.

Embodiment

The present invention specifically is achieved through the following technical solutions:

(1) A, B, the C three-phase voltage signal of detection utility grid are obtained line voltage vector anglec of rotation θ by the phase-locked loop pll method, utilize anglec of rotation θ and electrical network A, B, C three-phase voltage signal to calculate d, the q axle DC component e of line voltage simultaneously _d, e _q

(2) detect inverter output end A, B, C three-phase current signal, utilize the anglec of rotation θ in the step (1) to carry out the conversion of dq rotating vector, rotated the direct current component i under the dq axis coordinate system synchronously _d, i _q

(3) detect the photovoltaic array output voltage U _PvAnd electric current I _Pv, adopt MPPT maximum power point tracking MPPT method---disturbance observation commonly used, try to achieve the photovoltaic array maximum power point reference voltage U under the current environment condition _Ref, the basic principle of disturbance observation is: periodically give photovoltaic array maximum power point reference voltage U _RefIncrease disturbance, relatively photovoltaic array power output P _PvWith the size of the power output in last cycle, if power increase then add disturbance with equidirectional at next cycle; Otherwise, add disturbance in the opposite direction;

(4) the photovoltaic array output voltage U that obtains by step (3) _PvWith the U that obtains by step (3) _RefDifference through obtaining the d axle reference current i of inverter output behind the proportional integral pi regulator ^* _d,, the q axle reference current i of inverter output is set for making inverter output current and line voltage same-phase ^* _q=0, the current i that obtains according to step (2) again _dAnd i _q, obtain the sliding formwork s of the d shaft current of inverter output by formula (1) ₁Sliding formwork s with the q shaft current ₂, c in the formula (1) ₁And c ₂Be respectively the integral coefficient of sliding formwork of d, the q shaft current of inverter output, t is the time;

$\left\{\begin{array}{c}{\mathrm{<figure-callout\; id="1"\; label="s"\; filenames="H2009100320140E00031.png,H2009100320140E00041.png"\; state="\{\{state\}\}">s</figure-callout>}}_1=i_d^{*}-i_d+{\mathrm{<figure-callout\; id="1"\; label="c"\; filenames="H2009100320140E00031.png,H2009100320140E00041.png"\; state="\{\{state\}\}">c</figure-callout>}}_1{\&Integral;}_0^t(i_d^{*}-i_d)\mathrm{<figure-callout\; id="2"\; label="dt\; s"\; filenames="H2009100320140E00031.png"\; state="\{\{state\}\}">dt</figure-callout>}& \\ s_{}{}_2=i_q^{*}-i_q+{\mathrm{<figure-callout\; id="2"\; label="c"\; filenames="H2009100320140E00031.png"\; state="\{\{state\}\}">c</figure-callout>}}_2{\&Integral;}_0^t(i_q^{*}-i_q)\mathrm{dt}\end{array}\right.---\left(1\right)$

(5) make i=1,2, the s that step (4) is obtained ₁And s ₁Derivative As the input of first fuzzy controller, pass through obfuscation, fuzzy reasoning and reverse gelatinization successively after, obtain the output variable p of first fuzzy controller ₁, the s that step (4) is obtained ₂And s ₂Derivative

As the input of second fuzzy controller, pass through obfuscation, fuzzy reasoning and reverse gelatinization successively after, obtain the output variable p of second fuzzy controller ₂, s wherein _i,

And p _iFuzzy set all be taken as 7, be expressed as that { NB=is negative big, during NM=is negative, NS=is negative little, and ZE=zero, and PS=is just little, PM=center, PB=is honest }, 49 fuzzy rules that 49 fuzzy rules that first fuzzy controller is adopted and second fuzzy controller are adopted are shown in the following table:

Article 49, total formulation principle of fuzzy rule is: reduce to arrive sliding formwork line s as far as possible _iThe shake of=0 o'clock system is specially: according to sliding formwork s _iWith its derivative s _iDecide the output variable p of fuzzy controller _i, as rule wherein be: if " s _i=NB,

", " p then _i=NB ".Work as s _i=0 o'clock, i then _Dref=i _dAnd i _Qref=i _q, promptly realized the floating tracking; Work as s _i≠ 0 o'clock, the fuzzy control sliding formwork line s that will effectively weaken _iNear=0 buffeting makes sliding formwork s as far as possible _iAt sliding formwork line s _iSlide in near=0 the minimum zone;

(6) e that obtains according to step (1), (2), (4) and (5) _d, e _q, i _d, i _q, i ^* _d, i ^* _q, p ₁And p ₂, wherein, i ^* _q=0, try to achieve the d axle reference voltage u that inverter is exported by formula (2) ^* _dWith q axle reference voltage u ^* _q, L and R are respectively the inductance and the resistance of inverter outlet side reactor, k in the formula (2) ₁And k ₂Be respectively the exponential damping coefficient of the sliding formwork of inverter output d, q shaft current, k _cBe the feedforward compensation coefficient; K in the formula (2) _iS is the control component that index law changes, and its principle is for working as the system mode track from sliding formwork line s _iWhen=0 distance was far away more, controlled quentity controlled variable was exponential increase, greatly shortened the response time of system's initial start up phase, and worked as the system mode track from sliding formwork line s _iWhen=0 distance was near more, then controlled quentity controlled variable was exponential decay again, and enter the sliding-mode surface that system interference is had a good robust performance (is sliding formwork line s with guaranteeing the system mode smooth trajectory _iNear=0) interior motion, k _iThen decay soon more greatly more, k _iSize to comprehensively determine according to the maximum controlled quentity controlled variable that systematic function requires and system can provide; p _iFor the control component that the uncertain part of system model (perturbing as external interference and inner parameter) is estimated, in case s _iEnter sliding-mode surface, the buffeting problem that fuzzy control then utilizes the next effective reduction of the robustness system of self to exist, the output of softening sliding mode controller; k _ci ^* _dFor being used for system is carried out the control component of feedforward compensation, its effect is d, the q shaft current i that compensates inverter output fast _d, i _qBetween the part that intercouples, realize i _dWith i _qBetween quick dynamic decoupling;

$\left\{\begin{array}{c}{u}_d^{*}={Ri}_d+e_d+c_{1}L(i_d^{*}-i_d)+k_1{\mathrm{<figure-callout\; id="1"\; label="s"\; filenames="H2009100320140E00031.png,H2009100320140E00041.png"\; state="\{\{state\}\}">s</figure-callout>}}_1+p_1\\ u_q^{*}=k_c{i}_d^{*}+{\mathrm{Ri}}_q+e_q+c_{2}L(i_q^{*}-i_q)+k_2{\mathrm{<figure-callout\; id="2"\; label="s"\; filenames="H2009100320140E00031.png"\; state="\{\{state\}\}">s</figure-callout>}}_2+p_2\end{array}\right.---\left(2\right)$

(7) anglec of rotation θ that utilizes step (1) to obtain u that step (6) is obtained ^* _dAnd u ^* _qCarry out Parker Park inverse transformation, obtain the u under the two-phase rest frame ^* _αAnd u ^* _β, adopt space vector pulse width modulation SVPWM method then, handle obtaining 6 road pulse-width modulation PWM pulses through digital signal processor DSP.

With reference to the accompanying drawings and in conjunction with Matlab/Simulink ﹠amp; The present invention is described in further detail to the simulation example of 10kW monopole three-phase photovoltaic grid-connected system for Simpowersystems.But the invention is not restricted to given example.System topology and control block diagram as shown in Figure 1,10kW photovoltaic array standard environment condition (the intensity of illumination R=1kW/m that this example adopted ², ambient temperature T=25 ℃) and descend parameter to be: maximum power point voltage U _Max=390V, the maximum power point electric current I _Max=26A, open circuit voltage U _Oc=506V, short circuit current I _Sc=30A, the circuit system parameter is: condenser capacitance C=0.012F, reactor inductance L=0.018H, reactor resistance R=0.08 Ω, simulation step length Ts=50 μ s.The initial voltage at capacitor two ends, i.e. photovoltaic array output voltage U _PvInitial value be that (in intensity of illumination is 100W/m to 319.0V ²The time the maximum power point place), photovoltaic array maximum power point reference voltage U _RefInitial value is taken as 319.1V, the photovoltaic array output voltage U _PvAnd electric current I _PvSampling period be 2.5ms.

By MPPT maximum power point tracking MPPT method,, obtain the photovoltaic array maximum power point reference voltage U of current sampling instant as the disturbance observation _RefAfter, realize the photovoltaic array output voltage U by the double closed-loop control system of being formed by voltage PI controller and fuzzy sliding mode tracking control device again _PvTo U _RefTracking fast and accurately.The parameter of voltage ratio integral PI adjuster is respectively: k _p=10, k ₁=900; Fuzzy sliding mode tracking control device parameter k ₁=k ₂=1.5, c ₁=c ₂=1000; The feedforward compensation coefficient k _c=11.

The modified fuzzy sliding mode controlling method block diagram as shown in Figure 2, two input variables of the fuzzy controller in the fuzzy sliding mode tracking control device are respectively sliding formwork s _iAnd s _iDerivative s _i, output variable is p _is _i, s _iAnd p _iAll adopt 7 fuzzy subsets' Triangleshape grade of membership function, shown in Fig. 3 (a) and (b), (c), the ambiguity in definition set is { NB=bears big, and during NM=was negative, NS=was negative little, and ZE=zero, and PS=is just little, and PM=hits exactly, and PB=is honest } respectively.s _i, s _iAnd p _iQuantizing factor all be taken as 1, domain is respectively [3,3], [5000,5000] and [2,2].At first, s _iAnd s _iObtain corresponding fuzzy quantity by the Triangleshape grade of membership function shown in Fig. 3 (a) and (b) respectively, then, obtain the output fuzzy quantity of fuzzy controller by 49 fuzzy rule computings shown in the fuzzy reasoning table of the present invention, at last, Triangleshape grade of membership function according to Fig. 3 (c), adopt gravity model appoach with the gelatinization of fuzzy quantity reverse, obtain the output variable p of accurate fuzzy controller _i

The simulated effect that adopts the inventive method as shown in Figure 4, as seen from the figure:

1) strong robustness.By Fig. 4 (a) and (d) as seen, illumination intensity is by 300W/m during 0.5s ²Suddenly change to 600W/m ²The time, the sliding formwork s of the d shaft current of inverter output ₁Almost without any variation; By Fig. 4 (b) and (c) as seen, the d shaft current i of inverter output _dSteadily arrive 0.48 per unit value from 0.24 per unit value (P.U.) through about 0.05s, the q shaft current i of inverter output _qStill be 0 per unit value, do not change;

2) good stability.By Fig. 4 (a) and (b) as seen, illumination intensity is by 300W/m during 0.5s ²Suddenly change to 600W/m ²The time, the d shaft current i of inverter output _dFrom 0.24 per unit value through about 0.05s with regard to floating, non-overshoot reach its reference current i ^* _dSteady-state value 0.48 per unit value; By Fig. 4 (e) as seen, at intensity of illumination 600W/m ²The time stable situation under, the sliding formwork s of the d shaft current of inverter output ₁The buffeting scope only be [0.03,0.05], as seen adopt the fuzzy control peculiar chattering phenomenon of Sliding-Mode Control Based that effectively weakened, softening the controlled quentity controlled variable of sliding mode controller;

3) rapid dynamic response speed.By Fig. 4 (a) and (d) as seen, from system initial state to intensity of illumination 300W/m ²The time the system stability state, the sliding formwork s of modified fuzzy sliding mode controlling method proposed by the invention ₁Maximum only be about 5, and only just enter sliding-mode surface smoothly through about 0.12s; By Fig. 4 (a) and (b) as seen, illumination intensity is by 300W/m during 0.5s ²Suddenly change to 600W/m ²The time, the d shaft current i of inverter output _dJust steadily be increased to its reference current i from 0.24 per unit value apace through about 0.05s ^* _dSteady-state value 0.48 per unit value, and as seen by Fig. 4 (c), the q shaft current i of inverter output _qNo matter its reference current i is stably followed the tracks of in the variation of external environmental condition always ^* _q=0, therefore, effectively realized d, the q shaft current i of inverter output _dWith i _qBetween quick dynamic decoupling.

Claims (1)

1. the modified fuzzy sliding mode controlling method of a monopole three-phase photovoltaic grid-connected system is characterized in that this method may further comprise the steps:

(1) A, B, the C three-phase voltage signal of detection utility grid are obtained line voltage vector anglec of rotation θ by the phase-locked loop pll method, utilize anglec of rotation θ and electrical network A, B, C three-phase voltage signal to calculate d, the q axle DC component e of line voltage simultaneously _d, e _q

(2) detect inverter output end A, B, C three-phase current signal, utilize the anglec of rotation θ in the step (1) to carry out the conversion of dq rotating vector, rotated the direct current component i under the dq axis coordinate system synchronously _d, i _q

(3) detect the photovoltaic array output voltage U _PvAnd electric current I _Pv, employing disturbance observation is tried to achieve the photovoltaic array maximum power point reference voltage U under the current environment condition _Ref

(4) the photovoltaic array output voltage U that obtains by step (3) _PvWith the U that obtains by step (3) _RefDifference through obtaining the d axle reference current i of inverter output behind the proportional integral pi regulator ^* _d,, the q axle reference current i of inverter output is set for making inverter output current and line voltage same-phase ^* _q=0, again according to step

(2) the direct current component i that obtains _dAnd i _q, obtain the sliding formwork s of the d shaft current of inverter output by formula (1) ₁Sliding formwork s with the q shaft current ₂, c in the formula (1) ₁And c ₂Be respectively the integral coefficient of sliding formwork of d, the q shaft current of inverter output, t is the time;

$\left\{\begin{array}{c}{s}_1=i_d^{*}-i_d+c_1{\&Integral;}_0^t(i_d^{*}-i_d)\mathrm{dt}\\ s_2=i_q^{*}-i_q+c_2{\&Integral;}_0^t(i_q^{*}-i_q)\mathrm{dt}\end{array}\right.---\left(1\right)$

(5) make i=1,2, the s that step (4) is obtained ₁And s ₁Derivative

As the input of first fuzzy controller, pass through obfuscation, fuzzy reasoning and reverse gelatinization successively after, obtain the output variable p of first fuzzy controller ₁, the s that step (4) is obtained ₂And s ₂Derivative

As the input of second fuzzy controller, pass through obfuscation, fuzzy reasoning and reverse gelatinization successively after, obtain the output variable p of second fuzzy controller ₂, s wherein _i,

And p _iFuzzy set all be taken as 7, be expressed as that { NB=is negative big, during NM=is negative, NS=is negative little, and ZE=zero, and PS=is just little, PM=center, PB=is honest }, 49 fuzzy rules that 49 fuzzy rules that first fuzzy controller is adopted and second fuzzy controller are adopted are shown in the table 1:

Table 1

(6) e that obtains according to step (1), (2), (4) and (5) _d, e _q, i _d, i _q, i ^* _d, i ^* _q, s ₁, s ₂, p ₁And p ₂, wherein, i ^* _q=0, try to achieve the d axle reference voltage u that inverter is exported by formula (2) ^* _dWith q axle reference voltage u ^* _q, L and R are respectively the inductance and the resistance of inverter outlet side reactor, k in the formula (2) ₁And k ₂Be respectively the exponential damping coefficient of the sliding formwork of inverter output d, q shaft current, k _cBe the feedforward compensation coefficient;

$\left\{\begin{array}{c}{u}_d^{*}={Ri}_d+e_d+c_{1}L(i_d^{*}-i_d)+k_1{s}_1+p_1\\ u_q^{*}=k_c{i}_d^{*}+{\mathrm{Ri}}_q+e_q+c_{2}L(i_q^{*}-i_q)+k_2{s}_2+p_2\end{array}\right.---\left(2\right)$

(7) anglec of rotation θ that utilizes step (1) to obtain u that step (6) is obtained ^* _dAnd u ^* _qCarry out Parker Park inverse transformation, obtain the u under the two-phase rest frame ^* _αAnd u ^* _β, adopt space vector pulse width modulation SVPWM method then, handle obtaining 6 road pulse-width modulation PWM pulses through digital signal processor DSP.

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