CN105974995A - Maximum power point tracking system and method - Google Patents

Abstract

The invention discloses a maximum power point tracking system and method; the system comprises the following structures: a photovoltaic array module used for converting solar energy into electricity; a MPPT golden section ratio calculating unit using the golden section ratio method to track the maximum power point outputted by the photovoltaic array module, thus obtaining a power reference value close to the maximum power point; a model prediction control unit using a model prediction control method to calculate the output of the MPPT golden section ratio calculating unit, thus tracking the accurate maximum power point, so the system can operate on the maximum power point, and the tracked accurate maximum power point is compared with the power reference value obtained by the golden section ratio method so as to obtain a value function g, thus controlling switch states of a Boost circuit; the Boost circuit connected between the photovoltaic array module and a load, and controlled by the model prediction control unit. The maximum power point tracking system and method can improve the conversion efficiency of the photovoltaic power generation system.

Description

A kind of maximum power point tracking system and method

Technical field

The present invention relates to a kind of MPPT (Maximum Power Point Tracking, MPPT maximum power point tracking) Method, particularly relates to the maximum power point that a kind of Model Predictive Control combines with golden mean optimization and chases after Track method.

Background technology

In the last few years, global economy was fast-developing so that Fossil fuel luxus consumption, energy crisis occurred, Environmental problem is the severeest.Solar energy is more and more concerned, due to the sun as the regenerative resource of cleaning Being relatively small in size of energy photovoltaic panel, it is easy to install, it is also possible to close to user installation, noiseless during operation, Unharmful substance discharges, and the research of solar electrical energy generation is increasingly paid attention to.

Owing to the output voltage of photovoltaic cell has along with the change of intensity of sunshine and battery junction temperature with output electric current Have strong non-linear, under specific working environment, therefore there is a unique maximum power point (mpp) (MPP).In order to enable a system to always work at maximum power point, it is necessary to some specific algorithms come Maximum power point is tracked.

At present, the method for some conventional MPPT maximum power point trackings (MPPT) thankss for your hospitality dynamic observational method (P&Q), Conductance increment method (INC), fuzzy control, neural network etc., these algorithms have respective pluses and minuses, P&Q algorithm is simple, it is easy to implement, although INC is more accurate, but its implementation process is more complicated, and And in the case of condition Rapid Variable Design, INC is more suitable than P&Q, but under shade, P&Q and INC Follow the tracks of global maximum power point all can lose efficacy.Fuzzy control and these intelligent algorithms of neutral net, algorithm structure Complicated, it is difficult to realize, seldom use.

Summary of the invention

For the deficiency overcoming above-mentioned prior art to exist, the purpose of the present invention is to provide a kind of model prediction control The MPPT method that system combines with golden mean optimization, it is by pre-with model by golden mean optimization Observing and controlling system combines, so that system traces into maximum power point quickly and accurately, improves photovoltaic generation The conversion efficiency of system.

For reaching above and other purpose, the present invention proposes a kind of maximum power point tracking system, including:

Photovoltaic array module, for being converted into electric energy by solar energy by photovoltaic array；

MPPT golden section point computing unit, utilizes golden section point method to carry out the output of photovoltaic array module Maximum power point tracking, obtains the value and power reference close to maximum power point；

Model Predictive Control unit, re-uses model to the output of this MPPT golden section point computing unit pre- Survey control method, trace into maximum power point accurately, make system operate at maximum power point, and with Huang The value and power reference that gold cut-point method draws compares and draws cost function g, to control Boost circuit On off state；

Boost circuit, is connected between this photovoltaic array module and load, receives this Model Predictive Control The control of unit.

Further, this MPPT golden section point computing unit P-U characteristic curve by photovoltaic cell, Use golden mean optimization that maximum power point is tracked.

Further, this MPPT golden section point computing unit is achieved by the steps of:

(1) initial range [a is set₀, b₀】；.

(2) calculate golden section point x1, x2, and calculate corresponding power P_X1, P_X2。

(3) P is compared_X1And P_X2If, P_X1=P_X2, then next scope is [x1, x2]；If P_X1＜ P_X2, prune 【a₀, x₁], then next scope is [x1, b₀】；If P_X1＞ P_X2, prune [x2, b₀], then next scope is 【a₀, x2], wherein, a₀、b₀, x1, x2 be the U of P-U curve of photovoltaic cell；

(4) step (2) and (3) it are iteratively repeated, when the difference of 2 power is less than certain setting value specific During ε, close to maximum power point.

Further, this Model Predictive Control unit forecast model based on Boost circuit, utilize two steps Method is predicted.

Further, this Model Predictive Control unit uses and minimizes cost function acquisition cost function g as follows:

g_S=0,1=| P_{PV, S=0,1}(k+2)-P_ref|

Wherein, P_{PV, S=0,1}(k+2) being the photovoltaic output in K+2 moment, S=0 is switching tube off-state, S=1 For switching tube closure state, P_refThe value and power reference calculated for this MPPT golden section point computing unit.

For reaching above-mentioned purpose, the present invention also provides for a kind of maximum power point tracking method, comprises the steps:

Step one, utilizes photovoltaic array module to convert solar energy into electrical energy.

Step 2, utilizes golden mean optimization that the output of photovoltaic array module is carried out maximum power point tracking, Obtain the value and power reference close to maximum power point.

Step 3, re-uses model prediction control to the output utilizing golden section point to carry out maximum power point tracking Method processed, traces into maximum power point accurately, makes system operate at maximum power point, and divides with gold The value and power reference that cutpoint method draws compares and draws cost function g, to control opening of Boost circuit Off status.

Further, step 2 farther includes:

(1) initial range [a is set₀, b₀】。

(2) calculate golden section point x1, x2, and calculate corresponding power P_X1, P_X2。

(3) P is compared_X1And P_X2If, P_X1=P_X2, then next scope is [x1, x2]；If P_X1＜ P_X2, prune 【a₀, x1], then next scope is [x1, b₀】；If P_X1＞ P_X2, prune [x2, b₀], then next scope is 【a₀, x2], wherein a₀、b₀, x1, x2 be the U of P-U curve of photovoltaic cell；

(4) step (2) and (3) it are iteratively repeated, when the difference of 2 power is less than certain setting value specific During ε, close to maximum power point.

Further, in step 3, forecast model based on Boost circuit, utilize two-step method to carry out Prediction so that the value following the tracks of maximum power point is more accurate.

Further, in step 3, use and minimize cost function acquisition cost function g as follows:

g_S=0,1=| P_{PV, S=0,1}(k+2)-P_ref|

Wherein, P_{PV, S=0,1}(k+2) being the photovoltaic output in K+2 moment, S=0 is switching tube off-state, S=1 For switching tube closure state, P_refThe value and power reference calculated for this MPPT golden section point computing unit.

Further, the method is realized by the dutycycle changing pwm control signal.

Compared with prior art, one maximum power point tracking system and method for the present invention is by by golden section Point algorithm combines with Model Predictive Control, so that system traces into maximum power point quickly and accurately, And at maximum power point, do not produce concussion, improve the conversion efficiency of photovoltaic generating system.

Accompanying drawing explanation

Fig. 1 is the schematic equivalent circuit of photovoltaic cell；

Fig. 2 is photovoltaic property curve synoptic diagram；

Fig. 3 is the structural representation of the present invention a kind of maximum power point tracking system；

Fig. 4 is golden section point principle schematic；

Fig. 5 is golden mean optimization schematic diagram；

The equivalent circuit diagram switching off and closing of Fig. 6 and Fig. 7 respectively Boost circuit；

Fig. 8 is that MPC (Model Predictive Control) two-step method predicts explanatory diagram；

Fig. 9 is the MPPT procedure chart of the specific embodiment of the invention；

Figure 10 is the flow chart of steps of the present invention a kind of maximum power point tracking method.

Detailed description of the invention

Below by way of specific instantiation accompanying drawings embodiments of the present invention, art technology Personnel can be understood further advantage and effect of the present invention easily by content disclosed in the present specification.The present invention Also can be implemented by other different instantiation or be applied, the every details in this specification also can base In different viewpoints and application, under the spirit without departing substantially from the present invention, carry out various modification and change.

Before introducing the present invention, the characteristic of photovoltaic cell is first described:

The equivalent circuit of photovoltaic cell is as shown in Figure 1.The output of current source directly becomes ratio with light radiation level Example, diode in parallel has decisive role to the I-V curve feature of solaode.

This model comprises the photogenerated current I become with temperature, intensity of illumination_L, diode saturation current I₀, string Connection resistance R_S, and diode in parallel.The I-V characteristic of solaode is described by below equation:

$I=I_L-I_0(e^{\frac{q\left(V+{\mathrm{IR}}_S\right)}{nKT}}-1)---\left(1\right)$

I_L=I_L(T1)(1+K₀(T-T₁)) (2)

I_L(T1)=G*I_{SC (T1, nom})/G_nom (3)

$K_0=(I_{\mathrm{SC}\left(T_2\right)}-I_{\mathrm{SC}\left(T_1\right)})/(T_2-T_1)---\left(4\right)$

$I_0=I_{0\left(T1\right)}*{\left(\frac{T}{T_1}\right)}^{\frac{3}{n}}*e^{\frac{-qVg}{nk\left(\frac{1}{T}-\frac{1}{T_1}\right)}}---\left(5\right)$

$I_{0\left(T1\right)}=I_{SC\left(T1\right)}/\left(e^{\frac{{\mathrm{qV}}_{OC\left(T_1\right)}}{{\mathrm{nkT}}_1}}-1\right)---\left(6\right)$

$R_S=-\frac{dV}{{\mathrm{dI}}_{V_{OC}}}-\frac{1}{X_V}---\left(7\right)$

$X_V=I_{0\left(T_1\right)}*\frac{q}{{\mathrm{nkT}}_1}*e^{\frac{{\mathrm{qV}}_{OC\left(T_1\right)}}{{\mathrm{nkT}}_1}}---\left(8\right)$

Some constants of above-mentioned formula, such as open-circuit voltage and short circuit current in the T1 moment can be from equipment Data book obtains.Solar energy photovoltaic panel is unglazed according to when irradiating, and the relation of terminal voltage and end electric current can be used Famous four layer diode formula shows, represents by formula (9):

$I=I_0\left(e^{\frac{q\left(V+{\mathrm{IR}}_S\right)}{nkT}}-1\right)---\left(9\right)$

When cell panel and open circuit are irradiated in illumination, photoelectric current fully flows to diode.Formula (1) Represent the shunting of photoelectric current.Formula (2) represents photoelectric current and the linear relationship of temperature.Formula (4) is inferred Go out the relation that photoelectric current changes with temperature change.In the short circuit current cycle, diode current can be ignored Disregard, therefore proportionality constant I_{SC (T1, nom)}It is the short circuit current I set under specific illumination condition_SC, such as formula (3) shown in.That formula (5) illustrates is I₀Relation with temperature.What formula (6) illustrated is in temperature T₁Time Carve, from open-circuit voltage and calculation of short-circuit current out diode saturation current I₀.Ideal factor n is normally Under the conditions of can be 1.2.The series resistance of solar energy photovoltaic panel can be calculated from formula (7), (8), It is about 8m Ω.Fig. 2 is photovoltaic property curve.

Fig. 3 is the structural representation of the present invention a kind of maximum power point tracking system.As it is shown on figure 3, this Bright a kind of maximum power point tracking system, including: photovoltaic array module 301, MPPT golden section point calculate Unit 302, Model Predictive Control unit 303, Boost circuit 304.

Wherein, photovoltaic array module 301 is for being converted into electric energy by solar energy by photovoltaic array；MPPT is yellow Gold partition point calculation unit 302 utilizes golden section point method that the output of photovoltaic array module 301 is carried out maximum Power points is followed the trail of, and obtains the value and power reference close to maximum power point；Model Predictive Control unit 303 is right The output of MPPT golden section point computing unit 302 re-uses model predictive control method, traces into accurately Maximum power point, makes system operate at maximum power point, and the power reference drawn with golden section point method Value compares and draws cost function g, and to control the on off state of Boost circuit 305, this model is pre- Survey control unit 303 and can predict output voltage and the output electric current of photovoltaic panel, then calculate prediction Power；The value and power reference drawn with golden section point method compares and draws cost function g, finally controls What Boost circuit 304 switched opens, turns off；Boost circuit 304, is connected to photovoltaic array Between module 301 and load, receive the control of Model Predictive Control unit 303, photovoltaic array module 301 One end be connected with inductance L one end of Boost circuit 304, the other end of inductance L and Boost boost Switching tube S one end of circuit 304 and forward direction conducting diode D1 positive pole connect, another of photovoltaic array module End is connected with the switching tube S other end, and switching tube S can be IGBT pipe here, and electric capacity C one end connects two The negative pole of pole pipe D1, the other end connects this photovoltaic array module 301 and this switching tube S.

The control strategy of the present invention is based on Boost circuit, drives boost to rise piezoelectricity by control algolithm The switching tube on road, thus realize MPPT.Control object is the output of photovoltaic panel, power be by voltage, Current calculation obtains, and uses golden section point method to be tracked peak power, the value and power reference obtained Close to maximum power point, re-use model predictive control method, maximum power point accurately can be traced into, make System operates at maximum power point, it was predicted that model can predict output voltage and the output electric current of photovoltaic panel, Then calculate the power of prediction, then the value and power reference drawn with golden section point method compares to obtain bid Value function g, finally controls the opening of switch of Boost circuit, turns off.

Specifically, MPPT golden section point computing unit 302 is to utilize golden section point method to photovoltaic array mould The output of block 101 carries out maximum power point tracking, obtains the value and power reference close to maximum power point.Gold Cut-point principle is as shown in Figure 4.

X2=λ L, x1=L-λ L=L-x2

Wherein λ=0.618

Therefore, as optimum point interval [a again₀, b₀] time, it is taken at the 0.618 of interval, i.e. by souning out point X2=0.618 (b₀-a₀), then another point is just in its symmetric position, i.e. X1=(b₀-a₀)-x2=0.382 (b₀-a₀), upper once prune time, a little choose again in interval the taking of residue Golden section point, so repeats.

In the present invention, the MPPT golden section point computing unit 302 P-U characteristic curve by photovoltaic cell, The step using golden mean optimization to be tracked maximum power point is as follows:

(1) initial range [a is set₀, b₀], as shown in Figure 5.

(2) calculate golden section point x1, x2, and calculate corresponding power P_X1, P_X2。

(3) P is compared_X1And P_X2If, P_X1=P_X2, then next scope is [x1, x2]；If P_X1＜ P_X2, prune 【a₀, x1], then next scope is [x1, b₀】；If P_X1＞ P_X2, prune [x2, b₀], then next scope is 【a₀, x2].(above a₀、b₀, x1, x2 be the U of P-U curve)

(4) step (2) and (3) it are iteratively repeated, when the difference of 2 power is less than certain setting value specific During ε (ε=0.37), close to maximum power point.

Model Predictive Control unit 303 is that the output to MPPT golden section point computing unit 102 re-uses Model predictive control method, traces into maximum power point accurately, makes system operate at maximum power point, And the value and power reference drawn with golden section point method compares and draws cost function g, to control Boost liter The on off state of volt circuit 304.Specifically, the present invention utilizes two-step method to be predicted so that follow the tracks of maximum The value of power points is more accurate.Fig. 6 and Fig. 7 is the equivalent circuit switching off and closing of Boost circuit Figure.

When boost circuit switch disconnects, circuit can be expressed as formula 10 and formula 11:

$\begin{array}{cc}L\frac{{\mathrm{di}}_{PV}}{dt}=V_{PV}-V_C---\left(10\right)& C\frac{{\mathrm{dV}}_C}{dt}=I_{PV}-\frac{V_C}{R}---\left(11\right)\end{array}$

When boost circuit switch closes, circuit can be expressed as formula 12 and formula 13:

$\begin{array}{cc}L\frac{{\mathrm{di}}_{PV}}{dt}=V_{PV}---\left(12\right)& C\frac{{\mathrm{dv}}_c}{dt}=-\frac{V_C}{R}---\left(13\right)\end{array}$

By using Euler approximation method, the discrete time model of topological structure can be obtained, shown in formula 14.

$\frac{{\mathrm{di}}_{PV}}{dt}=\frac{i_{PV,k+1}-i_{PV,k}}{T_s},\frac{dv}{dt}=\frac{V_{c,k+1}-V_{c,k}}{T_s}---\left(14\right)$

By the discrete time equation formula obtained, the control variable at next sampling instant k+1 can be by advance Survey.

Again according to the relation of booster circuit input with output: V_PV=(1-D) V_C, wherein D is accounting for of switching tube Empty ratio.

It is the sampling time to be T when the sampling time_STime, formula 15 when the switches are opened, formula 16 and can be obtained Formula 17 when switching S Guan Bi and opening, formula 18.

$I_{PV}(k+1)=\frac{T_S}{L}{V}_{PV}\left(k\right)+I_{PV}\left(k\right)-\frac{T_S}{L}{V}_C\left(k\right)---\left(15\right)$

$V_{PV}(k+1)=V_{PV}\left(k\right)-\frac{T_S{V}_C\left(k\right)}{RC}(1-D)+\frac{T_S{I}_{PV}\left(k\right)}{C}(1-D)---\left(16\right)$

$I_{PV}\left(k+1\right)=I_{PV}\left(k\right)+\frac{T_S}{L}{V}_{PV}\left(k\right)---\left(17\right)$

$V_{PV}(k+1)=V_{PV}\left(k\right)-\frac{T_S{V}_C\left(k\right)}{RC}(1-D)---\left(18\right)$

I can be drawn according to formula 15,16,17,18_PVAnd V (k+1)_PV(k+1) predictive value, formula 19,20 Represent.

$I_{PV}(k+1)=I_{PV}\left(k\right)+\frac{T_S}{L}{V}_{PV}\left(k\right)-\frac{T_S}{L}{V}_c\left(k\right)S---\left(19\right)$

$V_{PV}(k+1)=V_{PV}\left(k\right)-\frac{T_S{V}_C\left(k\right)}{RC}(1-D)+\frac{T_S{I}_{PV}\left(k\right)}{C}(1-D)S---\left(20\right)$

S is the state (S=0 or S=1) of switch.

In order to predict the control variable at moment k+2, PV voltage, PV electric current and output voltage are when k+1 The estimated value carved is used.So at sampling instant k+2, it was predicted that go out four values of control variable, finally select One optimum, Fig. 8 describe in detail this process.Then MPC (Model Predictive Control) second stage Equation is formula 21,22.

$I_{PV}(k+2)=I_{PV}(k+1)+\frac{T_S}{L}{V}_{PV}(k+1)-\frac{T_S}{L}{V}_c(k+1)S---\left(21\right)$

$V_{PV}(k+2)=V_{PV}|(k+1)-\frac{T_S{V}_C(k+1)}{RC}(1-D)+|\frac{T_S{I}_{PV}(k+1)}{C}(1-D)S---\left(22\right)$

The forecast model of discrete time can use state-space representation, for formula (23):

$\left[\begin{array}{c}{I}_{PV}\left(k+2\right)\\ V_{PV}\left(k+2\right)\end{array}\right]=\left[\begin{array}{ccc}1& \frac{T_S}{L}& -\frac{T_{S}S}{L}\\ \frac{T_{S}S}{C}\left(1-D\right)& 1& -\left(\frac{T_S}{RC}\right)\left(1-D\right)\end{array}\right]\×\left[\begin{array}{c}{I}_{PV}\left(k+1\right)\\ V_{PV}\left(k+1\right)\\ V_c\left(k+1\right)\end{array}\right]---\left(23\right)$

Cost function plays conclusive effect in MPC control algorithm, and the deviation of expected value is carried out by it Constraint.P_refObtained by golden section point method.Minimize cost function and be expressed as formula 24:

g_S=0,1=| P_{PV, S=0,1}(k+2)-P_ref| (24)

Wherein, P_{PV, S=0,1}(k+2) being the photovoltaic output in K+2 moment, S=0 is switching tube off-state, S=1 For switching tube closure state, P_refThe value and power reference calculated for this MPPT golden section point computing unit.

In actual applications, the change of voltage is to be realized by the dutycycle changing pwm control signal, Therefore tracking range is the change scope of dutycycle D.Set initial range [D_a, D_b], calculate golden section Point D₁And D₂, arranging current duty cycle is D₁, the voltage x current of at this moment photovoltaic cell output of sampling, then calculate this Time power P₁；Again dutycycle is set to D₂, sample the at this moment voltage of photovoltaic cell, electric current, calculate now Power P₂.Relatively P₁And P₂If, P₁=P₂, then next scope is [D₁, D₂】；If P₁＜ P₂, then under One scope is [D₁, D_b】；If P₁＞ P₂, then next scope is [D_a, D₂】.Calculate the difference of two performance numbers, If its absolute value is less than setting value ε, then output reference power P_refGive and minimize cost function, calculate now Dutycycle D_k, arranging current duty cycle is D_k, sampled I_PV(k)、V_PV(k)、V_c(k), pre-by forecast model Measure optimum I_PV(k+2)、V_PV(k+2).Calculate P_PV(k+2), by minimizing cost function g control Boost The on off state of circuit, S=1, switch Guan Bi；S=0, switches off.Detail flowchart is as shown in Figure 9.

Figure 10 is the flow chart of steps of the present invention a kind of maximum power point tracking method.As shown in Figure 10, originally A kind of MPPT method of invention, comprises the steps:

Step 101, utilizes photovoltaic array module to convert solar energy into electrical energy.

Step 102, utilizes golden mean optimization that the output of photovoltaic array module is carried out maximum power point and chases after Track, obtains the value and power reference close to maximum power point.

Step 103, re-uses model prediction control to the output utilizing golden section point to carry out maximum power point tracking Method processed, traces into maximum power point accurately, makes system operate at maximum power point, and divides with gold The value and power reference that cutpoint method draws compares and draws cost function g, to control opening of Boost circuit Off status.

Specifically, in step 102, golden mean optimization is utilized to carry out the step of maximum power point tracking As follows:

(1) initial range [a is set₀, b₀】。

(2) calculate golden section point x1, x2, and calculate corresponding power P_X1, P_X2。

(3) P is compared_X1And P_X2If, P_X1=P_X2, then next scope is [x1, x2]；If P_X1＜ P_X2, prune 【a₀, x1], then next scope is [x1, b₀】；If P_X1＞ P_X2, prune [x2, b₀], then next scope is 【a₀, x2].(above a₀、b₀, x1, x2 be the U of P-U curve)

(4) step (2) and (3) it are iteratively repeated, when the difference of 2 power is less than certain setting value specific During ε (ε=0.37), close to maximum power point.

In step 103, forecast model based on Boost circuit, utilize two-step method to be predicted, make The value that must follow the tracks of maximum power point is more accurate.Specifically, MPC (Model Predictive Control) is at first stage (k+1 Moment) predictive value be:

$I_{PV}(k+1)=I_{PV}\left(k\right)+\frac{T_S}{L}{V}_{PV}\left(k\right)-\frac{T_S}{L}{V}_c\left(k\right)S$

$V_{PV}(k+1)=V_{PV}\left(k\right)-\frac{T_S{V}_C\left(k\right)}{RC}(1-D)+\frac{T_S{I}_{PV}\left(k\right)}{C}(1-D)S$

The MPC (Model Predictive Control) predictive value in second stage (k+2 moment) is:

$I_{PV}(k+2)=I_{PV}(k+1)+\frac{T_S}{L}{V}_{PV}(k+1)-\frac{T_S}{L}{V}_c(k+1)S$

$V_{PV}(k+2)=V_{PV}(k+1)-\frac{T_S{V}_S(k+1)}{RC}(1-D)+\frac{T_S{I}_{PV}(k+1)}{C}(1-D)S$

The forecast model of discrete time can use state-space representation, for:

$\left[\begin{array}{c}{I}_{PV}\left(k+2\right)\\ V_{PV}\left(k+2\right)\end{array}\right]=\left[\begin{array}{ccc}1& \frac{T_S}{L}& -\frac{T_{S}S}{L}\\ \frac{T_{S}S}{C}\left(1-D\right)& 1& -\left(\frac{T_S}{RC}\right)\left(1-D\right)\end{array}\right]\×\left[\begin{array}{c}{I}_{PV}\left(k+1\right)\\ V_{PV}\left(k+1\right)\\ V_c\left(k+1\right)\end{array}\right]$

Cost function plays conclusive effect in MPC control algorithm, and the deviation of expected value is carried out by it Constraint.P_refObtained by golden section point method.Minimize cost function as follows:.

g_S=0,1=| P_{PV, S=0,1}(k+2)-P_ref|

Wherein, P_{PV, S=0,1}(k+2) being the photovoltaic output in K+2 moment, S=0 is switching tube off-state, S=1 For switching tube closure state, P_refThe value and power reference calculated for this MPPT golden section point computing unit.

Visible, one maximum power point tracking system and method for the present invention is by by golden mean optimization and mould Type PREDICTIVE CONTROL combines, so that system traces into maximum power point quickly and accurately, and in maximum Concussion is not produced at power points.Golden section point (GSS) algorithm is the one that interval is pruned in method, and its advantage is Quickly response, strong robustness and convergence are guaranteed.The essence of golden mean optimization is to be steadily decreasing The receipts rope scope of advantage, its basic thought is: according to " go bad stay " principle, symmetry principle and etc. Progressively reducing hunting zone than shrinking principle, the main feature of Model Predictive Control (MPC) is to expectation Control variable future state prediction, it was predicted that control variable minimizes cost function by one and obtains optimal On off state, by the present invention, improves the conversion efficiency of photovoltaic generating system.

The principle of above-described embodiment only illustrative present invention and effect thereof, not for limiting the present invention. Above-described embodiment all can be carried out by any those skilled in the art under the spirit and the scope of the present invention Modify and change.Therefore, the scope of the present invention, should be as listed by claims.

Claims (10)

1. a maximum power point tracking system, including:

Photovoltaic array module, for being converted into electric energy by solar energy by photovoltaic array；

MPPT golden section point computing unit, utilizes golden section point method to carry out the output of photovoltaic array module Maximum power point tracking, obtains the value and power reference close to maximum power point；

Model Predictive Control unit, re-uses model to the output of this MPPT golden section point computing unit pre- Survey control method, trace into maximum power point accurately, make system operate at maximum power point, and with Huang The value and power reference that gold cut-point method draws compares and draws cost function g, to control Boost circuit On off state；

Boost circuit, is connected between this photovoltaic array module and load, receives this Model Predictive Control The control of unit.

2. a kind of maximum power point tracking system as claimed in claim 1, it is characterised in that: this MPPT Golden section point computing unit, by the P-U characteristic curve of photovoltaic cell, uses golden mean optimization to High-power point is tracked.

3. a kind of maximum power point tracking system as claimed in claim 2, it is characterised in that: this MPPT Golden section point computing unit is achieved by the steps of:

(1) initial range [a is set₀, b₀】；

(2) calculate golden section point x1, x2, and calculate corresponding power P_X1, P_X2；

(3) P is compared_X1And P_X2If, P_X1=P_X2, then next scope is [x1, x2]；If P_X1＜ P_X2, prune 【a₀, x1], then next scope is [x1, b₀】；If P_X1＞ P_X2, prune [x2, b₀], then next scope is 【a₀, x2], wherein, a₀、b₀, x1, x2 be the U of P-U curve of photovoltaic cell；

(4) step (2) and (3) it are iteratively repeated, when the difference of 2 power is less than certain setting value specific During ε, close to maximum power point.

4. a kind of maximum power point tracking system as claimed in claim 3, it is characterised in that: this model is pre- Survey control unit forecast model based on Boost circuit, utilize two-step method to be predicted.

5. a kind of maximum power point tracking system as claimed in claim 4, it is characterised in that this model is pre- Survey control unit uses and minimizes cost function acquisition cost function g as follows:

g_S=0,1=| P_{PV, S=0,1}(k+2)-P_ref|

Wherein, P_{PV, S=0,1}(k+2) being the photovoltaic output in K+2 moment, S=0 is switching tube off-state, S=1 For switching tube closure state, P_refThe value and power reference calculated for this MPPT golden section point computing unit.

6. a maximum power point tracking method, comprises the steps:

Step one, utilizes photovoltaic array module to convert solar energy into electrical energy.

Step 2, utilizes golden mean optimization that the output of photovoltaic array module is carried out maximum power point tracking, Obtain the value and power reference close to maximum power point.

Step 3, re-uses model prediction control to the output utilizing golden section point to carry out maximum power point tracking Method processed, traces into maximum power point accurately, makes system operate at maximum power point, and divides with gold The value and power reference that cutpoint method draws compares and draws cost function g, to control opening of Boost circuit Off status.

7. a kind of maximum power point tracking method as claimed in claim 6, it is characterised in that step 2 is entered One step includes:

(1) initial range [a is set₀, b₀】；

(2) calculate golden section point x1, x2, and calculate corresponding power P_X1, P_X2；

(3) P is compared_X1And P_X2If, P_X1=P_X2, then next scope is [x1, x2]；If P_X1＜ P_X2, prune 【a₀, x1], then next scope is [x1, b₀】；If P_X1＞ P_X2, prune [x2, b₀], then next scope is 【a₀, x2], wherein a₀、b₀, x1, x2 be the U of P-U curve of photovoltaic cell；

(4) step (2) and (3) it are iteratively repeated, when the difference of 2 power is less than certain setting value specific During ε, close to maximum power point.

8. a kind of maximum power point tracking method as claimed in claim 7, it is characterised in that: in step 3 In, forecast model based on Boost circuit, utilize two-step method to be predicted to follow the tracks of peak power The value of point is more accurate.

9. a kind of maximum power point tracking method as claimed in claim 8, it is characterised in that in step 3 In, use and minimize cost function acquisition cost function g as follows:

g_S=0,1=| P_{PV, S=0,1}(k+2)-P_ref|

Wherein, P_{PV, S=0,1}(k+2) being the photovoltaic output in K+2 moment, S=0 is switching tube off-state, S=1 is switching tube closure state, P_refThe value and power reference calculated for this MPPT golden section point computing unit.

10. a kind of maximum power point tracking method as claimed in claim 9, it is characterised in that: the method Realized by the dutycycle changing pwm control signal.