CN106356893A - Bi-fuzzy control method for maximum power point tracking in photovoltaic grid-connected system - Google Patents

Bi-fuzzy control method for maximum power point tracking in photovoltaic grid-connected system Download PDF

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CN106356893A
CN106356893A CN201610902994.5A CN201610902994A CN106356893A CN 106356893 A CN106356893 A CN 106356893A CN 201610902994 A CN201610902994 A CN 201610902994A CN 106356893 A CN106356893 A CN 106356893A
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fuzzy
mppt
pid
fuzzy control
photovoltaic
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顾佳易
王蒙
马寿虎
陆文涛
陆文伟
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Nanjing Institute of Technology
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    • H02J3/385—
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05F—SYSTEMS FOR REGULATING ELECTRIC OR MAGNETIC VARIABLES
    • G05F1/00—Automatic systems in which deviations of an electric quantity from one or more predetermined values are detected at the output of the system and fed back to a device within the system to restore the detected quantity to its predetermined value or values, i.e. retroactive systems
    • G05F1/66—Regulating electric power
    • G05F1/67—Regulating electric power to the maximum power available from a generator, e.g. from solar cell
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    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers

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Abstract

The invention discloses a bi-fuzzy control method for maximum power point tracking in a photovoltaic grid-connected system. In order to solve the problems that the traditional MPPT (maximum power point tracking) is low in control accuracy, poor in adaptability and large in energy consumption and may cause the system to stabilize in a local MPP (maximum power point), a method combining asymmetric fuzzy MPPT and fuzzy PID (proportion integration differentiation) is proposed. In the step of setting a reference voltage, fuzzy control is used to replace traditional methods such as a perturbation and observation method and the like, and in the step of eliminating difference between an actual voltage and the reference voltage, fuzzy PID is used to replace common PID control. Then, four indexes reflecting MPPT properties are proposed, namely, MPPT time when the environment changes slowly, the size of energy emitted by a photovoltaic array, the size of power fluctuation in a steady state and the size of energy emitted by the photovoltaic array when the environment changes severely. Finally, 4 computational examples are designed, 5 control methods are respectively controlled under a MATLAB/Simulink environment to perform simulated analysis, and through comparison, the proposed bi-fuzzy control method is verified to be an MPPT control method superior to the traditional method.

Description

A kind of MPPT maximum power point tracking bi-fuzzy control method in photovoltaic parallel in system
Technical field
The present invention relates to a kind of maximum power point tracking technology, carry out with bi-fuzzy control method particularly to one kind The method that high-power point is followed the tracks of.
Background technology
Photovoltaic array is an indispensable ingredient in photovoltaic generating system, and its peak power output is become with temperature Negative coefficient relation, and positive coefficient relation is become with intensity of illumination.This just proposes photovoltaic array peak power in theory and practice Point follows the tracks of the problem of mppt (maximum power point tracking).
The mppt problem that Chinese scholars are directed in photovoltaic generation at present proposes all multi-methods, such as constant voltage (cvt) Optimizing integration of (p＆o) method, admittance increment (inc) method and this several method is observed in method, disturbance.The advantage that cvt method controls It is to control simple, easily realization, but the tracking accuracy of system maximum power point (mpp) depends on the reasonability that voltage initial value selects, Control accuracy and bad adaptability.After p＆o method controls output to reach mpp, its disturbance does not stop, but shakes near mpp Swing, cause energy loss.When environment changes, inc method can quickly follow the tracks of its change, but may result in system stability Mpp a local；Additionally, such as p＆o method, the reference voltage change step δ uref of inc method be also fixing it is impossible to and Turn round and look at and follow the trail of speed and stable state accuracy.
For the mppt problem in grid-connected photovoltaic system, this paper presents a kind of asymmetric fuzzy mppt and fuzzy The bi-fuzzy control method that pid combines, by the modeling and simulating under matlab/simulink environment, contrasts existing Mppt method, demonstrates the method and has the advantages that tracking speed is fast and steady state power fluctuation is little.
Content of the invention
Purpose: traditional method p＆o method etc. cannot take into account tracking speed and stable state accuracy, always between makes Accept or reject.In order to overcome this shortcoming, this paper presents the bi-fuzzy control that a kind of asymmetric fuzzy mppt and fuzzy pid combines Method.
Technical scheme: for solving above-mentioned technical problem, the technical solution used in the present invention is: one kind is in photovoltaic parallel in system Middle MPPT maximum power point tracking bi-fuzzy control method, comprises the steps:
Step one: the symmetrical mppt of non-fuzzy controls；
Step 2: fuzzy pid controls；
Step 3: bi-fuzzy control；
The symmetrical mppt of described non-fuzzy controls and includes:
(1) reference voltage link uses fuzzy control to replace the traditional methods such as original p＆o method, it is possible to achieve variable step δ uref exports；Particularly as follows:
According to the p-u curve (power vs. voltage curve) of photovoltaic array, this characteristic curve is asymmetric with regard to mpp.Accordingly Herein operating point is that p-u curve suitably increases (scope: 0.1v to 0.5v) compared with the step-length δ uref of plateau in mpp left end Preferably to improve tracking speed, by operating point the step-length δ uref that mpp right-hand member is the steeper part of p-u curve suitably reduce with Increase stable state accuracy.
(2) non-fuzzy symmetrical mppt fuzzy controller is set；Being provided that of controller
Its input variable is δ p (k) and δ u (k) of k-th sampled point (sampled point on photovoltaic power-voltage curve) Represent the variable quantity of power and voltage on photovoltaic power-voltage curve respectively, and output variable is then the δ of k-th sampled point Uref (k) (variable quantity of reference voltage), wherein δ p (k), δ u (k) are tried to achieve by formula (1), (2).
δ p (k)=p (k)-p (k-1) (1)
δ u (k)=u (k)-u (k-1) (2)
Wherein, p (k), u (k) are respectively the power of k-th sampled point and voltage on p-u curve.
(3) member function of fuzzy controller in matlab fuzzy control case is set；
The member function of δ p (k) has 5 fuzzy subsets, respectively pb (positive big), ps (positive Small), ze (zero), ns (negative small), nb (negative big)；The member function of variable δ u (k) has 3 Fuzzy subset, is p, z, n respectively.
(4) corresponding relation formula between photovoltaic array output and output voltage is obtained according to photovoltaic array p-u curve, according to This sets dependent blur and controls rule.
The corresponding relation between photovoltaic array output and output voltage can be obtained according to photovoltaic array p-u curve Formula:
dp/du<0 u<umpp
Dp/du=0 u=umpp
dp/du<0 u>umpp
Wherein, umppFor corresponding terminal voltage at photovoltaic array mpp.
Described fuzzy pid controlling unit is used to eliminate the reference of actual photovoltaic array output voltage and a upper link output Magnitude of voltage deviation.Including:
(1) set conventional pid parameter
Although conventional pid controller is simple, one group of changeless pid parameter cannot adapt to environmental change, difficult To obtain satisfied control effect.Conventional pid is made up of ratio, integration, differential three part, and each of which part has difference again Effect.In fuzzy pid controls, some rule following is generally had to be worthy of consideration.
A. when absolute value of the bias e is larger, in order that system has preferable tracking performance, scale factorShould be very Greatly, differential divisorShould be smaller；It is to avoid integrating saturation and be likely to occur larger overshoot, reply integration is made simultaneously With being any limitation as.
B. when the absolute value ec size of absolute value of the bias e and deviation differential is medium, in order to enable a system to quick response,Value will be suitably smaller.
C. when absolute value of the bias e is less, in order that system has preferable steady-state behaviour,WithAll should obtain big A bit.
(2) accordingly, it is possible to use fuzzy control carries out different regulations in the different stages to 3 parameters of pid, just may be used Faster, further smoothly track the mpp of photovoltaic array.This fuzzy control with the differential of the deviation of power and this deviation for input, Its output is the adjustment amount δ k of 3 parameters of pidp、δki、δkd, then control parameter basic with controller be added obtain new Parameter kp、ki、kd, as follows:
k p = k p 0 + &delta;k p - - - ( 3 )
k i = k i 0 + &delta;k i - - - ( 4 )
k d = k d 0 + &delta;k d - - - ( 5 )
Based on this, replace traditional pid with this link of reference voltage deviation with fuzzy pid eliminating virtual voltage, Can make that output-power fluctuation is less, response time is shorter.
(3) set fuzzy control rule.The input quantity of fuzzy pid controller has 2, is e (k) respectively) and ec (k), can :
e ( k ) = d p d u ( k ) = p ( k ) - p ( k - 1 ) u ( k ) - u ( k - 1 ) - - - ( 6 )
e c ( k ) = &delta; &lsqb; d p d u ( k ) &rsqb; = e ( k ) - e ( k - 1 ) - - - ( 7 )
This controller has 3 output variables, is δ k respectivelyp、δki、δkd.Input and output totally 5 variables, its member Function has 5 fuzzy subsets of identical, respectively pb, ps, ze, ns, nb.
Described bi-fuzzy control method, in setting reference voltage and elimination voltage deviation link all using fuzzy controller, this It is bi-fuzzy control method (i.e. asymmetric fuzzy mppt- obscures pid).
Specifically using cooperatively of 2 fuzzy control links is as follows:
(1) situation of change according to photovoltaic array real output, voltage utilizes non-fuzzy symmetrical mppt controlling unit Set reference voltage.
(2) deviation of photovoltaic array actual output voltage and this reference voltage is input to fuzzy pid controlling unit, it is defeated Go out signal compare generation to control pulse to adjust dc-dc changer with triangular signal is boost DC transfer circuit (high-pressure side Adjust as steady state value) dutycycle d, the output voltage that constantly regulate photovoltaic array is come with this, make output voltage be equal to non-fuzzy The reference voltage that symmetrical mppt link sets, eliminates voltage deviation.
Beneficial effects of the present invention: combine the bi-fuzzy control method of asymmetric fuzzy mppt and fuzzy pid, by Modeling and simulating under matlab/simulink environment, contrasts existing mppt method, and it is fast and steady that the method has tracking speed The advantages of state power swing is little.
Brief description
Fig. 1 bi-fuzzy control method flow chart；
The member function of Fig. 2 11 output variable
The ultimate principle block diagram of Fig. 3 bi-fuzzy control method；
Fig. 4 is reference voltage variable quantity p＆o-pid control figure when step-length is for 0.16v；
Fig. 5 is reference voltage variable quantity step-length is p＆o-pid control figure during 0.06v；
Fig. 6 fuzzymppt-pid control figure；
Fig. 7 is reference voltage variable quantity step-length is p＆o-fuzzypid control figure during 0.16v；
Fig. 8 bi-fuzzy control figure；
Illumination curve chart in Fig. 9 present invention；
Temperature profile in Figure 10 present invention；
Figure 11 is photovoltaic p-u curve chart in the present invention.
Specific embodiment
Below in conjunction with the accompanying drawings the present invention is further described.
As Fig. 1-11, a kind of MPPT maximum power point tracking bi-fuzzy control method in photovoltaic parallel in system of the present invention, such as Fig. 1 Shown, comprise the steps:
Step one: the symmetrical mppt of non-fuzzy controls；
Step 2: fuzzy pid (proportional plus integral plus derivative controller) controls；
Step 3: bi-fuzzy control；
Specific implementation process is as follows:
According to the feature of grid-connected photovoltaic system, this paper presents the index of 4 reflection mppt performances: environment slowly becomes Mppt time during change；The energy size that photovoltaic array sends；Power swing size during stable state；Photovoltaic during environment acute variation The energy size that array sends.
Devise 4 examples herein, respectively simulation analysis are carried out to 5 kinds of mppt control methods.In the test of this example, light Photovoltaic array be by the series connection of 25 pieces of photovoltaic cells after, then obtained by such 2 connection in series-parallel.5 kinds of methods are respectively as follows: p＆o-pid control Method (p＆o step-length 0.16v), p＆o-pid control methods (p＆o step-length 0.06v), fuzzy mppt-pid control methods, p＆o-fuzzy Pid control methods (p＆o step-length 0.16v) and bi-fuzzy control method.
1st, the symmetrical mppt of non-fuzzy controls
(1) reference voltage link uses fuzzy control to replace the traditional methods such as original p＆o method, it is possible to achieve variable step δ uref exports.
(2) non-fuzzy symmetrical mppt fuzzy controller is set.
(3) member function of fuzzy controller in matlab fuzzy control case is set.
(4) corresponding relation formula between photovoltaic array output and output voltage is obtained according to photovoltaic array p-u curve, according to This sets dependent blur and controls rule.
According to the p-u curve of photovoltaic array, this characteristic curve is asymmetric with regard to mpp.Herein operating point is existed accordingly Mpp left end is that p-u curve suitably increases preferably to improve tracking speed compared with the step-length δ uref of plateau, and operating point is existed Mpp right-hand member is that the step-length δ uref of the steeper part of p-u curve suitably reduces to increase stable state accuracy.
Asymmetric fuzzy mppt fuzzy controller be provided that δ p (k) that its input variable is k-th sampled point and δ u (k), and output variable is then δ uref (k) of k-th sampled point, wherein δ p (k), δ u (k) are tried to achieve by formula (1), (2).
δ p (k)=p (k)-p (k-1) (1)
δ u (k)=u (k)-u (k-1) (2)
Being set to of fuzzy controller member function in matlab fuzzy control case: the member function of δ p (k) has 5 moulds Paste subset, respectively pb (positive big), ps (positive small), ze (zero), ns (negative small), nb(negative big)；The member function of variable δ u (k) has 3 fuzzy subsets, is p, z, n respectively.
The corresponding relation between photovoltaic array output and output voltage can be obtained according to photovoltaic array p-u curve Formula:
dp/du<0 u<umpp
Dp/du=0 u=umpp
dp/du<0 u>umpp
Wherein, umppFor corresponding terminal voltage at photovoltaic array mpp.
This property according to photovoltaic array, you can set dependent blur and control rule, be shown in Table 1.
Table 1 fuzzy control rule 1
tab.1 rules of fuzzy controller 1
2nd, obscure pid to control
Fuzzy pid controlling unit is used to eliminate the reference voltage of actual photovoltaic array output voltage and a upper link output Value deviation.
(1) set conventional pid parameter.
(2) using the differential of power deviation and deviation as fuzzy pid input, the adjustment amount δ k of 3 parametersp、δki、δ kd, as the output of fuzzy pid, then it is added with conventional pid and obtains new parameter.
(3) fuzzy control rule of correlation is gone out according to 3 pid parameter settings that step 2 draws.
Although conventional pid controller is simple, one group of changeless pid parameter cannot adapt to environmental change, difficult To obtain satisfied control effect.Conventional pid is made up of ratio, integration, differential three part, and each of which part has difference again Effect.In fuzzy pid controls, some rule following is generally had to be worthy of consideration.
A. when absolute value of the bias e is larger, in order that system has preferable tracking performance, scale factorShould be very Greatly, differential divisorShould be smaller；It is to avoid integrating saturation and be likely to occur larger overshoot, reply integration is made simultaneously With being any limitation as.
B. when the absolute value ec size of absolute value of the bias e and deviation differential is medium, in order to enable a system to quick response,Value will be suitably smaller.
C. when absolute value of the bias e is less, in order that system has preferable steady-state behaviour,WithAll should obtain big A bit.
Accordingly, it is possible to use fuzzy control carries out different regulations in the different stages to 3 parameters of pid, just can be more Hurry up, further smoothly track the mpp of photovoltaic array.This fuzzy control with the differential of the deviation of power and this deviation for input, its Output is the adjustment amount δ k of 3 parameters of pidp、δki、δkd, then control parameter basic with controller be added and obtain new ginseng Number, as follows:
k p = k p 0 + &delta;k p - - - ( 3 )
k i = k i 0 + &delta;k i - - - ( 4 )
k d = k d 0 + &delta;k d - - - ( 5 )
Based on this, replace traditional pid with this link of reference voltage deviation with fuzzy pid eliminating virtual voltage, Can make that output-power fluctuation is less, response time is shorter.
The input quantity of fuzzy pid controller has 2, is e (k) and ec (k) respectively, can obtain:
e ( k ) = d p d u ( k ) = p ( k ) - p ( k - 1 ) u ( k ) - u ( k - 1 ) - - - ( 6 )
e c ( k ) = &delta; &lsqb; d p d u ( k ) &rsqb; = e ( k ) - e ( k - 1 ) - - - ( 7 )
This controller has 3 output variables, is δ k respectivelyp、δki、δkd.Input and output totally 5 variables, its member Function has 5 fuzzy subsets of identical, respectively pb, ps, ze, ns, nb.
The not same-action being risen according to 3 parameters of the pid mentioning before, sets out the fuzzy control rule of correlation, is shown in Table 2.
Table 2 fuzzy control rule 2
tab.2 rules of fuzzy controller 2
Note: every group of 3 fuzzy control rules in table, are from left to right the fuzzy control rule of parameter kp, ki, kd respectively.
3rd, bi-fuzzy control
Described bi-fuzzy control method, in setting reference voltage and elimination voltage deviation link all using fuzzy controller, this It is bi-fuzzy control method: asymmetric fuzzy mppt- obscures pid.
Specifically using cooperatively of 2 fuzzy control links is as follows:
(1) situation of change according to photovoltaic array real output, voltage utilizes non-fuzzy symmetrical mppt controlling unit Set reference voltage.
(2) deviation of photovoltaic array actual output voltage and this reference voltage is input to fuzzy pid controlling unit, it is defeated Go out signal compare generation to control pulse to adjust dc-dc changer with triangular signal is boost DC transfer circuit (high-pressure side Adjust as steady state value) dutycycle d, the output voltage that constantly regulate photovoltaic array is come with this, make output voltage be equal to non-fuzzy The reference voltage that symmetrical mppt link sets, eliminates voltage deviation.
The initial condition of 4 examples is all identical: 22 DEG C of temperature, illumination 1000w/m2And photovoltaic array is defeated with peak power Go out.
Example 1
Temperature constant is constant, and intensity of illumination is in 1.4～1.5s time period 1000w/m2Linearly it is raised to 1200w/m2, extraneous ring Border controller after this change tracks the time used by mpp for t1.Between 3.0～3.1s, intensity of illumination is by 1200w/m2Linearly Drop to 1200w/m2, the time used by mpp that tracks after this environmental change is t2.In addition, other 2 performance indications are respectively as follows: During stable state, photovoltaic array sends the energy w that the fluctuation range δ p of power and photovoltaic array send during 1.0～4.4s.Example 1 The results are shown in Table 3
Table 3 example 1 interpretation of result
tab.3 comparison of mppt performance indexes for case 1
Example 2
Between 1.4～1.5s, temperature is linearly raised to 30 DEG C by 22 DEG C, and intensity of illumination is by 1000w/m2Linearly it is raised to 1200w/ m2；And temperature linearly drops to 25 DEG C by 30 DEG C between 3.0～3.1s, intensity of illumination is by 1200w/m2Linearly drop to 1100w/m2.Calculate The interpretation of result of example 2 is shown in Table 4.
Table 4 example 2 interpretation of result
tab.4 comparison of mppt performance indexes for case 2
Example 3 and 4
Example 3:1～2s ambient temperature is constant, only intensity of illumination acute variation；
Example 4:1～2s ambient temperature, the equal acute variation of intensity of illumination；
Example 3 and 4 results are as shown in Figure 5.
The interpretation of result of table 5 example 3 and 4
tab.5 comparison of power output between case 3and case 4
Each sample calculation analysis result:
To sum up 4 examples, can obtain as drawn a conclusion through relative analyses: after environmental change, bi-fuzzy control method is in track Very big advantage is had on the speed of mpp, it is obviously fast than other 4 kinds of methods that it follows the trail of speed；It is stable state work(in stable state accuracy In rate fluctuation range, bi-fuzzy control and fuzzy pid control are better than other 3 kinds of control methods；Numerical results are it is also shown that in ring Border is slowly varying and 2 kinds of acute variation in the case of, energy that bi-fuzzy control method sends is substantially most, and this illustrates this The bi-fuzzy control method that literary composition is proposed has higher mppt efficiency.
The above, the only specific embodiment of the present invention, but protection scope of the present invention is not limited thereto, and any The change or replacement expected without creative work, all should be included within the scope of the present invention.Therefore, the present invention Protection domain should be defined by the protection domain that claims are limited.

Claims (6)

1. one kind in photovoltaic parallel in system MPPT maximum power point tracking bi-fuzzy control method it is characterised in that include:
Step 1: the symmetrical mppt of non-fuzzy controls；
Step 2: fuzzy pid controls；
Step 3: bi-fuzzy control.
2. a kind of MPPT maximum power point tracking bi-fuzzy control method in photovoltaic parallel in system according to claim 1, its It is characterised by, in described step 1, non-fuzzy symmetrical mppt control is specific as follows:
11) reference voltage is set by fuzzy control；
12) non-fuzzy symmetrical mppt fuzzy controller is set；
13) member function of fuzzy controller in matlab fuzzy control case is set；
14) corresponding relation between photovoltaic array output and output voltage is obtained according to the p-u curve of photovoltaic array, set accordingly Determine fuzzy control rule.
3. a kind of MPPT maximum power point tracking bi-fuzzy control method in photovoltaic parallel in system according to claim 2, its It is characterised by: described 11) set the mpp left side that reference voltage is specially operating point on p-u curve by fuzzy control The step-length δ uref at end increases, and the step-length δ uref of mpp right-hand member on p-u curve for the operating point is reduced.
4. a kind of MPPT maximum power point tracking bi-fuzzy control method in photovoltaic parallel in system according to claim 2, its It is characterised by: described 12) setting non-fuzzy symmetrical mppt fuzzy controller is particularly as follows: input variable is the δ p of k-th sampled point (k) and δ u (k), and output variable is then δ uref (k) of k-th sampled point；
δ p (k)=p (k)-p (k-1) (1)
δ u (k)=u (k)-u (k-1) (2)
Wherein, δ p (k) represents the variable quantity of power on photovoltaic p-u curve, and δ u (k) represents the change of voltage on photovoltaic p-u curve Change amount.
5. a kind of MPPT maximum power point tracking bi-fuzzy control method in photovoltaic parallel in system according to claim 1, its Be characterised by, described step 2 obscure pid control particularly as follows:
21) set conventional pid parameter
22) using the differential of power deviation and deviation as fuzzy pid input, the adjustment amount of 3 parameters is δ kp、δki、δ kd, as the output of fuzzy pid, then it is added new parameter k after being adjusted with conventional pidp、ki、kd,
Wherein, δ kp、δki、δkdIt is respectivelyAdjustment amount；
23) according to step 22) 3 pid new parameters set fuzzy control rules.
6. a kind of MPPT maximum power point tracking bi-fuzzy control method in photovoltaic parallel in system according to claim 1, its Be characterised by, described step 3 bi-fuzzy control particularly as follows:
31) situation of change according to photovoltaic array real output, voltage utilizes non-fuzzy symmetrical mppt controlling unit to set Reference voltage；
32) deviation of photovoltaic array actual output voltage and this reference voltage is input to fuzzy pid controlling unit, is come not with this The disconnected output voltage adjusting photovoltaic array, makes output voltage be equal to the reference voltage of non-fuzzy symmetrical mppt link setting, eliminates Voltage deviation.
CN201610902994.5A 2016-10-17 2016-10-17 Bi-fuzzy control method for maximum power point tracking in photovoltaic grid-connected system Pending CN106356893A (en)

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Publication number Priority date Publication date Assignee Title
CN107664948A (en) * 2017-09-11 2018-02-06 南通大学 Photovoltaic cell MPPT asymmetric Varied scope fuzzy control method
CN114546023A (en) * 2022-02-25 2022-05-27 南京工程学院 Maximum power point tracking method of photovoltaic power generation system
CN114756082A (en) * 2022-04-14 2022-07-15 帝森克罗德集团有限公司 Maximum power tracking device of photovoltaic grid-connected inverter control system
CN117117992A (en) * 2023-10-25 2023-11-24 广州疆海科技有限公司 Output power adjusting method, device, computer equipment and storage medium
CN117117992B (en) * 2023-10-25 2024-04-12 广州疆海科技有限公司 Output power adjusting method, device, computer equipment and storage medium

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Application publication date: 20170125