CN109189146A - A kind of photovoltaic system maximum power tracing method obscuring synovial membrane control based on finite time - Google Patents

A kind of photovoltaic system maximum power tracing method obscuring synovial membrane control based on finite time Download PDF

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CN109189146A
CN109189146A CN201811238864.1A CN201811238864A CN109189146A CN 109189146 A CN109189146 A CN 109189146A CN 201811238864 A CN201811238864 A CN 201811238864A CN 109189146 A CN109189146 A CN 109189146A
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maximum power
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CN109189146B (en
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钟智雄
林文忠
张祖昌
邵振华
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Minjiang University
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    • 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • 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 present invention relates to a kind of photovoltaic system maximum power tracing methods that synovial membrane control is obscured based on finite time, first redefine the maximum power tracing problem of photovoltaic system under the model framework of singular nonlinear systems.Then, it using the method for T-S obscurity model building, chooses after 6 fuzzy sets obscure singular nonlinear systems, obtains unusual T-S fuzzy system.And then it designs finite time and obscures synovial membrane controller, and find out the time that photovoltaic system reaches synovial membrane face.On the basis of time interval based on the solution, further solve when photovoltaic control system reaches synovial membrane face, system realizes the bouds on error of maximum power tracing.The present invention may be implemented that there is the photovoltaic system under external disturbance maximum powerinjected method is realized in finite time, improves photovoltaic efficiency, has a vast market application prospect.

Description

Photovoltaic system maximum power tracking method based on finite time fuzzy sliding film control
Technical Field
The invention relates to the field of large and new energy power generation systems, in particular to a photovoltaic system maximum power tracking method based on finite time fuzzy sliding film control.
Background
With the aggravation of environmental pollution, people begin to increase the construction of new energy power generation systems. The most clean energy typically represents a solar photovoltaic power generation system with high investment cost, so it is very important to ensure the maximum power generation power. The traditional tracking control of the maximum power of solar photovoltaic power generation cannot ensure a quick tracking effect, and most of the proposed control theories lack strict quantitative analysis.
Disclosure of Invention
In view of the above, the present invention provides a method for tracking maximum power of a photovoltaic system based on finite time fuzzy sliding film control, which can effectively solve the above problems.
The invention is realized by adopting the following scheme: a photovoltaic system maximum power tracking method based on finite time fuzzy sliding film control comprises the following steps:
step S1: building a solar photovoltaic power generation experimental system; the solar photovoltaic power generation experimental system comprises a photovoltaic power generation board, a maximum power reference voltage calculation device, a finite time maximum power tracking fuzzy sliding film controller, a DC/DC converter and a load;
step S2: establishing a mathematical model of the solar photovoltaic power generation system with the maximum power tracking problem according to the physical principle, and expressing the mathematical model as a singular system model;
step S3: designing a finite time fuzzy synovial membrane controller based on the mathematical model;
step S4: calculating the time T of the closed-loop control system reaching the slide film surface*；
Step S5: calculating the time T of the closed-loop control system*Maximum power reference voltage error value at a time.
Further, in step S2, a mathematical model of the solar photovoltaic power generation system with the maximum power tracking problem is established as shown in formula (1):
in the formula, L and C0The inductance and the capacitance inside the converter; u represents the duty cycle value u e [0,1]，And vpvRespectively the output current and the output voltage of the solar photovoltaic;is the load current;is the reference voltage error for maximum power tracking; n ispAnd nsThe number of the parallel power generation units and the number of the cascade power generation units are respectively;wherein the electronic energy storage q is 1.6 multiplied by 10-19C，The value of structural characteristic parameter is in u epsilon [1,5 ]]Boltzmann constant K1.3805 × 10-23J/OK, T is the solar photovoltaic temperature; i isrsIs the reverse saturation current;representing the reference voltage for maximum power tracking.
Further, in step S2, the expression as a singular system model specifically includes the following steps:
step S21: definition of Z5＝vdc，Wherein v isdcRepresenting the output load voltage, vpvRepresenting the output voltage of the solar photovoltaic, and z is selected1-z6After the fuzzy antecedent variable, the output voltage v is taken into accountdcThere is an external disturbance ω (t) and this is assumed to be bounded, which is satisfiedδ represents the upper bound of the perturbation;
step S22: the solar photovoltaic power generation nonlinear system with the maximum power tracking problem is approximately expressed by the following singular T-S fuzzy model:
in the formula,z(t)＝[Z1,Z2,…,Z6]，Aland BlMathematical model of solar photovoltaic power generation system for maximum power tracking problem in Z1-Z6Carry out linearizationThe matrix of the system obtained is then used, g denotes the number of fuzzy sets and r denotes the number of fuzzy rules.
Further, in step S3, the finite time blur synovial controller has the form:
u(t)＝ub(t)+uc(t)(4)
in the formula,Klis the gain of the fuzzy controller and is,{ l, p } represents the fuzzy set, with T being a predetermined finite time period, αmin() represents the minimum rank of the matrix, | | | represents the norm of the matrix, |, sgn (|) is a sign function of the switching, specifically defined as follows:
wherein s (t) is an integral slide film area function defined as follows:
where G is a given matrix such that GBlIs a positive definite matrix.
Further, step S4 is to first define the following function:
after the derivation of the above function, the following results are obtained:
based on the above formula, the following finite time T is obtained*：
In the formula, mupRepresenting fuzzy membership functions of the controller, BpRepresenting a control input matrix.
Further, step S5 specifically includes the following steps:
step S51: and (3) substituting an expression of the finite time fuzzy synovial membrane controller into a singular T-S fuzzy model of the solar photovoltaic power generation nonlinear system with the maximum power tracking problem to obtain:
in the formula, KpRepresenting the fuzzy controller gain.
Step S52: the following function is established:
in the formula,P1∈R2×2is a symmetric positive definite matrix, matrix P2∈R1×2，P3Is a scalar quantity, the above definition can guaranteeETP＝PTE≥0。
Step S53: the following auxiliary functions are established:
wherein X (t) is [ < x > ]T(t)ωT(t)ρ(t)sgn(s(t))]T；
Sym(*)＝(*)T+ (.) (. is a matrix;represents a transpose of the diagonal matrix, τ represents a scalar greater than zero;
step S54: let Wll<0,1≤l≤r；Wlp+Wpl<0，1≤l<p ≦ r, then J (t)<0, that is:
wherein, WllAnd WplIs an augmented matrix defined below equation (12).
Left and right multiplication of the above inequality e-τtAnd from 0 to T ∈ [0, T ]*]Integration is performed to obtain:
in the formula,
step S55: obtained from formula (11):
from (14) and (15):
step S56: the slicing state variable x (t) is:
wherein
Step S57: obtained according to equations (11), (16) and (17):
further defined as follows:
in the formula, R1Representing a given symmetric positive definite matrix, c1Represents the zero initial limit of the system;
obtaining according to (18) and (19):
step S58: calculating state variablesThe bounded limits of (c) are as follows:
based on equation (10) we obtain:
wherein,
therefore, the maximum power tracking reference voltage error is epsilonpvEquation (20) can be calculated:
based on formula (20), formula (21) and formula (22):
compared with the prior art, the invention has the following beneficial effects: the photovoltaic system maximum power tracking method based on the finite time fuzzy sliding film control provided by the invention can ensure that the photovoltaic system can track the reference voltage quickly, realize maximum power generation and give a quantitative analysis result of the reference voltage error of the maximum power generation.
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FIG. 1 is a schematic flow chart of a method according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a solar photovoltaic power generation experimental system according to an embodiment of the present invention.
Detailed Description
The invention is further explained below with reference to the drawings and the embodiments.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments according to the present application. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
As shown in fig. 1 and fig. 2, the present embodiment provides a method for tracking the maximum power of a photovoltaic system based on finite-time fuzzy sliding film control, which includes the following steps:
step S1: building a solar photovoltaic power generation experimental system 100; the solar photovoltaic power generation experimental system 100 comprises a photovoltaic power generation panel 10, a maximum power reference voltage calculation device 11, a finite time maximum power tracking fuzzy sliding film controller 12, a DC/DC converter 13 and a load 14;
step S2: establishing a mathematical model of the solar photovoltaic power generation system with the maximum power tracking problem according to the physical principle, and expressing the mathematical model as a singular system model;
step S3: designing a finite time fuzzy synovial membrane controller based on the mathematical model;
step S4: calculating the time T of the closed-loop control system reaching the slide film surface*；
Step S5: calculating the time T of the closed-loop control system*Maximum power reference voltage error value at a time.
In the present embodiment, in step S2, a mathematical model of the solar photovoltaic power generation system with the problem of maximum power tracking is established as shown in formula (1):
in the formula, L and C0The inductance and the capacitance inside the converter; u represents the duty cycle value u e [0,1]，And vpvRespectively the output current and the output voltage of the solar photovoltaic;is the load current;is the reference voltage error for maximum power tracking; n ispAnd nsThe number of the parallel power generation units and the number of the cascade power generation units are respectively;wherein the electronic energy storage q is 1.6 multiplied by 10-19C，The value of structural characteristic parameter is in u epsilon [1,5 ]]Boltzmann constant K1.3805 × 10-23J/OK, T is the solar photovoltaic temperature; i isrsIs the reverse saturation current;representing the reference voltage for maximum power tracking.
In this embodiment, in step S2, the expression as the singular system model specifically includes the following steps:
step S21: definition of Z5＝vdc，Wherein v isdcRepresenting the output load voltage, vpvRepresenting the output voltage of the solar photovoltaic, and z is selected1-z6After the fuzzy antecedent variable, the output voltage v is taken into accountdcThere is an external disturbance ω (t) and this is assumed to be bounded, which is satisfiedδ represents the upper bound of the perturbation;
step S22: the solar photovoltaic power generation nonlinear system with the maximum power tracking problem is approximately expressed by the following singular T-S fuzzy model:
in the formula,z(t)＝[z1,z2,…,z6]，Aland BlMathematical model of solar photovoltaic power generation system for maximum power tracking problem in z1-z6Carry out linearizationThe matrix of the system obtained is then used, g denotes the number of fuzzy sets and r denotes the number of fuzzy rules.
In this embodiment, in step S3, the finite time blur synovial controller has the form:
u(t)＝ub(t)+uc(t)(4)
in the formula,Klis the gain of the fuzzy controller and is,{ l, p } represents the fuzzy set, with T being a predetermined finite time period, αmin() represents the minimum rank of the matrix, | | | represents the norm of the matrix, |, sgn (|) is a sign function of the switching, specifically defined as follows:
wherein s (t) is an integral slide film area function defined as follows:
where G is a given matrix such that GBlIs a positive definite matrix.
In this embodiment, step S4 is to first define the following function:
after the derivation of the above function, the following results are obtained:
based on the above formula, the following finite time T is obtained*：
In the formula, mupRepresenting fuzzy membership functions of the controller, BpRepresenting a control input matrix.
In this embodiment, step S5 specifically includes the following steps:
step S51: and (3) substituting an expression of the finite time fuzzy synovial membrane controller into a singular T-S fuzzy model of the solar photovoltaic power generation nonlinear system with the maximum power tracking problem to obtain:
in the formula, KpRepresenting the fuzzy controller gain.
Step S52: the following function is established:
in the formula,P1∈R2×2is a symmetric positive definite matrix, matrix P2∈R1×2，P3Is a scalar quantity, the above definition can ensure ETP＝PTE≥0。
Step S53: the following auxiliary functions are established:
wherein X (t) is [ < x > ]T(t)ωT(t)ρ(t)sgn(s(t))]T；
Sym(*)＝(*)T+ (.) (. is a matrix;represents a transpose of the diagonal matrix, τ represents a scalar greater than zero;
step S54: let Wll<0,1≤l≤r；Wlp+Wpl<0,1≤l<p ≦ r, then J (t)<0, that is:
wherein, WllAnd WplIs an augmented matrix, defined below equation (12),
to in pair withThe inequality above is left and right times e-τtAnd from 0 to T ∈ [0, T ]*]Integration is performed to obtain:
in the formula,
step S55: obtained from formula (11):
from (14) and (15):
step S56: the slicing state variable x (t) is:
wherein
Step S57: obtained according to equations (11), (16) and (17):
further defined as follows:
in the formula, R1Representing a given symmetric positive definite matrix, c1Represents the zero initial limit of the system;
obtaining according to (18) and (19):
step S58: calculating state variablesThe bounded limits of (c) are as follows:
based on equation (10) we obtain:
wherein,
therefore, the maximum power tracking reference voltage error is epsilonpvEquation (20) can be calculated:
based on formula (20), formula (21) and formula (22):
the embodiment can ensure that the photovoltaic system can track the reference voltage quickly to realize maximum power generation, and can give a quantitative analysis result of the reference voltage error of the maximum power generation.
The above description is only a preferred embodiment of the present invention, and all equivalent changes and modifications made in accordance with the claims of the present invention should be covered by the present invention.

Claims (6)

1. A photovoltaic system maximum power tracking method based on finite time fuzzy sliding film control is characterized in that: the method comprises the following steps:
step S1: building a solar photovoltaic power generation experimental system; the solar photovoltaic power generation experimental system comprises a photovoltaic power generation board, a maximum power reference voltage calculation device, a finite time maximum power tracking fuzzy sliding film controller, a DC/DC converter and a load;
step S2: establishing a mathematical model of the solar photovoltaic power generation system with the maximum power tracking problem according to the physical principle, and expressing the mathematical model as a singular system model;
step S3: designing a finite time fuzzy synovial membrane controller based on the mathematical model;
step S4: calculating the time T of the closed-loop control system to reach the slide film surface;
step S5: calculating the time T of the closed-loop control system*Maximum power reference voltage error value at a time.
2. The method of claim 1, wherein the photovoltaic system maximum power tracking method based on finite time fuzzy slip film control comprises: in step S2, a mathematical model of the solar photovoltaic power generation system with the problem of maximum power tracking is established as shown in formula (1):
in the formula, L and C0The inductance and the capacitance inside the converter; u represents the duty cycle value u e [0,1]，And vpvRespectively the output current and the output voltage of the solar photovoltaic;is the load current;is the reference voltage error for maximum power tracking; n ispAnd nsThe number of the parallel power generation units and the number of the cascade power generation units are respectively;wherein the electronic energy storage q is 1.6 multiplied by 10-19C，Is structural in natureThe value of the characteristic parameter is in u e [1,5 ]]Boltzmann constant K1.3805 × 10-23J/OK, T is the solar photovoltaic temperature; i isrsIs the reverse saturation current;representing the reference voltage for maximum power tracking.
3. The method of claim 1, wherein the photovoltaic system maximum power tracking method based on finite time fuzzy slip film control comprises: in step S2, the expression as a singular system model specifically includes the following steps:
step S21: definition of z5＝vdc，Wherein v isdcRepresenting the output load voltage, vpvRepresenting the output voltage of the solar photovoltaic, and z is selected1-z6After the fuzzy antecedent variable, the output voltage v is taken into accountdcThere is an external disturbance ω (t) and this is assumed to be bounded, which is satisfiedδ represents the upper bound of the perturbation;
step S22: the solar photovoltaic power generation nonlinear system with the maximum power tracking problem is approximately expressed by the following singular T-S fuzzy model:
in the formula,z(t)＝[z1,z2,…,z6]，Aland BlMathematical model of solar photovoltaic power generation system for maximum power tracking problem in z1-z6Carry out linearizationThe matrix of the system obtained is then used, g denotes the number of fuzzy sets and r denotes the number of fuzzy rules.
4. The method of claim 1, wherein the photovoltaic system maximum power tracking method based on finite time fuzzy slip film control comprises: in step S3, the finite time fuzzy synovial controller has the form:
u(t)＝ub(t)+uc(t) (4)
in the formula,Klis the gain of the fuzzy controller and is,{ l, p } represents the fuzzy set, with T being a predetermined finite time period, αmin() represents the minimum rank of the matrix, | | | represents the norm of the matrix, |, sgn (|) is a sign function of the switching, specifically defined as follows:
wherein s (t) is an integral slide film area function defined as follows:
where G is a given matrix such that GBlIs a positive definite matrix.
5. The method of claim 1, wherein the photovoltaic system maximum power tracking method based on finite time fuzzy slip film control comprises: step S4 is specifically defined as follows:
after the derivation of the above function, the following results are obtained:
based on the above formula, the following finite time T is obtained*：
In the formula, mupRepresenting fuzzy membership functions of the controller, BpRepresenting a control input matrix.
6. The method for tracking the maximum power of the photovoltaic system based on the finite-time fuzzy slip film control according to claim 1, wherein: step S5 specifically includes the following steps:
step S51: and (3) substituting an expression of the finite time fuzzy synovial membrane controller into a singular T-S fuzzy model of the solar photovoltaic power generation nonlinear system with the maximum power tracking problem to obtain:
in the formula, KpRepresenting the fuzzy controller gain;
step S52: the following function is established:
in the formula,P1∈R2×2is a symmetric positive definite matrix, matrix P2∈R1×2，P3Is a scalar quantity, the above definition can ensure ETP＝PTE≥0。
Step S53: the following auxiliary functions are established:
wherein X (t) is [ < x > ]T(t)ωT(t)ρ(t)sgn(s(t))]T；
Sym(*)＝(*)T+ (.) (. is a matrix;represents a transpose of the diagonal matrix, τ represents a scalar greater than zero;
step S54: let Wll<0,1≤l≤r；Wlp+Wpl<0，1≤l<p ≦ r, then J (t)<0, that is:
wherein, WllAnd WplIs an augmented matrix of the number of pixels,
left and right multiplication of the above inequality e-τtAnd from 0 to T ∈ [0, T ]*]Integration is performed to obtain:
in the formula,
step S55: obtained from formula (11):
from (14) and (15):
step S56: the slicing state variable x (t) is:
wherein
Step S57: obtained according to equations (11), (16) and (17):
further defined as follows:
in the formula, R1Representing a given symmetric positive definite matrix, c1Represents the zero initial limit of the system; obtaining according to (18) and (19):
step S58: calculating state variablesThe bounded limits of (c) are as follows:
based on equation (10) we obtain:
wherein,
therefore, the maximum power tracking reference voltage error is epsilonpvEquation (20) can be calculated:
based on formula (20), formula (21) and formula (22):
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Publication number Priority date Publication date Assignee Title
CN109917845A (en) * 2019-03-27 2019-06-21 闽江学院 Photovoltaic system maximum power tracing robust control method based on solar irradiance estimation
CN110032238A (en) * 2019-04-28 2019-07-19 闽江学院 A kind of wind turbine power generation yaw control system maximum power tracing method
CN111522242A (en) * 2020-05-18 2020-08-11 闽江学院 Gravity type active net cage lifting sliding film control method based on reachable set estimation
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CN113359938B (en) * 2021-06-23 2022-08-12 安徽工业大学 Photovoltaic system maximum power point tracking method based on nonsingular rapid terminal sliding mode control

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