CN108628385A - Based on the maximum photovoltaic power point tracking and controlling method for improving conductance increment method - Google Patents
Based on the maximum photovoltaic power point tracking and controlling method for improving conductance increment method Download PDFInfo
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- CN108628385A CN108628385A CN201810434954.1A CN201810434954A CN108628385A CN 108628385 A CN108628385 A CN 108628385A CN 201810434954 A CN201810434954 A CN 201810434954A CN 108628385 A CN108628385 A CN 108628385A
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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
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
- G05B13/0275—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using fuzzy logic only
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
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- 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
Abstract
The present invention relates to a kind of based on the maximum photovoltaic power point tracking and controlling method for improving conductance increment method, improvement variable step is used in be combined with asymmetric fuzzy control, the asymmetric fuzzy control near maximum power point is controlled less than the maximum power point period using variable step is improved.It is existing effectively to weaken oscillation of the system around maximum power point, it can be under the premise of ensureing system normal operation, improve stability, tracking accuracy and response time, simultaneously effective weaken oscillatory occurences of the system around maximum power point, ensure the safe and reliable operation of entire photovoltaic generating system, it is suitable for distributed new photovoltaic generating system, and extends in other new energy maximum power point control methods.
Description
Technical field
It is the present invention relates to a kind of photovoltaic generation control technology, more particularly to a kind of to be obscured with asymmetric based on improvement variable step
Improvement conductance increment method maximum photovoltaic power point tracking and controlling method.
Background technology
With the utilization of conventional fossil primary energy, it is while promoting social development, also accordingly in 21 generation
The first half of recording has welcome exhaustion, it means that future, traditional fossil energy can fade out the stage of human development.And solar energy is can
Occupy extremely important part in the new energy of sustainable development, at the same there is widely distributed, environmentally friendly, cleaning, can extensive profit
With the advantages that, therefore obtained large-scale application.
Numerous researchers study the MPPT (MPPT maximum power point tracking) of photovoltaic generating system in recent years
With innovation, many preferable control methods are proposed and emerged in large numbers, are totally said, it can be substantially according to its actual mechanism and algorithm characteristic
It is divided into the indirect control theory based on optimized mathematical model, the direct control method based on sampled data and based on advanced control theory
The three classes such as MPPT methods.1, the method for indirectly controlling based on optimized mathematical model includes mainly constant voltage process, open-circuit voltage
Y-factor method Y, short circuit current Y-factor method Y.Constant voltage process, it is temperature-resistant according to working as, when only extraneous intensity of illumination changes, photovoltaic electric
The characteristics of output power curve in pond is cluster single peak curve, and photovoltaic cell will always work near MPP, however it for
The requirement of temperature is more stringent, if ambient temperature changes, just will produce large error.Open-circuit voltage Y-factor method Y and short circuit
Current coefficient method, the two is similar, is all the Optimal improvements to constant voltage process, overcomes the problems, such as temperature change, still, the disadvantage is that
It carries out being periodically turned off photovoltaic cell with load to detect open-circuit voltage, power loss is larger, and what is obtained is not
MPP.2, the direct control method based on sampled data includes mainly conductance increment method, perturbation observation method etc., the spy of this kind of algorithm
Point is the terminal voltage and end current data for needing continuous sampling photovoltaic cell, goes to directly control goal systems by control algolithm
Operating point, such as duty ratio D, precision is higher, and robust property is preferable.The two similarity is to need constantly to export photovoltaic cell
Voltage is disturbed to track maximum power point, and difference is that conductance increment method is not applying disturbance once reaching MPP.3, base
It is based on advanced control theory, for photovoltaic generation in the characteristics of MPPT algorithm of advanced control theory, this kind of algorithm
The strong nonlinearity and timeinvariance feature that system has, the algorithm of proposition include mainly neural network, sliding moding structure, obscure
Logical algorithm etc..Neural network algorithm carries out MPPT, and control accuracy is higher, but needs to be trained solar panel to obtain control
System rule, when solar panel is variant, parameter is just different, and troublesome in poeration, the training time is long.And Sliding mode variable structure control amount is S,
As S >=0, U=0；As S ＜ 0, U=1.By continually changing switching characteristic, forces system is under certain condition in setting
State trajectory nearby do more by a small margin, upper frequency lower sliding formwork movement on the ground, to reach and be maintained on the sliding surface of design.Always
For body, research MPPT control strategies have new energy photovoltaic generating system important theoretical and practical significance.
Invention content
The present invention be directed to encounter maximum power point attachment oscillatory occurences in present MPPT control algolithms, it is proposed that
A kind of maximum photovoltaic power point tracking and controlling method based on improvement conductance increment method, can be before ensureing system normal operation
It puts, improves stability, tracking accuracy and response time, it is existing simultaneously effective to weaken oscillation of the system around maximum power point
As ensureing the safe and reliable operation of entire photovoltaic generating system.
The technical scheme is that：A kind of maximum photovoltaic power point tracing control side based on improvement conductance increment method
Method, the output power from photovoltaic cells formula P (u) carry out that a directive/guide is asked to obtain first derivative expression formula be：
Wherein u is output voltage, C1It is the filter capacitor emulated in Boost circuit；C2It is to emulate bearing in Boost circuit
Carry lateral capacitance；IscIt is the short circuit current of photovoltaic cell；UocOpen circuit voltage；
M is the control conversion switch value of setting,
When | P ' (u) | when the sections m ＞, MPPT maximum power point tracking is carried out to photovoltaic using the traditional controller for improving variable step
Control, variable step meet formula D (K)=D (K-1) ± β N (Δ P/ Δ U)
D (K) is the duty ratio in k-th period；N is the regulation coefficient of variable step, N=arctan [P (u)]；β is adjustable
Constant, Δ P, Δ U are respectively k-th Cyclical power and output voltage variable quantity；
When 0≤| P ' (u) | when the sections≤m, then MPPT maximum power point tracking is carried out to photovoltaic using asymmetric fuzzy controller
Control, asymmetric fuzzy logic controller input quantity are respectively：The variable quantity of the output power from photovoltaic cells P is with output voltage v's
The ratio and error rate Δ e of variable quantity, the kth moment expression formula of two input values are as follows：
Δ e (k)=e (k)-e (k-1) (2)
Wherein P (k), v (k) are current k cuns of output powers and voltage carved of photovoltaic cell respectively, in very short time, by e
(k) regard the slope of P-U characteristic curves certain point as；The output controlled quentity controlled variable of asymmetric fuzzy logic controller is voltage-regulation amount
dv。
The beneficial effects of the present invention are：The present invention is based on the maximum photovoltaic power point tracing controls for improving conductance increment method
Method can improve stability, tracking accuracy and response time, simultaneously effective under the premise of ensureing system normal operation
Oscillatory occurences of the weakening system around maximum power point ensures the safe and reliable operation of entire photovoltaic generating system, is suitable for
Distributed new photovoltaic generating system, and extend in other new energy maximum power point control methods.
Description of the drawings
Fig. 1 is solar cell equivalent circuit diagram of the present invention；
Fig. 2 is photovoltaic cell of the present invention P-U curve graphs at a constant temperature；
Fig. 3 is that photovoltaic cell of the present invention integrates output characteristics figure；
Fig. 4 be P-U curves of the present invention and | P ' (u) | performance diagram；
Fig. 5 is the change rate figure of variable step parameter of the present invention；
Fig. 6 is the asymmetric Fuzzy control strategies block diagram of the present invention；
Fig. 7 is the membership function figure of error e of the present invention；
Fig. 8 is the membership function figure of fuzzy controller output quantity of the present invention；
Fig. 9 is photovoltaic circuit simulation architecture block diagram of the present invention；
Figure 10 is the conductance increment method analogous diagram using traditional variable step；
Figure 11 is the present invention using improvement variable step and asymmetric fuzzy conductance increment method analogous diagram.
Specific implementation mode
Solar cell equivalent circuit diagram as shown in Figure 1.Have photovoltaic cell, improved MPPT controller, PWM, for examining
Photovoltaic electric current and the circuit of voltage, DC/DC circuits, load-side are surveyed, key component is improved variable step coefficient to optimization pair
The control of the duty ratio of controlled thyristor, also asymmetric fuzzy controller.
Photovoltaic cell portion.Photovoltaic cell (PV) can be changed solar energy using the physics photovoltaic effect of semi-conducting material
At electric energy, output characteristics is under the conditions of certain temperature, the characteristics of changing with the variation of intensity of illumination.Establish its mathematics etc.
Circuit block diagram is imitated, as shown in Figure 1.According to the theoretical photovoltaic cell mathematical model marked and obtained under condition, then in Matlab/
Simulink builds the emulation of photovoltaic cell, is carried out at the same time emulation, verifies photovoltaic cell under the conditions of different illumination intensity
T temperature is set in 25 DEG C by output characteristics, and the value that S intensities of illumination are then arranged is different, obtains its output characteristics P-U variation diagrams
Table.Easily the output power from photovoltaic cells P built in Matlab/Simulink is obtained, inside a certain range, with intensity of illumination
Increase and reinforce, meet the actual output characteristics of photovoltaic cell.Photovoltaic cell shown in Fig. 3 integrates output characteristics, then meets
Its subsequent simulation necessary requirement.
It as figure 1 shows solar cell equivalent circuit graph structure, in figure from left to right, be successively：IphFor short circuit current；
Equivalent current source in corresponding diagram；Diode；RshFor parallel resistance, general resistance value is larger；RsFor series resistance, general resistance value compared with
It is small；R is load resistance.
Fig. 2 shows photovoltaic cell P-U curves under constant temperature.Its mathematical equivalent model output current formula be：
Wherein,
In formula：IscIt is the short circuit current of photovoltaic cell；UocOpen circuit voltage；I is that photovoltaic electric pulls output current；U is defeated
Go out voltage (voltage in load)；ImCorresponding output current when photovoltaic battery plate Maximum Power Output point；UmMost for the output of photovoltaic battery plate
Corresponding output voltage at high-power；T, S is the temperature and intensity of illumination of photovoltaic battery panel respectively；TB、SBIt is under the status of criterion
Photovoltaic battery panel temperature and intensity of illumination, general mark be taken as 25 DEG C under condition, 1000W/m2；A, b is that photovoltaic battery plate electric current becomes
Temperature coefficient when temperature coefficient and voltage change when change；RsIt is series resistance.Under general situation, concatenated resistance RsVery
It is small, and resistance R in parallelshIt is very big, so R in theoretical calculationsWith RshPart is negligible not to be considered.Under general mark condition, photovoltaic electric
The horse-power formula of pond output：
Wherein u is output voltage (identical as U, here as variable small letter), C1It is the filtering emulated in Boost circuit
Capacitance；C2It is the load lateral capacitance emulated in Boost circuit.
According to the photovoltaic cell mathematical model obtained under theoretical mark condition above, then light is built in Matlab/Simulink
The emulation for lying prostrate battery is carried out at the same time emulation, verifies the output characteristics of photovoltaic cell under the conditions of different illumination intensity, photovoltaic electric
The major parameter I of pond partm、Um、Isc、UocIt is 4.2A, 32V, 4.6A, 41V respectively.T temperature is set in 25 DEG C, is then arranged
The value of S intensities of illumination is 600W/m respectively2、800W/m2、1000W/m2, its output characteristics P-U variation charts are obtained, such as Fig. 2 institutes
Show.Fig. 3 is photovoltaic cell output characteristic.
Improved variable step part.Because traditional step-length response speed has certain deficiency with tracking accuracy, adopt
The strategy of variable step is generally divided into two kinds：1, the step-length of different speeds is assigned according to related power first derivative values size；
2, the parameter the derivative of photovoltaic curve directly as disturbance step-length, to which step-length will do correlation certainly in maximum power point both sides
The adjustment of adaptability carries out positive direction disturbance for example, when being operated on the left of maximum power point, and at right side, then it carries out anti-
Direction disturbs, and step-length is smaller when closer apart from maximum power point.Output power formula P (u) is carried out a directive/guide is asked to obtain
P ' (u) correlation first derivative expression formula be：
Under standard testing, P-U curves and | P ' (u) are drawn | curve, as shown in Figure 4.P ' when on the left of maximum power point
(u) it is just that and it is negative to be operated in P ' (u) maximum power point on the right side of, meets the requirement of perturbation direction and both sides is about | u-Um|
Monotonous descending function, this just meets the condition as step change direct parameter, and variable step meets formula：D (K)=D (K-1) ±
βN(ΔP/ΔU) (5)
D (K) is the duty ratio in k-th of period；N is the regulation coefficient of variable step；β is adjustable constant, Δ P, Δ U difference
For k-th Cyclical power and output voltage variable quantity.
Optimize the basic thought of step parameter.Here the regulation coefficient of variable step takes N=arctan [P ' (u)], and β is according to defeated
Go out characteristic take as possible it is bigger.Fig. 5 is the first derivative of variable step coefficient, and according to higher mathematics antitrigonometric function, derivation can
It obtains.Better effects in order to obtain, there is employed herein the asymmetric fuzzy methods being combined with variable step, wherein variable step portion
Divide is when far from maximum power point both sides, for fast approaching maximum power point, near further towards maximum power point
Section when, for more one-step optimization performance, optimizing is carried out using asymmetric fuzzy control at this point, combining.
In the result figure 2 of emulation, the output power from photovoltaic cells P built in Matlab/Simulink is easily obtained, one
Determine inside range, reinforces with the increase of intensity of illumination, meet the actual output characteristics of photovoltaic cell.Photovoltaic shown in Fig. 3
Battery integrates output characteristics, then meets its subsequent simulation necessary requirement.As can be seen that photovoltaic cell P (u) and | P ' (u) in Fig. 4 |
Characteristic curve.Fig. 5 is the first derivative of variable step coefficient, and according to higher mathematics antitrigonometric function, derivation obtains
Asymmetric blurred portions.It is easily observed according to theory analysis above, appropriate duty ratio D and step-length is taken, to most
The optimization output characteristics effect of high-power point tracking, which will produce, to be directly affected, because conventional control mode is subordinate to conventional fuzzy control
Category degree function have symmetric characteristics, and the output characteristics on maximum power of photovoltaic cell point both sides and do not have symmetry feature,
If the traditional fuzzy of symmetry feature is taken to control, maximum power point both sides output characteristics effect will be biased, tool
Body is embodied in the maximum power point periphery small-scale oscillation defect of presentation and is proposed here so according to photovoltaic cell output characteristic
And asymmetric fuzzy control strategy is used, establish different membership functions and different control plans in maximum power point both sides
Slightly, to maximum power point into line trace.
Asymmetric Fuzzy control strategies block diagram, as shown in Figure 6.Asymmetric Fuzzy PID Control System proposed in this paper is as schemed
Shown in 6.M is the conversion switch value of the asymmetric fuzzy controller and PID controller of setting, available by emulating.When | P '
(u) | when the sections m ＞, using the traditional controller for improving variable step above；When 0≤| P ' (u) | when the sections≤m, then it is non-right to use
Fuzzy controller is claimed accurately to be tracked and optimized.Photovoltaic generating system is a strongly non-linear system, and photovoltaic cell obtains defeated
It is difficult to be described with particularly accurate mathematical model to go out characteristic curve, and the MPPT of photovoltaic cell does not need special photovoltaic cell yet
Accurate mathematical model so that the output characteristic curve of photovoltaic cell is sought close to MPP but by the controllable parameter value of constantly regulate
Excellent process, this has exactly suited the fuzzy control technology feature to controlled device, so, take fuzzy control strategy to photovoltaic
Battery MPPT control just proper.
Asymmetric fuzzy controller (Asymmetric Fuzzy Logic Controller, AFLC), here mainly to it
The asymmetric blurring of membership function is designed.Traditional fuzzy controller is usually using error e and error change amount Δ e as mould
The input of paste.
The asymmetric fuzzy logic controller input quantity designed herein is respectively：There is the variation of the output power from photovoltaic cells P
The ratio of amount and the variable quantity of output voltage v, the e power errors of expression, Δ e error rates.The expression formula at K moment is such as public
Shown in formula 8, formula 9.
Δ e (k)=e (k)-e (k-1) (9)
Wherein P (k), v (k) are that the output power and voltage at photovoltaic cell current k moment can in very short time respectively
E (k) to be regarded as to the slope of P-U characteristic curves certain point.The output controlled quentity controlled variable of controller is voltage-regulation amount dv.
During control, the amount of being observed is typically the exact numerical amount in certain exact extension, for the ease of controlling,
It first has to first be mapped to input variable on Fuzzy Linguistic Variable domain corresponding with it from its basic domain.Here, it adopts
With Fuzzy Linguistic Variable PB (honest), PM (center), PS (just small), ZE (zero), NS (negative small), NM (in negative), NB (negative big), this
Seven Linguistic Values divide the grade of the input quantity and output quantity of fuzzy controller.Generally in fuzzy control system, with person in servitude
The control accuracy of the increase of membership fuction number, system can accordingly increase.
In the design, select it is trapezoidal with Triangleshape grade of membership function based on, it is contemplated that photovoltaic cell P-U output characteristics it is non-
Symmetric characteristics can more accurately show the P-U output characteristics of photovoltaic cell, adopt here to promote Precision of Fuzzy Controller
Membership function all has asymmetry can.
Membership function design principle is caused by identical voltage change according to photovoltaic cell P-U characteristic curves here
Changed power it is more larger than left side on the right side of photovoltaic cell MPP, in order to preferably promote MPPT precision, to needing to do on the right side of MPP
Smaller step-length disturbance, therefore the maximum value that domain is born inside the output variable selected is smaller than the maximum value of positive domain.By
The function of degree of membership after repeatedly adjusting, as shown in Figure 7, Figure 8.
Here IF A AND B THEN C fuzzy rules are applied, obtain fuzzy reasoning table, as shown in table 1.
Table 1
Attached drawing 9 is proposed by the present invention a kind of based on improvement variable step and asymmetric fuzzy INC photovoltaic MPPT controlling parties
The overall structure block diagram of method, correctness to illustrate the invention and feasibility, emulation are established based on the expansion of Boost circuit module
, it is constituted containing photovoltaic module, DC/DC circuits, asymmetric fuzzy controller.Partial parameters are：The maximum of photovoltaic battery panel
Electric current Isc=3.5A, maximum power point electric current Im=3A, maximum output voltage Voc=600V, maximum power point voltage Vn=
380V, resistance R=100 Ω.It is 10e-6F, 1e-6F respectively that two capacitance C are left-to-right from circuit diagram, and inductance l values are set as 200e-
3H, emulation use ode45 algorithms.If the temperature T of photovoltaic battery panel is 25 DEG C, time of emulation is 0.8s, 0.2s when
It carves, intensity of illumination S is suddenly from 1000W/m2Drop to 800W/m2, then 1000W/m is raised again at the 0.4s moment again2, imitated
Very.By emulating comparison repeatedly, m=0.268 is generally chosen, i.e. P-U proportional tilts angle is 15 ° in Fig. 4, more properly, is emulated
Figure 10 is ideal with Figure 11, simulation result, as Figure 10 (conductance increment method of traditional variable step), Figure 11 (improve variable step with
Asymmetric fuzzy conductance increment method), show the conductance increment method being combined with asymmetric fuzzy control based on improvement variable step
Control algolithm can be relatively good track MPP, just worked in photovoltaic array, two methods can trace into MPP, but phase
Compare, it is improved more stablize with it is steady, without larger oscillation, when emulating the environmental factors of progress below and changing,
System also can quickly and accurately track MPP, it may have preferable stability.For general effect, than traditional step-length photovoltaic
MPPT control strategies are more excellent.
Claims (1)
1. a kind of based on the maximum photovoltaic power point tracking and controlling method for improving conductance increment method, which is characterized in that photovoltaic cell
Output power formula P (u) carries out that a directive/guide is asked to obtain first derivative expression formula：
Wherein u is output voltage, C1It is the filter capacitor emulated in Boost circuit；C2It is the load-side emulated in Boost circuit
Capacitance；IscIt is the short circuit current of photovoltaic cell；UocOpen circuit voltage；
M is the control conversion switch value of setting,
When | P ' (u) | when the sections m ＞, MPPT maximum power point tracking control is carried out to photovoltaic using the traditional controller for improving variable step
System, variable step meet formula D (K)=D (K-1) ± β N (Δ P/ Δ U),
D (K) is the duty ratio in k-th period；N is the regulation coefficient of variable step, N=arctan [P (u)]；β is adjustable normal
Number, Δ P, Δ U are respectively k-th Cyclical power and output voltage variable quantity；
When 0≤| P ' (u) | when the sections≤m, then MPPT maximum power point tracking control is carried out to photovoltaic using asymmetric fuzzy controller,
Asymmetric fuzzy logic controller input quantity is respectively：The variable quantity of the variable quantity and output voltage v of the output power from photovoltaic cells P
Ratio and error rate Δ e, the kth moment expression formula of two input values it is as follows：
Δ e (k)=e (k)-e (k-1) (2)
Wherein P (k), v (k) are the output power and voltage at photovoltaic cell current k moment respectively, in very short time, by e (k)
Regard the slope of P-U characteristic curves certain point as；The output controlled quentity controlled variable of asymmetric fuzzy logic controller is voltage-regulation amount dv.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102088256A (en) * | 2010-12-16 | 2011-06-08 | 永济新时速电机电器有限责任公司 | Tracking control method for maximum power point of photovoltaic cell |
| CN102611341A (en) * | 2012-03-12 | 2012-07-25 | 深圳市英威腾电气股份有限公司 | Photovoltaic inverter and method for tracking maximum power of same |
| CN103488239A (en) * | 2013-09-29 | 2014-01-01 | 武汉理工大学 | Tracking method for maximum power point in photovoltaic grid-connected inverter |
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2018
- 2018-05-08 CN CN201810434954.1A patent/CN108628385A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102088256A (en) * | 2010-12-16 | 2011-06-08 | 永济新时速电机电器有限责任公司 | Tracking control method for maximum power point of photovoltaic cell |
| CN102611341A (en) * | 2012-03-12 | 2012-07-25 | 深圳市英威腾电气股份有限公司 | Photovoltaic inverter and method for tracking maximum power of same |
| CN103488239A (en) * | 2013-09-29 | 2014-01-01 | 武汉理工大学 | Tracking method for maximum power point in photovoltaic grid-connected inverter |
Non-Patent Citations (1)
| Title |
|---|
| 杨旭红,尹聪聪: "基于变步长与非对称模糊的光伏MPPT控制策略", 《电机与控制应用》 * |
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