CN109753102A - A kind of fuzzy MPPT control method of improved photovoltaic - Google Patents
A kind of fuzzy MPPT control method of improved photovoltaic Download PDFInfo
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- CN109753102A CN109753102A CN201711075039.XA CN201711075039A CN109753102A CN 109753102 A CN109753102 A CN 109753102A CN 201711075039 A CN201711075039 A CN 201711075039A CN 109753102 A CN109753102 A CN 109753102A
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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
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- 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 improved photovoltaics to obscure MPPT control method, and technical characteristics are: obtaining best power using scanning, storage, disturbance and observation.Under primary condition or variable weather, this method meeting extensive search simultaneously stores photovoltaic system maximum power value.The acceptable difference run between power that preset value represents determining maximum power and determined by rule of controller.If the difference between identified maximum power and operation power is greater than preset value, duty ratio just be will increase；Otherwise, using the MPPT based on fuzzy logic.In this way, the algorithm can ensure that MPPT will not fall into local MPP, and it is promptly restored to new global MPP.The present invention combines the maximum power point tracing method based on fuzzy logic with scanning storage.Controller has fast convergence, is avoided that operating point is fluctuated near MPP, the control effect of MPPT obtains larger raising, enhances the dynamic response of system.
Description
Technical field
The present invention relates to a kind of methods for tracking solar maximum power, and in particular to a kind of improved photovoltaic fuzzy logic
The maximum power point tracing method of control.
Background technique
With the rapid development of industry, needs also sustainable growth of the mankind to the energy, the trend in the world is had been sought for
The new energy substitutes conventional energy resources.As one of available alternative energy source photovoltaic energy become it is most promising can
One of renewable sources of energy.Photovoltaic energy be it is clean, design is simple.Either household or industry all holds photovoltaic power generation now
Very optimistic attitude, it is desirable to which the available sufficient utilization of photovoltaic energy can be widely applied to people's life production later
Various aspects.But installation cost height and photovoltaic efficiency it is low be photovoltaic system two major defects, and photovoltaic efficiency is low main
That output characteristics has stronger nonlinear characteristic, with the difference of light intensity and environment temperature, the output electric current of solar panels and
Peak power output can all generate very big variation.
Traditional algorithm has fixed voltage method, perturbation observation method, incremental conductance method, optimum gradient method, stagnant ring comparison method, mind
Through metanetwork control methods, fuzzy logic control method etc..Domestic and international academia is suggested and applies there are also some novel control strategies
In practice.The scholars such as the female needle of the Peng Tao of Hohai University, fourth propose a kind of changing based on disturbance observation method and incremental conductance method
Into global maximum power point control algolithm, this method has of overall importance mention in terms of the stability of the rapidity of tracking and system
It is high.The Wen Jiabin scholar of Harbin University of Science and Technology carries out data fitting with Least square, devises fixed step size and becomes step
Long 3 least square methods combined carry out system tracking, obtain the maximum power of output.Miyatake M scholar adopts
Maximum power point is searched for Direct search algorithm, in order to ensure finding global MPP, it is necessary to it is carefully chosen initial point, otherwise,
Controller may be trapped in local MPP.It is influenced to reduce local shades bring, Nguyen D scholar proposes adaptively too
It is positive can photovoltaic array, the adaptive library of connection solar energy and photovoltaic array switch matrix are controlled with System design based on model algorithm
Fixed part.Equally, dynamic array restructing algorithm can improve the output of photovoltaic system under the conditions of local shades.Velasco-
Quesada G scholar is inserted into a controllable switch matrix between photovoltaic generating system and central inverter, keeps photovoltaic module real
Now electrical reconnection.In these methods, MPP can be also obtained using traditional MPPT algorithm, but their power stage is more multiple
Miscellaneous, cost also can be higher.Therefore the MPPT control method that research cost is low, high-efficient is needed.
Summary of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide it is a kind of design rationally and have good stable state and
Dynamic property obscures MPPT control method based on improved photovoltaic.
The present invention solves its technical problem and adopts the following technical solutions to achieve:
A kind of fuzzy MPPT control method of improved photovoltaic, it is characterised in that the following steps are included:
Step 1. photovoltaic system is sampled before obtaining best MPP, so using maximum duty cycle, to system
It is initialized.
Step 2. scans P-U curve, and stores global MPP；A big disturbance is preset, to increase search range.
Step 3. is by disturbance and observes to obtain global MPP.
The blurring of step 4. input quantity and output quantity.
The input and output of fuzzy logic controller are as follows:
Δ P=P (k)-P (k-1)
Δ I=I (k)-I (k-1)
ΔPM=PM(k)-P(k)
Δ D=D (k)-D (k-1)
Δ P and Δ I is respectively variation and the curent change of photovoltaic array output power, Δ P in formulaMFor the overall situation of storage
MPP(PM) and current power difference, Δ D be change in duty cycle.Δ P and Δ I points of four fuzzy subsets: honest (PB), just small
(PS), it bears big (NB) and bears small (NS).ΔPMIt is divided to two fuzzy subsets: PB, PS.Δ D points of six fuzzy subsets: PB, center
(PM), PS, NB, it is negative in (NM) and NS.Therefore, algorithm needs 32 control rules, these rules are based on PO algorithmic rule, and with ginseng
Power is examined to be adjusted.
The fuzzy quantity that above-mentioned reasoning obtains is converted to clear amount by step 5..
Deblurring operation is carried out using having maximum-the smallest Mamdani method to obscure combination to these.Formula is as follows:
In formula, Δ D is fuzzy control output, DiFor maximum-minimum zone center of output membership function.
The advantages and positive effects of the present invention are:
1. being different from traditional perturbation observation method (perturbation and observation, PO) tracking MPP to obtain
The optimum operation power of photovoltaic system is obtained, improved photovoltaic obscures MPPT method using scanning, storage, disturbance and observation to obtain most
Good power.Under primary condition or variable weather condition, this method meeting extensive search scans and stores photovoltaic system maximum
Performance number.The acceptable difference run between power that preset value represents determining maximum power and determined by rule of controller
It is different.If the difference between identified maximum power and operation power is greater than preset value, duty ratio just be will increase；Otherwise, it answers
With the MPPT based on fuzzy logic.In this way, the algorithm can ensure that MPPT will not fall into local MPP, and it is promptly restored to new complete
Office MPP.
2. improved photovoltaic fuzzy logic MPPT combines the MPPT based on fuzzy logic with scanning storage system, improve
The dynamic response of system；After the algorithm, operating point is fixed near MPP, and the control effect of MPPT has obtained significantly
It improves；Even MPPT can also scan within a short period of time and track global MPP, the controller under variable weather condition
With quick convergence rate, stronger system tracking performance.
Detailed description of the invention
Fig. 1 is that improved photovoltaic obscures MPPT flow chart and controller；
Fig. 2 is the shape and fuzzy subset's subregion of the membership function of input and output；
Specific embodiment
The embodiment of the present invention is further described below in conjunction with attached drawing:
A kind of fuzzy MPPT control method of improved photovoltaic, different from traditional perturbation observation method (perturbation
And observation, PO) MPP is tracked to obtain the optimum operation power of photovoltaic system, improved photovoltaic obscures MPPT method and adopts
Best power is obtained with scanning, storage, disturbance and observation.Under primary condition or variable weather condition, this method can be big
Range searching scans and stores photovoltaic system maximum power value.Preset value represents determining maximum power and is determined by rule of controller
Acceptable difference between fixed operation power.If the difference between identified maximum power and operation power is greater than pre-
If value, duty ratio just will increase；Otherwise, using the MPPT based on fuzzy logic.In this way, the algorithm can ensure that MPPT will not be fallen into
Local MPP, and it is promptly restored to new global MPP.Fig. 1 a is flow chart, and D is duty ratio, P in figureMFor global MPP, Δ PMFor
One constant, for identifying global MPP and running the permission difference between power points.
The algorithm uses three scannings and storage method: photovoltaic system is sampled before obtaining best MPP,
So being initialized using maximum duty cycle to system.Method is to store overall situation MPP by scanning P-U curve with search；
Increase the duty ratio of a fixed step size.Meanwhile P-U curve is scanned, and store global MPP；A big disturbance is preset, to increase
Add search range.Different from above-mentioned two method, this method is by disturbing and observing to obtain global MPP.Pass through above three
Kind method can ensure that system finds and store global MPP, and three identifies that the time of overall situation MPP is different.No matter in addition,
Global MPP when is found, as long as duty ratio is more than maximum threshold values, should necessarily return to minimum value.
The improved MPPT algorithm (Fig. 1 b) based on fuzzy logic can quickly position the overall situation using scanning and storing program
MPP.The input and output of fuzzy logic controller are as follows:
Δ P=P (k)-P (k-1)
Δ I=I (k)-I (k-1)
ΔPM=PM(k)-P(k)
Δ D=D (k)-D (k-1) (1)
Δ P and Δ I is respectively variation and the curent change of photovoltaic array output power, Δ P in formulaMFor the overall situation of storage
The difference of MPP (PM) and current power, Δ D are change in duty cycle.Δ P and Δ I points of four fuzzy subsets: honest (PB), just small
(PS), it bears big (NB) and bears small (NS).ΔPMIt is divided to two fuzzy subsets: PB, PS.Δ D points of six fuzzy subsets: PB, center
(PM), PS, NB, it is negative in (NM) and NS.Therefore, algorithm needs 32 control rules, these rules are based on PO algorithmic rule, and with ginseng
Power is examined to be adjusted.It is operated using having maximum-the smallest Mamdani method to obscure combination to these.De-fuzzy
When core algorithm be by the duty cycle conversion of fuzzy subset into real number, formula is as follows:
In formula, Δ D is fuzzy control output, DiFor maximum-minimum zone center of output membership function.Input and output
Membership function shape and fuzzy subset's subregion such as Fig. 2.
It is emphasized that embodiment of the present invention be it is illustrative, without being restrictive, therefore packet of the present invention
Include and be not limited to embodiment described in specific embodiment, it is all by those skilled in the art according to the technique and scheme of the present invention
The other embodiments obtained, also belong to the scope of protection of the invention.
Claims (4)
1. a kind of improved photovoltaic obscures MPPT control method, it is characterised in that the following steps are included:
Step 1. photovoltaic system is sampled before obtaining best MPP, so being carried out using maximum duty cycle to system
Initialization.
Step 2. scans P-U curve, and stores global MPP；A big disturbance is preset, to increase search range.
Step 3. is by disturbance and observes to obtain global MPP.
The blurring of step 4. input quantity and output quantity.
The fuzzy quantity that above-mentioned reasoning obtains is converted to clear amount by step 5..
2. a kind of improved photovoltaic according to claim 1 obscures MPPT control method, it is characterised in that: described obscure is patrolled
Collect the input and output of controller are as follows:
Δ P=P (k)-P (k-1)
Δ I=I (k)-I (k-1)
ΔPM=PM(k)-P(k)
Δ D=D (k)-D (k-1)
Δ P and Δ I is respectively variation and the curent change of photovoltaic array output power, Δ P in formulaMFor the global MPP (P of storageM)
And the difference of current power, Δ D are change in duty cycle.
3. a kind of improved photovoltaic according to claim 1 obscures MPPT control method, it is characterised in that: using with most
Greatly-the smallest Mamdani method carries out deblurring operation to these fuzzy combinations.Formula is as follows:
In formula, Δ D is fuzzy control output, and Di is maximum-minimum zone center of output membership function.
4. a kind of improved photovoltaic according to claim 2 obscures MPPT control method, it is characterised in that: the Δ P and
Δ I points of four fuzzy subsets: it honest (PB), just small (PS), bears big (NB) and bears small (NS).ΔPMIt is divided to two fuzzy subsets: PB,
PS.Δ D point six fuzzy subsets: PB, center (PM), PS, NB, bear in (NM) and NS.Therefore, algorithm needs 32 control rules,
These rules are based on PO algorithmic rule, and are adjusted with reference power.
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Citations (5)
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|---|---|---|---|---|
| CN102163067A (en) * | 2011-04-11 | 2011-08-24 | 武汉万鹏科技有限公司 | Solar maximum power tracking method and solar charging device |
| CN102799208A (en) * | 2012-07-20 | 2012-11-28 | 黄克亚 | Photovoltaic power generation maximum power point tracking fuzzy proportion integration differentiation (PID) control method |
| CN103955253A (en) * | 2014-05-05 | 2014-07-30 | 合肥工业大学 | Power closed-loop scanning-based maximum power point tracking method for multiple peak values of photovoltaic array |
| CN103995560A (en) * | 2014-05-26 | 2014-08-20 | 东南大学 | Photovoltaic array multi-peak maximum power point tracking method |
| CN106950857A (en) * | 2017-04-27 | 2017-07-14 | 南通大学 | Photovoltaic cell MPPT emulation modes based on fuzzy logic control |
-
2017
- 2017-11-01 CN CN201711075039.XA patent/CN109753102B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102163067A (en) * | 2011-04-11 | 2011-08-24 | 武汉万鹏科技有限公司 | Solar maximum power tracking method and solar charging device |
| CN102799208A (en) * | 2012-07-20 | 2012-11-28 | 黄克亚 | Photovoltaic power generation maximum power point tracking fuzzy proportion integration differentiation (PID) control method |
| CN103955253A (en) * | 2014-05-05 | 2014-07-30 | 合肥工业大学 | Power closed-loop scanning-based maximum power point tracking method for multiple peak values of photovoltaic array |
| CN103995560A (en) * | 2014-05-26 | 2014-08-20 | 东南大学 | Photovoltaic array multi-peak maximum power point tracking method |
| CN106950857A (en) * | 2017-04-27 | 2017-07-14 | 南通大学 | Photovoltaic cell MPPT emulation modes based on fuzzy logic control |
Non-Patent Citations (1)
| Title |
|---|
| 黄克亚 等: "组合模糊控制技术与扰动观察法提升光伏发电MPPT性能", 《测控技术》 * |
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