CN105242742B - Single-stage photovoltaic power generation system maximum power tracing method based on monkey group's algorithm - Google Patents
Single-stage photovoltaic power generation system maximum power tracing method based on monkey group's algorithm Download PDFInfo
- Publication number
- CN105242742B CN105242742B CN201510740680.5A CN201510740680A CN105242742B CN 105242742 B CN105242742 B CN 105242742B CN 201510740680 A CN201510740680 A CN 201510740680A CN 105242742 B CN105242742 B CN 105242742B
- Authority
- CN
- China
- Prior art keywords
- pvi
- photovoltaic
- photovoltaic array
- maximum power
- monkey
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- 238000000034 method Methods 0.000 title claims abstract description 41
- 241000282693 Cercopithecidae Species 0.000 title claims abstract description 33
- 238000010248 power generation Methods 0.000 title claims abstract description 9
- 230000000007 visual effect Effects 0.000 claims description 6
- 230000005611 electricity Effects 0.000 claims description 5
- 235000008694 Humulus lupulus Nutrition 0.000 claims description 3
- 230000009194 climbing Effects 0.000 abstract description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
Classifications
-
- 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 invention discloses a kind of single-stage photovoltaic power generation system maximum power tracing method based on monkey group's algorithm, the control method is used to control Single-Stage Grid Connected Solar Inverter System, comprised the following steps：Obtain the open-circuit voltage of photovoltaic array open-circuit voltage and photovoltaic module；Initialize monkey group；Journey processing is got over, process processing is hoped, jump process processing exports the position of now Monkey King, i.e., corresponding voltage at maximum power point.The hunting zone that the present invention hopes jump process change population by climbing, enables a system to accurately track global maximum power point under shadow condition, it is to avoid algorithm is absorbed in local optimum.It uses the alternative manner of pseudo- gradient, and energy fast track improves convergence of algorithm speed to global maximum power point.It employs less step-size in search at maximum power point, reduces vibration of the system at maximum power point, reduces power attenuation, improves the operational efficiency of system.
Description
Technical field
The present invention relates to a kind of single-stage photovoltaic power generation system maximum power tracing method, more particularly to one kind is based on monkey group
The single-stage photovoltaic power generation system maximum power tracing method of algorithm, the method for tracing generates electricity by way of merging two or more grid systems for stage photovoltaic single is
System, belongs to power supply control technical field.
Background technology
Photovoltaic generation because it is widely distributed, easy to use, pollution-free the advantages of, get more and more people's extensive concerning.Photovoltaic generation
System can be divided into two kinds of autonomous power supply system and grid-connected system, using it is more be grid-connected photovoltaic system.Stage photovoltaic single
Grid-connected system only one of which energy conversion link, topology is simply a kind of very promising novel circuit configuration.It
Inversion function is realized using voltage controlled grid-connected inverter；By corresponding control system realize maximal power tracing function and
Unity power factor is incorporated into the power networks.But single stage type grid-connected system also has many problem urgent need to resolve simultaneously, wherein efficiency is
Its subject matter.
In order to realize the maximization of output power of photovoltaic module, it is necessary to carry out MPPT maximum power point tracking to photovoltaic module
(MPPT).The MPPT control method of routine mainly has both at home and abroad at present：1) for single peak MPPT methods have disturbance observation method,
Search by hill climbing method, conductance increment method.2) the MPPT methods for multi-peak have artificial fish-swarm method, population, fuzzy control etc.
Intelligent MPPT algorithm.Due to cloud layer, tree shade, building block or part photovoltaic module aged deterioration, photovoltaic array
Multiple local peak values can be presented in P-V characteristic curves, and the MPPT methods for single peak can only track single power peak, in part
Effectively tracking can not be completed under the conditions of shade power output multi-peak, globally optimal solution has been lost.Conventional multi-peak intelligence
MPPT algorithm, using more complicated iterative calculation formula, convergence rate is slower；Though global optimum can be tracked but easily existed
Vibrated at maximum power point, cause power attenuation；The control parameter of intelligent algorithm is more simultaneously, and control structure is complicated.It is traditional single
The intelligent MPPT control method of peak value and multi-peak be required for and meanwhile detect the voltage and current of photovoltaic module with obtain power and its
Change direction, increases the operating cost of photovoltaic system, the reliability of system is reduced.
The content of the invention
The technical problem to be solved in the present invention is to provide a kind of single-stage photovoltaic power generation system based on monkey group's algorithm is maximum
Powerinjected method method.
The present invention uses following technical proposals：
A kind of single-stage photovoltaic power generation system maximum power tracing method based on monkey group's algorithm, the method for tracing is used for
Single-Stage Grid Connected Solar Inverter System, the Single-Stage Grid Connected Solar Inverter System includes photovoltaic array, and the photovoltaic array is by m
String n and photovoltaic module composition；It is characterized in that：Comprise the following steps：
Step 1：Obtain photovoltaic array open-circuit voltage Uoc_arrayWith the open-circuit voltage U of photovoltaic moduleoc_module, by following tool
Body is constituted step by step：
Step 1-1：Read the output voltage U of the photovoltaic arraypv；
Step 1-2：Detect the real-time output current i of the photovoltaic arraypvWhether current threshold i is less thanset；If it is, turning
To step 1-4；If not, turning to step 1-3；
Step 1-3：The output voltage U of the photovoltaic arraypvIncrease 0.5V；Turn to step 1-2；
Step 1-4：Record open-circuit voltage Uoc_arrayWith the output voltage U of the photovoltaic arraypv, the photovoltaic module
Open-circuit voltage is Uoc_module=Uoc_array/m；
Step 2：Initialize monkey group：It is AC output current d axle components i including setting target function valued；Decision-making is set
Variable is the output voltage U of the photovoltaic arraypv；Step-length a is climbed in setting, determines that prestige is regarded according to the distance between two neighboring crest
Wild length β, looks into the distance number of times for m-1, climbs maximum times for Citer_max；Counted out according to initial power peak value and monkey group's scale M is set；
According to initial power peak point position initialization monkey group { U1,U2…UM}；
Step 3：Get over journey processing：By constituting step by step in detail below：
Step 3-1：Disturbance quantity amount △ U when producing kth time iterationpvi(k), 1≤i≤M：
Step 3-2：The pseudo- gradient i' of object function when calculating kth time iterationd(k)：(1≤k≤Citer_max)
Wherein, idi(Upvi+ΔUpvi) it is to increase the target function value after disturbance, idi(Upvi) for disturbance before target
Functional value, Δ UpviFor the step 3-1 disturbance observation amount randomly generated, k is current iteration number of times；
Step 3-3：Update the value of object function and decision variable：
idi(k+1)=idi(k)+a*sign(i'di(k)),1≤i≤M (3)
Upvi(k+1)=Upvi(k)+ΔUpvi(k),1≤i≤M
(4)
Wherein idi(k+1),idi(k) be respectively kth+1 time and k iteration target function value；sign(idi' (k)) it is to take
The pseudo- gradient i for the kth time iterative target function that step 3-2 is calculateddi' (k) symbol, work as idi'(k)>When 0, value is 1, when
idi'(k)<When 0, value is -1；Upvi(k+1),Upvi(k) be respectively kth+1 time and k iteration photovoltaic array output voltage,
△Upvi(k) it is the disturbance quantity of the step 3-1 kth time iteration produced；
Step 3-4：Judge whether the difference of object function and last time object function is more than predetermined threshold value, if it is, turning to
Step 3-1, if not, turning to step 3-5；
Step 3-5：Judgement climbs whether number of times climbs number of times less than maximum, if it is, step 3-1 is turned to, if not, updating monkey
Throne is put, i.e., at maximum power point to voltageTurn to step 4；
Step 4：The processing of prestige process：It is 0.8U to set visual field length β according to the distance between two neighboring crestoc_module；
Step 5：Jump process processing：By constituting step by step in detail below：
Step 5-1：Update the output voltage U of photovoltaic arraypvi(p)：
UPVi(p+1)=UPVi(p)+β1≤p≤M
(5)
Wherein Upvi(p+1),Upvi(p) it is respectively that p-th monkey group is performed after jump process and photovoltaic array output before
Voltage；.
Step 5-2：Judge idi(p+1)>idi(p) whether set up；If it is, step 3-1 is turned to, if not, turning to step
5-3；
Wherein idi(p+1),idi(p) it is respectively that p-th monkey group is performed after jump process and object function before；.
Step 5-3：Whether judgement hops number less than number of times is looked into the distance, if it is, step 5-1 is turned to, if not, turning to step
6；
Step 6：The position of now Monkey King is exported, i.e. peak power points out corresponding voltage
It is using the beneficial effect produced by above-mentioned technical proposal：
1st, the present invention by climbing-hope-jump process changes the hunting zone of population, it is accurate under shadow condition to enable a system to
Track global maximum power point, it is to avoid algorithm is absorbed in local optimum.
2nd, the present invention uses the alternative manner of pseudo- gradient, and energy fast track improves algorithm to global maximum power point
Convergence rate.
3rd, the present invention employs less step-size in search at maximum power point, reduces system at maximum power point
Vibration, reduces power attenuation, improves the operational efficiency of system.
4th, The present invention reduces the use to multiplier, while reducing measuring apparatus, the cost of system is reduced.
5th, control parameter of the present invention is few, simplifies the control structure of system.
Brief description of the drawings
Fig. 1 is that single stage type generates electricity by way of merging two or more grid systems structural representation；
Fig. 2 is that single stage type generates electricity by way of merging two or more grid systems control structure；
Fig. 3 is the flow chart of the present invention；
Fig. 4 is that-jump process schematic diagram is climbed-hoped to multi-peak photovoltaic output characteristic curve in the present invention.
Embodiment
The present invention is further detailed explanation with reference to the accompanying drawings and detailed description.
Such as Fig. 1, shown in Fig. 2, photovoltaic array is made up of the photovoltaic modulies of m strings n simultaneously；, can be same using voltage source inverter
Shi Shixian inversions, unity power factor control and maximal power tracing control.Stage photovoltaic single generate electricity by way of merging two or more grid systems control system use
Three close-loop control structure, wherein most outer shroud is the maximum power tracing of photovoltaic array, the input quantity of most outer shroud is the defeated of photovoltaic array
Go out voltage UpvWith the d axle components i of AC output currentd, output quantity is maximum power point voltageMost outer shroud is output as
The input of Voltage loop, Voltage loop is controlled using PI, is output as the reference value of AC output current d axle componentsAnd willAs
The input of electric current loop, produces SPWM modulated signals.
As shown in figure 3, a kind of single-stage photovoltaic power generation system maximum power tracing method based on monkey group's algorithm, described to chase after
Track method is used for Single-Stage Grid Connected Solar Inverter System, and the Single-Stage Grid Connected Solar Inverter System includes photovoltaic array, described
Photovoltaic array is made up of m string n and photovoltaic module；Comprise the following steps：
Step 1：Obtain photovoltaic array open-circuit voltage Uoc_arrayWith the open-circuit voltage U of photovoltaic moduleoc_module, by following tool
Body is constituted step by step：
Step 1-1：Read the output voltage U of the photovoltaic arraypv；
Step 1-2：Detect the real-time output current i of the photovoltaic arraypvWhether current threshold i is less thanset；If it is, turning
To step 1-4；If not, turning to step 1-3；
Step 1-3：The output voltage U of the photovoltaic arraypvIncrease 0.5V；Turn to step 1-2；
Step 1-4：Record open-circuit voltage Uoc_arrayWith the output voltage U of the photovoltaic arraypv, the photovoltaic module
Open-circuit voltage is Uoc_module=Uoc_array/m；
Step 2：Initialize monkey group：It is AC output current d axle components i including setting target function valued；Decision-making is set
Variable is the output voltage U of the photovoltaic arraypv；Step-length a is climbed in setting, determines that prestige is regarded according to the distance between two neighboring crest
Wild length β, looks into the distance number of times for m-1, climbs maximum times for Citer_max；Counted out according to initial power peak value and monkey group's scale M is set；
According to initial power peak point position initialization monkey group { U1,U2…UM}；
Step 3：Get over journey processing：By constituting step by step in detail below：
Step 3-1：Produce random vector △ Upvi(k), 1≤i≤M：
Step 3-2：The pseudo- gradient of object function when calculating kth time iterationi'd(k)：
Wherein, idi(Upvi+ΔUpvi) it is to increase the target function value after disturbance, idi(Upvi) for disturbance before target
Functional value, Δ UpviFor the step 3-1 disturbance observation amount randomly generated, k is current iteration number of times；
Step 3-3：Update the value of object function and decision variable：
idi(k+1)=idi(k)+a*sign(i′di(k)),1≤i≤M (3)
Upvi(k+1)=Upvi(k)+ΔUpvi(k),1≤i≤M
(4)
Wherein idi(k+1),idi(k) be respectively kth+1 time and k iteration target function value；sign(idi' (k)) it is to take
The pseudo- gradient i of kth time iterative target function that step 3-2 is calculateddi' (k) symbol, work as idi'(k)>When 0, value is 1, when
idi'(k)<When 0, value is -1；Upvi(k+1),Upvi(k) be respectively kth+1 time and k iteration photovoltaic array output voltage,
△Upvi(k) it is the disturbance quantity of the step 3-1 kth time iteration produced.
Step 3-4：Judge whether the difference of object function and last time object function is more than predetermined threshold value, if it is, turning to
Step 3-1, if not, turning to step 3-5；
Step 3-5：Judgement climbs whether number of times climbs number of times less than maximum, if it is, step 3-1 is turned to, if not, updating monkey
Throne is put, i.e., at maximum power point to voltageTurn to step 4；
Step 4：The processing of prestige process：It is 0.8U to set visual field length β according to the distance between two neighboring crestoc_module；
Step 5：Jump process processing：By constituting step by step in detail below：
Step 5-1：Update the output voltage U of photovoltaic arraypvi(p)(1≤p≤M)
UPVi(p+1)=UPVi(p)+β1≤p≤M
(5)
Wherein Upvi(p+1),Upvi(p) it is respectively that p-th monkey group is performed after jump process and photovoltaic array output before
Voltage.
Step 5-2：Judge idi(p+1)>idi(p) whether set up；If it is, step 3-1 is turned to, if not, turning to step
5-3；
Wherein idi(p+1),idi(p) it is respectively that p-th monkey group is performed after jump process and object function before.
Step 5-3：Whether judgement hops number less than number of times is looked into the distance, if it is, step 5-1 is turned to, if not, turning to step
6；
Step 6：The position of now Monkey King is exported, i.e. peak power points out corresponding voltage
It is assumed that every series arm circumstance of occlusion of array is differed, then m work(in this case occurs
Rate peak point, the corresponding array voltage value of first peak point is located substantially at 0.7Uoc_modulePlace, second peak point is corresponding
Array voltage value is located substantially at 1.5Uoc_modulePlace；The corresponding array voltage value of m-th of peak point is about by that analogy
0.8Uoc_array.In maximum power point of photovoltaic array tracking, ignore inverter losses, the d axle components i of AC grid-connected currentd
With the power output P of photovoltaic modulepvThere is linear relationship.Work as idP during increasepvIncrease therewith.Analyzed more than, by right
idMaximum tracking replace to PpvMaximal power tracing.
After by getting over journey, every monkey all reach each where mountain peak top at, i.e., object function has reached office
Portion is optimal.Afterwards, it is looked into the distance to surrounding, and observation neighbouring field around it whether there is the mountain peak higher than current mountain peak.MA
Define a parameter beta and be referred to as visual field length.Visual field length β determines the maximum distance that monkey can be looked into the distance from current location.Root
0.8U is differed according between two neighboring peak valueoc_module, so β value is set into 0.8Uoc_module。
Claims (1)
1. a kind of single-stage photovoltaic power generation system maximum power tracing method based on monkey group's algorithm, it is characterised in that：It is described to chase after
Track method is used for Single-Stage Grid Connected Solar Inverter System, and the Single-Stage Grid Connected Solar Inverter System includes photovoltaic array, described
Photovoltaic array is made up of m string n and photovoltaic module；It is characterized in that：Comprise the following steps：
Step 1：Obtain photovoltaic array open-circuit voltage Uoc_arrayWith the open-circuit voltage U of photovoltaic moduleoc_module, by dividing in detail below
Step is constituted：
Step 1-1：Read the output voltage U of the photovoltaic arraypv；
Step 1-2：Detect the real-time output current i of the photovoltaic arraypvWhether current threshold i is less thanset；If it is, turning to step
Rapid 1-4；If not, turning to step 1-3；
Step 1-3：The output voltage U of the photovoltaic arraypvIncrease 0.5V；Turn to step 1-2；
Step 1-4：Record open-circuit voltage Uoc_arrayWith the output voltage U of the photovoltaic arraypv, the open circuit electricity of the photovoltaic module
Press as Uoc_module=Uoc_array/m；
Step 2：Initialize monkey group：It is AC output current d axle components i including setting target function valued；Decision variable is set
For the output voltage U of the photovoltaic arraypv；Step-length a is climbed in setting, is determined to hope that the visual field is long according to the distance between two neighboring crest
β is spent, number of times is looked into the distance for m-1, maximum times are climbed for Citer_max；Counted out according to initial power peak value and monkey group's scale M is set；According to
Initial power peak point position initialization monkey group { U1,U2…UM}；
Step 3：Get over journey processing：By constituting step by step in detail below：
Step 3-1：Disturbance quantity △ U when producing kth time iterationpvi(k), 1≤i≤M：
Step 3-2：The pseudo- gradient i' of object function when calculating kth time iterationd(k)：(1≤k≤Citer_max)
Wherein, idi(Upvi+ΔUpvi) it is to increase the target function value after disturbance, idi(Upvi) for disturbance before object function
Value, Δ UpviFor the step 3-1 disturbance observation amount randomly generated, k is current iteration number of times；
Step 3-3：Update the value of object function and decision variable：
idi(k+1)=idi(k)+a*sign(i'di(k)),1≤i≤M (3)
Upvi(k+1)=Upvi(k)+ΔUpvi(k),1≤i≤M (4)
Wherein idi(k+1),idi(k) be respectively kth+1 time and k iteration target function value；sign(idi' (k)) it is to take step
The pseudo- gradient i for the kth time iterative target function that rapid 3-2 is calculateddi' (k) symbol, work as idi'(k)>When 0, value is 1, when
idi'(k)<When 0, value is -1；Upvi(k+1),Upvi(k) be respectively kth+1 time and k iteration photovoltaic array output voltage,
△Upvi(k) it is the disturbance quantity of the step 3-1 kth time iteration produced；
Step 3-4：Judge whether the difference of object function and last time object function is more than predetermined threshold value, if it is, turning to step
3-1, if not, turning to step 3-5；
Step 3-5：Judgement climbs whether number of times climbs number of times less than maximum, if it is, step 3-1 is turned to, if not, updating Monkey King position
Put, i.e., at maximum power point to voltageTurn to step 4；
Step 4：The processing of prestige process：It is 0.8U to set visual field length β according to the distance between two neighboring crestoc_module；
Step 5：Jump process processing：By constituting step by step in detail below：
Step 5-1：Update the output voltage U of photovoltaic arraypvi(p)(1≤p≤M)
UPVi(p+1)=UPVi(p)+β1≤p≤M (5)
Wherein Upvi(p+1),Upvi(p) it is respectively that p-th monkey group is performed after jump process and photovoltaic array output voltage before；
Step 5-2：Judge idi(p+1)>idi(p) whether set up；If it is, step 3-1 is turned to, if not, turning to step 5-3；
Wherein idi(p+1),idi(p) it is respectively that p-th monkey group is performed after jump process and object function before；
Step 5-3：Whether judgement hops number less than number of times is looked into the distance, if it is, step 5-1 is turned to, if not, turning to step 6；
Step 6：The position of now Monkey King is exported, i.e. peak power points out corresponding voltage
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510740680.5A CN105242742B (en) | 2015-11-04 | 2015-11-04 | Single-stage photovoltaic power generation system maximum power tracing method based on monkey group's algorithm |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510740680.5A CN105242742B (en) | 2015-11-04 | 2015-11-04 | Single-stage photovoltaic power generation system maximum power tracing method based on monkey group's algorithm |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105242742A CN105242742A (en) | 2016-01-13 |
| CN105242742B true CN105242742B (en) | 2017-07-18 |
Family
ID=55040417
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510740680.5A Expired - Fee Related CN105242742B (en) | 2015-11-04 | 2015-11-04 | Single-stage photovoltaic power generation system maximum power tracing method based on monkey group's algorithm |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105242742B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106484026B (en) * | 2016-11-15 | 2018-10-30 | 北京信息科技大学 | A kind of control method and device of the maximum photovoltaic power point tracking based on grey wolf algorithm |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2011198011A (en) * | 2010-03-19 | 2011-10-06 | Seiko Epson Corp | Maximum power tracking control method of solar cell, and maximum power tracking control circuit of solar cell |
| CN101814735A (en) * | 2010-05-19 | 2010-08-25 | 天津大学 | Method for expansion planning of power transmission network |
| WO2012090242A1 (en) * | 2010-12-27 | 2012-07-05 | 日立アプライアンス株式会社 | Power converter and solar power generation system |
| CN103093027B (en) * | 2012-12-06 | 2015-09-16 | 广东电网公司电力科学研究院 | Based on the Power System Analysis method of double-fed fan motor field Equivalent Model |
| CN103123514B (en) * | 2013-02-26 | 2014-11-12 | 浙江工业大学 | Photovoltaic array multimodal maximum power point tracing method |
| CN104268721B (en) * | 2014-10-17 | 2017-10-31 | 广西民族大学 | A kind of aircraft landing runway system of selection of the monkey colony optimization algorithm based on integer coding |
-
2015
- 2015-11-04 CN CN201510740680.5A patent/CN105242742B/en not_active Expired - Fee Related
Also Published As
| Publication number | Publication date |
|---|---|
| CN105242742A (en) | 2016-01-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105207606B (en) | DMPPT photovoltaic generating modules based on timesharing adaptive M CT algorithms | |
| CN108614612B (en) | Method and system for tracking maximum power of solar photovoltaic cell | |
| Ounnas et al. | An efficient maximum power point tracking controller for photovoltaic systems using Takagi–Sugeno fuzzy models | |
| CN103123514A (en) | Photovoltaic array multimodal maximum power point tracing method | |
| CN109270982A (en) | A kind of photovoltaic maximum power tracking and controlling method | |
| CN103995558B (en) | A kind of maximum power point of photovoltaic array tracking based on chaos optimization search | |
| Anoop et al. | A novel maximum power point tracking method based on particle swarm optimization combined with one cycle control | |
| CN107479618A (en) | Multi-peak MPPT algorithm based on ant group algorithm and conductance increment method | |
| CN102902298A (en) | Photovoltaic array maximum power point tracking (MPPT) controller based on segmented model and controlling method | |
| Ahmed et al. | PSO-SMC controller based GMPPT technique for photovoltaic panel under partial shading effect | |
| Elzein | Maximum power point tracking system for photovoltaic station: A review | |
| Gaur et al. | Maximum power point tracking algorithms for photovoltaic applications: A comparative study | |
| CN110707754B (en) | Optimization method for water-wind-light power supply capacity configuration in micro-grid | |
| Pawar et al. | Review of PV MPPT based battery charging techniques under partial shading conditions | |
| Osman et al. | Highly efficient MPP tracker based on adaptive neuro-fuzzy inference system for stand-alone photovoltaic generator system | |
| CN105242742B (en) | Single-stage photovoltaic power generation system maximum power tracing method based on monkey group's algorithm | |
| Ba et al. | Optimization of the P&O-MPPT controller by the adaptive method (Ad-P&O) for stand-alone PV systems | |
| CN105068591B (en) | Maximum power point tracing method under a kind of photovoltaic array partial occlusion | |
| CN111061331A (en) | Photovoltaic maximum power control system and method | |
| Zabia et al. | A novel equilibrium optimizer for tracking the maximum power of a photovoltaic system under non-uniform conditions | |
| CN112631365A (en) | Photovoltaic power generation multi-peak MPPT control method based on SCASL | |
| Hassan et al. | Performance of different MPPT control techniques for photovoltaic systems | |
| CN107292768B (en) | Photovoltaic power generation system daily generated energy fuzzy probability calculation method and device | |
| Sule et al. | Optimal rotor blade control using Grey Wolf Optimizer for small signal stability of SCIG Wind Turbine | |
| CN109725674A (en) | A kind of optimization algorithm of the photovoltaic system maximal power tracing based on SA+PSO hybrid algorithm |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20170718 Termination date: 20181104 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |