CN102651087A - Maximum power point-tracking photovoltaic system based on ant colony-artificial immune hybrid optimization algorithm - Google Patents

Maximum power point-tracking photovoltaic system based on ant colony-artificial immune hybrid optimization algorithm Download PDF

Info

Publication number
CN102651087A
CN102651087A CN2011102516463A CN201110251646A CN102651087A CN 102651087 A CN102651087 A CN 102651087A CN 2011102516463 A CN2011102516463 A CN 2011102516463A CN 201110251646 A CN201110251646 A CN 201110251646A CN 102651087 A CN102651087 A CN 102651087A
Authority
CN
China
Prior art keywords
algorithm
immune
ant colony
ant
maximum power
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.)
Pending
Application number
CN2011102516463A
Other languages
Chinese (zh)
Inventor
李捷
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
GUANGXI NANNING HUATAI DELONG INFORMATION TECHNOLOGY Co Ltd
Original Assignee
GUANGXI NANNING HUATAI DELONG INFORMATION TECHNOLOGY Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by GUANGXI NANNING HUATAI DELONG INFORMATION TECHNOLOGY Co Ltd filed Critical GUANGXI NANNING HUATAI DELONG INFORMATION TECHNOLOGY Co Ltd
Priority to CN2011102516463A priority Critical patent/CN102651087A/en
Publication of CN102651087A publication Critical patent/CN102651087A/en
Pending legal-status Critical Current

Links

Images

Landscapes

  • Photovoltaic Devices (AREA)

Abstract

The invention provides an ant colony-artificial immune hybrid optimization algorithm-based maximum power point-tracking solution in a set of photovoltaic power generation system, in particular to a maximum power point-tracking photovoltaic system based on an ant colony-artificial immune hybrid optimization algorithm. The ant colony algorithm has a powerful advantage in solving the complex combinatorial optimization problem but has certain defects as well, and aimed at the problem that individual ants in the ant colony algorithm lack the ability of identifying problem characteristic information, the idea of vaccine in the immune algorithm is introduced into the ant colony algorithm to provide the ant colony-immune hybrid algorithm. Power optimizers applying the algorithm carry out dual-tracking on solar panels; on one hand, the optimal local MPP (maximum power point) is tracked; and on the other hand, the energy transmission in the system is increased to the max. The power optimizers are indirectly connected with one another, have cognitive ability and self-organization ability, and can detect and independently regulate respective current and voltage environments until the whole string of solar panels reaches an optimal value, and meanwhile, the level of the solar panels reaches a local optimal point.

Description

MPPT maximum power point tracking photovoltaic system based on ant crowd, artificial immunity hybrid optimization algorithm
Technical field
Technical scheme of the present invention belongs to electric and electronic technical field, is a kind of power supply optimization system based on advanced intelligent algorithm, is used for photovoltaic generating system and improves generating efficiency.
Background technology
Because solar battery array has the strong nonlinear characteristic,, all introduced solar cell MPPT maximum power point tracking control technology usually for guaranteeing solar battery array peak power output accordingly all the time under any illumination and environment temperature.Through to the volt-ampere characteristic of the principle of solar cell power generation, photovoltaic cell and junction temperature and intensity of illumination researching and analysing to the influence of solar cell output characteristics; For carrying out maximum power tracing research theoretical foundation and research correlation data are provided; After photovoltaic generating system having been had understanding clearly; Project team is to present research about the MPPT strategy; The method that has occurred comprises that constant voltage back tracking method, disturbance observation, increment conductance method, ripple method of perturbation, power meter algorithm, electric current optimizing method and fuzzy logic control method etc. analyze and research, and these solutions have search time and dead time long etc. not enough.The present invention has incorporated ant crowd, Artificial Immune Algorithm on these MPPT maximum power point tracking technical foundation; Make its large-scale parallel adaptive information processing system characteristics be applied to MPPT maximum power point tracking, demonstrate accurate regulating power detecting and eliminate interference problem.
Summary of the invention
The objective of the invention is in order to solve at present MPPT maximum power point tracking system needs than long search time, easy precocity, the stagnation behavior of occurring, raising photovoltaic generating system generating efficiency.
The present invention provides in the cover photovoltaic generating system based on the MPPT maximum power point tracking solution of ant crowd, artificial immunity hybrid optimization algorithm.Ant group algorithm has powerful advantage finding the solution on the complex combination optimization problem, it has characteristics such as positive feedback, concurrency, distributivity, self-organization.But the ant group algorithm part that also comes with some shortcomings: for example, algorithm needs long search time, precocious, stagnation behavior occur easily.Lack the ability of identification problem characteristic information to the individual ant in the ant group algorithm, the thought of vaccine in the immune algorithm is incorporated in the ant group algorithm, proposed the hybrid algorithm of ant group algorithm and immune algorithm.Give ant with the characteristic information of problem as vaccine injection, make ant have the ability of immunity, be intended to use for reference the strong point of other bionic Algorithm, utilize its advantage to remedy the deficiency of ant group algorithm, thereby improve the performance of finding the solution of ant group algorithm.These immune optimization algorithms have absorbed immune different characteristics respectively, and the algorithm behind feasible the optimization is compared to traditional evolution algorithm, at different aspect improvement has in various degree been arranged.The power supply optimizer of using this algorithm carries out dual tracking to cell panel: on the one hand, they follow the tracks of best local MPP; On the other hand, they are different output voltage/electric current with input voltage/current conversion, transmit with the energy in the raising system to greatest extent.The power supply optimizer interconnects with indirect mode.They have cognitive and organizational capacity voluntarily, can detect own electric current and voltage environment and adjustment voluntarily, reach optimum value up to the whole cell panel of going here and there, and the while reaches the local optimum point in the cell panel rank.
The invention has the beneficial effects as follows, further improve photovoltaic generation equipment MPPT maximum power point tracking efficient, reach more accurate regulating power, significantly improve the power generation performance ratio of photovoltaic generating system detecting and eliminate interference problem.Before the power supply optimizer is installed; The equipment performance ratio has only 65%, in the cell panel system, installs after the power supply optimizer, even have shielding shadow, cell panel and circuit imbalance problem; Whole output power has also promoted 20%, and the performance ratio of system reaches unprecedented 85%.
Description of drawings
Fig. 1 is a systematic schematic diagram of the present invention.
Fig. 2 is the overall process flow diagram of algorithm.
Fig. 3 is a signal schematic representation.
Embodiment
Power supply optimizer shown in Figure 1 has kept the series-connected cell plate arrangement mode of experiencing all sorts of checking, and realizes improvement through only DC/DC being distributed to cell panel with the PMMT function.Meanwhile, power supply optimizer framework and existing multi-level inverter are perfect compatible, they can be moved more efficiently, because bus voltage can keep higher level and more constant.The power supply optimizer is not only limited to the performance that promotes DC-DC converter, and they can handle the many situation of the energy, also can handle the situation that the energy reduces.The irradiation (mismatch problem opposite with shielding shadow) that increases because of reflection also can be utilized to increase production capacity.The capable processing power of same power supply optimizer changes, and method is to add cell panel (making this tandem produce more electric weight) to certain tandem, perhaps reduces by one or two cell panels (thereby reducing electric weight) from certain tandem.
Ant group algorithm has powerful advantage finding the solution on the complex combination optimization problem, it has characteristics such as positive feedback, concurrency, distributivity, self-organization.But the ant group algorithm part that also comes with some shortcomings: for example, algorithm needs long search time, precocious, stagnation behavior occur easily.Lack the ability of identification problem characteristic information to the individual ant in the ant group algorithm, the thought of vaccine in the immune algorithm is incorporated in the ant group algorithm, proposed the hybrid algorithm of ant group algorithm and immune algorithm.Give ant with the characteristic information of problem as vaccine injection, make ant have the ability of immunity, be intended to use for reference the strong point of other bionic Algorithm, utilize its advantage to remedy the deficiency of ant group algorithm, thereby improve the performance of finding the solution of ant group algorithm.These immune optimization algorithms have absorbed immune different characteristics respectively, and the algorithm behind feasible the optimization is compared to traditional evolution algorithm, at different aspect improvement has in various degree been arranged.For example, introduce the diversity that immune self-regulatory mechanism can keep population, loss and the premature convergence of avoiding outstanding gene are in locally optimal solution; Introduce vaccine inoculation mechanism and can make full use of the priori experience that has accumulated in the particular problem, make problem possess rational guidance quality, help the pilot model fast-ripenin in some key component; The memory mechanism of introducing immune antiboidy then makes algorithm have learning ability to a certain degree; Automatically store outstanding antibody, when identical or similar antigen was invaded once more, system can be through selectivity clone, the existing memory antibody of variation; Find out corresponding optimum solution rapidly; Dwindled the hunting zone, improved the reaction velocity of system, and this effect is tangible further along with the increase of working experience.Concrete implementation algorithm is as shown in Figure 2.The power supply optimizer of using this algorithm carries out dual tracking to cell panel: on the one hand, they follow the tracks of best local MPP; On the other hand, they are different output voltage/electric current with input voltage/current conversion, transmit with the energy in the raising system to greatest extent.The power supply optimizer interconnects with indirect mode.They have cognitive and organizational capacity voluntarily, can detect own electric current and voltage environment and adjustment voluntarily, reach optimum value up to the whole cell panel of going here and there, and the while reaches the local optimum point in the cell panel rank.
When environment temperature or intensity of illumination exceed certain limit and obviously have influence on the photovoltaic generating system output power, just can start immune response and follow the trail of maximum power point again.Therefore; The number of times that immune response starts is limited; As long as the time that immune response takies is enough little with respect to the time of photovoltaic generating system operate as normal; A period of time internal cause immune response process output-power fluctuation and the electric energy loss that causes is enough little with respect to the whole output of this section photovoltaic timing electricity generation system electric energy as long as the order of magnitude can be controlled at 1000 Milliseconds, is superior to international standard.In order to verify the ageing of immune optimization algorithm, extract 20 groups of random temperatures and light intensity and carried out MPPT maximum power point tracking, and the recording, tracking time, as shown in Figure 3.The data presentation time of at every turn following the trail of mainly concentrates between the 50ms to 200ms and fluctuates in the table, well beyond the requirement of the 1000ms of system.

Claims (1)

1. based on the MPPT maximum power point tracking photovoltaic system of ant crowd, artificial immunity hybrid optimization algorithm, the thought of vaccine in the immune algorithm is incorporated in the ant group algorithm, the hybrid algorithm of ant group algorithm and immune algorithm has been proposed.Give ant with the characteristic information of problem as vaccine injection, make ant have the ability of immunity, be intended to use for reference the strong point of other bionic Algorithm, utilize its advantage to remedy the deficiency of ant group algorithm, thereby improve the performance of finding the solution of ant group algorithm.These immune optimization algorithms have absorbed immune different characteristics respectively, and the algorithm behind feasible the optimization is compared to traditional evolution algorithm, at different aspect improvement has in various degree been arranged.For example, introduce the diversity that immune self-regulatory mechanism can keep population, loss and the premature convergence of avoiding outstanding gene are in locally optimal solution; Introduce vaccine inoculation mechanism and can make full use of the priori experience that has accumulated in the particular problem, make problem possess rational guidance quality, help the pilot model fast-ripenin in some key component; The memory mechanism of introducing immune antiboidy then makes algorithm have learning ability to a certain degree; Automatically store outstanding antibody, when identical or similar antigen was invaded once more, system can be through selectivity clone, the existing memory antibody of variation; Find out corresponding optimum solution rapidly; Dwindled the hunting zone, improved the reaction velocity of system, and this effect is tangible further along with the increase of working experience.Concrete implementation algorithm is as shown in Figure 2.The power supply optimizer of using this algorithm carries out dual tracking to cell panel: on the one hand, they follow the tracks of best local MPP; On the other hand, they are different output voltage/electric current with input voltage/current conversion, transmit with the energy in the raising system to greatest extent.The power supply optimizer interconnects with indirect mode.They have cognitive and organizational capacity voluntarily, can detect own electric current and voltage environment and adjustment voluntarily, reach optimum value up to the whole cell panel of going here and there, and the while reaches the local optimum point in the cell panel rank.
CN2011102516463A 2011-08-30 2011-08-30 Maximum power point-tracking photovoltaic system based on ant colony-artificial immune hybrid optimization algorithm Pending CN102651087A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN2011102516463A CN102651087A (en) 2011-08-30 2011-08-30 Maximum power point-tracking photovoltaic system based on ant colony-artificial immune hybrid optimization algorithm

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN2011102516463A CN102651087A (en) 2011-08-30 2011-08-30 Maximum power point-tracking photovoltaic system based on ant colony-artificial immune hybrid optimization algorithm

Publications (1)

Publication Number Publication Date
CN102651087A true CN102651087A (en) 2012-08-29

Family

ID=46693091

Family Applications (1)

Application Number Title Priority Date Filing Date
CN2011102516463A Pending CN102651087A (en) 2011-08-30 2011-08-30 Maximum power point-tracking photovoltaic system based on ant colony-artificial immune hybrid optimization algorithm

Country Status (1)

Country Link
CN (1) CN102651087A (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104635834A (en) * 2015-01-16 2015-05-20 华北电力大学 Experimental device and method for tracking photovoltaic maximum power based on immune genetic algorithm
CN104793691A (en) * 2015-03-30 2015-07-22 南昌大学 Photovoltaic array whole situation MPPT method based on ant colony algorithm under partial shadow
CN105373183A (en) * 2015-10-20 2016-03-02 同济大学 Method for tracking whole-situation maximum power point in photovoltaic array
CN105955394A (en) * 2016-06-24 2016-09-21 华北水利水电大学 MPPT method of photovoltaic system based on ant colony optimization and variable step size disturbance observation algorithms
CN118410995A (en) * 2024-07-01 2024-07-30 四川省林业和草原调查规划院(四川省林业和草原生态环境监测中心) Lin Caoguang complementary photovoltaic panel plate distribution method and system based on forest grass growth requirement

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2005124381A (en) * 2003-09-26 2005-05-12 Matsumiya Handotai Kenkyusho:Kk Photovoltaic power generation system and photovoltaic power generation device using the system
CN201928205U (en) * 2011-03-07 2011-08-10 河海大学 Photovoltaic inversion system with maximum power tracking capability

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2005124381A (en) * 2003-09-26 2005-05-12 Matsumiya Handotai Kenkyusho:Kk Photovoltaic power generation system and photovoltaic power generation device using the system
CN201928205U (en) * 2011-03-07 2011-08-10 河海大学 Photovoltaic inversion system with maximum power tracking capability

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
J.A.GOW ETAL.: "Development of a photovoltaic array model for use in power-electronics simulation studies", 《 IEE PROC-ELECTR.POWER APPLE》 *
RALF MUENSTER: "电源优化器技术:集中式与分布式MPPT的分析和比较", 《电子设计应用》 *
姚利明: "蚁群并联光伏发电系统研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑 》 *
步燕芳: "免疫蚁群算法及其应用", 《中国优秀硕士学位论文全文数据库 信息科技辑》 *

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104635834A (en) * 2015-01-16 2015-05-20 华北电力大学 Experimental device and method for tracking photovoltaic maximum power based on immune genetic algorithm
CN104635834B (en) * 2015-01-16 2017-07-07 华北电力大学 The experimental provision and method of the photovoltaic maximal power tracing based on immune genetic algorithm
CN104793691A (en) * 2015-03-30 2015-07-22 南昌大学 Photovoltaic array whole situation MPPT method based on ant colony algorithm under partial shadow
CN104793691B (en) * 2015-03-30 2016-06-15 南昌大学 A kind of photovoltaic array under local shadow based on ant group algorithm overall situation MPPT method
CN105373183A (en) * 2015-10-20 2016-03-02 同济大学 Method for tracking whole-situation maximum power point in photovoltaic array
CN105955394A (en) * 2016-06-24 2016-09-21 华北水利水电大学 MPPT method of photovoltaic system based on ant colony optimization and variable step size disturbance observation algorithms
CN105955394B (en) * 2016-06-24 2017-09-15 华北水利水电大学 The photovoltaic system MPPT methods of observation algorithm are disturbed based on ant group optimization and variable step
CN118410995A (en) * 2024-07-01 2024-07-30 四川省林业和草原调查规划院(四川省林业和草原生态环境监测中心) Lin Caoguang complementary photovoltaic panel plate distribution method and system based on forest grass growth requirement
CN118410995B (en) * 2024-07-01 2024-08-30 四川省林业和草原调查规划院(四川省林业和草原生态环境监测中心) Lin Caoguang complementary photovoltaic panel plate distribution method and system based on forest grass growth requirement

Similar Documents

Publication Publication Date Title
CN107957743B (en) A kind of photovoltaic maximum power point method for tracing
CN102651087A (en) Maximum power point-tracking photovoltaic system based on ant colony-artificial immune hybrid optimization algorithm
Scognamiglio et al. Photovoltaics in net zero energy buildings and clusters: Enabling the smart city operation
Safarudin et al. Maximum power point tracking algorithm for photovoltaic system under partial shaded condition by means updating β firefly technique
CN105207606A (en) DMPPT photovoltaic power generation module based on time-sharing self-adaptive MCT algorithm
Javed et al. A comparative study of maximum power point tracking techniques for solar systems
CN104699166A (en) Multipath MPPT device based on particle swarm optimization
Shafaati Shemami et al. Fuzzy control assisted vehicle-to-home (V2H) energy management system
Rao et al. A generalized mppt controlled dc-dc boost converter for pv system connected to utility grid
Shao et al. A novel PV array connection strategy with PV-buck module to improve system efficiency
Safarudin et al. Combining simplified firefly and modified P&O algorithm for maximum power point tracking of photovoltaic system under partial shading condition
CN102593217A (en) Intelligent photovoltaic assembly capable of preventing hot spot
CN109687428A (en) Provide multiple forms of energy to complement each other distributed energy microgrid running optimizatin control system and method based on analytic hierarchy process (AHP)
CN105425894B (en) A kind of photovoltaic system MPPT maximum power point tracking optimization method
Taherkhani et al. A GMPPT design using the following optimization algorithm for PV systems
Muhammad et al. Experimental study on modified GOA-MPPT for PV system under mismatch conditions
Mary et al. A dual DC output power supply for a stand-alone photovoltaic system
Chen et al. Optimal control for a wind-hydrogen-fuel cell multi-vector energy system
CN202997941U (en) Novel photovoltaic power generation system of energy-feedback power unit
CN108233373B (en) Probability harmonic analysis method considering weather scene for distributed photovoltaic access power distribution network
CN202906789U (en) A distributed photovoltaic system
CN106352546A (en) Photovoltaic air energy water heater system
Aijaz et al. Optimal control of a two-area hybrid microgrid system incorporating electric vehicles
Sagayaraj et al. IoT Monitoring for Hybrid Photovoltaic Fuel Cell System
CN108549456A (en) Photovoltaic array MPPT control method based on a flying moth darts into the fire 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
WD01 Invention patent application deemed withdrawn after publication
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20120829