CN107957743A - A kind of photovoltaic maximum power point method for tracing - Google Patents

A kind of photovoltaic maximum power point method for tracing Download PDF

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CN107957743A
CN107957743A CN201711114897.0A CN201711114897A CN107957743A CN 107957743 A CN107957743 A CN 107957743A CN 201711114897 A CN201711114897 A CN 201711114897A CN 107957743 A CN107957743 A CN 107957743A
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wolf
grey
mutation
iteration
prey
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CN107957743B (en
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石季英
张登雨
薛飞
凌乐陶
乔文
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Tianjin University
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Tianjin University
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05F—SYSTEMS FOR REGULATING ELECTRIC OR MAGNETIC VARIABLES
    • G05F1/00—Automatic systems in which deviations of an electric quantity from one or more predetermined values are detected at the output of the system and fed back to a device within the system to restore the detected quantity to its predetermined value or values, i.e. retroactive systems
    • G05F1/66—Regulating electric power
    • G05F1/67—Regulating electric power to the maximum power available from a generator, e.g. from solar cell
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy
    • Y02E10/56—Power conversion systems, e.g. maximum power point trackers

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  • Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
  • Sustainable Energy (AREA)
  • Power Engineering (AREA)
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  • Electromagnetism (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Automation & Control Theory (AREA)
  • Control Of Electrical Variables (AREA)

Abstract

The present invention relates to a kind of photovoltaic maximum power point method for tracing, including：Choose grey wolf initial position；After photovoltaic system stabilization, the output current and output voltage of the corresponding photovoltaic array of each Xi (n) are measured, and calculate corresponding power P i (n)；Maximum corresponding two grey wolves of two Pi (n) are set to wolf king, and record the position of the wolf king；The grey wolf position Xi (n+1) of iteration n+1 times is determined by grey wolf algorithm；When two wolf kings obtain the approximate location of prey, it is believed that be the approximate location for being found that prey, be directly entered at this time by the local search of golden ratio algorithm performs, otherwise enter back into local search until reaching maximum iteration；Whether detection external environment condition undergos mutation.

Description

A kind of photovoltaic maximum power point method for tracing
Technical field
The present invention relates to photovoltaic generation field of engineering technology, more particularly to a kind of maximum power point tracking method.
Background technology
To alleviate international energy crisis, reduce environmental pollution, regenerative resource is all being greatly developed in countries in the world.Various In regenerative resource, solar energy is considered as a kind of inexhaustible, nexhaustible important eco-friendly power source.In order to efficiently utilize Solar energy carries out photovoltaic generation, and maximum power point tracking (maximum power point tracking, MPPT) technology can not Or lack.The main problem that MPPT technique faces can be attributed at 2 points：First, output characteristic curve is by light intensity, temperature, load Influenced etc. factor, output characteristic curve is in non-linear.Second, to avoid hot spot effect must the inverse parallel one in each photovoltaic panel A bypass diode, but multimodal state is presented in the case of part is covered which results in output characteristic curve.
Traditional MPPT algorithm such as perturbation observation method and conductance increment method etc. are simple in structure but may be absorbed in local extremum, Face complicated if intelligent algorithm such as particle cluster algorithm, glowworm swarm algorithm, wolf pack searching algorithm, cuckoo algorithm etc. and calculate The problems such as time is longer, the MPPT methods based on model are then needed by the cumbersome derivation of equation.
The content of the invention
The object of the present invention is to provide a kind of photovoltaic maximum power point method for tracing, which can have concurrently and chase after Track speed and tracking efficiency, and can solve the problems, such as that tradition is restarted method of discrimination and faced under specific circumstances and restart unsuccessfully. Concrete technical scheme is as follows：
A kind of photovoltaic maximum power point method for tracing, comprises the following steps：
1) N number of point is chosen in duty cycle [0,1], as grey wolf initial position；
2) current iteration is set as nth iteration, and the position of grey wolf is Xi(n),i∈[1,2,……N]；
3) after photovoltaic system stabilization, each X is measuredi(n) output current and output voltage of corresponding photovoltaic array, and Calculate corresponding power Pi(n)；
4) to the Pi(n) it is ranked up；
5) two maximum Pi(n) corresponding two grey wolves are set to wolf king, and record the position of the wolf king；
6) the grey wolf position X of iteration n+1 times is determined by improving grey wolf algorithmi(n+1), two improved in grey wolf algorithm The decision weights coefficient of wolf king is adjusted with the process dynamics of hunting, i.e.,With Wherein W1And W2The decision weights coefficient of respectively described two wolf kings, n are iterations, nmaxFor maximum iteration；
7) when following the trail of, grey wolf can be jumped on the position that prey is likely to occur；And when two wolf kings obtain the big of prey When causing position, it is believed that it is the approximate location for being found that prey, is directly entered at this time by the local search of golden ratio algorithm performs, Otherwise local search is entered back into until reaching maximum iteration；
8) whether detection external environment condition undergos mutation：Default mutation threshold epsilon0If P0And P1It is before being mutated and after mutation respectively Power, U0And U1It is the preceding voltage with after mutation of mutation respectively, μ is set to 0.001 to prevent that zero is female, judges | (P1-P0)/ (U1-U0+ μ) | ＞ ε0, if satisfied, then thinking to undergo mutation, restarting algorithm follows the trail of maximum power point, and otherwise system stabilization exists In global optimum's duty cycle.
Brief description of the drawings
Fig. 1 is the maximum power point tracking system using Boost circuit
Fig. 2 hybrid algorithm flow charts
Fig. 3 expands initial ranging interval diagram
Photovoltaic array P-D curves when Fig. 4 particular lights are mutated
Embodiment
In order to quickly and accurately track global maximum power point, the present invention proposes that a kind of improvement grey wolf-golden ratio that is based on is mixed Hop algorithm (modified grey wolf optimization and golden-section optimization, MGWO- GSO mixing control method).First using improved grey wolf algorithm (modified grey wolf optimization, MGWO global search) is carried out to determine optimal partial；Then, using golden ratio partitioning algorithm (golden-section Optimization, GSO) carry out local search.Different Strategies are used in different phase, realize the optimization of control effect.It is former The decision weights of wolf king remain unchanged in beginning grey wolf algorithm, and it is slow that this may cause between wolf king to produce decision-making in later stage decision-making It is stagnant.For the decision weights of wolf king with the propulsion dynamic change of hunting, this causes grey wolf to have hunting mesh definitely in the present invention Mark.Also, the present invention propose a kind of new based on the class P-U slopes of curve restart method of discrimination should to strengthen MPPT systems Reliability during to illuminance abrupt variation.
In order to make the foregoing objectives, features and advantages of the present invention clearer and more comprehensible, below in conjunction with the accompanying drawings to the present invention Embodiment be described in detail.The present invention uses the maximum power point tracking system of Boost circuit as shown in Figure 1 System, photovoltaic array use 3 × 1 photovoltaic arrays, switching frequency f=50kHz, C1=100 μ F, L=0.5mH, C2=100 μ F, Rload =40 Ω.The hybrid algorithm flow chart is as shown in Figure 2, and concrete scheme is as follows：
The present invention uses direct Duty ratio control mode, N number of point is chosen in duty cycle [0,1] first, as at the beginning of grey wolf Beginning position Xi(n), i ∈ [1,2 ... N], n represent iterations.By global maximum power in maximum power point tracking algorithm Point is considered as prey, and the quality of prey is replaced with watt level；
N number of point is chosen in duty cycle [0,1], as grey wolf initial position Xi(n), i ∈ [1,2 ... N], n represent to change Generation number.Global maximum power point is considered as prey in maximum power point tracking algorithm, and the quality power of prey is big It is small to replace；
After photovoltaic system stabilization, each X is measuredi(n) the output current I of corresponding photovoltaic arrayPVWith output voltage VPV, And calculate corresponding power Pi(n)；
To the Pi(n) it is ranked up, and i ∈ [1,2 ... N], n represents iterations；
Two maximum Pi(n) corresponding two grey wolves are set to wolf king, and record the position of the wolf kingWith
The grey wolf position X of iteration n+1 times is determined by improving grey wolf algorithmi(n+1), two improved in grey wolf algorithm The decision weights coefficient of wolf king is adjusted with the process dynamics of hunting, i.e.,With Wherein W1And W2The decision weights coefficient of respectively described two wolf kings, n are iterations, nmaxFor maximum iteration；
During tracking, grey wolf can be jumped on the position that prey is likely to occur.And when two wolf kings obtain prey substantially During position, it is believed that be the approximate location for being found that prey, i.e. d1-2≤ 1/80N, in formula：d1-2It is the distance between two head wolves, N It is series board subnumber.It is directly entered at this time by the local search of golden ratio algorithm performs, otherwise until reaching greatest iteration time Number enters back into local search.And the position of two head wolves is set to the initial ranging section of golden ratio partitioning algorithm, it is possible to Global optimum can be run into not in the situation in initial ranging section.So initial ranging siding-to-siding block length is expanded into desiTo avoid upper The occurrence of stating.desiSize be desi=1/40N, direction are as shown in Figure 3；
Whether detection external environment condition undergos mutation, and after external condition changes, global power maximum will become Change, at this moment will restart algorithm to follow the trail of new global power maximum.Power variation rate restarts before and after being mutated based on detection Differentiation mechanism is most common to restart one of method of discrimination：|(P1-P0)/P0| ＞ τ0, in formula：P0And P1It is that mutation is preceding and prominent respectively Power after change, τ0To be mutated threshold value.But there is the problem of restarting unsuccessfully in this method, such as under the particular case of similar Fig. 4 Changed power very little before and after illuminance abrupt variation is so that described restart method of discrimination and can not detect, i.e. τ ＜ τ0.By conductance increment The inspiration of method, the present invention are restarted method of discrimination and are strengthened the reliability of MPPT, the novel heavy using the new of the P-U slopes of curve Method of discrimination is opened to be represented by：|(P1-P0)/(U1-U0+ μ) | ＞ ε0.In formula：U0And U1It is the preceding electricity with after mutation of mutation respectively Pressure, μ are set to 0.001 to prevent that zero is female, ε0It is threshold value, ε in the present invention0Elect 2 as.New restart method of discrimination meter through described It can be obtained after calculation, ε is 3.83 in Fig. 4, has been enough to detect external condition that there occurs acute variation.

Claims (1)

1. a kind of photovoltaic maximum power point method for tracing, comprises the following steps：
1) N number of point is chosen in duty cycle [0,1], as grey wolf initial position；
2) current iteration is set as nth iteration, and the position of grey wolf is Xi(n),i∈[1,2,……N]；
3) after photovoltaic system stabilization, the output current and output voltage of the corresponding photovoltaic array of each Xi (n) are measured, and calculate Corresponding power Pi(n)；
4) to the Pi(n) it is ranked up.
5) two maximum Pi(n) corresponding two grey wolves are set to wolf king, and record the position of the wolf king；
6) the grey wolf position X of iteration n+1 times is determined by improving grey wolf algorithmi(n+1), improvements are：The decision-making power of two wolf kings Weight coefficient is adjusted with the process dynamics of hunting, i.e.,With Wherein W1And W2The decision weights coefficient of respectively described two wolf kings, n are iterations, nmaxFor maximum iteration；
7) when following the trail of, grey wolf can be jumped on the position that prey is likely to occur, and when two wolf kings obtain the substantially position of prey When putting, it is believed that be the approximate location for being found that prey, be directly entered at this time by the local search of golden ratio algorithm performs, otherwise Local search is entered back into until reaching maximum iteration；
8) whether detection external environment condition undergos mutation：Default mutation threshold epsilon0If P0And P1It is the preceding work(with after mutation of mutation respectively Rate, U0And U1It is the preceding voltage with after mutation of mutation respectively, μ is set to 0.001 to prevent that zero is female, judges | (P1-P0)/(U1-U0+ μ) | ＞ ε0, if satisfied, then think to undergo mutation, restarting algorithm tracking maximum power point, otherwise system stabilization it is global most In excellent duty cycle.
CN201711114897.0A 2017-11-13 2017-11-13 A kind of photovoltaic maximum power point method for tracing Expired - Fee Related CN107957743B (en)

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CN108549456A (en) * 2018-05-10 2018-09-18 天津大学 Photovoltaic array MPPT control method based on a flying moth darts into the fire algorithm
CN108646849A (en) * 2018-07-11 2018-10-12 东北大学 Based on the maximum power point of photovoltaic power generation system tracking for improving wolf pack algorithm
CN113342124A (en) * 2021-06-11 2021-09-03 中国电建集团华东勘测设计研究院有限公司 Photovoltaic MPPT method based on improved wolf optimization algorithm
CN114442725A (en) * 2022-02-16 2022-05-06 东南大学 Photovoltaic maximum power point tracking method, storage medium and tracking device
CN115509294A (en) * 2022-09-16 2022-12-23 哈尔滨工程大学 Photovoltaic array maximum power tracking method and system
CN116301183A (en) * 2023-03-06 2023-06-23 哈尔滨工业大学 Maximum power point tracking method of space power generation system

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Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108549456A (en) * 2018-05-10 2018-09-18 天津大学 Photovoltaic array MPPT control method based on a flying moth darts into the fire algorithm
CN108646849A (en) * 2018-07-11 2018-10-12 东北大学 Based on the maximum power point of photovoltaic power generation system tracking for improving wolf pack algorithm
CN113342124A (en) * 2021-06-11 2021-09-03 中国电建集团华东勘测设计研究院有限公司 Photovoltaic MPPT method based on improved wolf optimization algorithm
CN113342124B (en) * 2021-06-11 2022-08-09 中国电建集团华东勘测设计研究院有限公司 Photovoltaic MPPT method based on improved wolf optimization algorithm
CN114442725A (en) * 2022-02-16 2022-05-06 东南大学 Photovoltaic maximum power point tracking method, storage medium and tracking device
CN114442725B (en) * 2022-02-16 2023-09-05 东南大学 Photovoltaic maximum power point tracking method, storage medium and tracking device
CN115509294A (en) * 2022-09-16 2022-12-23 哈尔滨工程大学 Photovoltaic array maximum power tracking method and system
CN115509294B (en) * 2022-09-16 2023-08-01 哈尔滨工程大学 Photovoltaic array maximum power tracking method and system
CN116301183A (en) * 2023-03-06 2023-06-23 哈尔滨工业大学 Maximum power point tracking method of space power generation system
CN116301183B (en) * 2023-03-06 2023-09-08 哈尔滨工业大学 Maximum power point tracking method of space power generation system

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