Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Electrical Engineering
Erschienen in: Electrical Engineering 3/2017

17.10.2016 | Original Paper

Simulation of global MPPT based on teaching–learning-based optimization technique for partially shaded PV system

verfasst von: Hegazy Rezk, Ahmed Fathy

Erschienen in: Electrical Engineering | Ausgabe 3/2017

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

The power against voltage curve for PV power system during shadow condition contains number of local maximum power points (MPPs) and only one global. The classical maximum power point tracking (MPPT) algorithms are designed to follow the global MPP, but they stuck around local MPPs such as fuzzy logic controller (FLC). Therefore, A global MPPT based on teaching–learning-based optimization (TLBO) algorithm has been presented in this paper. The performance of PV system under abnormal conditions such as partial shading has been improved. TLBO algorithm is simple computational steps and faster convergence to optimal solution. A comprehensive assessment of TLBO-based tracker is carried out against FLC and particle swarm optimization (PSO) techniques for same conditions. Six different partial shading patterns have been employed to investigate TLBO performance using MATLAB/Simulink. The parameters of comparison include the tracking speed and overall tracking efficiency. The results confirm that TLBO-based tracker exactly convergence to global MPP under different studied cases. TLBO has best performance compared to the other studied techniques. The tracking speed is increased using TLBO-based tracker; the average tracking time of global MPP is reduced by more than 23.8 % compared with PSO in all studied different partial shading patterns.
Vorheriger Artikel Implementation of a modified P&O-MPPT algorithm adapted for varying solar radiation conditions
Nächster Artikel Prediction of the static unbalanced magnetic pull in synchronous surface mounted permanent magnet machines

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Literatur
1.
Bader Alajmi N, Khaled Ahmed H (2013) A maximum power point tracking technique for partially shaded photovoltaic systems in microgrids. IEEE Trans Ind Electron 60(4):3195–1596
2.
Eltamaly AM (2010) Modeling of fuzzy logic controller for photovoltaic maximum power point tracker. In: Solar future 2010 conf. proc., Istanbul, Turkey, pp 4–9
3.
Ahmed J, Salam Z (2014) A maximum power point tracking (MPPT) for PV system using cuckoo search with partial shading capability. Appl Ener 119:118–130CrossRef
4.
Liu Y et al (2012) A particle swarm optimization based maximum power point tracking algorithm for PV systems operating under partially shaded conditions. IEEE Trans Energy Convers 27(4):1027–1035
5.
Sarvi M, Ahmadi S, Abdi S (2015) A PSO-based maximum power point tracking for photovoltaic systems under environmental and partially shaded conditions. Prog Photovolt Res Appl 23:201–214CrossRef
6.
Ma J et al (2013) Low-cost global MPPT scheme for photovoltaic systems under partially shaded conditions. In: IEEE international symposium on circuits and systems (ISCAS), pp 245–248
7.
Tey KS, Mekhilef S, Yang H, Chuang M (2014) A differential evolution based MPPT method for photovoltaic modules under partial shading conditions. Int J Photoener 2014:1–10CrossRef
8.
Daraban S, Petreus D, Morel C (2013) A novel global MPPT based on genetic algorithms for photovoltaic systems under the influence of partial shading. In: IECON 2013-39\(^{\rm th}\) annual conference of the IEEE, pp 1490–1495
9.
Phimmasone V, Kondo Y, Kamejima T, Miyatake M (2010) Evaluation of extracted energy from PV with PSO-based MPPT against various types of solar irradiation changes. In: IEEE international conference on electrical machines and systems, Korea, pp 487–492
10.
Jiang L, Maskell D, Patra J (2013) A novel ant colony optimization-based maximum power point tracking for photovoltaic systems under partially shaded conditions. Energy Build 58:227–236CrossRef
11.
Ishaque K, Salam Z, Amjad M, Mekhilef S (2012) An improved particle swarm optimization (PSO)-based MPPT for PV with reduced steady-state oscillation. IEEE Trans Power Electron 27(8):3627–3638CrossRef
12.
Sundareswaran K, Peddapati S, Palani S (2014) MPPT of PV systems under partial shaded conditions through a colony of flashing fireflies. IEEE Trans Energy Convers 29(2):463–472CrossRef
13.
Sundareswaran K, kumar V, Palani S (2015) Application of a combined particle swarm optimization and perturb and observe method for MPPT in PV systems under partial shading conditions. Renew Energy 75:308–317CrossRef
14.
Kulaksız AA, Akkaya R (2012) A genetic algorithm optimized ann-based MPPT algorithm for a stand-alone PV system with induction motor drive. Solar Energy 86(9):2366–2375CrossRef
15.
Paraskevadaki EV, Papathanassiou SA (2011) Evaluation of MPP voltage and power of mc-Si PV modules in partial shading conditions. IEEE Trans Energy Convers 26(3):923–932CrossRef
16.
Tajuddin MFN, Arif MS, Ayob SM, Salam Z (2015) Perturbative methods for maximum power point tracking (MPPT) of photovoltaic (PV) systems: a review. Int J Energy Res 39(12):1153–1178CrossRef
17.
Besheer AH, Adly M (2012) Ant colony system based PI maximum power point tracking for stand-alone photovoltaic system. In: 2012 IEEE international conference on industrial technology (ICIT), pp 693–698
18.
Lei M, Yaojie S, Yandan L, Zhifeng B, Liquin T, Jieqiong S (2011) A high performance MPPT control method. Int Conf Mater Renew Energy Environ (ICMREE) 1:195–199CrossRef
19.
Kazmi S, Goto H, Ichinokura O, Guo H (2009) An improved and very efficient MPPT controller for PV systems subjected to rapidly varying atmospheric conditions and partial shading. In: Power engineering conference (AUPEC 2009), pp 1–6
20.
Kobayashi K, Takano I, Sawada Y (2006) A study of a two stage maximum power point tracking control of a photovoltaic system under partially shaded insolation condition. Solar Energy Mater Solar cells 90:2975–2988CrossRef
21.
Sundareswaran K et al (2015) Enhanced energy output from a PV system under partial shaded conditions through artificial bee colony. IEEE Trans Sustain Energy 6(1):198–209MathSciNetCrossRef
22.
Chen K, Tian S, Cheng Y, Bai L (2014) An improved MPPT controller for photovoltaic system under partial shading condition. IEEE Trans Sustain Energy 5(3):978–985CrossRef
23.
Rezk H, Eltamaly AM (2015) A comprehensive comparison of different MPPT techniques for photovoltaic systems. Solar Energy 112:1–11CrossRef
24.
Boutasseta N (2012) PSO-PI based control of photovoltaic arrays. Int J Comput Appl 48(17):36–40
25.
Mirhassaniet SM et al (2015) An improved particle swarm optimization based maximum power pointtracking strategy with variable sampling time. Electr Power Energy Syst 64:761–770CrossRef
26.
Ishaque K, Salam Z (2013) A deterministic particle swarm optimization maximum power point tracker for photovoltaic system under partial shading condition. IEEE Trans Ind Electron 60(8):3195–3205
27.
Gounden NA, Sabitha Peter A, Nallandula H, Krithiga S (2009) Fuzzy logic controller with MPPT using line-commutated inverter for three-phase grid-connected photovoltaic systems. Renew Energy J 34:909–915CrossRef
28.
Ben Salah C, Chaabenea M, Ben Ammara M (2008) Multi-criteria fuzzy algorithm for energy management of a domestic photovoltaic panel. Renew Energy 33:993–1001CrossRef
29.
Karlis AD, Kottas TL, Boutalisb YS (2007) A novel maximum power point tracking method for PV systems using fuzzy cognitive networks. Electr Power Syst Res 3–4:315–327CrossRef
30.
Khaehintung N, Wiangtong T, Sirisuk P (2006) FPGA implementation of MPPT using variable step-size P&O algorithm for PV applications. In: International symposium on digital object identifier, ISCIT, pp 212–215
31.
Rao R, Patel V (2013) an improved teaching learning based optimization algorithm for solving unconstrained optimization problems. Scientia Iranica 20(3):710–720
32.
Rao R, Savsani V, Vakharia D (2011) Teaching-learning-based optimization: a novel method for constrained mechanical design optimization problems. Comput Aided Des 2011(43):303–315CrossRef
33.
Pawar P, Rao R (2013) Parameter optimization of machining processes using teaching–learning-based optimization algorithm. Int J Adv Manuf Technol 67(5):995–1006CrossRef
34.
Cerpinsek M, Liu S, Mernik L (2012) A note on teaching learning based optimization algorithm. Inf Sci 212:79–93CrossRef
35.
LA361K51S-multi-crystalline photovoltaic module datasheet
Metadaten
Titel
Simulation of global MPPT based on teaching–learning-based optimization technique for partially shaded PV system
verfasst von
Hegazy Rezk
Ahmed Fathy
Publikationsdatum
17.10.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Electrical Engineering / Ausgabe 3/2017
Print ISSN: 0948-7921
Elektronische ISSN: 1432-0487
DOI
https://doi.org/10.1007/s00202-016-0449-3

Weitere Artikel der Ausgabe 3/2017

Electrical Engineering 3/2017 Zur Ausgabe

Original Paper

Prediction of the static unbalanced magnetic pull in synchronous surface mounted permanent magnet machines

Original Paper

A convergence broadcasting transmission of fixed 4K UHD and mobile HD services through a single terrestrial channel by employing FEF multiplexing technique in DVB-T2

Original Paper

Cycle recovery charging (CRC) methods for single used lead-acid batteries

Original Paper

A robust continuous conduction mode control strategy of switched reluctance generator for wind power plant applications

Original Paper

Robust stator currents sensorless control of stator powers for wind generator based on DFIG and matrix converter

Original Paper

Mean shift densification of scarce data sets in short-term electric power load forecasting for special days

Neuer Inhalt

    Bildnachweise