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Güneş Panellerinde Hibrit ve YSA Tabanlı Algoritmalar ile Güç Takibi

Year 2018, , 258 - 266, 23.10.2018
https://doi.org/10.17780/ksujes.444418

Abstract

Bu çalışmada, ilk olarak panel çıkış akım - gerilim büyüklüklerini
kullanan IC algoritmasını bulanık mantık yardımıyla değişken adım aralıklarına
sahip bir hibrit algoritma ile doğrudan MPPT yapılmaktadır. İkinci olarak çeşitli
sıcaklık ve radyasyon büyüklükleri ile YSA kullanılarak panel modeli elde
edilmiştir. Uygulamada bu model kullanılarak PID kontrolör aracılığıyla MPPT
yapılmıştır. Son olarak da bu iki algoritmanın değişken radyasyon, sıcaklık, yük
ve ön görülmeyen şartlar için karşılaştırmalı performansları benzetim ortamında
incelenmiştir.

References

  • Agwa A. M., Mahmoud I. Y. (2017) Photovoltaic Maximum Power Point Tracking by Artificial Neural Networks, Journal of Multidisciplinary Engineering Science and Technology (JMEST), Vol. 4 Issue 1, January.
  • Bouraiou A.,Hamoudaa M.,Chakerb A. ,Sadoka M.,Mostefaouia M.,Lachtara S. (2015) Modeling and Simulation of Photovoltaic Module and array based on One and Two Diode Model Using Matlab/Simulink, ScienceDirect,864 – 877
  • Bounechba H., Bouzid A.,Nabti K. and Benalla H. (2014) Comparison of perturb & observe and fuzzy logic in Maximum power point tracker for PV systems, The International Conference on Technologies and Materials for Renewable Energy.
  • Forsyth A.J. and Mollov S.V. (1998) Modelling and control of DC-DC converters,IEEE Power Engineering Journal, pp. 229-236.
  • Hasan M.,Mekhilef S. and Metselaar I. (2013) Photovoltaic System Modeling with Fuzzy Logic Based Maximum Power Point Tracking Algorithm, Hindawi Publishing Corporation International Journal of Photoenergy Volume.
  • Ishaque K., Salam Z. (2013) A review of maximum power point tracking techniques of PV system for uniform insolation and partial shading condition ,Renewable and Sustainable Energy Reviews, 475–488.
  • 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 Transactıons On Power Electronıcs, Vol. 27, No. 8, August.
  • Kumar M., Kapoor S.R., Nagar R.,Verma A. (2015) Comparison between IC and Fuzzy LogicMPPT Algorithm Based Solar PV System using Boost Converter,International Journal of Advanced Research in Electrical,Electronics and Instrumentation Engineering, Vol. 4, Issue 6, June.
  • Liang-Rui Chen, Chih-Hui Tsai, Yuan-Li Lin, and Yen-Shin Lai, (2010) A Biological Swarm Chasing Algorithm for Tracking the PV Maximum Power Point”, IEEE Transactıons On Energy Conversıon, Vol. 25, No. 2, June.
  • Load R. B. A., Zobaa A.F. (2017) A Novel MPPT Algorithm Based on Particle Swarm Optimization for Photovoltaic Systems, IEEE Transactıons On Sustaınable Energy, Vol. 8, No. 2, Aprıl.
  • Middlebook R.D. and Cuk S. (1977) A General Unified Approach to Modeling Switching-Converter Power Stages International Journal of Electronics,vol. 42, pp. 521-550, June.
  • Macaulay J., Zhou Z. (2018) A Fuzzy Logical-Based Variable Step Size P&O MPPT Algorithm for Photovoltaic System, Energies, Vol-11,1340,May.
  • Nabipour M.,Razaz M.,Seifossadat S.G.H.,Mortazavi S.S. (2017) A new MPPT scheme based on a novel fuzzy approach, Renewable and Sustainable Energy Reviews 74, pp.1147–1169.
  • Radjai T.,Rahmani L., Mekhilef S., Gaubert J.P. (2014) Implementation of a modified incremental conductance MPPTalgorithm with Direct control based on a fuzzy görev süresichange estimator using Dspace, ScienceDirect, 325–337.
  • Radjaı T., Rahmanı L., Gaubert P., Gassab S. (2014) Fuzzy Logic Variable Step of P&O MPPT with Direct Control Method Using Cuk Converter, ELECTRIMACS, 19th –22nd May,Valencia, Spain,.
  • Swati S., Lini M., Shimi S.L. (2013) Design and Simulation of Intelligent Control MPPT Technique for PV Module Using MATLAB SIMSCAPE, International Journal of Advanced Research in Electrical,Electronics and Instrumentation Engineering.
Year 2018, , 258 - 266, 23.10.2018
https://doi.org/10.17780/ksujes.444418

Abstract

References

  • Agwa A. M., Mahmoud I. Y. (2017) Photovoltaic Maximum Power Point Tracking by Artificial Neural Networks, Journal of Multidisciplinary Engineering Science and Technology (JMEST), Vol. 4 Issue 1, January.
  • Bouraiou A.,Hamoudaa M.,Chakerb A. ,Sadoka M.,Mostefaouia M.,Lachtara S. (2015) Modeling and Simulation of Photovoltaic Module and array based on One and Two Diode Model Using Matlab/Simulink, ScienceDirect,864 – 877
  • Bounechba H., Bouzid A.,Nabti K. and Benalla H. (2014) Comparison of perturb & observe and fuzzy logic in Maximum power point tracker for PV systems, The International Conference on Technologies and Materials for Renewable Energy.
  • Forsyth A.J. and Mollov S.V. (1998) Modelling and control of DC-DC converters,IEEE Power Engineering Journal, pp. 229-236.
  • Hasan M.,Mekhilef S. and Metselaar I. (2013) Photovoltaic System Modeling with Fuzzy Logic Based Maximum Power Point Tracking Algorithm, Hindawi Publishing Corporation International Journal of Photoenergy Volume.
  • Ishaque K., Salam Z. (2013) A review of maximum power point tracking techniques of PV system for uniform insolation and partial shading condition ,Renewable and Sustainable Energy Reviews, 475–488.
  • 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 Transactıons On Power Electronıcs, Vol. 27, No. 8, August.
  • Kumar M., Kapoor S.R., Nagar R.,Verma A. (2015) Comparison between IC and Fuzzy LogicMPPT Algorithm Based Solar PV System using Boost Converter,International Journal of Advanced Research in Electrical,Electronics and Instrumentation Engineering, Vol. 4, Issue 6, June.
  • Liang-Rui Chen, Chih-Hui Tsai, Yuan-Li Lin, and Yen-Shin Lai, (2010) A Biological Swarm Chasing Algorithm for Tracking the PV Maximum Power Point”, IEEE Transactıons On Energy Conversıon, Vol. 25, No. 2, June.
  • Load R. B. A., Zobaa A.F. (2017) A Novel MPPT Algorithm Based on Particle Swarm Optimization for Photovoltaic Systems, IEEE Transactıons On Sustaınable Energy, Vol. 8, No. 2, Aprıl.
  • Middlebook R.D. and Cuk S. (1977) A General Unified Approach to Modeling Switching-Converter Power Stages International Journal of Electronics,vol. 42, pp. 521-550, June.
  • Macaulay J., Zhou Z. (2018) A Fuzzy Logical-Based Variable Step Size P&O MPPT Algorithm for Photovoltaic System, Energies, Vol-11,1340,May.
  • Nabipour M.,Razaz M.,Seifossadat S.G.H.,Mortazavi S.S. (2017) A new MPPT scheme based on a novel fuzzy approach, Renewable and Sustainable Energy Reviews 74, pp.1147–1169.
  • Radjai T.,Rahmani L., Mekhilef S., Gaubert J.P. (2014) Implementation of a modified incremental conductance MPPTalgorithm with Direct control based on a fuzzy görev süresichange estimator using Dspace, ScienceDirect, 325–337.
  • Radjaı T., Rahmanı L., Gaubert P., Gassab S. (2014) Fuzzy Logic Variable Step of P&O MPPT with Direct Control Method Using Cuk Converter, ELECTRIMACS, 19th –22nd May,Valencia, Spain,.
  • Swati S., Lini M., Shimi S.L. (2013) Design and Simulation of Intelligent Control MPPT Technique for PV Module Using MATLAB SIMSCAPE, International Journal of Advanced Research in Electrical,Electronics and Instrumentation Engineering.
There are 16 citations in total.

Details

Primary Language Turkish
Subjects Electrical Engineering
Journal Section Research Articles
Authors

Ayhan Özdemir

Okan Güngör 0000-0001-5258-1765

Publication Date October 23, 2018
Submission Date July 17, 2018
Published in Issue Year 2018

Cite

APA Özdemir, A., & Güngör, O. (2018). Güneş Panellerinde Hibrit ve YSA Tabanlı Algoritmalar ile Güç Takibi. Kahramanmaraş Sütçü İmam Üniversitesi Mühendislik Bilimleri Dergisi, 21(3), 258-266. https://doi.org/10.17780/ksujes.444418