A Novel Global MPP Tracking of Photovoltaic System based on Whale Optimization Algorithm

*Cherukuri Santhan Kumar  -  JNT University Kakinada, India
Rayapudi Srinivasa Rao  -  JNT University Kakinada, India
Published: 4 Nov 2016.
Open Access Copyright (c) 2016 International Journal of Renewable Energy Development

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Article Info
Section: Original Research Article
Language: EN
Statistics: 2482 3021

To harvest maximum amount of solar energy and to attain higher efficiency, photovoltaic generation (PVG) systems are to be operated at their maximum power  point (MPP) under both variable climatic and partial shaded condition (PSC). From literature most of conventional MPP tracking (MPPT) methods are able to guarantee MPP successfully under uniform shading condition but fails to get global MPP as they may trap at local MPP under PSC, which adversely deteriorates the efficiency of Photovoltaic Generation (PVG) system. In this paper a novel MPPT based on Whale Optimization Algorithm (WOA) is proposed to analyze analytic modeling of PV system considering both series and shunt resistances for MPP tracking under PSC. The proposed algorithm is tested on 6S, 3S2P and 2S3P Photovoltaic array configurations for different shading patterns and results are presented. To compare the performance, GWO and PSO MPPT algorithms are also simulated and results are also presented.  From the results it is noticed that proposed MPPT method is superior to other MPPT methods with reference to accuracy and tracking speed.

Article History: Received July 23rd 2016; Received in revised form September 15th 2016; Accepted October 1st 2016; Available online

How to Cite This Article: Kumar, C.H.S and Rao, R.S. (2016) A Novel Global MPP Tracking of Photovoltaic System based on Whale Optimization Algorithm. Int. Journal of Renewable Energy Development, 5(3), 225-232.


Keywords: Maximum power point tracking; Partial shaded condition; Photovoltaic generation system; Single diode model; Whale optimization algorithm

Article Metrics:

  1. Kamarzaman, N.A. & Tan, C.W. (2014) A comprehensive review of maximum power point tracking algorithms for photovoltaic systems. Renewable & Sustainable Energy Rev, 32, 585-598.
  2. Reisi, A.R., Moradi, M.H. & Jamasb, S. (2013) Classification and comparison of maximum power point tracking techniques for photovoltaic system: A review. Renewable & Sustainable Energy Rev, 19, 433-443, 2013.
  3. Silvestre, S., Boronat, A. & Chouder, A. (2009) Study of bypass diodes configuration on PV modules. Applied Energy, 86, 1632-1640.
  4. Ishaque, K. & Salam, Z. (2013) A review of maximum power point tracking techniques of PV system for uniform isolation and partial shading condition. Renewable & Sustainable Energy Rev, 19, 475-488.
  5. Zainal, Salam., Jubaer, Ahmed. & Beny, S.Merugu. (2013) The application of soft computing methods for MPPT of PV system: A technological and status review. Applied Energy, 107, 135-148.
  6. Ishaque, K., Salam, Z., Amjad, M. & Mekhilef, S. (2012) An improved particle swarm optimization (PSO)-based MPPT for PV with reduced steady state oscillations. IEEE Trans Power Electron, 27(8), 3627-3637.
  7. Ishaque, K., Salam, Z., Shamsudin, A. & Amjad, M. (2012) A direct control based maximum power point tracking method for photovoltaic system under partial shading conditions using particle swarm optimization algorithm. Applied Energy, 99, 414-422.
  8. Liu, Y.H., Huang, S.C., Huang, J.W. & Liang, W.C. (2012), “A particle swarm optimization based maximum power point tracking algorithm for PV systems operating under partially shaded conditions. IEEE Trans Energy Conv, 27(4), 1027-1035.
  9. Benyoucef, A.S., Chouder, A., Kara, K., Silvestre, S. & Sahed, O.A. (2015) Artificial bee colony based algorithm for maximum power point tracking (MPPT) for PV systems operating under partial shaded conditions. Applied Soft Computing, 32, 38-48.
  10. Sundareswaran, K., Sankar, P., Nayak, P.S.R., Simon, S.P. & Palani, S.(2015) Enhanced energy output from a PV system under partial shaded conditions through Artificial bee colony. IEEE Trans Sustainable Ener, 6(1), 198-209.
  11. Jiang, L.L., Maskell, D.L. & Patra, J.C. (2013) A novel ant colony optimization based maximum power point tracking for photovoltaic systems under partially shaded condition. Energy & Buildings, 58, 227-236.
  12. Tajuddin, M.F.N., Ayob, S.M, Sala, Z. & Saad, M.S. (2013) Evolutionary based maximum power point tracking technique using differential evolution algorithm. Energy & Buildings, 67, 245-252.
  13. Ahmed, J. & Salam, Z. (2014) A maximum power point tracking (MPPT) for PV system using Cuckoo search with Partial shading capability. Appl Energy, 119, 118-130.
  14. Daraban, S., Petreus, D. & Morel, C. (2014) A novel MPPT algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading. Energy, 74, 374-388.
  15. Sundareswaran, K., Sankar, P. & Sankaran, P. (2014) MPPT of PV systems under partial shaded Conditions through a colony of flashing fireflies. IEEE Trans Ener Conv, 29(2), 463-472.
  16. Satyajit, Mohanty., Bidyadhar, Subudhi. & Pravat, Kumar.Ray. (2016) A new MPPT design using grey wolf optimizer technique for photovoltaic system under partial shading conditions. IEEE Trans on sustainable energy, 7(1), 181-188.
  17. Liu, Y.H., Chen, J.H. & Huang, J.W. (2015) A review of maximum power point tracking techniques for use in partially shaded condition. Renewable & Sustainable Energy Rev, 41, 436-453.
  18. Ahmed, J. & Salam, Z. (2015) A critical evaluation on maximum power point tracking methods for partial shading in PV systems, Renewable & Sustainable Energy Rev, 47, 933-953.
  19. Mirjalili, S. & Lewis, A. (2016) The whale optimization algorithm, Advances in Engg Software, 95, 51-67.
  20. T, Ma., H, Yang. & L, Lu. (2014) Solar photovoltaic system modeling and performance prediction, Renewable & Sustainable Energy Rev, 36, 304-315.
  21. Bader, N.A., Khaled. H.A., Stephen, J.F. & Barry. W.W. (2013) A Maximum power point tracking technique for partially shaded photovoltaic systems in microgrids, IEEE Trans.Ind.Electro, 60(4), 1596-1606.

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