MPSO-MPPT based Single Phase Grid PV System for Power Enhancement


  • Mrs. Ruchi Singh Chauhan M.Tech Scholar, Department of Electrical & Electronics Engineering, Lakshmi Narain College of Technology, Bhopal, M.P, India
  • Mr. Amol Barve Professor, Department of Electrical & Electronics Engineering, Lakshmi Narain College of Technology, Bhopal, M.P, India



The solar power became a challenging area among other renewable energy sources (RESs) since the photovoltaic (PV) systems have the benefits of not inflicting pollution, having low maintenance, and durable operation life. Besides these benefits, a PV system has many drawbacks like significantly higher installation cost comparing some other RESs, and limited potency ranges between 9–18%. The feasibility analyses have a good role so as to work out the foremost appropriate plant site before installation. On the other hand, the operating analyses and enhancements supported maximum power point tracking (MPPT) are quite necessary to extend the harvested total energy. To maximize the performance of solar photovoltaics (PV) under dynamic climatic conditions, MPPT (Maximum Power Point Tracking) controllers are integrated into photovoltaic systems. This research presents a modified PSO algorithm based on the method of tracking the maximum global power point used for photovoltaic systems with variable co-efficient. The modified PSO (MPSO) algorithm is able to trace the maximum global power point faster. This improves the effectiveness of follow-up. Simulation results show that MPSO coordination control methods have better tracking accuracy as compared to P&O as well as PSO MPPT Technique. This also improves the energy efficiency of the photovoltaic system.


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Mohammad Faridun Naim Tajuddin, Shahrin Md Ayob, Zainal Salam and Mohd Sazli Saad, “Evolutionary based maximum power point tracking technique using differential evolution algorithm” Elsevier Energy and Building Volume 67 pp 245 – 252 December 2013.

Liqun Liu and Chunxia Liu, “A Novel Combined Particle Swarm Optimization and Genetic Algorithm MPPT Control Method for Multiple Photovoltaic Arrays at Partial Shading”, ASME, Journal of Engineering Resources Technology Vol. 135 , Publish on line December 2012.

Rodriguez, J.D.B., Franco, E., Petrone, G., “Maximum power point tracking architectures for photovoltaic systems in mismatching conditions: a review”, IET Power Electron., 2014, 7, (6), pp. 1396–1413.

Mehdi Seyedmahmoudian, Ben Horan, Rasoul Rahmani, Aman Maung Than and Alex Stojcevski, “Efficient Photovoltaic System Maximum Power Point Tracking Using a New Technique”, Energies, 2016.

D. Sera, L. Mathe, T. Kerekes, S. Spataru, and R. Teodorescu, “On the perturb-and-observe and incremental conductance MPPT methods for PV systems,” IEEE J. Photovoltaics, Vol. 3, No. 3, pp. 1070–1078, Jul. 2013.

N. Femia, G. Petrone, G. Spagnuolo, and M. Vitelli, “A technique for improving p and o MPPT performances of double-stage grid-connected photovoltaic systems,” IEEE Trans. Ind. Electron., Vol. 56, No. 11, pp. 4473– 4482, Nov. 2009.

Syafaruddin, E. Karatepe and T. Hiyama, “Artificial neural network-polar coordinated fuzzy controller based maximum power point tracking control under partially shaded conditions,” IET Renewable Power Generation, Vol. 3, No. 2, pp. 239–253, Jun. 2009.

Donny Radianto, Dimas Anton Asfani, Syafaruddin, Takashi Hiyama, “Fuzzy Logic Controller Based Maximum Power Point Tracking for Total Cross Tied Photovoltaic Under Partial Shading”, IREACO, Vol 6, No 3, 2013.

Po-Chen Cheng, Bo-Rei Peng, Yi-Hua Liu, Yu-Shan Cheng and Jia-Wei Huang, “Optimization of a Fuzzy-Logic-Control-Based MPPT Algorithm Using the Particle Swarm Optimization Technique”, Energies 2015.

K. L. Lian, J. H. Jhang, I. S. Tian, “A Maximum Power Point Tracking Method Based on Perturb-and-Observe Combined With Particle Swarm Optimization”, IEEE Journal of Photovoltaics, Volume: 4, issue 2, 2014.

Fernando M. de Oliveira, Sérgio A. Oliveira da Silva, Fábio R. Durand, Leonardo P. Sampaio, Vinícius D. Bacon, Leonardo B.G. Campanhol, “Grid-tied photovoltaic system based on PSO MPPT technique with active power line Conditioning”, IET Power Electronics, 2016.

Karol Basi?ski, Bart?omiej Ufnalski, Lech M. Grzesiak, “Hybrid MPPT Algorithm for PV Systems under Partially Shaded Conditions using a Stochastic Evolutionary Search and A Deterministic Hill Climbing”, Power Electronics and Drives, 2(37), No. 2, 2017.

Aakash Shukla, Dr Anula Khare, “Review on Power Electronics Circuits in Renewable Energy Systems”IJO-SCIENCE, Volume III, Issue VI July 2017.

Yau, H.T.; Wu, C.H. Comparison of extremum-seeking control techniques for maximum power point tracking in photovoltaic systems. Energies 2011, 4, 2180–2195.

Sera, D.; Kerekes, T.; Teodorescu, R.; Blaabjerg, F. Improved MPPT Algorithms for Rapidly Changing Environmental Conditions. In Proceedings of Power Electronics and Motion Control, Portoroz, Slovenia, 30 August–1 September 2006; pp. 1614–1619.

Chen, Y.T.; Lai, Z.H.; Liang, R.H. A novel auto-scaling variable step-size MPPT method for a PV system. Sol. Energy 2014, 102, 247–256.

Chih-Chiang Hua and Wei-Yi Kuo, “A new maximum power point tracking method for PV string under PS condition”, IEEE, 2017.

Chao Huang, Zijun Zhang, Long Wang, Zhe Song, Huan Long, “A novel global maximum power point tracking method for PV system using Jaya algorithm”, IEEE, 2017.

Faicel El Aamri, Hattab Maker, Dezso Sera, Sergiu Spataru, Josep M. Guerrero, Azeddine Mouhsen, “A Direct Maximum Power Point Tracking Method for Single-Phase Grid Connected PV Inverters”, IEEE, 2017.

Guan-Jie Fang, Kuo-Lung Lian, “A maximum power point tracking method based on multiple perturb-and-observe method for overcoming solar partial shaded problems”, IEEE, 2017.




How to Cite

Singh Chauhan, M. R. ., & Barve, M. A. . (2018). MPSO-MPPT based Single Phase Grid PV System for Power Enhancement. SMART MOVES JOURNAL IJOSCIENCE, 4(4), 1–9.