# An Extensive Study on Online, Offline and Hybrid MPPT Algorithms for Photovoltaic Systems

Keywords:
MPPT algorithms, Solar Power, Renewable Energy, Hybrid System, PV system

### Abstract

To moderate global warming, conventional fossil fuels are depleted. As the population increased with the rising standard of living and industrial growth, the global environment is affected and cause the greenhouse gases occurrence, which are frequently increased by unlimited use of fossil fuels. The generation of electric power loads increases the power demand on the basics of modern power technology development. Several benefits can be attained by installing the distribution generation with the quality and reliability of power delivered. However, the global energy problem can be resolved by renewable energy sources as an alternative energy generation. Technological developments in the last decade have increased the use of renewable energy sources. In worldwide, several renewable energy sources are used to attain their own power demand. The photovoltaic (PV) generation is the essential renewable energy source to serve the increasing electrical loads. The fastest-growing PV system has the naturally available energy sources of robust evolution with elegant benefits. The foremost objective of this paper is to examine the performance of the PV system with various Maximum Power Point Tracking (MPPT) algorithms. The solar irradiance and temperature make it complex to track the MPPT of PV systems. This review is about various MPPT algorithms like online, offline, and hybrid methods. The selected algorithms from each discussion are simulated in MATLAB/Simulink environment to match their performance in footings of the dynamic response and efficiency of the PV system under the variations of solar irradiance and temperature. An explanation and discussion of the PV system are achieved with the study of different types of MPPT algorithms of PV systems.### References

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[26] Adel Y, Abdelhady R, Ibrahim AM. “Assessment of a proposed hybrid photovoltaic array maximum power point tracking method”. Water Sci, Vol, 30, pp. 108–19, 2016.

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[30] Rezk H, Fathy A. “Simulation of global MPPT based on teaching–learning-based optimization technique for partially shaded PV system”. Electr Eng, Vol. 99, pp. 847–59, 2017.

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[33] Fathy A, Ziedan I, Amer D. “Improved teaching–learning-based optimization algorithm-based maximum power point trackers for photovoltaic system”. Electr Eng, Vol. 100, pp. 1773–84, 2018.

[34] Oshaba AS, Ali ES, Elazim SMA. “PI controller design via ABC algorithm for MPPT of PV system supplying DC motor–pump load”. Electr Eng, Vol. 99, pp. 505–18, 2017.

[35] Kumar N, Hussain I, Singh B, Panigrahi BK. “Single sensor based MPPT for partially shaded solar photovoltaic by using human psychology optimisation algorithm”. Transm Distrib IET Gener, Vol. 11, pp. 2562–74, 2017.

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[37] Rani BI, Ilango GS, Nagamani C. “Enhanced Power Generation From PV Array Under Partial Shading Conditions by Shade Dispersion Using Su Do Ku Configuration”. IEEE Trans Sustain Energy, Vol. 4, pp. 594–601, 2013.

[38] Seyedmahmoudian M, Rahmani R, Mekhilef S, Maung Than Oo A, Stojcevski A, Soon TK, et al. “Simulation and Hardware Implementation of New Maximum Power Point Tracking Technique for Partially Shaded PV System Using Hybrid DEPSO Method”. IEEE Trans Sustain Energy, Vol. 6:pp. 850–62, 2015.

[39] Renaudineau H, Donatantonio F, Fontchastagner J, Petrone G, Spagnuolo G, Martin J-P, et al. “A PSO-Based Global MPPT Technique for Distributed PV Power Generation”. IEEE Trans Ind Electron, Vol. 62, pp. 1047–58, 2015.

[40] Manickam C, Raman GR, Raman GP, Ganesan SI, Nagamani C. “A Hybrid Algorithm for Tracking of GMPP Based on P O and PSO With Reduced Power Oscillation in String Inverters”. IEEE Trans Ind Electron, Vol. 63, pp. 6097–106. 2016.

[41] Koad RBA, Zobaa AF, El-Shahat A. “A Novel MPPT Algorithm Based on Particle Swarm Optimization for Photovoltaic Systems”. IEEE Trans Sustain Energy, Vol. 8, pp. 468–76, 2017.

[42] Patel H, Agarwal V. “MPPT Scheme for a PV-Fed Single-Phase Single-Stage Grid-Connected Inverter Operating in CCM With Only One Current Sensor”. IEEE Trans Energy Convers, Vol. 24, pp. 256–63, 2009.

[43] Gladwell M. Outliers: the story of success. 1st ed. New York: Little, Brown and Co; 2008.

[44] Sundareswaran K, Sankar P, Nayak PSR, Simon SP, Palani S. “Enhanced Energy Output From a PV System Under Partial Shaded Conditions Through Artificial Bee Colony”. IEEE Trans Sustain Energy, Vol. 6, pp. 198–209, 2015.

[45] Sundareswaran K, Peddapati S, Palani S. “MPPT of PV Systems Under Partial Shaded Conditions Through a Colony of Flashing Fireflies”. IEEE Trans Energy Convers, Vol. 29, pp. 463–72, 2014.

[46] Mohanty S, Subudhi B, Ray PK. “A New MPPT Design Using Grey Wolf Optimization Technique for Photovoltaic System Under Partial Shading Conditions”. IEEE Trans Sustain Energy, Vol. 7, pp. 181–8, 2016.

[47] Kahneman D. Thinking, Fast and Slow. Farrar, Straus and Giroux; 2011.

[48] Bhukya MN, Kota VR. “DCA-TR-based MPP tracking scheme for photovoltaic power enhancement under dynamic weather conditions”. Electr Eng, Vol. 100, pp. 2383–96, 2018.

[49] Wu Z, Yu D, Kang X. “Application of improved chicken swarm optimization for MPPT in photovoltaic system”. Optim Control Appl Methods, Vol. 39, pp. 1029–42, 2018.

[50] Liu C-P, Ye C-M. “Bat algorithm with chaotic search strategy and analysis of its property”. Xitong Fangzhen Xuebao, J Syst Simul, Vol. 25, pp. 1183-1188+1195, 2013.

[51] Yan K, Du Y, Ren Z. “MPPT Perturbation Optimization of Photovoltaic Power Systems Based on Solar Irradiance Data Classification”. IEEE Trans Sustain Energy, Vol. 10, pp. 514–21, 2019.

[52] Lakshmi M, Hemamalini S. “Coordinated control of MPPT and voltage regulation using single-stage high gain DC–DC converter in a grid-connected PV system”. Electr Power Syst Res, Vol. 169, pp. 65–73, 2019.

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Published

2021-09-01

How to Cite

*Majlesi Journal of Electrical Engineering*,

*15*(3), 1-16. https://doi.org/https://doi.org/10.52547/mjee.15.3.1

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Articles