Power Performance Evaluation of a PV Module Using MPPT with Fuzzy Logic Control

Authors

  • Suman Chowdhury Department of Electrical and Electronic Engineering, International University of Business Agriculture and Technology, Dhaka, Bangladesh
  • Dilip Kumar Das Department of Mathematics, International University of Business Agriculture and Technology, Dhaka, Bangladesh
  • Md. Sharafat Hossain Department of Electrical and Electronic Engineering, Dhaka University of Engineering and Technology, Gazipur, Bangladesh

DOI:

https://doi.org/10.38032/jea.2021.01.002

Keywords:

Power, Module, MPPT, Fuzzy, PV

Abstract

This paper exhibits performance of power of photovoltaic (PV) module in the case of shading effect. A comparison is made with performance of power of PV module void of MPPT solution. From the MATLAB simulation it is found that around 9.92% more average power generation is possible if MPPT (maximum power power point) solution is taken. To take the effect of partial shading a variation of irradiance profile has been proposed since change of irradiance causes the variation of output power to a great extent. Again to observe the performance of output power with MPPT Fuzzy logic control has been introduced for making the tracking fast and accurate. Mamdani control has been chosen as a technique for fuzzy controller. On top of this, mathematical structure of PV module has been prepared in MATLAB simulink to see output preview of PV module and this module has been linked to the fuzzy logic system to trace the peak power. In the simulation process the instantaneous power, average power and percentage power development are being analyzed with figures.

References

Farhat, M. and Sbita, L., 2011. Advanced fuzzy MPPT control algorithm for photovoltaic systems. Science Academy Transactions on Renewable Energy Systems Engineering and Technology, 1(1), pp.29-36.

Tafticht, T., Agbossou, K., Doumbia, M.L. and Cheriti, A., 2008. An improved maximum power point tracking method for photovoltaic systems. Renewable energy, 33(7), pp.1508-1516. DOI: https://doi.org/10.1016/j.renene.2007.08.015

Philibert, C., Frankl, P., Tam, C., Abdelilah, Y., Bahar, H., Marchais, Q. and Wiesner, H., 2014. Technology roadmap: solar photovoltaic energy. International Energy Agency: Paris, France.

Tomabechi, K., 2010. Energy resources in the future. Energies, 3(4), pp.686-695. DOI: https://doi.org/10.3390/en3040686

Ocran, T.A., Cao, J., Cao, B. and Sun, X., 2005. Artificial neural network maximum power point tracker for solar electric vehicle. Tsinghua science and technology, 10(2), pp.204-208.

Hua, C. and Shen, C., 1998, February. Comparative study of peak power tracking techniques for solar storage system. In APEC'98 Thirteenth Annual Applied Power Electronics Conference and Exposition (Vol. 2, pp. 679-685). IEEE.

Koutroulis, E., Kalaitzakis, K. and Voulgaris, N.C., 2001. Development of a microcontroller-based, photovoltaic maximum power point tracking control system. IEEE Transactions on power electronics, 16(1), pp.46-54. DOI: https://doi.org/10.1109/63.903988

Enslin, J.H. and Snyman, D.B., 1992, November. Simplified feed-forward control of the maximum power point in PV installations. In Proceedings of the 1992 International Conference on Industrial Electronics, Control, Instrumentation, and Automation (pp. 548-553). IEEE.

Bodur, M. and Ermis, M., 1994, April. Maximum power point tracking for low power photovoltaic solar panels. In Proceedings of MELECON'94. Mediterranean Electrotechnical Conference (pp. 758-761). IEEE.

Sullivan, C.R. and Powers, M.J., 1993, June. A high-efficiency maximum power point tracker for photovoltaic arrays in a solar-powered race vehicle. In Proceedings of IEEE Power Electronics Specialist Conference-PESC'93 (pp. 574-580). IEEE.

Veerachary, M., Senjyu, T. and Uezato, K., 2003. Neural-network-based maximum-power-point tracking of coupled-inductor interleaved-boost-converter-supplied PV system using fuzzy controller. IEEE Transactions on Industrial Electronics, 50(4), pp.749-758. DOI: https://doi.org/10.1109/TIE.2003.814762

Ocran, T.A., Cao, J., Cao, B. and Sun, X., 2005. Artificial neural network maximum power point tracker for solar electric vehicle. Tsinghua science and technology, 10(2), pp.204-208. DOI: https://doi.org/10.1016/S1007-0214(05)70055-9

Bose, B.K., 2002. Modern power electronics and AC drives (Vol. 123). Upper Saddle River, NJ: Prentice hall.

Balasubramanian, G. and Singaravelu, S., 2012. Fuzzy logic controller for the maximum power point tracking in photovoltaic system. International Journal of Computer Applications, 41(12), pp.22-28. DOI: https://doi.org/10.5120/5594-7840

Femia, N., Petrone, G., Spagnuolo, G. and Vitelli, M., 2005. Optimization of perturb and observe maximum power point tracking method. IEEE transactions on power electronics, 20(4), pp.963-973. DOI: https://doi.org/10.1109/TPEL.2005.850975

Hussein, K.H., Muta, I., Hoshino, T. and Osakada, M., 1995. Maximum photovoltaic power tracking: an algorithm for rapidly changing atmospheric conditions. IEE Proceedings-Generation, Transmission and Distribution, 142(1), pp.59-64. DOI: https://doi.org/10.1049/ip-gtd:19951577

Zainuri, M.M., Radzi, M.M., Soh, A.C. and Rahim, N.A., 2012, December. Adaptive P&O-fuzzy control MPPT for PV boost dc-dc converter. In 2012 IEEE International Conference on Power and Energy (PECon) (pp. 524-529). IEEE.

Tian, Y., Xia, B., Xu, Z. and Sun, W., 2014. Modified asymmetrical variable step size incremental conductance maximum power point tracking method for photovoltaic systems. Journal of Power Electronics, 14(1), pp.156-164. DOI: https://doi.org/10.6113/JPE.2014.14.1.156

Alajmi, B.N., Ahmed, K.H., Finney, S.J. and Williams, B.W., 2010. Fuzzy-logic-control approach of a modified hill-climbing method for maximum power point in microgrid standalone photovoltaic system. IEEE transactions on power electronics, 26(4), pp.1022-1030.

Iqbal, A., Abu-Rub, H. and Ahmed, S.M., 2010, December. Adaptive neuro-fuzzy inference system based maximum power point tracking of a solar PV module. In 2010 IEEE International Energy Conference (pp. 51-56). IEEE. DOI: https://doi.org/10.1109/ENERGYCON.2010.5771737

Chin, C.S., Neelakantan, P., Yoong, H.P. and Teo, K.T.K., 2011. Optimisation of fuzzy based maximum power point tracking in PV system for rapidly changing solar irradiance. Transaction on Solar Energy and Planning, 2, pp.130-137.

Radjai, T., Gaubert, J.P. and Rahmani, L., 2014, June. The new FLC-variable incremental conductance MPPT with direct control method using Cuk converter. In 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE) (pp. 2508-2513). IEEE. DOI: https://doi.org/10.1109/ISIE.2014.6865014

Cheikh, M.A., Larbes, C., Kebir, G.T. and Zerguerras, A., 2007. Maximum power point tracking using a fuzzy logic control scheme. Revue des energies Renouvelables, 10(3), pp.387-395.

Rahmani, R., Seyedmahmoudian, M., Mekhilef, S. and Yusof, R., 2013. Implementation of fuzzy logic maximum power point tracking controller for photovoltaic system. American Journal of Applied Sciences, 10, pp.209-218. DOI: https://doi.org/10.3844/ajassp.2013.209.218

Liu, C.L., Chen, J.H., Liu, Y.H. and Yang, Z.Z., 2014. An asymmetrical fuzzy-logic-control-based MPPT algorithm for photovoltaic systems. Energies, 7(4), pp.2177-2193. DOI: https://doi.org/10.3390/en7042177

Takun, P., Kaitwanidvilai, S. and Jettanasen, C., 2010, March. Maximum power point tracking using fuzzy logic control for photovoltaic systems. In World Congress on Engineering 2012. July 4-6, 2012. London, UK. (Vol. 2189, pp. 986-990). International Association of Engineers.

Putri, R.I., Wibowo, S. and Rifa’i, M., 2015. Maximum power point tracking for photovoltaic using incremental conductance method. Energy Procedia, 68, pp.22-30. DOI: https://doi.org/10.1016/j.egypro.2015.03.228

Sakly, A. and Smida, B., 2012, February. M. Adequate fuzzy inference method for MPPT fuzzy control of Photovoltaic systems. In Proceedings of the 2012 International Conference on Future Electrical Power and Energy systems, Lecture Notes in Information Technology (Vol. 9, pp. 457-468).

Mahamudul, H., Saad, M. and Ibrahim Henk, M., 2013. Photovoltaic system modeling with fuzzy logic based maximum power point tracking algorithm. International Journal of Photoenergy, 2013. DOI: https://doi.org/10.1155/2013/762946

El Khateb, A.H., Rahim, N.A. and Selvaraj, J., 2013. Type-2 fuzzy logic approach of a maximum power point tracking employing sepic converter for photovoltaic system. Journal of Clean Energy Technologies, 1(1), pp.41-44. DOI: https://doi.org/10.7763/JOCET.2013.V1.10

Roy, C.P., Vijaybhaskar, D. and Maity, T., 2013, December. Modelling of fuzzy logic controller for variable-step MPPT in photovoltaic system. In 2013 IEEE 1st International Conference on Condition Assessment Techniques in Electrical Systems (CATCON) (pp. 341-346). IEEE. DOI: https://doi.org/10.1109/CATCON.2013.6737524

Natsheh, E.M. and Albarbar, A., 2013. Hybrid power systems energy controller based on neural network and fuzzy logic. DOI: https://doi.org/10.4236/sgre.2013.42023

Bos, M.J., Abhijith, S., Aswin, V., Basil, R. and Dhanesh, R., 2014. Fuzzy logic controlled PV powered buck converter with MPPT. Int. J. Adv. Res. Electr. Electron. Instrum. Eng, 3, pp.9370-9377.

Takun, P., Kaitwanidvilai, S. and Jettanasen, C., 2010, March. Maximum power point tracking using fuzzy logic control for photovoltaic systems. In World Congress on Engineering 2012. July 4-6, 2012. London, UK. (Vol. 2189, pp. 986-990). International Association of Engineers.

Agorreta, J.L., Reinaldos, L., Gonzalez, R., Borrega, M., Balda, J. and Marroyo, L., 2009. Fuzzy switching technique applied to PWM boost converter operating in mixed conduction mode for PV systems. IEEE Transactions on Industrial Electronics, 56(11), pp.4363-4373. http://dx.doi.org/10.1109/TIE.2009.2019567 DOI: https://doi.org/10.1109/TIE.2009.2019567

Alajmi, B.N., Ahmed, K.H., Finney, S.J. and Williams, B.W., 2010. Fuzzy-logic-control approach of a modified hill-climbing method for maximum power point in microgrid standalone photovoltaic system. IEEE transactions on power electronics, 26(4), pp.1022-1030. http://dx.doi.org/10.1109/TPEL.2010.2090903 DOI: https://doi.org/10.1109/TPEL.2010.2090903

Jose, P. and Jose, P.R., 2014. Grid connected photovoltaic system with fuzzy logic control based MPPT. International Journal of Engineering and Innovative Technology (IJEIT), 3(8), pp.142-148.

Tsai, H.L., Tu, C.S. and Su, Y.J., 2008, October. Development of generalized photovoltaic model using MATLAB/SIMULINK. In Proceedings of the world congress on Engineering and computer science (Vol. 2008, pp. 1-6).

Gupta, A.K., Gupta, M. and Saxena, R., 2018. Modeling and Comparative Analysis of PV Module with Improved Perturbation & Observation Based MPPT Technique for PV Applications. Archives of Current Research International, pp.1-12.

Durago, J.G., 2011. Photovoltaic Emulator Adaptable to Irradiance, Temperature and Panel Specific IV Curves.

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Published

04-01-2021
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How to Cite

Chowdhury, S., Kumar Das, D., & Hossain, M. S. . (2021). Power Performance Evaluation of a PV Module Using MPPT with Fuzzy Logic Control. Journal of Engineering Advancements, 2(01), 07–12. https://doi.org/10.38032/jea.2021.01.002
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