Fuzzy adaptive proportional-integral-derivative controller with dynamic set-point adjustment for maximum power point tracking in solar photovoltaic system

REFERENCES

• Aldobhani, A. M. S., & John, R. (2008). MPPT of PV system using ANFIS prediction and fuzzy logic tracking. Proceedings of int. multi-conf. of engg. and comp. sci, Hong Kong.
   Google Scholar
• Algazar, M. M., Monier, H., Halim, H., & Salem, M. (2012). Maximum power point tracking using fuzzy logic control. Elsevere Journal on Electrical Power and Energy Systems, 39, 21–28. doi: 10.1016/j.ijepes.2011.12.006
   Web of Science ®Google Scholar
• Bahgat, A. B. G., Helwa, N. H., Ahmad, G. E., & Shenawy, E. T. E. (2005). MPPT controller for PV systems using neural networks. Renewable Energy, 30(8), 1257–1268. doi: 10.1016/j.renene.2004.09.011
   Web of Science ®Google Scholar
• Besheer, A. H., & Adly, M. (2012). Ant colony system based pi maximum power point tracking for stand alone photovoltaic system. In Proceedings of IEEE international conference on industrial technology (pp. 693–698). Athens, Greece.
   Google Scholar
• Brito, M., Galotto, L., Sampaio, L., Melo, G., & Canesin, C. (2013, March). Evaluation of the main MPPT techniques for photovoltaic applications. IEEE Transactions on Industrial Electronics, 60(3), 1156–1167. doi: 10.1109/TIE.2012.2198036
   Web of Science ®Google Scholar
• Dounis, A. I., Kofinas, P., Alafodimos, C., & Tseles, D. (2013, December). Adaptive fuzzy gain scheduling PID controller for maximum power point tracking of photovoltaic system. Renewable Energy, 60, 202–214. doi: 10.1016/j.renene.2013.04.014
   Web of Science ®Google Scholar
• Dyk, V. (2002). Long-term monitoring of photovoltaic devices. Renewable Energy, 22, 183–197.
   Google Scholar
• Erickson, R.W., & Macsimovic, D. (2001). Fundamentals of power electronics (2nd ed., pp. 464–471). New York, NY: Kluwer Academic.
   Google Scholar
• Esram, T., & Chapman, P. (2007). Comparison of photovoltaic array maximum power point tracking techniques. IEEE Transactions on Energy Conversion, 22, 439–449. doi: 10.1109/TEC.2006.874230
   Web of Science ®Google Scholar
• Green, M. A. (1992). PV modules-operating principles, technology and system applications. Kensington, Australia: Prentice-Hall.
   Google Scholar
• Hiyama, T., & Kitabayashi, K. (1997). Neural network based estimation of maximum power generation from PV module using environment information. IEEE Transactions on Energy Conversion, 12(3), 241–247. doi: 10.1109/60.629709
   Web of Science ®Google Scholar
• Hui, J., & Sun, X. (2010). MPPT strategy of PV system based on adaptive fuzzy PID algorithm. In Proceedings of international conference on intelligent computing for sustainable energy and environment (pp. 220–228). Wuxi, China.
   Google Scholar
• International Energy Agency. (2003). Guidelines for monitoring stand-alone photo-voltaic power systems (Report: IEA PVPS T3, pp. 18–22).
   Google Scholar
• Iqbal, A., Rub, H. A., & Ahmed, S. M. (2010). Adaptive neuro-fuzzy inference system based maximum power point tracking of a solar PV module. In Proceedings of IEEE international energy conference (pp. 51–56).
   Google Scholar
• Jain, A. (2013). Synchronous vs asynchronous buck regulators (pp. 1–5). Camarillo, CA: Semtech Corp. Retrieved August 2013, from url: http://www.digikey.com/Web%20Export/Supplier%20Content/Semtech_600/PDF/Semtech_synchronous-vs-asynchronous-buck-regulators.pdf?redirected=1
   Google Scholar
• Jantsch, M., Real, M., Haberlin, H., Whitaker, C., Kurokawa, K., Blasser, G., & Kremer, P. (1997). Measurement of PV maximum power point tracking performance. Proceedings of photovolt. solar energ. Conf, Barcelona.
   Google Scholar
• Kartika, S., Rathika, P., & Devaraj, D. (2013). Fuzzy logic based maximum power point tracking designed for 10 Kw solar photovoltaic system. International Journal of Computer Science and Management Research, 2, 4121–1427.
   Google Scholar
• Khateb, A. E., Rahim, N. A., Selvaraj, J., & Uddin, M. N. (2013). Maximum power point tracking of single-ended primary-inductor converter employing a novel optimisation technique for proportional-integral-derivative controller. The Institution of Engineering and Technology Journal on Power Electronics, 6(6), 1111–1121.
   Google Scholar
• Kumari, J. S., Babu, S., & Yugandhar, J. (2011). Design and investigation of short circuit current based maximum power point tracking for photovoltaic system. Science Academy Publisher International Journal of Research and Reviews in Electrical and Computer Engineering, 2, 63–68.
   Google Scholar
• Liptak, B. (2006). Instrument engineer's handbook: Process optimization and control (4th ed., pp. 117–119). Boca Raton, FL: ISA-CRC Publication.
   Google Scholar
• Luis, C., & Sivestre, S. (2002). Modelling photovoltaic systems using PSpice. Chichester: John Wiley & Sons Ltd.
   Google Scholar
• Mahammad, A. K., Saon, S., & Chee, W. S. (2013). Development of optimum controller based on MPPT for photovoltaic system during shading condition. In Proceedings of Malaysian technical universities conference on engineering & technology (Vol. 53, pp. 337–346). Retrieved from url: http://www.sciencedirect.com/science/article/pii/S187770581300163X
   Google Scholar
• Marcelo, M. G., Gazoli, J., & Filho, E. (2009). Comprehensive approach to modeling and simulation of photovoltaic arrays. IEEE Transactions on Power Electronics, 24, 1198–1208.
   Web of Science ®Google Scholar
• Panda, A., Pathak, M. K., & Srivastava, S. P. (2011). Fuzzy intelligent controller for the maximum power point tracking of a photovoltaic module at varying atmospheric conditions. Journal of Energy Technologies and Policy, 1(2), 18–27.
   Google Scholar
• Park, J., Cho, H., & Kim, D. (2012). Neural PID based MPPT algorithm for photovoltaic generator system. New & Renewable Energy, 8(3), 14–22. doi: 10.7849/ksnre.2012.8.3.014
   Google Scholar
• Rashid, M. (2001). Power electronics handbook (pp. 213–214). New York, NY: Academic Press.
   Google Scholar
• Salhi, M., & Bachtiri, R. (2011, June). A maximum power point tracking photovoltaic system using a proportional integral regulator. Science Academy Transactions on Renewable Energy Systems Engineering and Technology, 1(2), 37–44.
   Google Scholar
• Shafy, A., & Nafeh, A. (2011). A modified MPPT control loop for PV/battery-charging system using PI controller optimally tuned with GA. International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, 24, 111–122. doi: 10.1002/jnm.764
   Web of Science ®Google Scholar
• Stephanopoulos, G. (1984). Chemical process control, an introduction to theory and practice (pp. 431–432). Englewood cliff, NJ: PHI.
   Google Scholar
• Subudhi, B., & Pradhan, R. (2013). A comparative study on maximum power point tracking techniques for photovoltaic power systems. IEEE Transactions on Sustainable Energy, 4, 89–98. doi: 10.1109/TSTE.2012.2202294
   Web of Science ®Google Scholar
• Veerachary, M., & Yadaiah, N. (2000). ANN based maximum power tracking for PV supplied dc motors. Solar Energy, 69(4), 343–350. doi: 10.1016/S0038-092X(00)00085-2
   Web of Science ®Google Scholar
• Wilson, D. I. (2005, March). Relay-based PID tuning. Automation & Control, 10–12, New Zeland.
   Google Scholar
• Yang, W., Ding, L., & Nan, L. (2011). The application of fuzzy parameters self-tuning PID controller in MPPT of photovoltaic power system. In Proceedings of IEEE conference on transport., mech. and elect. engg. (pp. 1129–1132). Changchun, Jilin.
   Google Scholar
• Zhang, F., Thanapalan, K., Procter, A., Carr, S., & Maddy, J. (2013, June). Adaptive hybrid maximum power point tracking method for a photovoltaic system. IEEE Transactions on Energy Conversion, 28(2), 353–360. doi: 10.1109/TEC.2013.2255292
   Web of Science ®Google Scholar
• Zhou, W., Yang, H., & Fang, Z. (2007). A novel model for photovoltaic array performance prediction. Journal of Applied Energy, 84, 1187–1198. doi: 10.1016/j.apenergy.2007.04.006
   Web of Science ®Google Scholar