Year 2012,
Volume: 2 Issue: 4, 730 - 735, 01.12.2012
Abstract
This paper present two approaches for improving intelligence and performance optimization control of a photovoltaic system, the method further maximum power point tracking (MPPT) based on fuzzy logic method and artificial neural networks.The MPPT controller based neural networks, is developed and compared to the fuzzy logic algorithm. The results obtained under different operating conditions show that the system of control by fuzzy logic MPPT PV system is faster compared to the algorithm for neural networks against the latter is more stable than fuzzy logic.
References
- M.A.S.Masoum, M.Sarvi, “Design, Simulation and Implementation of A Fuzzy-Based MPP Tracker under Variable Insolation and Temperature Conditions“, Iranian Journal of Science & Technology, Transaction B, Engineering, Vol. 29, No. B1, Shiraz University 2005.
- C.Larbes, S.M. A t Cheikh, T.Obeidi, A.Zerguerras, “Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system“, Renewable Energy, Vol 34, pp. 2093-2100,2009.
- S.Lalouni, D.Rekioua, T.Rekioua, E.Matagne, “Fuzzy logic control of stand-alone photovoltaic system with battery storage“, Journal of Power Sources, Vol.193, No.2, pp. 899-907, 2009.
- C. Ben Salah, M.Ouali, “Comparison of fuzzy logic and neural network in maximum power point tracker for PV systems“, Electric Power Systems Research, Vol.81, No.2, pp. 43-50, 2011.
- A.Mellit, “Sizing of photovoltaic systems: a review“, journal of Renewable Energy, Vol.10, N°4, pp. 463-472, 2007.
- A.Kulaksiz, R.Akkaya, “Training data optimization for ANNs using genetic algorithms to enhance MPPT efficiency of a stand-alone system“, Turk J Elec Eng. & Comp. Sci, Vol.20, No.2, 2012.
- A. Mathew, A. I. Selvakumar, “MPPT Based Stand- Alone Water Pumping System“, International Conference on Computer, Communication & Electrical Technology - ICCCET2011, 18-19 March 2011.
Year 2012,
Volume: 2 Issue: 4, 730 - 735, 01.12.2012
Abstract
References
- M.A.S.Masoum, M.Sarvi, “Design, Simulation and Implementation of A Fuzzy-Based MPP Tracker under Variable Insolation and Temperature Conditions“, Iranian Journal of Science & Technology, Transaction B, Engineering, Vol. 29, No. B1, Shiraz University 2005.
- C.Larbes, S.M. A t Cheikh, T.Obeidi, A.Zerguerras, “Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system“, Renewable Energy, Vol 34, pp. 2093-2100,2009.
- S.Lalouni, D.Rekioua, T.Rekioua, E.Matagne, “Fuzzy logic control of stand-alone photovoltaic system with battery storage“, Journal of Power Sources, Vol.193, No.2, pp. 899-907, 2009.
- C. Ben Salah, M.Ouali, “Comparison of fuzzy logic and neural network in maximum power point tracker for PV systems“, Electric Power Systems Research, Vol.81, No.2, pp. 43-50, 2011.
- A.Mellit, “Sizing of photovoltaic systems: a review“, journal of Renewable Energy, Vol.10, N°4, pp. 463-472, 2007.
- A.Kulaksiz, R.Akkaya, “Training data optimization for ANNs using genetic algorithms to enhance MPPT efficiency of a stand-alone system“, Turk J Elec Eng. & Comp. Sci, Vol.20, No.2, 2012.
- A. Mathew, A. I. Selvakumar, “MPPT Based Stand- Alone Water Pumping System“, International Conference on Computer, Communication & Electrical Technology - ICCCET2011, 18-19 March 2011.
There are 7 citations in total.
Details
| Primary Language | English |
|---|---|
| Authors | |
| Publication Date | December 1, 2012 |
| IZ | https://izlik.org/JA82TU67SF |
| Published in Issue | Year 2012 Volume: 2 Issue: 4 |