Year 2021,
Volume: 5 Issue: 1, 20 - 28, 01.01.2021
Ö. Fatih Keçecioğlu
,
Ahmet Gani
,
Mustafa Şekkeli
Supporting Institution
Kahramanmaraş Sütçü İmam Üniversitesi, Bilimsel Araştırma Projeleri Birimi
Project Number
2018/5-11 D
References
- Acikgoz H, Kumar A, Beiranvand H & Sekkeli M (2019). Hardware implementation of type-2 neuro-fuzzy controller-based direct power control for three- phase active front-end rectifiers. International Transactions on Electrical Energy Systems, 29(10), 693-702. DOI: 10.1002/2050-7038.12066
- Coteli R, Acikgoz H, Ucar F & Dandil B (2017). Design and implementation of Type-2 fuzzy neural system controller for PWM rectifiers. International Journal of Hydrogen Energy, 42(32), 20759-20771. DOI: 10.1016/j.ijhydene.2017.07.032
- Dixit T V, Yadav A & Gupta S (2018). Experimental assessment of maximum power extraction from solar panel with different converter topologies. International Transactions on Electrical Energy Systems, 29(2), 1-33. DOI: 10.1002/etep.2712
- Dogmus O, Kilic E, Sit S & Gunes M (2017). Adaptation of Optimized PID Controller with PSO Algorithm to Photovoltaic MPPT System. Kahramanmaraş Sütçü İmam University Journal of Engineering Sciences, 20(4), 1–8.
- Karnik N N, Mendel J M & Liang Q (1999). Type-2 fuzzy logic systems. IEEE Transactions on Fuzzy Systems, 7(6), 643–658. DOI: 10.1109/91.811231
- Kececioglu O F (2019). Robust control of high gain DC-DC converter using Type-2 fuzzy neural network controller for MPPT. Journal of Intelligent & Fuzzy Systems, 37(1), 941-651. DOI: 10.3233/JIFS-181770
- Kececioglu O F, Acikgoz H & Gani A (2018). Fuzzy - PI Based MPPT Control for Photovoltaic Systems. Innovations in Intelligent Systems and Applications Conference (ASYU), Adana, Turkey. DOI: 10.1109/ASYU.2018.8554023
- Kumbasar T (2016). Robust stability analysis and systematic design of single-input interval type-2 fuzzy logic controllers. IEEE Transactions on Fuzzy Systems, 24(3), 675–694. DOI: 10.1109/TFUZZ.2015.2471805
- Luo F L (1997). Luo-converters, a series of new DC-DC step-up (boost) conversion circuits. Proceedings of Second International Conference on Power Electronics and Drive Systems, Singapore, 882-888. DOI: 10.1109/PEDS.1997.627511
- Mendel J M & John R I B (2002).Type-2 fuzzy sets made simple. IEEE Transactions on Fuzzy Systems, 10(2), 117-127. DOI: 10.1109/91.995115
- Ozdemir S, Altin N & Sefa I (2017). Fuzzy logic based MPPT controller for high conversion ratio quadratic boost converter. International Journal of Hydrogen Energy, 42(38), 17748-17759. DOI: 10.1016/j.ijhydene.2017.02.191
- Pansare C, Sharma S K, Jain C & Saxena R (2017). Analysis of a modified positive output Luo converter and its application to solar PV system. IEEE Industry Applications Society Annual Meeting, Cincinnati, OH, USA, 1–6.
- Radjai T, Gaubert J P, Rahmani L & Mekhilef S (2015). Experimental verification of P&O MPPT algorithm with direct control based on fuzzy logic control using CUK converter. International Transactions on Electrical Energy Systems, 25(12), 3492–3508. DOI: 10.1002/etep.2047
- Soon T K & Mekhilef S (2015). A fast-converging MPPT technique for photovoltaic system under fast-varying solar irradiation and load resistance. IEEE Transactions on Industrial Informatics, 11(1), 176-186. DOI: 10.1109/TII.2014.2378231
- Tai K, El-Sayed A R, Biglarbegian M, Gonzalez C I, Castillo O & Mahmud S (2016). Review of recent type-2 fuzzy controller applications. Algorithms, 9(2), 1-19. DOI: 10.3390/a9020039
Improved hybrid intelligent controller design for MPPT of stand-alone PV System
Year 2021,
Volume: 5 Issue: 1, 20 - 28, 01.01.2021
Ö. Fatih Keçecioğlu
,
Ahmet Gani
,
Mustafa Şekkeli
Abstract
Photovoltaic (PV) systems have low power conversion efficiency, so maximum power point tracking (MPPT) control methods are utilized to maximize the efficiency of PV systems. The present study proposes an improved hybrid intelligent controller design for the MPPT of stand-alone PV system. The hybrid intelligent control structure is integrated into Angle of Incremental Conductance (AIC) method and Interval Type-2 Takagi-Sugeno-Kang Fuzzy Logic Controller (IT2-TSKFLC). The proposed hybrid intelligent controller offers a superior performance in terms of dealing with uncertainties of sudden changes under different environmental conditions. A simulation model is created in Matlab/Simulink using daily data from a real solar PV plant to evaluate the performance of the proposed hybrid intelligent controller. The simulation findings demonstrated that the proposed hybrid intelligent controller displays a highly stable and robust performance in terms of tracking maximum power point compared to a conventional AIC MPPT method against various uncertainties stemming from disturbing inputs such as solar irradiance and panel temperature variations.
Project Number
2018/5-11 D
References
- Acikgoz H, Kumar A, Beiranvand H & Sekkeli M (2019). Hardware implementation of type-2 neuro-fuzzy controller-based direct power control for three- phase active front-end rectifiers. International Transactions on Electrical Energy Systems, 29(10), 693-702. DOI: 10.1002/2050-7038.12066
- Coteli R, Acikgoz H, Ucar F & Dandil B (2017). Design and implementation of Type-2 fuzzy neural system controller for PWM rectifiers. International Journal of Hydrogen Energy, 42(32), 20759-20771. DOI: 10.1016/j.ijhydene.2017.07.032
- Dixit T V, Yadav A & Gupta S (2018). Experimental assessment of maximum power extraction from solar panel with different converter topologies. International Transactions on Electrical Energy Systems, 29(2), 1-33. DOI: 10.1002/etep.2712
- Dogmus O, Kilic E, Sit S & Gunes M (2017). Adaptation of Optimized PID Controller with PSO Algorithm to Photovoltaic MPPT System. Kahramanmaraş Sütçü İmam University Journal of Engineering Sciences, 20(4), 1–8.
- Karnik N N, Mendel J M & Liang Q (1999). Type-2 fuzzy logic systems. IEEE Transactions on Fuzzy Systems, 7(6), 643–658. DOI: 10.1109/91.811231
- Kececioglu O F (2019). Robust control of high gain DC-DC converter using Type-2 fuzzy neural network controller for MPPT. Journal of Intelligent & Fuzzy Systems, 37(1), 941-651. DOI: 10.3233/JIFS-181770
- Kececioglu O F, Acikgoz H & Gani A (2018). Fuzzy - PI Based MPPT Control for Photovoltaic Systems. Innovations in Intelligent Systems and Applications Conference (ASYU), Adana, Turkey. DOI: 10.1109/ASYU.2018.8554023
- Kumbasar T (2016). Robust stability analysis and systematic design of single-input interval type-2 fuzzy logic controllers. IEEE Transactions on Fuzzy Systems, 24(3), 675–694. DOI: 10.1109/TFUZZ.2015.2471805
- Luo F L (1997). Luo-converters, a series of new DC-DC step-up (boost) conversion circuits. Proceedings of Second International Conference on Power Electronics and Drive Systems, Singapore, 882-888. DOI: 10.1109/PEDS.1997.627511
- Mendel J M & John R I B (2002).Type-2 fuzzy sets made simple. IEEE Transactions on Fuzzy Systems, 10(2), 117-127. DOI: 10.1109/91.995115
- Ozdemir S, Altin N & Sefa I (2017). Fuzzy logic based MPPT controller for high conversion ratio quadratic boost converter. International Journal of Hydrogen Energy, 42(38), 17748-17759. DOI: 10.1016/j.ijhydene.2017.02.191
- Pansare C, Sharma S K, Jain C & Saxena R (2017). Analysis of a modified positive output Luo converter and its application to solar PV system. IEEE Industry Applications Society Annual Meeting, Cincinnati, OH, USA, 1–6.
- Radjai T, Gaubert J P, Rahmani L & Mekhilef S (2015). Experimental verification of P&O MPPT algorithm with direct control based on fuzzy logic control using CUK converter. International Transactions on Electrical Energy Systems, 25(12), 3492–3508. DOI: 10.1002/etep.2047
- Soon T K & Mekhilef S (2015). A fast-converging MPPT technique for photovoltaic system under fast-varying solar irradiation and load resistance. IEEE Transactions on Industrial Informatics, 11(1), 176-186. DOI: 10.1109/TII.2014.2378231
- Tai K, El-Sayed A R, Biglarbegian M, Gonzalez C I, Castillo O & Mahmud S (2016). Review of recent type-2 fuzzy controller applications. Algorithms, 9(2), 1-19. DOI: 10.3390/a9020039