References
- L. Xiaoping, Q. Yunyou, and S. SaeidNahaei, A novel maximum power point tracking in partially shaded PV systems using a hybrid method, Int. J. Hydrogen Energy 46 (2021), 37351-37366. https://doi.org/10.1016/j.ijhydene.2021.08.202
- I. Dincer, Renewable energy and sustainable development: A crucial review, Renew. Sustain. Energy Rev. 4 (2000), 157-175. https://doi.org/10.1016/S1364-0321(99)00011-8
- A. Chatterjee, K. Mohanty, V. S. Kommukuri, and K. Thakre, Design and experimental investigation of digital model predictive current controller for single phase grid integrated photovoltaic systems, Renew. Energy 108 (2017), 438-448. https://doi.org/10.1016/j.renene.2017.02.057
- R. Gross, M. Leach, and A. Bauen, Progress in renewable energy, Environ. Int. 29 (2003), 105-122. https://doi.org/10.1016/S0160-4120(02)00130-7
- M. AlShabi, C. Ghenai, M. Bettayeb, and F. F. Ahmad, Estimating one-diode-PV model using autonomous groups particle swarm optimization, IAES Int. J. Artif. Intell. 10 (2021), no. 1, 166-174.
- M. AlShabi, C. Ghenai, M. Bettayeb, F. F. Ahmad and M. El Haj Assad, Estimating pv models using multi-group salp swarm algorithm, IAES Int. J. Artif. Intell. 10 (2021), no. 2, 398-406.
- M. Bahrami, R. Gavagsaz-Ghoachani, M. Zandi, M. Phattanasak, G. Maranzanaa, B. Nahid-Mobarakeh, S. Pierfederici, and F. Meibody-Tabar, Hybrid maximum power point tracking algorithm with improved dynamic performance, Renew. Energy 130 (2019), 982-991. https://doi.org/10.1016/j.renene.2018.07.020
- A. O. Baba, G. Liu, and X. Chen, Classification and evaluation review of maximum power point tracking methods, Sustain. Futur. 2 (2020), 100020.
- S. Dubey, J. N. Sarvaiya, and B. Seshadri, Temperature dependent photovoltaic (PV) efficiency and its effect on PV production in the world-a review, Energy Procedia 33 (2013), 311-321. https://doi.org/10.1016/j.egypro.2013.05.072
- A. A. Abdulrazzaq and A. H. Ali, Efficiency performances of two MPPT algorithms for PV system with different solar panels irradiances, Int. J. Power Electron. Drive Syst. 9 (2018), no. 4, 1755-1764.
- E. Roman, R. Alonso, P. Ibanez, S. Elorduizapatarietxe, and D. Goitia, Intelligent PV module for grid-connected PV systems, IEEE Trans. Ind. Electron. 53 (2006), 1066-1073. https://doi.org/10.1109/TIE.2006.878327
- S. D. Al-Majidi, M. F. Abbod, and H. S. Al-Raweshidy, A novel maximum power point tracking technique based on fuzzy logic for photovoltaic systems, Int. J. Hydrogen Energy 43 (2018), 14158-14171. https://doi.org/10.1016/j.ijhydene.2018.06.002
- J. Ahmed and Z. Salam, An enhanced adaptive P&O MPPT for fast and efficient tracking under varying environmental conditions, IEEE Trans. Sustain. Energy 9 (2018), 1487-1496. https://doi.org/10.1109/TSTE.2018.2791968
- A.-R. Youssef, H. H. H. Mousa, and E. E. M. Mohamed, Development of self-adaptive P&O MPPT algorithm for wind generation systems with concentrated search area, Renew. Energy 154 (2020), 875-893. https://doi.org/10.1016/j.renene.2020.03.050
- M. Abdel-Salam, M. T. El-Mohandes, and M. El-Ghazaly, An efficient tracking of MPP in PV systems using a newlyformulated P&O-MPPT method under varying irradiation levels, J. Electr. Eng. Technol. 15 (2020), 501-513. https://doi.org/10.1007/s42835-019-00283-x
- M. N. Ali, K. Mahmoud, M. Lehtonen, and M. M. F. Darwish, An efficient fuzzy-logic based variable-step incremental conductance MPPT method for grid-connected PV systems, IEEE Access 9 (2021), 26420-26430.
- A. K. Gupta, R. K. Pachauri, T. Maity, Y. K. Chauhan, O. P. Mahela, B. Khan, and P. K. Gupta, Effect of various incremental conductance MPPT methods on the charging of battery load feed by solar panel, IEEE Access 9 (2021), 90977-90988. https://doi.org/10.1109/ACCESS.2021.3091502
- H. Shahid, M. Kamran, Z. Mehmood, M. Y. Saleem, M. Mudassar, and K. Haider, Implementation of the novel temperature controller and incremental conductance MPPT algorithm for indoor photovoltaic system, Sol. Energy 163 (2018), 235-242. https://doi.org/10.1016/j.solener.2018.02.018
- V. Jately, B. Azzopardi, J. Joshi, A. Sharma, and S. Arora, Experimental analysis of hill-climbing MPPT algorithms under low irradiance levels, Renew. Sustain. Energy Rev. 150 (2021), 111467.
- W. Zhu, L. Shang, P. Li, and H. Guo, Modified hill climbing MPPT algorithm with reduced steady-state oscillation and improved tracking efficiency, J. Eng. 2018 (2018), 1878-1883.
- C. B. N. Fapi, P. Wira, M. Kamta, A. Badji, and H. Tchakounte, Real-time experimental assessment of hill climbing MPPT algorithm enhanced by estimating a duty cycle for PV system, Int. J. Renew. Energy Res. 9 (2019), no. 3, 1180-1189.
- N. Kumar, B. Singh, and B. K. Panigrahi, LLMLF-based control approach and LPO MPPT technique for improving performance of a multifunctional three-phase two-stage grid integrated PV system, IEEE Trans. Sustain. Energy 11 (2019), 371-380. https://doi.org/10.1109/TSTE.2019.2891558
- N. Kumar, B. Singh, and B. K. Panigrahi, Integration of solar PV with low-voltage weak grid system: Using maximize-M Kalman filter and self-tuned P&O algorithm, IEEE Trans. Ind. Electron. 66 (2019), 9013-9022. https://doi.org/10.1109/TIE.2018.2889617
- N. Kumar, B. Singh, B. K. Panigrahi, and L. Xu, Leaky-least-logarithmic-absolute-difference-based control algorithm and learning-based InC MPPT technique for grid-integrated PV system, IEEE Trans. Ind. Electron. 66 (2019), 9003-9012. https://doi.org/10.1109/TIE.2018.2890497
- N. Kumar, B. Singh, B. K. Panigrahi, C. Chakraborty, H. M. Suryawanshi, and V. Verma, Integration of solar PV with lowvoltage weak grid system: Using normalized laplacian kernel adaptive kalman filter and learning based InC algorithm, IEEE Trans. Power Electron. 34 (2019), 10746-10758. https://doi.org/10.1109/TPEL.2019.2898319
- N. Kumar, B. Singh, J. Wang, and B. K. Panigrahi, A framework of L-HC and AM-MKF for accurate harmonic supportive control schemes, IEEE Trans. Circuits Syst. I Regul. Pap. 67 (2020), 5246-5256. https://doi.org/10.1109/TCSI.2020.2996775
- H. Rezk, M. Aly, M. Al-Dhaifallah, and M. Shoyama, Design and hardware implementation of new adaptive fuzzy logic-based MPPT control method for photovoltaic applications, IEEE Access 7 (2019), 106427-106438.
- S. Farajdadian and S. M. H. Hosseini, Optimization of fuzzy-based MPPT controller via metaheuristic techniques for standalone PV systems, Int. J. Hydrogen Energy 44 (2019), 25457-25472. https://doi.org/10.1016/j.ijhydene.2019.08.037
- X. Li, H. Wen, Y. Hu, and L. Jiang, A novel beta parameter based fuzzy-logic controller for photovoltaic MPPT application, Renew. Energy 130 (2019), 416-427. https://doi.org/10.1016/j.renene.2018.06.071
- U. Yilmaz, A. Kircay, and S. Borekci, PV system fuzzy logic MPPT method and PI control as a charge controller, Renew. Sustain. Energy Rev. 81 (2018), 994-1001. https://doi.org/10.1016/j.rser.2017.08.048
- X. Ge, F. W. Ahmed, A. Rezvani, N. Aljojo, S. Samad, and L. K. Foong, Implementation of a novel hybrid BAT-fuzzy controller based MPPT for grid-connected PV-battery system, Control Eng. Pract. 98 (2020), 104380.
- R. B. Roy, M. Rokonuzzaman, N. Amin, M. K. Mishu, S. Alahakoon, S. Rahman, N. Mithulananthan, K. S. Rahman, M. Shakeri, and J. Pasupuleti, A comparative performance analysis of ANN algorithms for MPPT energy harvesting in solar PV system, IEEE Access 9 (2021), 102137-102152. https://doi.org/10.1109/ACCESS.2021.3096864
- B. Babes, A. Boutaghane, and N. Hamouda, A novel natureinspired maximum power point tracking (MPPT) controller based on ACO-ANN algorithm for photovoltaic (PV) system fed arc welding machines, Neural Comput. Applic. 34 (2022), 299-317. https://doi.org/10.1007/s00521-021-06393-w
- K. J. Reddy and N. Sudhakar, ANFIS-MPPT control algorithm for a PEMFC system used in electric vehicle applications, Int. J. Hydrogen Energy 44 (2019), 15355-15369. https://doi.org/10.1016/j.ijhydene.2019.04.054
- K. Amara, A. Fekik, D. Hocine, M. L. Bakir, E. -B. Bourennane, T. A. Malek, and A. Malek, Improved performance of a PV solar panel with adaptive neuro fuzzy inference system ANFIS based MPPT, (2018 7th International Conference on Renewable Energy Research and Applications (ICRERA), Paris, France), 2018, pp. 1098-1101.
- A. A. Aldair, A. A. Obed, and A. F. Halihal, Design and implementation of ANFIS-reference model controller based MPPT using FPGA for photovoltaic system, Renew. Sustain. Energy Rev. 82 (2018), 2202-2217. https://doi.org/10.1016/j.rser.2017.08.071
- M. Birane, C. Larbes, and A. Cheknane, Comparative study and performance evaluation of central and distributed topologies of photovoltaic system, Int. J. Hydrogen Energy 42 (2017), 8703-8711. https://doi.org/10.1016/j.ijhydene.2016.09.192
- Z. Salam, J. Ahmed, and B. S. Merugu, The application of soft computing methods for MPPT of PV system: A technological and status review, Appl. Energy 107 (2013), 135-148. https://doi.org/10.1016/j.apenergy.2013.02.008
- S. Ozdemir, N. Altin, and I. Sefa, Fuzzy logic based MPPT controller for high conversion ratio quadratic boost converter, Int. J. Hydrogen Energy 42 (2017), 17748-17759. https://doi.org/10.1016/j.ijhydene.2017.02.191
- N. Zhang, D. Sutanto, K. M. Muttaqi, B. Zhang, and D. Qiu, High-voltage-gain quadratic boost converter with voltage multiplier, IET Power Electron. 8 (2015), 2511-2519. https://doi.org/10.1049/iet-pel.2014.0767
- P. Saadat and K. Abbaszadeh, A single-switch high step-up DC-DC converter based on quadratic boost, IEEE Trans. Ind. Electron. 63 (2016), 7733-7742. https://doi.org/10.1109/TIE.2016.2590991
- A. C. Subrata, T. Sutikno, S. Padmanaban, and H. S. Purnama, Maximum power point tracking in pv arrays with high gain DC-DC boost converter, in International Conference on Electrical Engineering, Computer Science and Informatics (EECSI), 2019.
- X. Zhang, Y. Hu, W. Mao, T. Zhao, M. Wang, F. Liu, and R. Cao, A grid-supporting strategy for cascaded H-bridge PV converter using VSG algorithm with modular active power reserve, IEEE Trans. Ind. Electron. 68 (2020), 186-197. https://doi.org/10.1109/TIE.2019.2962492
- Y. Pan, A. Sangwongwanich, Y. Yang, and F. Blaabjerg, A phase-shifting MPPT to mitigate interharmonics from cascaded H-bridge PV inverters, IEEE Trans. Ind. Appl. 57 (2020), 3052-3063. https://doi.org/10.1109/TIA.2020.3000969
- S. Srinivasan, R. Tiwari, M. Krishnamoorthy, M. P. Lalitha, and K. K. Raj, Neural network based MPPT control with reconfigured quadratic boost converter for fuel cell application, Int. J. Hydrogen Energy 46 (2021), 6709-6719. https://doi.org/10.1016/j.ijhydene.2020.11.121
- K. Kumar, S. R. Kiran, T. Ramji, S. Saravanan, P. Pandiyan, and N. Prabaharan, Performance evaluation of photo voltaic system with quadratic boost converter employing with MPPT control algorithms, Int. J. Renew. Energy Res. 10 (2020), 1083-1091.
- S. K. Manas and B. Bhushan, Performance Analysis of Fuzzy Logic-Based MPPT Controller for Solar PV System Using Quadratic Boost Converter, In Advances in energy technology, Springer, 2022, 69-79.
- P. A. Dahono, Derivation of high voltage-gain step-up DC-DC power converters, Int. J. Electr. Eng. Informatics 11 (2019).
- A. R. Jordehi, Parameter estimation of solar photovoltaic (PV) cells: A review, Renew. Sustain. Energy Rev. 61 (2016), 354-371. https://doi.org/10.1016/j.rser.2016.03.049
- M. A. Green, Accuracy of analytical expressions for solar cell fill factors, Sol. Cells 7 (1982), 337-340. https://doi.org/10.1016/0379-6787(82)90057-6
- M. G. Batarseh and M. E. Za'ter, Hybrid maximum power point tracking techniques: A comparative survey, suggested classification and uninvestigated combinations, Sol. Energy 169 (2018), 535-555. https://doi.org/10.1016/j.solener.2018.04.045
- J. Kivimaki, S. Kolesnik, M. Sitbon, T. Suntio, and A. Kuperman, Design guidelines for multiloop perturbative maximum power point tracking algorithms, IEEE Trans. Power Electron. 33 (2017), 1284-1293. https://doi.org/10.1109/TPEL.2017.2683268
- A. Bin Jusoh, O. J. E. I. Mohammed, and T. Sutikno, Variable step size perturb and observe MPPT for PV solar applications, Telkomnika 13 (2015), 1.
- D. N. Luta and A. K. Raji, Comparing fuzzy rule-based MPPT techniques for fuel cell stack applications, Energy Procedia 156 (2019), 177-182. https://doi.org/10.1016/j.egypro.2018.11.124
- S. Assahout, H. Elaissaoui, A. El Ougli, B. Tidhaf, and H. Zrouri, A neural network and fuzzy logic based MPPT algorithm for photovoltaic pumping system, Int. J. Power Electron. Drive Syst. 9 (2018), 1823-1833.
- T. Sutikno, A. C. Subrata, and A. Elkhateb, Evaluation of fuzzy membership function effects for maximum power point tracking technique of photovoltaic system, IEEE Access 9 (2021), 109157-109165. https://doi.org/10.1109/ACCESS.2021.3102050
- M. Killi and S. Samanta, Modified perturb and observe MPPT algorithm for drift avoidance in photovoltaic systems, IEEE Trans. Ind. Electron. 62 (2015), 5549-5559. https://doi.org/10.1109/TIE.2015.2407854
- X. Li, H. Wen, Y. Hu, and L. Jiang, Drift-free current sensorless MPPT algorithm in photovoltaic systems, Sol. Energy 177 (2019), 118-126. https://doi.org/10.1016/j.solener.2018.10.066