MAXIMUM POWER POINT TRACKING IN A PEROVSKITE SOLAR PUMPING SYSTEM WITH A SIX-PHASE INDUCTION MOTOR
DOI:
https://doi.org/10.59277/RRST-EE.2024.1.3Keywords:
Renewable energy, Six-phase induction motor, Maximum power point tracking (MPPT), Genetic algorithm (GA), Perovskite solar cellsAbstract
In this work, the maximum power point (MPP) of a photovoltaic (PV) array utilized as a source of electricity in standalone mode is tracked using a genetic algorithm (GA) as an optimization tool. The major objective of this work is to implement and regulate a six-phase induction motor (SPIM) powered by a centrifugal pump and fed by a perovskite solar array through a three-phase inverter. Perovskite solar cells are the most promising third-generation photovoltaic technology to replace silicon-based photovoltaic. These cells are made cheaply, at a low temperature, and efficiently. The outcomes are then investigated utilizing a SPIM scaler (v/f) closed-loop control. PID controllers are tuned to keep the motor speed aligned with the reference value. The transformer's six-phase secondary is linked to an LC filter to reduce the voltage and current waveform ripple. A test setup was created and installed to investigate the potential of controlling the SPIM fed via a three-to-six-phase transformer. The findings showed that the area needed for the plates when utilizing perovskite solar cells is just 14 % of what it would be if a silicon-based solar array were used for the identical purpose. Perovskite solar cells' tiny surface area helps to prevent partial shading and lower costs. It was discovered that the suggested method works well for powering SPIM from a three-phase source.
References
(1) Y. Kali et al., Current control of a six-phase induction machine drive based on discrete-time sliding mode with time delay estimation, Energies, 12, 1, pp. 1–17 (2019).
(2) H. Patel, V. Agarwal, S. Member, MATLAB-based modeling to study the effects of partial shading on PV array characteristics, 23, 1, pp. 302–310 (2008).
(3) H. Attia, High performance PV system based on artificial neural network MPPT with PI controller for direct current water pump applications, Int. J. Power Electron. Drive Syst., 10, 3, p. 1329 (2019).
(4) A.K. Mishra, B. Singh, Solar powered water pumping station utilizing improved cuk converter integrating to storage system, 20th Natl. Power Syst. Conf. NPSC 2018, pp. 1–6 (2018).
(5) R. Kumar, B. Singh, Solar PV powered-sensorless BLDC motor driven water pump, IET Renew. Power Gener., 13, 3, pp. 389–398 (2019).
(6) J. Maes et al., Light Absorption coefficient of CsPbBr 3 perovskite nanocrystals, J. Phys. Chem. Lett., 9, 11, pp. 3093–3097 (2018).
(7) S.D. Stranks et al., Electron-hole diffusion lengths exceeding 1 micrometer in an organometal trihalide perovskite absorber, Science, 342, 6156, pp. 341–344 (2013).
(8) A. Kojima, K. Teshima, Y. Shirai, T. Miyasaka, Organometal halide perovskites as visible-light sensitizers for photovoltaic cells, J. Am. Chem. Soc., 131, 17, pp. 6050–6051 (2009).
(9) M. Liu, M.B. Johnston, H.J. Snaith, Efficient planar heterojunction perovskite solar cells by vapour deposition, Nature, 501, 7467, pp. 395–398 (2013).
(10) D. Liu et al., Efficient planar heterojunction perovskite solar cells with Li-doped compact TiO2 layer, Nano Energy, 31, pp. 462–468 (2017).
(11) A.A. Zaky et al., Enhancing efficiency and decreasing photocatalytic degradation of perovskite solar cells using a hydrophobic copper-modified titania electron transport layer, Appl. Catal. B Environ., 284, p. 119714 (May 2021).
(12) A.A. Zaky, A. Fathy, H. Rezk, K. Gkini, P. Falaras, A. Abaza, A modified triple-diode model parameters identification for perovskite solar cells via nature-inspired search optimization algorithms, Sustainability, 13, 23, p. 12969 (Nov. 2021).
(13) A. Messai, A. Mellit, A. Guessoum, S.A. Kalogirou, Maximum power point tracking using a GA optimized fuzzy logic controller and its FPGA implementation, Sol. Energy, 85, 2, pp. 265–277 (2011).
(14) A. Borni et al., Optimized MPPT controllers using GA for grid connected photovoltaic systems, Comparative study, Energy Procedia, 119, pp. 278–296 (2017).
(15) R.E.-S. Mohamed I. Abdelwanis, Efficient parameter estimation procedure using sunflower optimization algorithm for six-phase induction motor, Rev. Roum. Sci. Techn.–Électrotechn. et Énerg, 67, 3, pp. 259–264, 2022.
(16) M.I. Abdelwanis, R.A. Sehiemy, M.A. Hamida, Hybrid optimization algorithm for parameter estimation of poly-phase induction motors with experimental verification, Energy AI, 5, 100083, pp. 1–15 (Sep. 2021),
(17) G.C. Seritan, B.A. Enache, F.C. Adochiei, F.C. Argatu, C. Christodoulou, V. Vita et al., Performance evaluation of photovoltaic panels containing cells with different bus bars configurations in partial shading conditions, Rev. Roum. Sci. Tech.-Ser. Electrotech. Energ., 65, 1-2, pp. 67–70 (2020).
(18) S. Seba, M. Birane, K. Benmouiza, A comparative analysis of boost converter topologies for photovoltaic systems using mppt and beta methods under partial shading, Rev. Roum. Sci. Tech.-Ser. Electrotech. Energ., 68, 4, pp. 375–380 (2023).
(19) A. Asadi, M.S. Karimzadeh, X. Liang, M. S. Mahdavi, G B. Gharehpetian, A novel control approach for a single-inductor multi-input single-output dc–dc boost converter for PV applications, IEEE Access, 11, pp. 114753–114764 (2023).
(20) L. Fan, X. Ma, Maximum power point tracking of PEMFC based on hybrid artificial bee colony algorithm with fuzzy control, Sci. Rep., vol. 12, no. 1, p. 4316, Mar. 2022
(21) S.M. Ulaganathan, R. Muniraj, R. Vijayanand, D. Devaraj, Novel solar photovoltaic emulation for validating the maximum power point algorithm and power converter,” Rev. Roum. Sci. Techn.–Électrotechn. et Énerg, 68, 4, pp. 407–412 (2023).
(22) S. Chtita et al., A novel hybrid GWO–PSO-based maximum power point tracking for photovoltaic systems operating under partial shading conditions, Sci. Rep., 12, 1, p. 10637 (2022).
(23) A.A.S. Mohamed, A. Berzoy, O. Mohammed, Optimized-fuzzy MPPT controller using GA for stand-alone photovoltaic water pumping system, IECON Proc. Industrial Electron. Conf., pp. 2213–2218 (2014).
(24) M.I. Abdelwanis, R.A. El-Sehiemy, A fuzzy-based controller of a modified six-phase induction motor driving a pumping system, Iran. J. Sci. Technol. - Trans. Electr. Eng. (2019).
(25) M.I. Abdelwanis, E. M. Rashad, I.B.M. Taha, F.F. Selim, Implementation and control of six-phase induction motor driven by a three-phase supply, Energies, 14, 22, p. 7798 (2021).
(26) H. Heidari et al., A parallel estimation system of stator resistance and rotor speed for active disturbance rejection control of six-phase induction motor, Energies, 13, 5 (2020).
(27) A.M. Shata, A.S. Abdel-Khalil, R.A. Hamdy, M.Z. Mostafa, Improved mathematical modeling of six phase induction machines based on fractional calculus, IEEE Access, 9, 1-1, pp 53146-53155 (2021).
(28) L. Sadiki, S. El Hani, I. Ouachtouk, S. Guedira, Optimized feed of six phase induction machine using special transformers, Intl. Conf. on Electrical and Information Techn., ICEIT, pp. 2020–2022 (2020).
(29) K.B. Rathore, V. Yadav, Experimental analysis of multilevel inverter fed six-phase induction motor for high power applications, Rev. Roum. Sci. Techn.–Électrotechn. et Énerg, 67, 4, pp. 389–394 (2022).
(30) M.I. Abdelwanis, F. Selim, A sensorless six-phase induction motor driving a centrifugal pump system, 19th International Middle-East Power Systems Conference, MEPCON 2017 (2018).
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