- Ukoba, K., Olatunji, K. O., Adeoye, E., Jen, T. C., & Madyira, D. M. (2024). Optimizing renewable energy systems through artificial intelligence: Review and future prospects. Energy & Environment, 35(7), 3833-3879. https://doi.org/10.1177/0958305X241256293
- Sakouvogui, A., Diarra, A., Oulare, F., Camara, E. O., Barry, S., & Keita, M. (2021). Multidisciplinary Technovation. Nature, 3(4). https://doi.org/10.34256/irjmt2142
- Dharmarajan, R., & Ramachandran, R. (2019). PV module parameters estimation using Newton Raphson. International Research Journal of Multidisciplinary Technovation, 1(4), 28-40. https://doi.org/10.34256/irjmt19219
- Priyadarshi, N., Padmanaban, S., Hiran, K. K., Holm-Nielson, J. B., & Bansal, R. C. (Eds.). (2021). Artificial intelligence and internet of things for renewable energy systems(Vol. 12). Walter de Gruyter GmbH & Co KG. https://doi.org/10.1515/9783110714043-202
- Gunapriya, B., Abinaya, I., Karthik, M., & Vidhya, H. (2020). Anti-wind up PI controller with tracking for motor drive system: Modelling, simulation and implementation in lab view based FPGA. International Journal of Recent technology and Engineering, 8(5). DOI:10.35940/ijrte.D9510.018520
- Munir, S. (2022). Estimator Torsi Beban Sistem Servo Modular MS150 DC Berbasis Jaringan Syaraf Tiruan. CYCLOTRON, 5(2). https://doi.org/10.30651/cl.v5i2.12936
- Vijayan, V., Mohapatra, A., Singh, S. N., & Dewangan, C. L. (2023). An efficient modular optimization scheme for unbalanced active distribution networks with uncertain EV and PV penetrations. IEEE Transactions on Smart Grid, 14(5), 3876-3888. https://doi.org/10.1109/TSG.2023.3234551
- Wang, H., Binti Mansor, N. N., & Mokhlis, H. B. (2024). Novel hybrid optimization technique for solar photovoltaic output prediction using Improved Hippopotamus Algorithm. Applied Sciences, 14(17), 7803. https://doi.org/10.3390/app14177803.
- Kavin, K. S., & Subha Karuvelam, P. (2023). PV-based grid interactive PMBLDC electric vehicle with high gain interleaved DC-DC SEPIC Converter. IETE Journal of Research, 69(7), 4791-4805. https://doi.org/10.1080/03772063.2021.1958070
- Nafeh, A. E. S. A., Omran, A. E. F. A., Elkholy, A., & Yousef, H. M. (2024). Optimal economical sizing of a PV-battery grid-connected system for fast charging station of electric vehicles using modified snake optimization algorithm. Results in Engineering, 21, 101965. https://doi.org/10.1016/j.rineng.2024.101965
- Kavin, K. S., (2020). Energy Management of AC Grid by the Solar PV System Using Landsman Converter. https://dx.doi.org/10.2139/ssrn.3668766
- Abdulla, H., Sleptchenko, A., & Nayfeh, A. (2024). Photovoltaic systems operation and maintenance: A review and future directions. Renewable and Sustainable Energy Reviews, 195, 114342. https://doi.org/10.1016/j.rser.2024.114342
- Saxena, A., Kumar, R., Sagade, A. A., Singh, D. B., Tyagi, V. V., Cuce, E., & Goel, V. (2024). A state-of-art review on photovoltaic systems: Design, performance, and progress. Process Safety and Environmental Protection, 190, 1324-1354. https://doi.org/10.1016/j.psep.2024.07.111
- Nezhad, M. A., & Bevrani, H. (2023). μ and H∞ optimization control based on optimal oxygen excess ratio for the Proton Exchange Membrane Fuel Cell (PEMFC). Journal of Industrial &Management Optimization, 19(6). DOI: 10.3934/jimo.2022116
- Antarasee, P., Premrudeepreechacharn, S., Siritaratiwat, A., & Khunkitti, S. (2022). Optimal design of electric vehicle fast-charging station’s structure using metaheuristic algorithms. Sustainability, 15(1), 771. https://doi.org/10.3390/su15010771
- Kraiem, H., Flah, A., Mohamed, N., Alowaidi, M., Bajaj, M., Mishra, S., & Sharma, S. K. (2021). Increasing electric vehicle autonomy using a photovoltaic system controlled by particle swarm optimization. IEEE Access, 9, 72040-72054. https://doi.org/10.1109/ACCESS.2021.3077531
- Singh, B., Verma, A., Chandra, A., & Al-Haddad, K. (2020). Implementation of solar PV-battery and diesel generator based electric vehicle charging station. IEEE Transactions on Industry Applications, 56(4), 4007-4016. https://doi.org/10.1109/TIA.2020.2989680
- Elshara, R., Hançerlioğullari, A., Rahebi, J., & Lopez-Guede, J. M. (2024). PV cells and modules parameter estimation using coati optimization algorithm. Energies, 17(7), 1716. https://doi.org/10.3390/en17071716
- Habib, H. U. R., Waqar, A., Junejo, A. K., Elmorshedy, M. F., Wang, S., Büker, M. S., & Kim, Y. S. (2021). Optimal planning and EMS design of PV based standalone rural microgrids. IEEE Access, 9, 32908-32930. https://doi.org/10.1109/ACCESS.2021.3060031
- Irshad, A. S., Ludin, G. A., Masrur, H., Ahmadi, M., Yona, A., Mikhaylov, A., & Senjyu, T. (2023). Optimization of grid-photovoltaic and battery hybrid system with most technically efficient PV technology after the performance analysis. Renewable Energy, 207, 714-730. https://doi.org/10.1016/j.renene.2023.03.062
- Golroodbari, S. Z., & Van Sark, W. (2020). Simulation of performance differences between offshore and land‐based photovoltaic systems. Progress in Photovoltaics: Research and Applications, 28(9), 873-886. https://doi.org/10.1002/pip.3276
- Arandian, B., Eslami, M., Khalid, S. A., Khan, B., Sheikh, U. U., Akbari, E., & Mohammed, A. H. (2022). An effective optimization algorithm for parameters identification of photovoltaic models. IEEE Access, 10, 34069-34084. https://doi.org/10.1109/ACCESS.2022.3161467
- Long, W., Wu, T., Xu, M., Tang, M., & Cai, S. (2021). Parameters identification of photovoltaic models by using an enhanced adaptive butterfly optimization algorithm. Energy, 229, 120750. https://doi.org/10.1016/j.energy.2021.120750
- Mubaarak, S., Zhang, D., Chen, Y., Liu, J., Wang, L., Yuan, R., & Li, M. (2020). Techno-economic analysis of grid-connected PV and fuel cell hybrid system using different PV tracking techniques. Applied Sciences, 10(23), 8515. https://doi.org/10.3390/app10238515
- Abdolrasol, M. G., Ayob, A., Mutlag, A. H., & Ustun, T. S. (2023). Optimal fuzzy logic controller based PSO for photovoltaic system. Energy Reports, 9, 427-434. https://doi.org/10.1016/j.egyr.2022.11.039
- Diab, A. A. Z., Sultan, H. M., Aljendy, R., Al-Sumaiti, A. S., Shoyama, M., & Ali, Z. M. (2020). Tree growth based optimization algorithm for parameter extraction of different models of photovoltaic cells and modules. IEEE Access, 8, 119668-119687. https://doi.org/10.1109/ACCESS.2020.3005236
- Ernst, M., Liu, X., Asselineau, C. A., Chen, D., Huang, C., & Lennon, A. (2024). Accurate modelling of the bifacial gain potential of rooftop solar photovoltaic systems. Energy Conversion and Management, 300, 117947. https://doi.org/10.1016/j.enconman.2023.117947
- Liu, H., Zhang, Y., Ge, S., Gu, C., & Li, F. (2019). Day-ahead scheduling for an electric vehicle PV-based battery swapping station considering the dual uncertainties. IEEE Access, 7, 115625-115636. https://doi.org/10.1109/ACCESS.2019.2935774
- Naser, A. T., Mohammed, K. K., Ab Aziz, N. F., binti Kamil, K., & Mekhilef, S. (2024). Improved coot optimizer algorithm-based MPPT for PV systems under complex partial shading conditions and load variation. Energy Conversion and Management: X, 22, 100565. https://doi.org/10.1016/j.ecmx.2024.100565
- Ibrahim, A. W., Shafik, M. B., Ding, M., Sarhan, M. A., Fang, Z., Alareqi, A. G., & Al-Rassas, A. M. (2020). PV maximum power-point tracking using modified particle swarm optimization under partial shading conditions. Chinese Journal of Electrical Engineering, 6(4), 106-121. https://doi.org/10.23919/CJEE.2020.000035
- Wu, A., Gong, R., Mao, J., Yu, X., He, J., & Li, E. X. (2024). Voltage Feed-Forward Control of Photovoltaic-Battery DC Microgrid Based on Improved Seeker Optimization Algorithm. IEEE Access, 12, 46067-46080. https://doi.org/10.1109/ACCESS.2024.3382134
- Bollipo, R. B., Mikkili, S., & Bonthagorla, P. K. (2020). Critical review on PV MPPT techniques: classical, intelligent and optimisation. IET Renewable Power Generation, 14(9), 1433-1452. https://doi.org/10.1049/iet-rpg.2019.1163
- Hanzaei, S. H., Gorji, S. A., & Ektesabi, M. (2020). A scheme-based review of MPPT techniques with respect to input variables including solar irradiance and PV arrays’ temperature. IEEE Access, 8, 182229-182239. https://doi.org/10.1109/ACCESS.2020.3028580
- Hussaian Basha, C. H., & Rani, C. (2020). Performance analysis of MPPT techniques for dynamic irradiation condition of solar PV. International Journal of Fuzzy Systems, 22(8), 2577-2598. https://doi.org/10.1007/s40815-020-00974-y
- Lopez, L., Lopez, I., Gomez-Cornejo, J., Aranzabal, I., & Eguia, P. (2025). Analysis of impact for PV-BES strategies in low-voltage distribution system. Electrical Engineering, 107(2), 2147-2162. https://doi.org/10.1007/s00202-024-02620-4
- Motahhir, S., Chouder, A., El Hammoumi, A., Benyoucef, A. S., El Ghzizal, A., Kichou, S., & Silvestre, S. (2020). Optimal energy harvesting from a multistrings PV generator based on artificial bee colony algorithm. IEEE Systems Journal, 15(3), 4137-4144. https://doi.org/10.1109/JSYST.2020.2997744
- Zaghba, L., Borni, A., Benbitour, M. K., Fezzani, A., Alwabli, A., Bajaj, M., & Ghoneim, S. S. (2024). Enhancing grid-connected photovoltaic system performance with novel hybrid MPPT technique in variable atmospheric conditions. Scientific Reports, 14(1), 8205. https://doi.org/10.1038/s41598-024-59024-4
- Shaheen, A. M., Ginidi, A. R., El-Sehiemy, R. A., & Ghoneim, S. S. (2020). A forensic-based investigation algorithm for parameter extraction of solar cell models. IEEE Access, 9, 1-20. https://doi.org/10.1109/ACCESS.2020.3046536
- Liu, H., Wang, S., Liu, G., Zhang, J., & Wen, S. (2020). SARAP algorithm of multi-objective optimal capacity configuration for WT-PV-DE-BES stand-alone microgrid. IEEE access, 8, 126825-126838. https://doi.org/10.1109/ACCESS.2020.3008553
- Premkumar, M., Jangir, P., Ramakrishnan, C., Nalinipriya, G., Alhelou, H. H., & Kumar, B. S. (2021). Identification of solar photovoltaic model parameters using an improved gradient-based optimization algorithm with chaotic drifts. IEEE Access, 9, 62347-62379. https://doi.org/10.1109/ACCESS.2021.3073821
- Pradhan, C., Senapati, M. K., Malla, S. G., Nayak, P. K., & Gjengedal, T. (2020). Coordinated power management and control of standalone PV-hybrid system with modified IWO-based MPPT. IEEE Systems Journal, 15(3), 3585-3596. https://doi.org/10.1109/JSYST.2020.3020275
- Angadi, S., Yaragatti, U. R., Suresh, Y., & Raju, A. B. (2021). System parameter based performance optimization of solar PV systems with perturbation based MPPT algorithms. Energies, 14(7), 2007. https://doi.org/10.3390/en14072007
- Revathy, S. R., Kirubakaran, V., Rajeshwaran, M., Balasundaram, T., Sekar, V. C., Alghamdi, S., & Anbese, E. M. (2022). Design and analysis of ANFIS–based MPPT method for solar photovoltaic applications. International Journal of Photoenergy, 2022(1), 9625564. https://doi.org/10.1155/2022/9625564
- Babu, D. V. S., Jayavani, L., Bhuvaneswari, T. R., Mageswaran, R., Kavin, K. S., & Kaliappan, K. (2024). IoT interfaced improved smart P&O MPPT assisted PV-wind based smart grid monitoring system. In 2024 7th International Conference on Circuit Power and Computing Technologies (ICCPCT), 1, 1078-1084. https://doi.org/10.1109/ICCPCT61902.2024.10673150
- Saberi, A., Niroomand, M., & Dehkordi, B. M. (2023). An improved P&O based MPPT for PV systems with reduced steady‐state oscillation. International Journal of Energy Research, 2023(1), 4694583. https://doi.org/10.1155/2023/4694583
- Moyo, R. T., Tabakov, P. Y., & Moyo, S. (2021). Design and modeling of the ANFIS-based MPPT controller for a solar photovoltaic system. Journal of Solar Energy Engineering, 143(4), 041002. https://doi.org/10.1115/1.4048882
- Ahmed, M., Abdelrahem, M., Harbi, I., & Kennel, R. (2020). An adaptive model-based MPPT technique with drift-avoidance for grid-connected PV systems. Energies, 13(24), 6656. https://doi.org/10.3390/en13246656
- Abdel-Rahim, O., & Wang, H. (2020). A new high gain DC-DC converter with model-predictive-control based MPPT technique for photovoltaic systems. CPSS Transactions on Power Electronics and Applications, 5(2), 191-200. https://doi.org/10.24295/CPSSTPEA.2020.00016
- Kavin, K. S., Subha Karuvelam, P., Devesh Raj, M., & Sivasubramanian, M. (2024). A novel KSK converter with machine learning MPPT for PV applications. Electric power components and systems, 1-19. https://doi.org/10.1080/15325008.2024.2346806
- Kavin, K. S., Karuvelam, P. S., Kumar, R. T., Sivasubramanian, M., Kavitha, P., & Priyadharsini, S. (2023, July). GWO Optimized PI Controller Fed PV Based Interleaved Luo Converter for EV Applications. In 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT)(pp. 1-6). IEEE. https://doi.org/10.1109/ICCCNT56998.2023.10307340
- Alshabi, M., Ghenai, C., Bettayeb, M., & Ahmad, F. F. (2021). Estimating one-diode-PV model using autonomous groups particle swarm optimization. IAES International Journal of Artificial Intelligence, 10(1), 166. DOI: 10.11591/ijai.v10.i1.pp166-174
- Singh, A., Sharma, A., Rajput, S., Bose, A., & Hu, X. (2022). An investigation on hybrid particle swarm optimization algorithms for parameter optimization of PV cells. Electronics, 11(6), 909. https://doi.org/10.3390/electronics11060909
- El Hariz, Z., Hicham, A., & Mohammed, D. (2022). A novel optimiser of MPPT by using PSO-AG and PID controller. International Journal of Ambient Energy, 43(1), 5199-5206. https://doi.org/10.1080/01430750.2021.1934116
- Han, F., Abdelaziz, I. I. M., Ghazali, K. H., Zhao, Y., & Li, N. (2023). Optimized range-free localization scheme using autonomous groups particles swarm optimization for anisotropic wireless sensor networks. IEEE Access, 11, 26906-26920. https://doi.org/10.1109/ACCESS.2023.3257567
- Shehata, A. A., Refaat, A., Ahmed, M. K., & Korovkin, N. V. (2021). Optimal placement and sizing of FACTS devices based on Autonomous Groups Particle Swarm Optimization technique. Archives of Electrical Engineering, 70(1), 161-172. DOI 10.24425/aee.2021.136059
- David, M., Boland, J., Cirocco, L., Lauret, P., & Voyant, C. (2021). Value of deterministic day-ahead forecasts of PV generation in PV+ Storage operation for the Australian electricity market. Solar Energy, 224, 672-684. https://doi.org/10.1016/j.solener.2021.06.011
- Georgiou, G. S., Christodoulides, P., & Kalogirou, S. A. (2020). Optimizing the energy storage schedule of a battery in a PV grid-connected nZEB using linear programming. Energy, 208, 118177. https://doi.org/10.1016/j.energy.2020.118177
- Sangaiah, A. K., Tirkolaee, E. B., Goli, A., & Dehnavi-Arani, S. (2020). Robust optimization and mixed-integer linear programming model for LNG supply chain planning problem. Soft computing, 24(11), 7885-7905. https://doi.org/10.1007/s00500-019-04010-6
- Ramli, S. P., Mokhlis, H., Wong, W. R., Muhammad, M. A., Mansor, N. N., & Hussain, M. H. (2021). Optimal coordination of directional overcurrent relay based on combination of improved particle swarm optimization and linear programming considering multiple characteristics curve. Turkish Journal of Electrical Engineering and Computer Sciences, 29(3), 1765-1780. Doi: 10.3906/elk-2008-23
- Daqaq, F., Ouassaid, M., Kamel, S., Ellaia, R., & El-Naggar, M. F. (2022). A novel chaotic flower pollination algorithm for function optimization and constrained optimal power flow considering renewable energy sources. Frontiers in Energy Research, 10, 941705. https://doi.org/10.3389/fenrg.2022.941705
- Daqaq, F., Ellaia, R., & Ouassaid, M. (2020, November). A constrained chaotic flower pollination algorithm for solving ORPD problem. In 2020 international symposium on advanced electrical and communication technologies (ISAECT)(pp. 1-6). IEEE. https://doi.org/10.1109/ISAECT50560.2020.9523712
- Mergos, P. E., & Yang, X. S. (2021). Flower pollination algorithm parameters tuning. Soft computing, 25(22), 14429-14447. https://doi.org/10.1007/s00500-021-06230-1
- Khluabwannarat, P., & Puangdownreong, D. (2021). Optimal fractional-order PID controller design for BLDC motor speed control system by using parallel flower pollination algorithm. An International Journal of Research and Surveys, 15(2). Doi: 10.24507/icicel.15.02.165
- Dhivya, S., & Arul, R. (2021, April). Improved flower pollination algorithm-based optimal placement and sizing of DG for practical indian 52 bus system. In 2021 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS), 1-5. https://doi.org/10.1109/IEMTRONICS52119.2021.9422562
- Cortes-Vega, D., Alazki, H., & Rullan-Lara, J. L. (2022). Current sensorless MPPT control for PV systems based on robust observer. Applied Sciences, 12(9), 4360. https://doi.org/10.3390/app12094360
- Endiz, M. S. (2024). Design and implementation of microcontroller-based solar charge controller using modified incremental conductance MPPT algorithm. Journal of Radiation Research and Applied Sciences, 17(2), 100938. https://doi.org/10.1016/j.jrras.2024.100938
- Harrison, A., Alombah, N. H., & de Dieu Nguimfack Ndongmo, J. (2023). A new hybrid MPPT based on incremental conductance‐integral back stepping controller applied to a PV system under fast‐changing operating conditions. International Journal of Photo energy, 2023(1), 9931481. https://doi.org/10.1155/2023/9931481
- Shang, L., Guo, H., & Zhu, W. (2020). An improved MPPT control strategy based on incremental conductance algorithm. Protection and Control of Modern Power Systems, 5(2), 1-8. https://doi.org/10.1186/s41601-020-00161-z
- Feroz Mirza, A., Mansoor, M., Ling, Q., Khan, M. I., & Aldossary, O. M. (2020). Advanced variable step size incremental conductance MPPT for a standalone PV system utilizing a GA-tuned PID controller. Energies, 13(16), 4153. https://doi.org/10.3390/en13164153
- Krishnan G, S., Kinattingal, S., Simon, S. P., & Nayak, P. S. R. (2020). MPPT in PV systems using ant colony optimisation with dwindling population. IET Renewable Power Generation, 14(7), 1105-1112. https://doi.org/10.1049/iet-rpg.2019.0875
- González-Castaño, C., Restrepo, C., Kouro, S., & Rodriguez, J. (2021). MPPT algorithm based on artificial bee colony for PV system. IEEE Access, 9, 43121-43133. https://doi.org/10.1109/ACCESS.2021.3066281
- Chao, K. H., & Rizal, M. N. (2021). A hybrid MPPT controller based on the genetic algorithm and ant colony optimization for photovoltaic systems under partially shaded conditions. Energies, 14(10), 2902. https://doi.org/10.3390/en14102902
- Xia, K., Li, Y., & Zhu, B. (2024). Improved photovoltaic MPPT algorithm based on ant colony optimization and fuzzy logic under conditions of partial shading. IEEE Access, 12, 44817-44825. https://doi.org/10.1109/ACCESS.2024.3381345
- Huang, K. H., Chao, K. H., & Lee, T. W. (2023). An improved photovoltaic module array global maximum power tracker combining a genetic algorithm and ant colony optimization. Technologies, 11(2), 61. https://doi.org/10.3390/technologies11020061
- Charfeddine, S., Alharbi, H., Jerbi, H., Kchaou, M., Abbassi, R., & Leiva, V. (2022). A stochastic optimization algorithm to enhance controllers of photovoltaic systems. Mathematics, 10(12), 2128. https://doi.org/10.3390/math10122128
- Rezk, H., & Fathy, A. (2020). Stochastic fractal search optimization algorithm based global MPPT for triple-junction photovoltaic solar system. Energies, 13(18), 4971. https://doi.org/10.3390/en13184971
- Fu, C., Zhang, L., & Dong, W. (2022). Research and application of Mppt control strategy based on improved slime mold algorithm in shaded conditions. Electronics, 11(14), 2122. https://doi.org/10.3390/electronics11142122
- Srinivasan, R., & Ramalingam Balamurugan, C. (2022). Deep neural network based MPPT algorithm and PR controller based SMO for grid connected PV system. International Journal of Electronics, 109(4), 576-595. https://doi.org/10.1080/00207217.2021.1914192
- Ramadan, A., Kamel, S., & Ibrahim, A. (2021). Parameters estimation of photovoltaic cells using self-adaptive multi-population Rao optimization algorithm. Aswan University Journal of Sciences and Technology, 1(1), 26-40.
- Rao, R. V., & Pawar, R. B. (2020). Self-adaptive multi-population Rao algorithms for engineering design optimization. Applied Artificial Intelligence, 34(3), 187-250. https://doi.org/10.1080/08839514.2020.1712789
- Federici, L., Benedikter, B., & Zavoli, A. (2020, July). EOS: a parallel, self-adaptive, multi-population evolutionary algorithm for constrained global optimization. In 2020 IEEE congress on evolutionary computation (CEC)(pp. 1-10). IEEE. https://doi.org/10.1109/CEC48606.2020.9185800
- Kumar, V., & Yadav, S. M. (2020). Self-adaptive multi-population-based Jaya algorithm to optimize the cropping pattern under a constraint environment. Journal of Hydro informatics, 22(2), 368-384. https://doi.org/10.2166/hydro.2019.087
- Fathy, A., Rezk, H., & Yousri, D. (2020). A robust global MPPT to mitigate partial shading of triple-junction solar cell-based system using manta ray foraging optimization algorithm. Solar Energy, 207, 305-316. https://doi.org/10.1016/j.solener.2020.06.108
- Aly, M., & Rezk, H. (2021). A MPPT based on optimized FLC using manta ray foraging optimization algorithm for thermo‐electric generation systems. International Journal of Energy Research, 45(9), 13897-13910. https://doi.org/10.1002/er.6728
- Mahmoud, M. M., Atia, B. S., Abdelaziz, A. Y., & Aldin, N. A. N. (2022). Dynamic performance assessment of PMSG and DFIG-based WECS with the support of manta ray foraging optimizer considering MPPT, pitch control, and FRT capability issues. Processes, 10(12), 2723. https://doi.org/10.3390/pr10122723
- Xie, R., Wu, S., & Yang, B. (2023, July). MPPT design for hybrid PV-TEG system under partial shading condition via Manta Ray Foraging Optimization. In 2023 5th International Conference on Power and Energy Technology (ICPET)(pp. 765-770). IEEE. https://doi.org/10.1109/ICPET59380.2023.10367668
- Alturki, F. A., Omotoso, H. O., Al-Shamma’a, A. A., Farh, H. M., & Alsharabi, K. (2020). Novel manta rays foraging optimization algorithm based optimal control for grid-connected PV energy system. IEEE Access, 8, 187276-187290. https://doi.org/10.1109/ACCESS.2020.3030874
- Saadaoui, D., Elyaqouti, M., Assalaou, K., & Lidaighbi, S. (2021). Parameters optimization of solar PV cell/module using genetic algorithm based on non-uniform mutation. Energy Conversion and Management: X, 12, 100129. https://doi.org/10.1016/j.ecmx.2021.100129
- Zhao, J., He, K., Kang, L., & Wang, X. (2025). Genetic algorithm with enhanced non-uniform mutation strategy for high-order polynomial optimization in temperature drift compensation of quartz flexible accelerometers. Sensors and Actuators A: Physical, 387, 116371. https://doi.org/10.1016/j.sna.2025.116371
- Hassan, A., Bass, O., & Masoum, M. A. (2023). An improved genetic algorithm based fractional open circuit voltage MPPT for solar PV systems. Energy Reports, 9, 1535-1548. https://doi.org/10.1016/j.egyr.2022.12.088
- de Oliveira, F. M., Brandt, M. H. M., Salvadori, F., Izquierdo, J. E. E., Cavallari, M. R., & Ando Junior, O. H. (2024). Development of an MPPT-based genetic algorithm for photovoltaic systems versus classical MPPT techniques in scenarios with partial shading. Inventions, 9(3), 64. https://doi.org/10.3390/inventions9030064
- Hilali, A., Mardoude, Y., Essahlaoui, A., Rahali, A., & El Ouanjli, N. (2022). Migration to solar water pump system: Environmental and economic benefits and their optimization using genetic algorithm Based MPPT. Energy Reports, 8, 10144-10153. https://doi.org/10.1016/j.egyr.2022.08.017
- Eltamaly, A. M. (2021). A novel musical chairs algorithm applied for MPPT of PV systems. Renewable and Sustainable Energy Reviews, 146, 111135. https://doi.org/10.1016/j.rser.2021.111135
- Eltamaly, A. M., & Rabie, A. H. (2023). A novel musical chairs optimization algorithm. Arabian Journal for Science and Engineering, 48(8), 10371-10403. https://doi.org/10.1007/s13369-023-07610-5
- Alshareef, M. J. (2025). An enhanced fractional open circuit voltage MPPT method for rapid and precise MPP tracking in standalone photovoltaic systems. IEEE Access. https://doi.org/10.1109/ACCESS.2025.3543327
- Eltamaly, A. M., & Almutairi, Z. A. (2025). A novel star-nosed mole optimization algorithm applied for MPPT of PV systems. Scientific Reports, 15(1), 17807. https://doi.org/10.1038/s41598-025-02938-4
- Eltamaly, A. M., & Almutairi, Z. A. (2025). Synergistic Coordination Between PWM Inverters and DC-DC Converters for Power Quality Improvement of Three-Phase Grid-Connected PV Systems. Sustainability, 17(8), 3748. https://doi.org/10.3390/su17083748
- Ramadan, A. E., Kamel, S., Khurshaid, T., Oh, S. R., & Rhee, S. B. (2021). Parameter extraction of three diode solar photovoltaic model using improved grey wolf optimizer. Sustainability, 13(12), 6963. https://doi.org/10.3390/su13126963
- Hou, Y., Gao, H., Wang, Z., & Du, C. (2022). Improved grey wolf optimization algorithm and application. Sensors, 22(10), 3810. https://doi.org/10.3390/s22103810
- Liu, J., Wei, X., & Huang, H. (2021). An improved grey wolf optimization algorithm and its application in path planning. IEEE Access, 9, 121944-121956. https://doi.org/10.1109/ACCESS.2021.310897.
- Taha, S. A., Al-Sagar, Z. S., Abdulsada, M. A., Alruwaili, M., & Ibrahim, M. A. (2025). Design of an efficient MPPT topology based on a grey wolf optimizer-particle swarm optimization (GWO-PSO) algorithm for a grid-tied solar inverter under variable rapid-change irradiance. Energies, 18(8), 1997. https://doi.org/10.3390/en18081997
- Naserbegi, A., Aghaie, M., & Zolfaghari, A. (2020). Implementation of Grey Wolf Optimization (GWO) algorithm to multi-objective loading pattern optimization of a PWR reactor. Annals of Nuclear Energy, 148, 107703. https://doi.org/10.1016/j.anucene.2020.107703
- Eltamaly, A. M., Al-Saud, M. S., & Abokhalil, A. G. (2020). A novel scanning bat algorithm strategy for maximum power point tracker of partially shaded photovoltaic energy systems. Ain Shams Engineering Journal, 11(4), 1093-1103. https://doi.org/10.1016/j.asej.2020.02.015
- Ge, X., Ahmed, F. W., Rezvani, A., Aljojo, N., Samad, S., & Foong, L. K. (2020). Implementation of a novel hybrid BAT-Fuzzy controller based MPPT for grid-connected PV-battery system. Control engineering practice, 98, 104380. https://doi.org/10.1016/j.conengprac.2020.104380
- de Jesús Rubio, J. (2023). Bat algorithm based control to decrease the control energy consumption and modified bat algorithm based control to increase the trajectory tracking accuracy in robots. Neural Networks, 161, 437-448. https://doi.org/10.1016/j.neunet.2023.02.010
- Amalo, K. A., Birninkudu, S. I., Bukata, B. B., Salawudeen, A. T., & Ahmad, A. A. (2020, March). Cultured bat algorithm for optimized MPPT tracking under different shading conditions. In 2020 International Conference in mathematics, computer engineering and computer science (ICMCECS)(pp. 1-8). IEEE. https://doi.org/10.1109/ICMCECS47690.2020.246985
- Kadhim, K. H. Solar PV System for Water Pumping Incorporating an MPPT based Bat Optimization Circuits and Systems. Doi: 10.5373/JARDCS/V12SP1/20201130
- Gao, B., Yang, H., Lin, H. C., Wang, Z., Zhang, W., & Li, H. (2022). A hybrid improved whale optimization algorithm with support vector machine for short-term photovoltaic power prediction. Applied Artificial Intelligence, 36(1), 2014187. https://doi.org/10.1080/08839514.2021.2014187
- Percin, H. B., & Caliskan, A. (2023). Whale optimization algorithm based MPPT control of a fuel cell system. International journal of hydrogen energy, 48(60), 23230-23241. https://doi.org/10.1016/j.ijhydene.2023.03.180
- Rana, N., Latiff, M. S. A., Abdulhamid, S. I. M., & Chiroma, H. (2020). Whale optimization algorithm: a systematic review of contemporary applications, modifications and developments. Neural Computing and Applications, 32(20), 16245-16277. https://doi.org/10.1007/s00521-020-04849-z
- Tiwari, A., & Agarwal, R. (2023). Optimal control for a photovoltaic integrated grid system using PSO and modified whale optimization to enhance power quality. Engineering Research Express, 5(2), 025001. Doi:1088/2631-8695/acc929
- Liu, Y. W., Feng, H., Li, H. Y., & Li, L. L. (2021). An improved whale algorithm for support vector machine prediction of photovoltaic power generation. Symmetry, 13(2), 212. https://doi.org/10.3390/sym13020212
- Kashefi, H., Sadegheih, A., Mostafaeipour, A., & Mohammadpour Omran, M. (2021). Parameter identification of solar cells and fuel cell using improved social spider algorithm. COMPEL-The international journal for computation and mathematics in electrical and electronic engineering, 40(2), 142-172. https://doi.org/10.1108/COMPEL-12-2019-0495
- Koshkarbay, N., Mohammed, K. K., Mekhilef, S., Kuttybay, N., Almen, D., Saymbetov, A., & Nurgaliyev, M. (2025). Improved MPPT technology for PV systems using Social Spider optimization (SSO): Efficient handling of partial shading and load variations. Electric Power Systems Research, 247, 111822. https://doi.org/10.1016/j.epsr.2025.111822
- Fathy, A., Kaaniche, K., & Alanazi, T. M. (2020). Recent approach based social spider optimizer for optimal sizing of hybrid PV/wind/battery/diesel integrated microgrid in aljouf region. IEEE Access, 8, 57630-57645. https://doi.org/10.1109/ACCESS.2020.2982805
- Adhvaryyu, S., & Adhvaryyu, P. K. (2020). Application of bio-inspired social spider algorithm in multi-area economic emission dispatch of solar, wind and CHP-based power system. Soft Computing, 24(13), 9611-9624. https://doi.org/10.1007/s00500-019-04468-4
- Pappu, S. L., & Janamala, V. (2023). A multi-objective hunter-prey optimization for optimal integration of capacitor banks and photovoltaic distribution generation units in radial distribution systems. ITEGAM-JETIA, 9(43), 42-53. https://doi.org/10.5935/jetia.v9i43.907
- Li, Z., & Fu, C. (2024). Critical Analysis and Application of Enhanced Hunter-Prey Algorithm for MPPT in Photovoltaic Systems under Complex Partial Shading Conditions. http://dx.doi.org/10.21203/rs.3.rs-4460931/v1
- Ranga, M. R., RaoBathina, V., & Kotni, S. (2024, July). A review of solar cell parameters extraction using metaheuristic optimization methods based on various diode models. In 2024 International Conference on Computational Intelligence for Green and Sustainable Technologies (ICCIGST)(pp. 1-6). IEEE. https://doi.org/10.1109/ICCIGST60741.2024.10717470
- Li, Z., Fu, C., Zhang, L., & Zhao, J. (2024). Comprehensive Analysis of Improved Hunter–Prey Algorithms in MPPT for Photovoltaic Systems Under Complex Localized Shading Conditions. Electronics, 13(21), 4148. https://doi.org/10.3390/electronics13214148
- Bousselamti, L., Ahouar, W., & Cherkaoui, M. (2020, September). Mono-objective optimization of PV-CSP system using PSO algorithm. In 2020 IEEE 4th International Conference on Intelligent Energy and Power Systems (IEPS)(pp. 186-189). IEEE. https://doi.org/10.1109/IEPS51250.2020.9263232
- Pervez, I., Shams, I., Mekhilef, S., Sarwar, A., Tariq, M., & Alamri, B. (2021). Most valuable player algorithm based maximum power point tracking for a partially shaded PV generation system. IEEE Transactions on Sustainable Energy, 12(4), 1876-1890. https://doi.org/10.1109/TSTE.2021.3069262
- Liu, H., Shi, Y., & Zhang, W. (2021, August). A MPPT Control Method Based on the Improved Wind-Driven Optimization. In 2021 IEEE 16th Conference on Industrial Electronics and Applications (ICIEA),995-1000. https://doi.org/10.1109/ICIEA51954.2021.9516244
- Diab, A. A. Z., Sultan, H. M., Do, T. D., Kamel, O. M., & Mossa, M. A. (2020). Coyote optimization algorithm for parameters estimation of various models of solar cells and PV modules. IEEE Access, 8, 111102-111140. https://doi.org/10.1109/ACCESS.2020.3000770
- Priyadarshi, N., Padmanaban, S., Holm-Nielsen, J. B., Blaabjerg, F., & Bhaskar, M. S. (2019). An experimental estimation of hybrid ANFIS–PSO-based MPPT for PV grid integration under fluctuating sun irradiance. IEEE Systems Journal, 14(1), 1218-1229. https://doi.org/10.1109/JSYST.2019.2949083
- Eltamaly, A. M., & Alotaibi, M. A. (2021). Novel fuzzy-swarm optimization for sizing of hybrid energy systems applying smart grid concepts. IEEE Access, 9, 93629-93650. https://doi.org/10.1109/ACCESS.2021.3093169
- Moshksar, E., Ghanbari, T., Samet, H., & Guay, M. (2018). Estimation-based extremum-seeking control: A real-time approach for improving energy efficiency in photovoltaic systems. IEEE systems journal, 13(3), 3141-3152. https://doi.org/10.1109/JSYST.2018.2868125
- Guo, K., Cui, L., Mao, M., Zhou, L., & Zhang, Q. (2020). An improved gray wolf optimizer MPPT algorithm for PV system with BFBIC converter under partial shading. IEEE Access, 8, 103476-103490. https://doi.org/10.1109/ACCESS.2020.2999311
- Senapati, M. K., Pradhan, C., Padmanaban, S., & Al Zaab, O. (2025). Photovoltaic MPPT performance adaptability to partial shading resilience and load variations with modified adaptive jaya optimization. IEEE Transactions on Consumer Electronics. https://doi.org/10.1109/TCE.2025.3532660
- Eltamaly, A. M., Al-Saud, M. S., & Abokhalil, A. G. (2020). A novel bat algorithm strategy for maximum power point tracker of photovoltaic energy systems under dynamic partial shading. IEEE Access, 8, 10048-10060. https://doi.org/10.1109/ACCESS.2020.2964759
|