Photovoltaic MPPT Control Strategy Based on Tuna Swarm Optimization TSO Algorithm
DOI:
https://doi.org/10.24237/djes.2026.19305Keywords:
Maximum Power Point Tracking (MPPT), Tuna Swarm Optimization, Partial Shading, Photovoltaic Systems, Hybrid AlgorithmAbstract
In photovoltaic systems, multiple power peaks imitated by the partial shading led to trapping of conventional maximum power point tracking MPPT algorithms such as Perturb and Observe (P&O) at local maxima resulting in about 30–50% power loss. A hybrid Tuna Swarm Optimization-Perturb and Observe (TSO-P&O) algorithm is proposed in this paper where the location of global maximum power point (MPP) estimated by using TSO and local refinement provided through P&O based on a sudden change from environmental with an adaptive restart mechanism. TSO-P&O outperforms P&O, Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Grey Wolf Optimizer (GWO) validated by MATLAB/Simulink. It reaches a maximum static shading efficiency of 99.06% and dynamic shading convergence in as fast as 0.071s (98.52%) with the same equipment, respectively; It also displays a minimized steady-state oscillation (0.42% standard deviation) and superior statistical performance at p < 0.05 as well. The algorithm is very suitable for real-time embedded implementation, with a runtime of 2.5 ms per iteration and a memory footprint of only 5 KB. Experimental validation of the proposed algorithm against a hardware-prototype, extension to larger PV arrays experiencing more complex shading patterns, and hybridizations with learning-based methods could yield additional opportunities for enhanced performance in future work
Downloads
References
[1] S. Xie, X. Chu, M. Zheng, and C. Liu, "Ship predictive collision avoidance method based on an improved beetle antennae search algorithm," Ocean Engineering, vol. 192, Art. no. 106542, Nov 2019. doi: 10.1016/j.oceaneng.2019.106542.
[2] Y. Fan, J. Shao, and G. Sun, "Optimized PID controller based on beetle antennae search algorithm for electro-hydraulic position servo control system," Sensors, vol. 19, no. 12, Art. no. 2727, Jun 2019. doi: 10.3390/s19122727.
[3] K. Balachandran and K. Ramasamy, "Maximum power point tracking based on a self-adaptive neural network combined with incremental conductance," Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, vol. 44, no. 3, pp. 7895–7913, Aug 2022. doi: 10.1080/15567036.2022.2115168.
[4] J. J. Wang, K. Wei, M. D. Ansari, M. S. A. Ansari, and A. Verma, "Photovoltaic power generation systems and applications using particle swarm optimization algorithms," Electrica, vol. 22, no. 3, pp. 403-409, Sep 2022. doi: 10.5152/electrica.2022.22086.
[5] M. Atia et al., "Maximum power harvesting from a PV system using an improved two-stage MPPT scheme based on incremental conductance algorithm and integral controller," International Journal of Modelling, Identification and Control, vol. 40, no. 2, pp. 176–191, July 2022. doi: 10.1504/IJMIC.2022.124722.
[6] Q. Li et al., "An improved perturbation and observation maximum power point tracking algorithm based on a PV module four-parameter model for higher efficiency," Applied Energy, vol. 195, pp. 523–537, Jun 2017. doi: 10.1016/j.apenergy.2017.03.062.
[7] Y. Wang, S. Dai, P. Liu, and X. Zhao, "A hybrid particle swarm optimization with butterfly optimization algorithm based maximum power point tracking for photovoltaic array under partial shading conditions," Sustainability, vol. 15, no. 16, Art. no. 12402, Aug 2023. doi: 10.3390/su151612402.
[8] S. Makhloufi and S. Mekhilef, "Logarithmic PSO-Based Global/Local Maximum Power Point Tracker for Partially Shaded Photovoltaic Systems," in IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 10, no. 1, pp. 375-386, Feb 2022, doi: 10.1109/JESTPE.2021.3073058.
[9] Z. K. Fan, A. Setianingrum, K.-L. Lian, and S. Suwarno, "A hybrid approach for photovoltaic maximum power tracking under partial shading using honey badger and genetic algorithms," Energies, vol. 17, no. 16, Art. no. 3935, Aug 2024. doi: 10.3390/en17163935.
[10] F. Abdelmalek, H. Afghoul, F. Krim, M. Bajaj, and V. Blazek, "Experimental validation of novel hybrid Grey Wolf Equilibrium Optimization for MPPT to improve the efficiency of solar photovoltaic system," Results in Engineering, vol. 25, Art. no. 103831, Mar 2025. doi: 10.1016/j.rineng.2024.103831.
[11] K. Xia, Y. Li, and B. Zhu, "Improved Photovoltaic MPPT Algorithm Based on Ant Colony Optimization and Fuzzy Logic Under Conditions of Partial Shading," IEEE Access, vol. 12, pp. 44817–44825, Mar 2024. doi: 10.1109/ACCESS.2024.3381345.
[12] L. Xie et al., "Tuna swarm optimization: a novel swarm-based metaheuristic algorithm for global optimization," Computational Intelligence and Neuroscience, vol. 2021, No. 1, Art. no. 9210050, Oct 2021. doi: 10.1155/2021/9210050.
[13] Q. Wang and X. Chang, "Maximum power point tracking of PV system under partial shading conditions based on TSO-IP&O algorithm," in Proc. 3rd Int. Conf. Energy, Power and Electrical Engineering (EPEE), Wuhan, China, Sep 2023, pp. 155–159. doi: 10.1109/EPEE59859.2023.10351794.
[14] X. Li, Y. He, and M. Li, "Research on photovoltaic maximum power point tracking control based on improved tuna swarm algorithm and adaptive perturbation observation method," Energies, vol. 17, no. 12, Art. no. 2985, Jun 2024. doi: 10.3390/en17122985.
[15] M. L. Katche et al., " A Comprehensive Review of Maximum Power Point Tracking (MPPT) Techniques Used in Solar PV Systems," Energies, vol. 16, Art. no. 2206, Feb 2023. doi.org/10.3390/en16052206.
[16] I. Shams, S. Mekhilef, and K. S. Tey, "Improved social ski driver-based MPPT for partial shading conditions hybridized with constant voltage method for fast response to load variations," IEEE Transactions on Sustainable Energy, vol. 12, no. 4, pp. 2255–2267, Jun 2021. doi: 10.1109/TSTE.2021.3088119.
[17] Y. Zhu, M. K. Kim, and H. Wen, "Simulation and analysis of perturbation and observation-based self-adaptable step size maximum power point tracking strategy with low power loss for photovoltaics," Energies, vol. 12, no. 1, Art. No. 92, 2019. doi.org/10.3390/en12010092.
[18] S. R. Pendem, S. Mikkili, and V. V. Katru, "Total-cross-tied configuration of MICs for enhancing the performance of PV D-MPPT systems under various PSCs using P&O algorithm," in Proc. 15th IEEE India Counc. Int. Conf. (INDICON), Dec 2018, pp. 1–6. doi: 10.1109/INDICON45594.2018.8987172.
[19] M. M. A. Awan and F. G. Awan, "Improvement of maximum power point tracking perturb and observe algorithm for a standalone solar photovoltaic system," Mehran University Research Journal of Engineering and Technology, vol. 36, no. 3, pp. 501–510, July 2017. doi: 10.22581/muet1982.1703.07.
[20] S. Belhimer, M. Haddadi, and A. Mellit, "Design of a quadratic boost converter for a standalone PV system based on INC MPPT algorithm," in Proc. Int. Conf. Electronics Engineering and Renewable Energy, Singapore, 2018, pp. 447–453. doi.org/10.1007/978-981-13-1405-6_53.
[21] S S. Prajapati and E. Fernandez, "Performance Evaluation of Membership Function on Fuzzy Logic Model for Solar PV array," 2020 IEEE International Conference on Computing, Power and Communication Technologies (GUCON), Greater Noida, India, 2020, pp. 609-613, doi: 10.1109/GUCON48875.2020.9231202.
[22] S. A. Mohamed, M. A. Tolba, A. A. Eisa, and A. M. El-Rifaie, "Comprehensive modeling and control of grid-connected hybrid energy sources using an MPPT controller," Energies, vol. 14, no. 16, Art. no. 5142, 2021. doi: 10.3390/en14165142.
[23] M. Y. Worku et al., "Comprehensive review of recent maximum power point tracking techniques for photovoltaic systems under partial shading," Sustainability, vol. 15, Art. no. 11132, 2023. doi.org/10.3390/su151411132.
[24] X. Zhang, B. Zhao, H. Cui, G. Zhao, Y. Li, and Y. Huangfu, "A hybrid global maximum power point tracking control method based on particle swarm optimization (PSO) and perturbation and observation (P&O)," Electric Power Systems Research, vol. 248, Art. no. 111967, Nov 2025. doi: 10.1016/j.epsr.2025.111967.
[25] A. Demirci, I. Dagal, S. M. Tercan, H. Gundogdu, M. Terkes, and U. Cali, "Enhanced ANN-Based MPPT for photovoltaic systems: Integrating metaheuristic and analytical algorithms for optimal performance under partial shading," IEEE Access, vol. 13, pp. 92783–92799, May 2025. doi: 10.1109/ACCESS.2025.3572554.
[26] X. Guo, W. P. Li, Y. Pan, and J. Liu, "A novel power switching control method of the wind power MPPT system based on the switching system theory," in Proc. Int. Electron. Symp. (IES), 2022, pp. 79–84. doi: 10.1109/IES55876.2022.9888494.
[27] M. Padmanaban, C. Sasi, P. Parthasarathy, and N. Pachaivannan, "An improved BAS MPPT algorithm in DC–DC converter for grid connected SPVS with PQ enhancement," Sādhanā, vol. 48, Art. no. 126, Jul 2023. doi.org/10.1007/s12046-023-02155-7.
[28] M. Mao, L. Zhang, M. Musembi, B. Chong, and Q. Duan, "Artificial fish swarm algorithm based-maximum power generation for grid-connected PV panels," in Proc. 19th International Conference on Computer Modelling & Simulation (UKSim), Cambridge, UK, 2017. pp. 149-154. doi:10.1109/UKSIM.2017.13.
[29] F. M. de Oliveira, M. H. M. Brandt, F. Salvadori, J. E. E. Izquierdo, M. R. Cavallari, and O. H. Ando Junior, "Development of an MPPT-based genetic algorithm for photovoltaic systems versus classical MPPT techniques in scenarios with partial shading," Inventions, vol. 9, no. 3, Art. no. 64, Jun 2024. doi: 10.3390/inventions9030064.
[30] S. Vijayakumar and C. Govindaraju, "Generation of maximum power in grid connected PV system based MPPT control using hybrid elephant herding optimization algorithm," Electric Power Components and Systems, vol. 50, no. 6–7, pp. 301–317, Nov 2022. doi: 10.1080/15325008.2022.2136293.
[31] T. Imtiaz, B. H. Khan, and N. Khanam, "Fast and improved PSO (FIPSO)-based deterministic and adaptive MPPT technique under partial shading conditions," IET Renewable Power Generation, vol. 14, no. 16, pp. 3164–3171, Sep 2020. doi: 10.1049/iet-rpg.2020. 0039.
[32] A. X. Y. Mah et al., "Optimization of photovoltaic-based microgrid with hybrid energy storage: A P-graph approach," Energy, vol. 233, Art. no. 121088, Oct 2021. doi: 10.1016/j.energy.2021.121088.
[33] A. S. Kaittan, Z. A. Obaid, and A. N. Abdullah, "Development of a comprehensive frequency control model for the GB power system: A research and educational tool," DJES, vol. 18, no. 1, pp. 136–154, Mar 2025. doi: 10.24237/djes.2025.18108.
[34] Vinod, R. Kumar, and S.K. Singh, " Solar photovoltaic modeling and simulation: As a renewable energy solution," Energy Reports, vol. 4, pp. 701-712, Nov 2018. doi.org/10.1016/j.egyr.2018.09.008.
[35] S. Kamdale and V. Bhole, "Enhanced voltage regulation in solar PV systems using ANN-based MPPT control for DC-DC converter," in Proc. Asian Conf. Innovation in Technology (ASIANCON), Ravet IN, India, 2023, pp. 1–5. doi: 10.1109/ASIANCON58793.2023.10269921.
[36] R. Bhattacharjee, A. Deb, and N. Adhikary, "A comparative performance analysis of P&O and ANN algorithm based MPPT energy harvesting in PV systems," in Proc. Int. Conf. Computing, Systems and Information Technology for Sustainable Solutions (CSITSS), Bangalore, India, 2023, pp. 1–6. doi: 10.1109/CSITSS60515.2023.10334115.
[37] M. S. Wasim, "A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditions," Energy Reports, vol. 8, pp. 4871–4898, Nov 2022. doi.org/10.1016/j.egyr.2022.03.175.
[38] S. T. Bahar and H. Qiu, “Amelioration of Traditional PI Boost Converter Utilizing Linear Active Disturbance Rejection Controller - Mode Predictive Control Strategy,” International Journal of Robotics and Control Systems, vol. 6, no. 1, pp. 305–323, Jan 2026. doi: 10.31763/ijrcs.v6i1.2364.
[39] M. A. Ebrahim, A. Osama, K. M. Kotb, and F. Bendary, "Whale inspired algorithm based MPPT controllers for grid-connected solar photovoltaic system," Energy Procedia, vol. 162, pp. 77–86, Apr 2019. doi: 10.1016/j.egypro.2019.04.009.
[40] C. G. Lee et al., "Analysis of electrical and thermal characteristics of PV array under mismatching conditions caused by partial shading and short circuit failure of bypass diodes," Energy, vol. 218, Art. no. 119480, Mar 2021. doi: 10.1016/j.energy.2020.119480.
[41] H. Wang and J. Shen, "Analysis of the characteristics of solar cell array based on MATLAB/Simulink in solar unmanned aerial vehicle," IEEE Access, vol. 6, pp. 21195–21201, Apr 2018. doi: 10.1109/ACCESS.2018.2802927.
[42] D. Sera, R. Teodorescu, and P. Rodriguez, "PV panel model based on datasheet values," in Proc. IEEE Int. Symp. Industrial Electronics (ISIE), Vigo, Spain, Jun 2007, pp. 2392–2396. doI: 10.1109/ISIE.2007.4374981.
[43] H. J. Mohammed, A. S. Kaittan, L. R. Gainullina, and A. I. Jaber, "Effective temperature on the electric breakdown of transformer oil," in Proc. Conf. Young Researchers in Electrical and Electronic Engineering (ElCon), 2024. doi: 10.1109/ElCon61730.2024.10468080.
[44] M. V. Dambhare, B. Butey, and S. V. Moharil, "Solar photovoltaic technology: A review of different types of solar cells and its future trends," Journal of Physics: Conference Series, vol. 1913, no. 1, Art. no. 012053, 2021. doi: 10.1088/1742-6596/1913/1/012053.
[45] C. Fu and L. Zhang, "A novel method based on tuna swarm algorithm under complex partial shading conditions in PV system," Solar Energy, vol. 248, pp. 28–40, Dec 2022. doi: 10.1016/j.solener.2022.10.056.
[46] S. T. Bahar, Y. G. Rashid, “A Study on An MPPT Control Approach Using Artificial Intelligence and the Perturb and Observe Method,” DJES, vol. 17, no. 2, pp. 131–143, Jun. 2024. doi: 10.24237/djes.2024.17210.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Zeyad Obaid, Ali Sachit Kaittan, Hassan Jasim Mohammed
This work is licensed under a Creative Commons Attribution 4.0 International License.
