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Research Article

Hybrid Red Deer with Moth Flame Optimization for Reconfiguration Process on Partially Shaded Photovoltaic Array

Pages 6940-6966 | Received 15 Sep 2021, Accepted 24 Dec 2021, Published online: 03 Feb 2022

References

  • Aghaie, R., and M. Farshad. 2019. Maximum power point tracker for photovoltaic systems based on moth-flame optimization considering partial. Shading Conditions 7 (2):176–86.
  • Ali, S., S. Miah, J. Haque, M. Rahman, and K. Islam. 2021. An enhanced technique of skin cancer classification using deep convolutional neural network with transfer learning models. Machine Learning with Applications 5:100036. doi:10.1016/j.mlwa.2021.100036.
  • Ayache, K., A. Chandra, and A. Chériti. 2020. An embedded reconfiguration for reliability enhancement of photovoltaic shaded panels against hot spots. IEEE Transactions on Industry Applications 56 (2):1815–26. doi:10.1109/TIA.2019.2956912.
  • Babu, T. S., J. P. Ram, T. Dragičević, M. Miyatake, F. Blaabjerg, and N. Rajasekar. 2018. Particle swarm optimization based solar PV array reconfiguration of the maximum power extraction under partial shading conditions. IEEE Transactions on Sustainable Energy 9 (1):74–85. doi:10.1109/TSTE.2017.2714905.
  • Boothalingam, R. 2018. Optimization using lion algorithm: A biological inspiration from lion’s social behavior. Evolutionary Intelligence 11 (1–2):31–52. doi:10.1007/s12065-018-0168-y.
  • Chang, N., M. Pedram, H. G. Lee, Y. Wang, and Y. Kim. 2015. Reconfigurable photovoltaic array systems for adaptive and fault-tolerant energy harvesting. Nano Devices and Circuit Techniques for Low-Energy Applications and Energy Harvesting 181–209.
  • Dhanalakshmi, B., and N. Rajasekar. 2017. The particle swarm optimization algorithm for maximum power extraction of solar PV array. Advances in Smart Grid and Renewable Energy (435), 39–48.
  • El-Dein, M. Z. S., M. Kazerani, and M. M. A. Salama. 2013a. Optimal photovoltaic array reconfiguration to reduce partial shading losses. IEEE Transactions on Sustainable Energy ,4 (1):145–53. doi:10.1109/TSTE.2012.2208128.
  • El-Dein, M. Z. S., M. Kazerani, and M. M. A. Salama. 2013b. Optimal photovoltaic array reconfiguration to reduce partial shading losses. IEEE Transactions on Sustainable Energy ,Volume 4 (1):145–53.
  • Farh, H. M. H., and A. M. Eltamaly. 2019. Maximum power extraction from the photovoltaic system under partial shading conditions. Modern Maximum Power Point Tracking Techniques for Photovoltaic Energy Systems 107–29.
  • Fathollahi-Fard, A. M., M. Hajiaghaei-Keshteli, and R. Tavakkoli-Moghaddam. 2020. Red deer algorithm (RDA): A new nature-inspired meta-heuristic. Soft Computing 24 (19):14637–65. doi:10.1007/s00500-020-04812-z.
  • Fathy, A. 2018. Recent meta-heuristic grasshopper optimization algorithm for optimal reconfiguration of partially shaded PV array. Solar Energy 171:638–51. doi:10.1016/j.solener.2018.07.014.
  • Fathy, A. 2020. Butterfly optimization algorithm based methodology for enhancing the shaded photovoltaic array extracted power via reconfiguration process. Energy Conversion and Management 220 (113115):113115. doi:10.1016/j.enconman.2020.113115.
  • Harrag, A., and S. Messalti. 2018. Adaptive GA-based reconfiguration of photovoltaic array combating partial shading conditions. Neural Computing & Applications 30 (4):1145–70. doi:10.1007/s00521-016-2757-y.
  • Krishna, G. S., and T. Moger. 2019a. Improved SuDoKu reconfiguration technique for total-cross-tied PV array to enhance maximum power under partial shading conditions. Renewable and Sustainable Energy Reviews 109:333–48. doi:10.1016/j.rser.2019.04.037.
  • Krishna, S. G., and T. Moger. 2019b. Optimal SuDoKu reconfiguration technique for total-cross-tied PV array to increase power output under non-uniform irradiance. IEEE Transactions on Energy Conversion 34 (4):1973–84. doi:10.1109/TEC.2019.2921625.
  • Laudani, A., G. M. Lozito, M. Radicioni, F. R. Fulginei, and A. Salvini. 2019. Optimal PV panel reconfiguration using wireless irradiance distributed sensing. Electrimacs 525–37.
  • Mirjalili, S. 2015. Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm. Knowledge-Based Systems 89:228–49. doi:10.1016/j.knosys.2015.07.006.
  • Nihanth, M. S. S., N. Rajasekar, D. S. Pillai, and J. P. Ram. 2019. A new array reconfiguration scheme for solar PV systems under partial shading conditions. Intelligent Computing Techniques for Smart Energy Systems ,(607),387–96.
  • Nowdeh, S. A., M. J. H. Moghaddam, S. Nasri, A. Y. Abdelaziz, M. Ghanbari, and I. Faraji. 2020. A new hybrid moth flame optimizer-perturb and observe method for maximum power point tracking in photovoltaic energy system. Springer International Publishing, Germany.
  • Pareek, S., and R. Dahiya. 2016. Enhanced power generation of partial shaded photovoltaic fields by forecasting the interconnection of modules. Energy 95:561–72. doi:10.1016/j.energy.2015.12.036.
  • Rajan, N. A., K. D. Shrikant, B. Dhanalakshmi, and N. Rajasekar. 2017. Solar PV array reconfiguration using the concept of standard deviation and genetic algorithm. Energy Procedia 117:1062–69. doi:10.1016/j.egypro.2017.05.229.
  • Rakesh, N., and T. V. Madhavaram. 2016. Performance enhancement of partially shaded solar PV array using novel shade dispersion technique. Frontiers in Energy 10 (2):227–39. doi:10.1007/s11708-016-0405-y.
  • Rani, I., and Nagamani. 2013. Enhanced power generation from PV array under partial shading conditions by shade dispersion using Su Do Ku configuration. IEEE Transactions Sustainable Energy 4 (3):594–601. doi:10.1109/TSTE.2012.2230033.
  • Rao, P. S., P. Dinesh, G. S. Ilango, and C. Nagamani. 2015. Optimal Su-Do-Ku based interconnection scheme for increased power output from PV array under partial shading conditions. Frontiers in Energy 9 (2):199–210. doi:10.1007/s11708-015-0350-1.
  • Rezk, H., A. Fathy, and M. Aly. 2021. A robust photovoltaic array reconfiguration strategy based on coyote optimization algorithm for enhancing the extracted power under partial shadow condition. Energy Reports 7:109–24. doi:10.1016/j.egyr.2020.11.035.
  • Sarkar, R., J. R. Kumar, R. Sridhar, and S. Vidyasagar. 2021. A new hybrid BAT-ANFIS-Based Power Tracking Technique for Partial Shaded Photovoltaic Systems. International Journal of Fuzzy Systems 23 (5):1313–25. doi:10.1007/s40815-020-01037-y.
  • Shende, D. K., and S. S. Sonavane. 2020. CrowWhale-ETR: CrowWhale optimization algorithm for energy and trust aware multicast routing in WSN for IoT applications. Wireless Netw 26 (6):4011–29. doi:10.1007/s11276-020-02299-y.
  • Shi, J.-Y., D.-Y. Zhang, F. Xue, Y.-J. Li, W. Qiao, W.-J. Yang, Y.-M. Xu, and T. Yang. 2019. Moth-flame optimization-based maximum power point tracking for photovoltaic systems under partial shading conditions. Journal of Power Electronics 19 (5):1248–58.
  • Tabanjat, A., M. Becherif, and D. Hissel. 2014. Reconfiguration solution for shaded PV panels using fuzzy logic. ICREGA’14 - Renewable Energy: Generation and Applications (14),161–77.
  • Tolabi, H. B., M. H. Ali, and M. Rizwan. 2015. Simultaneous reconfiguration, optimal placement of DSTATCOM, and photovoltaic array in a distribution system based on fuzzy-ACO approach. IEEE Transactions on Sustainable Energy 6 (1):210–18. doi:10.1109/TSTE.2014.2364230.
  • Ul-Haq, A., R. Alammari, A. Iqbal, M. Jalal, and S. Gul. 2020. Computation of power extraction from photovoltaic arrays under various fault conditions. IEEE Access 8:47619–39. doi:10.1109/ACCESS.2020.2978621.
  • Vijayalekshmy, S., G. R. Bindu, and S. R. Iyer. 2016. Performance improvement of partially shaded photovoltaic arrays under moving shadow conditions through shade dispersion. Journal of the Institution of Engineers (India): Series B 97 (4):569–75. doi:10.1007/s40031-015-0199-z.
  • Yousri, D., S. B. Thanikanti, K. Balasubramanian, A. Osama, and A. Fathy. 2020. Multi-objective grey wolf optimizer for optimal design of switching matrix for shaded PV array dynamic reconfiguration. IEEE Access 8:159931–46. doi:10.1109/ACCESS.2020.3018722.
  • Zhu, Z., M. Hou, L. Ding, G. Zhu, and Z. Jin. 2020. Optimal photovoltaic array dynamic reconfiguration strategy based on direct power evaluation. IEEE Access 8:210267–76. doi:10.1109/ACCESS.2020.3036124.

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