References
- J. W. Cao, K. Meng, J. Y. Wang, M. B. Yang, Z. Chen, W. Z. LI, and C. Lin, “An energy internet and energy routers,” Scientia Sinica (Informationis), Vol. 44, No. 6, pp. 714-727, Jun. 2014. https://doi.org/10.1360/N112014-00001
- D. Verma, S. Nema, A. M. Shandilya, and S. K. Dash, "Maximum power point tracking (MPPT) techniques: Recapitulation in solar photovoltaic systems," Renew. Sustain. Energy Rev., Vol. 54, pp. 1018-1034, Feb. 2016. https://doi.org/10.1016/j.rser.2015.10.068
- J. P. Ram, T. S. Babu, and N. Rajasekar, "A comprehensive review on solar PV maximum power point tracking techniques," Renew. Sustain. Energy Rev., Vol. 67, pp. 826-847, Jan. 2017. https://doi.org/10.1016/j.rser.2016.09.076
- N. Karami, N. Moubayed, and R. Outbib, "General review and classification of different MPPT Techniques," Renew. Sustain. Energy Rev., Vol. 68, pp. 1-18, Feb. 2017. https://doi.org/10.1016/j.rser.2016.09.132
- M. A. M. Ramli, S. Twaha, K. Ishaque, and Y. A. Al-Turki, "A review on maximum power point tracking for photovoltaic systems with and without shading conditions," Renew. Sustain. Energy Rev., Vol. 67, pp. 144-159, Jan. 2017. https://doi.org/10.1016/j.rser.2016.09.013
- A. A. Elbaset, H. Ali, M. Abd-El Sattar, and M. Khaled, “Implementation of a modified perturb and observe maximum power point tracking algorithm for photovoltaic system using an embedded microcontroller,” IET Renew. Power Gener., Vol. 10, No. 4, pp. 551-560, Jan. 2016. https://doi.org/10.1049/iet-rpg.2015.0309
- J. Ahmed and Z. Salam, “An enhanced adaptive P&O MPPT for fast and efficient tracking under varying environmental conditions,” IEEE Trans. Sustain. Energy, Vol. 9, No. 3, pp. 1487-1496, Jul. 2018. https://doi.org/10.1109/TSTE.2018.2791968
- M. A. Elgendy, D. J. Atkinson, and B. Zahawi, “Experimental investigation of the incremental conductance maximum power point tracking algorithm at high perturbation rates,” IET Renew. Power Gener., Vol. 10, No. 2, pp. 133-139, Feb. 2016. https://doi.org/10.1049/iet-rpg.2015.0132
- M. A. Ozcelik and A. S. Yilmaz, "Improving the incremental conductance algorithm for two-stage grid-connected photovoltaic systems," Turkish J. Electr. Eng. Comput. Sci., Vol. 26, No. 1, pp. 442-453, Jan. 2018. https://doi.org/10.3906/elk-1412-119
- H. Renaudineau, F. Donatantonio, J. Fontchastagner, G. Petrone, G. Spagnuolo, J.-P. Martin, and S. Pierfederici, “A PSO-based global MPPT technique for distributed PV power generation,” IEEE Trans. Ind. Electron., Vol. 62, No. 2, pp. 1047-1058, Feb. 2015. https://doi.org/10.1109/TIE.2014.2336600
- J. Y. Shi, W Zhang, Y. G. Zhang, F. Xue, and T. Yang, "MPPT for PV systems based on a dormant PSO algorithm," Electr. Power Syst. Res., Vol. 123, pp. 100-107, Jun. 2015. https://doi.org/10.1016/j.epsr.2015.02.001
- R. B. Koad, A. F. Zobaa, and A. El-Shahat, “A novel MPPT algorithm based on particle swarm optimization for photovoltaic systems,” IEEE Trans. Sustain. Energy, Vol. 8, No. 2, pp. 468-476, Apr. 2017. https://doi.org/10.1109/TSTE.2016.2606421
- J. Y. Shi, F. Xue, Z.-J. Qin, L.-T. Ling, T. Yang, Y. Wang, and J. Wu, “Tracking the global maximum power point of a photovoltaic system under partial shading conditions using a modified firefly algorithm,” J. Renew. Sustain. Energy, Vol. 8, No. 3, pp. 033501, 2016. https://doi.org/10.1063/1.4948524
- D. F. Teshome, C. H. Lee, Y. W. Lin, and K. L. Lian, “A modified firefly algorithm for photovoltaic maximum power point tracking control under partial shading,” IEEE J. Emerg. Sel. Topics Power Electron., Vol. 5, No. 2, pp. 661-671, Jun. 2017. https://doi.org/10.1109/JESTPE.2016.2581858
- J. Y. Shi, F. Xue, Z. J. Qin, W. Zhang, L. T. Ling, and T. Yang, “Improved global maximum power point tracking for photovoltaic system via cuckoo search under partial shaded conditions,” J. Power Electron., Vol. 16, No. 1, pp. 287-296, Jan. 2016. https://doi.org/10.6113/JPE.2016.16.1.287
- B. R. Peng, K. C. Ho, and Y. H. Liu, “A novel and fast MPPT method suitable for both fast changing and partially shaded conditions,” IEEE Trans. Ind. Electron., Vol. 65, No. 4, pp. 3240-3251, Apr. 2018. https://doi.org/10.1109/TIE.2017.2736484
- M Mao, Q Duan, P Duan, and B. Hu, "Comprehensive improvement of artificial fish swarm algorithm for global MPPT in PV system under partial shading conditions," Trans. Inst. Meas. Contr., pp. 0142331217697374, 2017.
- M. Mao, Q. Duan, Z. Yang, and P. Duan, "Modelling and global MPPT for PV system under partial shading conditions using modified artificial fish swarm algorithm," Systems Engineering (ISSE), 2016 IEEE International Symposium on. IEEE, 1-7, 2016.
- S. K. Cherukuri and S. R. Rayapudi, “Enhanced grey wolf optimizer based MPPT algorithm of PV system under partial shaded condition,” Int. J. Renew. Energy Develop., Vol. 6, No. 3, pp. 203-212, 2017. https://doi.org/10.14710/ijred.6.3.203-212
- J. Y. Shi, D. Y. Zhang, L. T. Ling, F. Xue, Y. J. Li, Z. J Qin, and T. Yang, “Dual-algorithm maximum power point tracking control method for photovoltaic systems based on grey wolf optimization and golden-section optimization,” J. Power Electron., Vol. 18, No. 3, pp. 841-852, May 2018. https://doi.org/10.6113/JPE.2018.18.3.841
- S. K. Cherukuri and S. R. Rayapudi, “A novel global MPP tracking of photovoltaic system based on whale optimization algorithm,” Int. J. Renew. Energy Develop., Vol. 5, No. 3, pp. 225-232, 2016. https://doi.org/10.14710/ijred.5.3.225-232
- S. Gupta and K. Saurabh, "Modified artificial killer whale optimization algorithm for maximum power point tracking under partial shading condition," 2017 International Conference on Recent Trends in Electrical, Electronics and Computing Technologies (ICRTEECT), pp. 87-92, 2017.
- N. Kumar, I. Hussain, B. Singh, and B. K. Panigrahi, “MPPT in dynamic condition of partially shaded PV system by using WODE technique,” IEEE Trans. Sustain. Energy, Vol. 8, No. 3, pp. 1204-1214, Jul. 2017. https://doi.org/10.1109/TSTE.2017.2669525
- S Mirjalili, "Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm," Knowledge-Based Syst., Vol. 89, pp. 228-249, Nov. 2015. https://doi.org/10.1016/j.knosys.2015.07.006
- D. Allam, D. A. Yousri, and M. B. Eteiba, "Parameters extraction of the three diode model for the multi-crystalline solar cell/module using moth-flame optimization algorithm," Energy Convers. Manag., Vol. 123, pp. 535-548, Sep. 2016. https://doi.org/10.1016/j.enconman.2016.06.052
- W. Yamany, M. Fawzy, A. Tharwat, and A. E. Hassanien, "Moth-flame optimization for training Multi-Layer Perceptrons," Int. Comput. Eng. Conference. IEEE, pp. 267-272, 2015.
- Z. Q. Wang, J. F. Chen, G. F. Zhang, Q. Yang, and Y. H. Dai. "Optimal power flow calculation with moth-flame optimization algorithm," Power Syst. Technol., Vol. 41, No. 11, pp. 3641-3647, 2017.
- K. Ishaque, Z. Salam, A. Shamsudin, and M. Amjad, “A direct control based maximum power point tracking method for photovoltaic system under partial shading conditions using particle swarm optimization algorithm,” Appl. Energy, Vol. 99, No. 2, pp. 414-422, Nov. 2012. https://doi.org/10.1016/j.apenergy.2012.05.026
- F. Keyrouz, “Enhanced bayesian based MPPT controller for PV systems,” IEEE Power Energy Technol. Syst. J., Vol. 5, No. 1, pp. 11-17, Mar. 2018. https://doi.org/10.1109/JPETS.2018.2811708
- F. Salem, M. S. A. Moteleb, and H. T. Dorrah, “An enhanced fuzzy-PI controller applied to the MPPT problem,” J. Sci. Eng, Vol. 8, No. 2, pp. 147-153, 2005.
- K. Ishaque, Z. Salam, and H. Taheri, “Simple, fast and accurate two-diode model for photovoltaic modules,” Solar Energy Materials and Solar Cells, Vol. 95, No. 2, pp. 586-594, 2011. https://doi.org/10.1016/j.solmat.2010.09.023