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Application of Improved Salp Swarm Algorithm Based on MPPT for PV Systems under Partial Shading Conditions | ||
| International Journal of Industrial Electronics Control and Optimization | ||
| مقاله 3، دوره 3، شماره 4، آذر 2020، صفحه 407-414 اصل مقاله (1.53 MB) | ||
| نوع مقاله: Research Articles | ||
| شناسه دیجیتال (DOI): 10.22111/ieco.2020.31320.1200 | ||
| نویسندگان | ||
Javad Farzaneh1؛ Ali Karsaz  2
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| 1Electrical and Computer Engineering Faculty, Semnan University, Semnan, Iran | ||
| 2Khorasan Istitute of Higher Education | ||
| چکیده | ||
| Maximum Power Point Tracking (MPPT) is an important concept for both uniform solar irradiance and Partial Shading Conditions (PSCs). The paper presents an Improved Salp Swarm Algorithm (ISSA) for MPPT under PSCs. The proposed method benefits a fast convergence speed in tracking the Maximum Power Point (MPP), in addition to overcoming the problems of conventional MPPT methods, such as failure to detect the Global MPP (GMPP) under PSCs, getting trapped in the local optima, and oscillations around the MPP. The proposed method is compared with original algorithms such as Perturbation and Observation (P&O) method (which is widely employed in MPPT applications), Differential Evolutionary (DE) algorithm, Particle Swarm Optimization (PSO), and Firefly Algorithm (FA). The obtained results show that the proposed method can detect and track the MPP in a very short time, and its accuracy outperforms the other methods in terms of detecting the GMPP. The proposed ISSA algorithm has a higher speed and the convergence rate than the other traditional algorithms. | ||
| کلیدواژه‌ها | ||
| Photovoltaic systems؛ Maximum power point tracking؛ Improved Salp swarm algorithm؛ Partial shading condition | ||
| مراجع | ||
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[1] J. Zhao, X. Zhou, Z. Gao, Y. Ma, and Z. Qin, “A novel global maximum power point tracking strategy (GMPPT) based on optimal current control for photovoltaic systems adaptive to variable environmental and partial shading conditions,” Solar Energy. Vol. 144 pp. 767–779, Mar. 2017. [2] H. Rezk, M. Al-oran, M.R. Gomaa, M.A. Tolba, A. Fathy, M. Ali, A.G. Olabi, A.H.M. El-sayed, W. Addawaser, P. Sattam, B. Abdulaziz, and S. Arabia, “A novel statistical performance evaluation of most modern optimization- based global MPPT techniques for partially shaded PV system,” Renewable and Sustainable Energy Reviews, Vol. 115, Nov. 2019. [3] J. Farzaneh, R. Keypour, and A. Karsaz, “A novel fast maximum power point tracking for a PV system using hybrid PSO-ANFIS algorithm under partial shading conditions,” International Journal of Industrial Electronics, Control and Optimization, Vol. 2, No. 1, pp. 47-58, Nov. 2019. [4] J. Farzaneh, R. Keypour, and M. Ahmadieh, “A New Maximum Power Point Tracking Based on Modified Firefly Algorithm for PV System Under Partial Shading Conditions,” Technology and Economics of Smart Grids and Sustainable Energy, Vol. 3, No. 1, Jun. 2018. [5] S. Titri, C. Larbes, K.Y. Toumi, and K. Benatchba, “A new MPPT controller based on the ant colony optimization algorithm for photovoltaic systems under partial shading conditions,” Applied Soft Computing, Vol. 58, pp. 465–479. Sep. 2017. [6] N. Femia, G. Petrone, G. Spagnuolo, and M. Vitelli, “Optimization of perturb and observe maximum power point tracking method, Power Electron,” IEEE transactions on power electronics, Vol. 20, no. 4, pp. 963–973, Jul. 2005. [7] Y. C. Kuo, T. J. Liang, and J. F. Chen, “Novel maximum-power-point-tracking controller for photovoltaic energy conversion system,” IEEE transactions on industrial electronics. Vol. 48, no. 3, pp. 594–601, Jun. 2001. [8] A. El Khateb, N.A. Rahim, and S. Member, “Fuzzy- logic-controller-based SEPIC converter for maximum power point tracking,” IEEE Transactions on Industry Applications, Vol. 50, no. 4, pp. 2349–2358, Jan 2014. [9] S. Saravanan, and N. R. Babu, “RBFN based MPPT algorithm for PV system with high step up converter, Energy conversion and Management,” Vol. 122. pp. 239–251. Aug. 2016. [10] M. a. S. Masoum, H. Dehbonei, and E.F. Fuchs, “Theoretical and experimental analyses of photovoltaic systems with voltage and current-based maximum power-point tracking,” IEEE Transactions on energy conversion, Vol. 17, No. 4, Dec. 2002. [11] E. Koutroulis, K. Kalaitzakis, and N.C. Voulgaris, “Development of a microcontroller-based, photovoltaic maximum power point tracking control system,” IEEE Transactions on power electronics. Vol. 16, No. 1, PP. 46–54, Jan. 2001. [12] A. Belkaid, I. Colak, and O. Isik, “Photovoltaic maximum power point tracking under fast varying of solar radiation,” Applied energy. Vol.179, PP. 523– 530, Oct. 2016. [13] M. Farhat, O. Barambones, and L. Sbita, “A new maximum power point method based on a sliding mode approach for solar energy harvesting,” Applied energy, Vol. 185, pp. 1185–1198, Jan. 2017. [14] R. Aboelsaud, and S. Obukhov, “Improved particle swarm optimization for global maximum power point tracking of partially shaded PV array,” Electrical Engineering, Vol. 101 NO. 2, pp. 443–455, Jun. 2019. [15] J. Ahmed, and Z. Salam, “A maximum power point tracking (MPPT) for PV system using cuckoo search with partial shading capability,” Applied Energy, Vol. 119, pp. 118–130, Apr. 2014. [16] K. Sundareswaran, V. Vigneshkumar, P. Sankar, S.P. Simon, P. Srinivasa Rao Nayak, and S. Palani, “Development of an improved P&O algorithm assisted through a colony of foraging ants for MPPT in PV system,” IEEE Transactions on Industrial Informatics, Vol. 12, No. 1, pp. 187–200, Nov. 2015. [17] S. Mohanty, B. Subudhi, S. Member, and P.K. Ray, “A new MPPT design using grey wolf optimization technique for photovoltaic system under partial shading conditions,” IEEE Transactions on Sustainable Energy, Vol. 7, No. 1, pp. 181-188, Oct. 2015. [18] K. Sundareswaran, P. Sankar, P.S.R. Nayak, S.P. Simon, and S. Palani, “Enhanced energy output From a PV system under partial shaded conditions through artificial bee colony,” IEEE transactions on sustainable energy, Vol. 6, No. 1, pp. 198-209, Nov. 2014. [19] Z. Wu, and D. Yu, “Application of improved bat algorithm for solar PV maximum power point tracking under partially shaded condition,” Applied Soft Computing, Vol. 62, pp. 101–109, Jan. 2018. [20] M. Faridun, N. Tajuddin, and S. Ayob, “Evolutionary based maximum power point tracking technique using differential evolution algorithm,” Energy and Buildings, Vol. 67, pp. 245–252, Dec. 2013. [21] L. L. Li, G. Q. Lin, M. L. Tseng, K. Tan, and M. K. Lim, “A maximum power point tracking method for PV system with improved gravitational search algorithm,” Applied Soft Computing, Vol. 65, pp. 333– 348, Apr. 2018. [22] K. Sundareswaran, S. Peddapati, and S. Palani, “MPPT of PV systems under partial shaded conditions through a colony of flashing fireflies,” IEEE transactions on energy conversion, Vol. 29, pp. 463–472, Jan. 2014. [23] S. Mohanty, B. Subudhi, and P.K. Ray, “A new MPPT design using grey wolf optimization technique for photovoltaic system under partial shading conditions,” IEEE Transactions on Sustainable Energy, Vol. 7 No. 1, pp. 181–188. Oct. 2015. [24] N.A. Ahmed, and M. Miyatake, “A novel maximum power point tracking for photovoltaic applications under partially shaded insolation conditions,” Electric Power Systems Research, Vol. 78, No.5, pp. 777–784, May. 2008. [25] B.N. Alajmi, K.H. Ahmed, S.J. Finney, B.W. Williams, and B. Wayne Williams, “A maximum power point tracking technique for partially shaded photovoltaic systems in microgrids,” IEEE Transactions on Industrial Electronics, Vol. 60, No. 4, pp. 1596–1606, Sep. 2011. [26] R.K. Kharb, S.L. Shimi, S. Chatterji, and M.F. Ansari, “Modeling of solar PV module and maximum power point tracking using ANFIS,” Renewable and Sustainable Energy Reviews, Vol. 33, pp. 602–612, May. 2014. [27] V. Phimmasone, T. Endo, Y. Kondo, and M. Miyatake, “Improvement of the maximum power point tracker for photovoltaic generators with particle swarm optimization technique by adding repulsive force among agents,” International conference on electrical machines and systems, pp. 1-6, Nov. 2009. [28] M. Miyatake, M. Veerachary, F. Toriumi, N. Fujii, and H. Ko, “Maximum power point tracking of multiple photovoltaic arrays: A PSO approach,” IEEE Transactions on Aerospace and Electronic Systems, Vol. 47, No. 1, pp. 367–380, Jan. 2011. [29] Y. Liu, S. Huang, J. Huang, and W. Liang, “A particle swarm optimization-based maximum power point tracking algorithm for PV systems operating under partially shaded conditions,” IEEE Transactions on Energy Conversion, Vol. 27, No. 4, pp. 1027-1035. Oct. 2012. [30] L.L. Jiang, D.L. Maskell, and J.C. Patra, “A novel ant colony optimization-based maximum power point tracking for photovoltaic systems under partially shaded conditions,” Energy and Buildings, Vol. 58, pp. 227–236, Mar. 2013. [31] S. Daraban, D. Petreus, and C. Morel, “A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading,” Energy. Vol.74, pp. 374– 388, Sep. 2014. [32] K.L. Lian, J.H. Jhang, and I.S. Tian, “A maximum power point tracking method based on perturb-and- observe combined with particle swarm optimization,” IEEE journal of photovoltaics, Vol.4, No. 2, pp. 626– 633, Jan. 2014. [33] C. Manickam, G.R. Raman, G.P. Raman, S.I. Ganesan, C. Nagamani, A hybrid algorithm for tracking of GMPP based on P&O and PSO with reduced power oscillation in string inverters, IEEE Transactions on Industrial Electronics, Vol. 63, No. 10, pp. 6097–6106. Jul. 2016 [34] S. Mohanty, B. Subudhi, and P.K. Ray, “A grey wolf assisted perturb & observe MPPT algorithm for a photovoltaic power system,” IEEE Transactions on Energy Conversion, Vol. 32, No. 1, pp. 340–347, Dec. 2016. [35] 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 Journal of Emerging and Selected Topics in Power Electronics, Vol. 5, No. 2, pp. 661–671, Jun. 2016. [36] H. Li, S. Member, D. Yang, and W. Su, “An Overall Distribution Particle Swarm Optimization MPPT Algorithm for Photovoltaic System under Partial Shading,” IEEE Transactions on Industrial Electronics, Vol. 66, No.1, pp. 265-275, Apr. 2018. [37] B. Yang, L. Zhong, X. Zhang, H. Shu, T. Yu, H. Li, L. Jiang, and L. Sun, “Novel bio-inspired memetic salp swarm algorithm and application to MPPT for PV systems considering partial shading condition,” Journal of cleaner production, Vol. 215, pp. 1203– 1222, Apr. 2019. [38] J.P. Ram, T.S. Babu, T. Dragicevic, and N. Rajasekar, “A new hybrid bee pollinator flower pollination algorithm for solar PV parameter estimation,” Energy conversion and management, Vol. 135, pp. 463–476, Mar. 2017. [39] V.R. Kota, and M.N. Bhukya, A novel linear tangents based P & O scheme for MPPT of a PV system, Renewable and Sustainable Energy Reviews. Vol. 71, pp. 257–267, May. 2017. [40] K. Sundareswaran, V. Vignesh kumar, and S. Palani, “Application of a combined particle swarm optimization and perturb and observe method for MPPT in PV systems under partial shading conditions,” Renewable Energy, Vol. 75, pp. 308– 317, Mar. 2015. [41] S. Lyden, and M.E. Haque, “A simulated annealing global maximum power point tracking approach for PV Modules under Partial Shading Conditions,” IEEE Transactions on Power Electronics, Vol. 31, pp. 4171-4181, Aug. 2015. [42] S. Mirjalili, A.H. Gandomi, S.Z. Mirjalili, S. Saremi, H. Faris, and S.M. Mirjalili, “Salp swarm algorithm: a bio-inspired optimizer for engineering design problems,” Advances in Engineering Software, Vol. 114, pp. 163-191, Dec. 2017. | ||
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آمار تعداد مشاهده مقاله: 191 تعداد دریافت فایل اصل مقاله: 256 |
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