Research on Maximum Power Point Algorithm Based on Adaptive Duty Cycle
Journal of Electrical and Electronic Engineering
Volume 5, Issue 6, December 2017, Pages: 235-241
Received: Dec. 27, 2017; Published: Dec. 28, 2017
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Authors
Suting Liang, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China
Lei Zhao, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China
Wenjing Wang, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China
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Abstract
In solar photovoltaic (PV) system it has been a tendency to extract the maximum output power from the PV panel with the decrease of production price. There are many novel control algorithms to track the maximum power point. The commonly used control algorithm is based on perturbation and observation algorithm (P&O). However, the traditional P&O method has some problems between the tracking speed and the control accuracy. In this paper, the mathematic model of photovoltaic cells is studied and a modified perturbation observation method is proposed. The algorithm adjusts the duty cycle step by step according to the variation of the slope of the power voltage curve. Simulink simulation of the PV module with the buck circuit proves the superiority of the variable duty cycle perturbation method in terms of tracking speed and stability compared with the traditional perturbation observation method.
Keywords
Photovoltaic System, Maximum Power Point, Variable Step Size, Adaptive
To cite this article
Suting Liang, Lei Zhao, Wenjing Wang, Research on Maximum Power Point Algorithm Based on Adaptive Duty Cycle, Journal of Electrical and Electronic Engineering. Vol. 5, No. 6, 2017, pp. 235-241. doi: 10.11648/j.jeee.20170506.14
References
[1]
Hengyang Luo, Huiqing Wen and Xingshuo Li. " Distributed MPPT control under partial shading condition, "2016 IEEE 8th International Power Electronics and Motion Control Conference (IPEMC-ECCE Asia), Hefei, 2016, pp. 928-932.
[2]
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, "in IEEE Journal of Photovoltaics, vol. 4, no. 2, pp. 626-633, March 2014.
[3]
N. Khaldi, H. Mahmoudi, M. Zazi and Y. Barradi, "The MPPT control of PV system by using neural networks based on Newton Raphson method," 2014 International Renewable and Sustainable Energy Conference (IRSEC), Ouarzazate, 2014, pp. 19-24.
[4]
H. Renaudineau et al., "A PSO-Based Global MPPT Technique for Distributed PV Power Generation," in IEEE Transactions on Industrial Electronics, vol. 62, no. 2, pp. 1047-1058, Feb. 2015.
[5]
X. Liu and L. A. C. Lopes, "An improved perturbation and observation maximum power point tracking algorithm for PV arrays, "2004 IEEE 35th Annual Power Electronics Specialists Conference (IEEE Cat. No.04CH37551), 2004, pp. 2005-2010 Vol. 3.
[6]
Y. Ma, T. Bai, X. Zhou and Z. Gao, "Summary of photo voltaic and maximum power point tracking," 2017 29th Chinese Control And Decision Conference (CCDC), Chongqing, 2017, pp. 2298-2303.
[7]
K. Ding, X. Bian, H. Liu and T. Peng, "A MATLAB-Simulink-Based PV Module Model and Its Application Under Conditions of Nonuniform Irradiance, " in IEEE Transactions on Energy Conversion, vol. 27, no. 4, pp. 864-872, Dec. 2012.
[8]
M. Azab, "A New Maximum Power Point Tracking for Photovoltaic Systems," WASET, vol. 34, 2008, pp. 571-574.
[9]
R. Sankarganesh and S. Thangavel, "Maximum power point tracking in PV system using intelligence based P&O technique and hybrid cuk converter," 2012 International Conference on Emerging Trends in Science, Engineering and Technology (INCOSET), Tiruchirappalli, Tamilnadu, India, 2012, pp. 429-436.
[10]
M. W. Rahman, C. Bathina, V. Karthikeyan and R. Prasanth, "Comparative analysis of developed incremental conductance (IC) and perturb & observe (P&O) MPPT algorithm for photovoltaic applications, "2016 10th International Conference on Intelligent Systems and Control (ISCO), Coimbatore, 2016, pp. 1-6.
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