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S.Joshibha Ponmalar
P.Valsalal P.Valsalal

Abstract

The output power produced by the solar cells shows a nonlinear current-voltage characteristic with respect to varying solar irradiance and ambient temperature. Maximum Power Point Tracking (MPPT) is utilized in Photovoltaic (PV) systems to maximize its output power. By monitoring the voltage and current of the PV system and controlling the duty cycle of the DC/ DC converter, a new MPPT controller is proposed in this paper. The design of MPPT is framed as an optimization problem whose solution is reached by using Gravitational search algorithm (GSA) to obtain the optimal parameters for the controller. Simulation results have shown that the proposed technique is delivering maximum power of photovoltaic system under different irradiance and ambient temperature. The performance of the developed GSA algorithm is comparable to Particle Swarm Optimization (PSO), Ant colony Optimization (ACO) for different conditions to validate its robustness

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References

[1] Rebei Najet. , Modeling and control of photovoltaic energy conversion connected to the grid, Frontiers in Energy, 03/2012
[2] A.Messai, A. Mellit, A. Massi Pavan, A.Guessoum and H.Mekki, , FPGA-based implementation of a fuzzy controller (MPPT) for photovoltaic module, An International Journal of Energy Conversion and Management, Vol.52, pp.2695–2704, 2011
[3] G.Dileep and S.N.Singh, , Maximum power point tracking of solar photovoltaic system using modified perturbation and observation method, An International Journal of Renewable and Sustainable Energy, Vol.50, pp.109–129, 2015
[4] Enrico Bianconi, Javier Calvente, Roberto Giral, Emilio Mamarelis, Giovanni Petrone, Carlos Andres Ramos-Paja, Giovanni Spagnuolo and Massimo Vitelli, , Perturb and Observe MPPT algorithm with a current controller based on the sliding mode, An International Journal of Electrical Power and Energy Systems, Vol.44, pp.346–356, 2013
[5] Xudong Wang, Yibo Pi, Wenguang Mao and Hua Huang, , Network Coordinated Power Point Tracking for Grid-Connected Photovoltaic Syst, IEEE Journal of Selected Areas in Communications, Vol.32, No.7, pp.1425 -1440, 2014
[6] Mohamed Tahar Makhloufi, Yassine Abdessemed and Mohamed Salah Khireddine, "Maximum Power Point Tracker for Photovoltaic Systems using On-line Learning Neural Networks", , An International Journal of Computer Applications, Vol.72, No.10, 2013
[7] Abdelhamid Loukriz, Mourad Haddadi and Sabir Messalti, , Simulation and experimental design of a new advanced variable step size Incremental Conductance MPPT algorithm for PV systems, ISA Transactions, Vol.62, pp.30–38, 2016
[8] Tarak Salmi, Mounir Bouzguenda, Adel Gastli,Ahmed Masmoudi, MATLAB/Simulink Based Modelling of Solar Photovoltaic Cell, International Journal of Renewable Energy ,Vol.2,No.2,2012.
[9] Parimita Mohanty, G. Bhuvaneswari, R. Balasubramanian and Navdeep Kaur Dhaliwal, , MATLAB based modeling to study the performance of different MPPT techniques used for solar PV system under various operating conditions, An International Journal of Renewable and Sustainable Energy Reviews, Vol.38, pp.581–593, 2014
[10] Santi Agatino Rizzo and Giacomo Scelba, ANN based MPPT method for rapidly variable shading conditions, An International Journal of Applied Energy, Vol.145, pp.124–132, 2015
[11] Esmat Rashedi, Hossein Nezamabadi-pour and Saeid Saryazdi,, GSA: A Gravitational Search Algorithm, An International Journal of Information Sciences, Vol.179, No.13, pp.2232–2248, 2009
[12] Gonggui Chen, Lilan Liu, Zhizhong Zhang and Shanwai Huang, Optimal reactive power dispatch by improved GSA-based algorithm with the novel strategies to handle constraints, An International Journal of Applied Soft Computing, Vol.50, pp.58–70, 2017
[13] Arup Ratan Bhowmik and A.K. Chakraborty, , Solution of optimal power flow using nondominated sorting multi objective gravitational search algorithm, An International Journal of Electrical Power and Energy Systems, Vol.62, pp.323–334, 2014
[14] Michael Fairbank, Shuhui Li, Xingang Fu, Eduardo Alonso and Donald Wunsch, , An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances, An International Journal of Neural Networks, Vol.49, pp.74–86, 2014
[15] A. Safari and S. Mekhilef, Simulation and hardware implementation of incremental conductance MPPT with direct control method using cuk converter,, IEEE Trans. Ind. Electron., vol. 58, no. 4, pp. 1154–1161,Apr. 2011.
[16] K. Ishaque and Z. Salam,, A deterministic particle swarm optimization maximum power point tracker for photovoltaic system under partial shading condition, IEEE Trans. Ind. Electron., vol. 60, no. 8, pp. 3195–3206, Aug. 2013
[17] Michael Fairbank, Shuhui Li, Xingang Fu, Eduardo Alonso and Donald Wunsch, An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances, An International Journal of Neural Networks, Vol.49, pp.74–86, 2014
[18] Mohammadmehdi Seyedmahmoudian, Rasoul Rahmani, Saad Mekhilef, Amanullah Maung Than Oo, Alex Stojcevski, Tey Kok Soon,and Alireza Safdari Ghandhari , Simulation and Hardware Implementation of New Maximum Power Point Tracking Technique for Partially Shaded PV System Using Hybrid DEPSO Method, IEEE Transactions On Sustainable Energy , pp.1-13,2015
[19] Duy An. Pham, Frédéric. Nollet, Najib. Essounbouli, A One Input Fuzzy Logic Controller for Maximum Power Point Tracking of a Photovoltaic System, Journal of Electrical Engineering, pp.1-7, 2016.