An improved MPPT controller for photovoltaic system using fuzzy logic-particle swarm optimization

Aji Akbar Firdaus, Riky Tri Yunardi, Eva Inaiyah Agustin

Abstract


Photovoltaic (PV) is a renewable source of electrical energy. Because PV can convert solar energy into electrical energy. However, the level of PV power efficiency is less good. To get Maximum Power Point (MPP) from PV, Maximum Power Point Tracking (MPPT) is needed. There are several methods to adjust the duty cycle of MPPT. In this paper, the duty cycle is controlled by Fuzzy Logic-Particle Swarm Optimization (FL-PSO) to get optimal MPP with the small ripple and oscillation from MPPT. From the simulation results, the values of output current, voltage, and power from the boost converter are 3.464 A, 183.6 V, and 637.7 W, respectively. The ripple of output power from PV with FL-PSO is 69.5 W. The time required by Fuzzy Logic-PSO reaches MPP is 0.354 s. The results of the proposed algorithm are compared with the PSO method. The results show that the MPPT technique using Fuzzy Logic-PSO indicates better performance and faster than the PSO method.

References


B. Subudhi and R. Pradhan, “A comparative study on maximum power point tracking techniques for photovoltaic power systems,” IEEE Trans. Sustain. Energy, vol. 4, no. 1, pp. 89–98, Jan. 2013.

Suyanto, Soedibyo, Aji Akbar Firdaus, “Design and Simulation of Neural Network Predictive Controller Pitch-Angle in Permanent Magnetic Synchronous Generator Wind Turbine Variable Pitch System,” 1st International Conference on Information Technology, Computer and Electrical Engineering (ICITACEE) vol. 1, pp. 345-349, 2014.

Scarpa V, Buso S, Spiazzi G. Low complexity MPPT technique exploiting the effect of the PV cell series resistance. IEEE Applied Power Electronics Conference and Exhibition. 2008; February: 1958-1964.

D.V.N. Ananth, Venkata Nagesh Kumar, “Flux Based Sensorless Speed Sensing and Real and Reactive Power Flow Control with Look-up Table based Maximum Power Point Tracking Technique for Grid Connected Doubly Fed Induction Generator,” Indonesian Journal of Electrical Engineering and Informatics on, vol. 3, no. 4, pp. 239-260, Dec. 2015.

K. S. Tey and S. Mekhilef, “Modified incremental conductance MPPT algorithm to mitigate inaccurate responses under fast changing solar irradiation level,” Solar Energy, vol. 101, pp. 333–342, Jan. 2014.

Sathish Kumar Kollimalla, and Mahesh Kumar Mishra, “Variable Perturbation Size Adaptive P&O MPPT Algorithm for Sudden Changes in Irradiance,” IEEE Trans. Sustain. Energy, vol. 5, no. 4, pp. 718–728, July 2014.

M. A. Elgendy, B. Zahawi, and D. J. Atkinson, “Operating characteristics of the P&O algorithm at high perturbation frequencies for standalone PV systems,” IEEE Trans. Energy Convers., vol. 30, no. 1, pp. 189–198, Jun. 2015.

Jusoh A, Alik R, Guan TK, Sutikno T. MPPT for PV System Based on Variable Step Size P & O Algorithm. TELKOMNIKA Telecommunication Computing Electronics Control. 2017; 15(1): 79–92.

S. B. Kjaer, “Evaluation of the hill climbing and the incremental conductance maximum power point trackers for photovoltaic power systems,” IEEE Trans. Energy Convers., vol. 27, no. 4, pp. 922–929, Dec. 2012.

A. K. Rai, N. D. Kaushika, B. Singh, and N. Agarwal, “Simulation model of ANN based maximum power point tracking controller for solar PV system,” Solar Energy Mater. Solar Cells, vol. 95, no. 2, pp. 773–778, Feb. 2011.

Elobaid L. Artificial neural network based maximum power point tracking technique for PV systems. IECON 2012-38 th . 2012; October: 937–942.

B. Alajmi, K. Ahmed, S. Finney, and B. Williams, “Fuzzy logic control approach of a modified hill-climbing method for maximum power point in microgrid stand alone photovoltaic system,” IEEE Trans. Power Electron., vol. 26, no. 4, pp. 1022–1030, Apr. 2011.

K. Ishaque, Z. Salam, M. Amjad, and S. Mekhilef, “An improved particle swarm optimization (PSO)–based MPPT for PV with reduced steady-state oscillation,” IEEE Trans. Power Electron., vol. 27, no. 8, pp. 3627–3638, Aug. 2012.

K. Sundareswaran, S. Peddapati, and S. Palani, “MPPT of PV systems under partial shading conditions through a colony of flashing fireflies,” IEEE Trans. Energy Convers., vol. 29, no. 2, pp. 463–472, Jun. 2014.

Satyajit Mohanty, Bidyadhar Subudhi, and Pravat Kumar 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, January 2016.

Ali Rahnamaei, Mahdi Salimi, “A Novel Grid Connected Photovoltaic System,” Bulletin of Electrical Engineering and Informatics on, vol. 5, no. 2, pp. 133-143, June. 2016.

T. K. Soon and S. Mekhilef, “A fast converging MPPT technique for photovoltaic system under fast varying solar irradiation and load resistance,” IEEE Trans. Ind. Informat., vol. 11, no. 1, pp. 176–186, Feb. 2015.

Shilpa Sreekumar, Anish Benny, “Fuzzy Logic Controller Based Maximum Power Point Tracking of Photovoltaic System Using Boost Converter,” 4th ICCCNT, July 4-6, 2013.

K. Ishaque and Z. Salam, "A deterministic particle swarm optimization maximum power point tracker for photovoltaic system under partial shading condition," Industrial Electronics, IEEE Transactions on, vol. 60, pp. 3195-3206, 2013.

Aji Akbar Firdaus, Ontoseno Penangsang, Adi Soeprijanto, Dimas Fajar U. P., " Distribution Network Reconfiguration Using Binary Particle Swarm Optimization to Minimize Losses and Decrease Voltage Stability Index," Bulletin of Electrical Engineering and Informatics on, vol. 7, no. 4, pp. 514-521, Dec. 2018.

Zhanghong, Lishengzhu, Zhangxiaonan, Xiayilan, “MPPT control strategy for photovoltaic cells based on fuzzy control, “12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), pp. 450-454, 13-15 Aug. 2016.

Ahmad Saudi Samosir, Herri Gusmedi, Sri Purwiyanti, Endah Komalasari, “Modeling and Simulation of Fuzzy Logic based Maximum Power Point Tracking (MPPT) for PV Application, “International Journal of Electrical and Computer Engineering (IJECE) on, vol. 8, no. 3, pp. 1315-1323, June 2018.

Algazar MM, Al-Monier H, El-Halim HA, Salem MEEK. Maximum power point tracking using fuzzy logic control. International Journal of Electrical Power & Energy Systems. 2012; 39(1): 21–28.

Sobhan Dorahaki., " A Survey on Maximum Power Point Tracking Methods in Photovoltaic Power Systems," Bulletin of Electrical Engineering and Informatics on, vol. 4, no. 3, pp. 169-175, September. 2015.

Killi M, Samanta S. Modified perturb and observe MPPT algorithm for drift avoidance in photovoltaic systems. IEEE Transactions on Industrial Electronics. 2015; 62(9): 5549–5559.




DOI: http://doi.org/10.11591/ijpeds.v11.i2.pp%25p
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