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Features of PSO – BFOA Based Increment Conductance Method with FPGA

Ch. Venkateswara Rao*, S. S. Tulsiram**, B. Brahmaiah ***, Ch. Ramya****

* Lecturer, Department of Electrical and Electronics Engineering, Salalah College of Technology, Salalah, Oman.

** Dean and Professor, Department of Electrical and Electronics Engineering, Salalah College of Technology, GNITS, Hyderabad , Telangana, India.

*** Principal, Pydah College of Engineering and Technology, Visakhapatnam, Andhra Pradesh, India.

**** M.TechStudent, Department of Electrical and Electronics Engineering, Swarnandhra College of Engineering and Technology, Narasapuram, Andhra Pradesh, India.

Periodicity:December - February'2019
DOI : https://doi.org/10.26634/jcir.7.1.15391

Abstract

The global primary energy demands are increasing rapidly, which arrives at almost double the growth rate of energy consumption (Senjyu, Nakaji, Uezato, & Funabashi, 2005). An enhanced network-based control structure is essential, especially to get rid of the frequency deviations, power sharing errors, and stability concerns associated with the conservative droop control mainly in the micro grids (Jiang, Cao, Li, & Peng, 2012). One of the solutions for the issues is, to introduce renewable energy, among others PV and wind energy are clean and abundantly available in nature (Faranda & Leva, 2008). The Photovoltaic (PV) systems output power fluctuates according to the irradiation and temperature (weather conditions) (Kahrobaeian & Mohamed, 2015). Irregular PV output power results in frequency variations in the power systems, especially when the penetration is high. A photovoltaic (PV) array has nonlinear I-V (current-voltage) characteristics and its output power varies with solar insolation level, besides the ambient temperature. Only one point, called Maximum Power Point (MPP), exists on the P–V (power–voltage) curve, in which the power is maximum and the MPP fluctuates if there are changes in atmospheric conditions. The maximization of power output that takes place with greater efficiency becomes significant (Rao, Tulasiram, & Brahmaiah,2005). MPPT is the technique in use for extracting maximum power which is made available from the PV module (Subudhi & Pradhan, 2013). In this paper, a new hybrid algorithm is proposed combining the features of BFOA and Particle Swarm Optimization (PSO) for tuning PID controller, to give the better output from the solar power. PSO-BFOA based Incremental Conductance method to reduce sustained oscillations and fast searching of MPPT Computer simulations illustrate the effectiveness of the proposed approach compared to that of basic versions of PSO and BFO with FPGA. The results show that there are very good correlations between the controller parameters and the process parameters.

Keywords

MPPT, INC, PSO, BFOA.

How to Cite this Article?

Rao, V., Tulaisram, S.S., Brahmaiah, B., and Ramya. (2019). Features of PSO – BFOA Based Increment Conductance Method With FPGA. i-manager's Journal on Circuits and Systems , 7(1), 14-23. https://doi.org/10.26634/jcir.7.1.15391

References

[1]. Adhikari, S. & Li, F. (2014). Coordinated V-f and P-Q control of solar photovoltaic generators with MPPT and battery storage in microgrids. IEEE Transactions on Smart Grid, 5(3), 1270-1281.

[2]. Chen, J. H., Yau, H. T., & Hung, T. H. (2015). Design and implementation of FPGA-based Taguchi-chaos-PSO sun tracking systems. Mechatronics, 25, 55-64.

[3]. Chen, Y. M., Hung, S. C., Cheng, C. S., & Liu, Y. C. (2005, March). Multiinput inverter for grid-connected hybrid PV/wind power system. In Twentieth Annual IEEE Applied Power Electronics Conference and Exposition, 2005. APEC 2005. (Vol. 2, pp. 850-856). IEEE.

[4]. Das, S., Dasgupta, S., Biswas, A., Abraham, A., &Konar, A. (2009). On stability of the chemotactic dynamics in bacterial-foraging optimization algorithm. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 39(3), 670-679.

[5]. Faranda, R. & Leva, S. (2008). Energy comparison of MPPT techniques for PV Systems. WSEAS Transactions on Power Systems, 3(6), 446-455.

[6]. García, P., García, C. A., Fernández, L. M., Llorens, F., &Jurado, F. (2014). ANFIS-based control of a gridconnected hybrid system integrating renewable energies, hydrogen and batteries. IEEE Transactions on Industrial Informatics, 10(2), 1107-1117.

[7]. Hodashinskii, I. A., Zemtsov, N. N., & Meshcheryakov, R. V. (2012). Construction of fuzzy approximators based on the bacterial foraging method. Russian Physics Journal, 55(3),301-305.

[8]. Ishaque, K., Salam, Z., Amjad, M., & Mekhilef, S. (2012). An improved Particle Swarm Optimization (PSO)–based MPPT for PV with reduced steady-state oscillation. IEEE Transactions on Power Electronics, 27(8), 3627-3638.

[9]. Jiang, S., Cao, D., Li, Y., & Peng, F. Z. (2012). Gridconnected boost-half-bridge photovoltaic microinverter system using repetitive current control and maximum power point tracking. IEEE Transactions on power Electronics, 27(11), 4711-4722.

[10]. Kahrobaeian, A. & Mohamed, Y. A. R. I. (2015). Networked-based hybrid distributed power sharing and control for islanded microgrid systems. IEEE Transactions on Power Electronics, 30(2), 603-617.

[11]. Koutroulis, E., Kalaitzakis, K., & Tzitzilonis, V. (2009). Development of an FPGA-based system for real-time simulation of photovoltaic modules. Microelectronics Journal, 40(7), 1094-1102.

[12]. Li, J., Dang, J., Bu, F., & Wang, J. (2014). Analysis and improvement of the bacterial foraging optimization algorithm. Journal of Computing Science and Engineering, 8(1), 1-10.

[13]. Miyatake, M., Veerachary, M., Toriumi, F., Fujii, N., & Ko, H. (2011). Maximum power point tracking of multiple photovoltaic arrays: A PSO approach. IEEE Transactions on Aerospace and Electronic Systems, 47(1), 367-380.

[14]. Nejabatkhah, F., Danyali, S., Hosseini, S. H., Sabahi, M., &Niapour, S. M. (2012). Modeling and control of a new three-input DC–DC boost converter for hybrid PV/FC/battery power system. IEEE Transactions on Power Electronics, 27(5), 2309-2324.

[15]. Qian, H., Zhang, J., Lai, J. S., & Yu, W. (2011). A high-efficiency grid-tie battery energy storage system. IEEE Transactions on Power Electronics, 26(3), 886-896.

[16]. Rao, Ch. V., Tulasiram, S. S. & Brahmaiah, B. (2005). Digital controlled highpower synchronous boost converter based MPPT charge controller for SPV system. IJIE 5(2), 104-110.

[17]. Rao, Ch. V., Tulasiram, S. S., & Brahmaiah, B. (2011). Mathematical Modelling of Solar-Based-Inverter with Maximum Power Point Tracking. International Journal of Engineering Sciences and Management (IJESM), 1(2), 42-49.

[18]. Rao, Ch. V., Tulasiram, S. S., & Brahmaiah, B. (2015). FPGA controlled solar photovoltaic system fed induction motor through MLI. International Journal of Industrial Electronics and Electrical Engineering (IJIEEE), 3(2), 6-11.

[19]. Safari, A., & Mekhilef, S. (2011). Simulation and hardware implementation of incremental conductance MPPT with direct control method using cuk converter. IEEE Transactions on Industrial Electronics, 58(4), 1154-1161.

[20]. Senjyu, T., Nakaji, T., Uezato, K., & Funabashi, T. (2005). A hybrid power system using alternative energy facilities in isolated island. IEEE Transactions on Energy Conversion, 20(2), 406-414.

[21]. Sher, H. A., Murtaza, A. F., Noman, A., Addoweesh, K. E., Al-Haddad, K., & Chiaberge, M. (2015). A new sensorless hybrid MPPT algorithm based on fractional short-circuit current measurement and P&O MPPT. IEEE Transactions on Sustainable Energy, 6(4), 1426-1434.

[22]. Steimer, P. K. (2010, June). Enabled by high power electronics-Energy efficiency, renewables and smart grids. In The 2010 International Power Electronics Conference-ECCE (pp. 11-15). IEEE.

[23]. Subudhi, B., & Pradhan, R. (2013). A comparative study on maximum power point tracking techniques for photovoltaic power systems. IEEE Transactions on Sustainable Energy, 4(1), 89-98.

[24]. Taghvaee, M. H., Radzi, M. A. M., Moosavain, S. M., Hizam, H., & Marhaban, M. H. (2013). A current and future study on non-isolated DC-DC converters for photovoltaic applications. Renewable and Sustainable Energy Reviews, 17, 216-227.

[25]. Tuan, T., Kao, S., Rahman, A., Das, S., & Trimberger, S. (2006, February). A 90 nm low-power FPGA for batterypowered applications. In Proceedings of the 2006 ACM/SIGDA 14^th International Symposium on Field Programmable Gate Arrays (pp. 3-11). ACM.

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