Modeling and Swarm Intelligence Based Control of Hybrid Wind-PV System for Grid Integration

Authors

  • B. Manoj Kumar  PG Scholar, Department of EEE, QCET, Venkatachelam, Andhra Pradesh, India.
  • P. Ramesh  Assistant Professor, Department of EEE, QCET, Venkatachelam, Andhra Pradesh, India

DOI:

https://doi.org//10.32628/IJSRST18401115

Keywords:

Phase Lock Loop, Swarm Intelligence, PV System, Grid Integration, ITAE, integral square error, Particle Swarm Optimization Algorithm.

Abstract

With the degradation of fossil fuels, recent era witness the penetration of renewable energy sources like wind and solar energy into various electrical applications. Integration of these renewable energy sources is of prime importance as they possess zero carbon emission, environmental friendly and zero fuel cost. However, the unpredictability and unreliable nature of solar and wind motivates the combine utilization of these sources i.e. hybrid energy systems. These systems are more reliable and have better continuous production of electrical energy than using the sources individually. Combination of hybrid energy system into grid/standalone applications demands the use of power electronic interface and appropriate control strategy. In this context, this thesis aims at development of a hybrid Photovoltaic (PV)/wind energy based systems for grid connected application. PV and wind are hybridized on a DC side to avoid the synchronizing issues between the sources. However, the proposed hybrid system is integrated on distribution side of the grid with a DC/AC converter (inverter). Considering the essential need of synchronization, the control input i.e. pulses to the inverter are generated from a voltage and frequency controller i.e. Phase Lock Loop (PLL).The task of tuning the controller is formulated as an optimization problem and is solved using Particle Swarm Optimization (PSO) technique. The objective of the system is to meet the load demand and to manage the power generated from different sources at different operating conditions. Each module in the complete system is modeled on Matlab/Simulink platform. Also, the performance of the system is tested for additional utilization of battery charging.

References

  1. EBarklund, N.Pogaku, M.Prodanovic, C.Hernandez-Aramburo, and T.C.Green, "Energy Management System with Stability Constraints for Stand-alone Autonomous MicroGrid," in Proc. 2007 IEEE Electrical & Electronic Engineering Conf. pp. 1 - 6.
  2. CAHernandez-Aramburo, T.C.Green, and N. Mugniot, "Fuel Consumption Minimization of a MicroGrid," IEEE Transactions on Industry Applications, vol. 41, pp. 673-681, May/June. 2005.
  3. Enrico Carpaneto, Gianfranco Chicco , "Distribution system minimum loss reconfiguration in the Hyper-Cube Ant Colony Optimization framework ," in Proc. 2008 Electric Power Systems Research the 6th World Energy System Conf. pp. 2037 - 2045.
  4. Mehdi Dali a, Jamel Belhadj a, and Xavier Roboam, "Hybrid solarewind system with battery storage operating in grid-connected and standalone mode: Control and energy management e Experimental investigation," in Proc. 2010 7th International Sustainable Energy Technologies Conf. pp. 2587-2595.
  5. Chen Lin, Zhong Jin, Ni Yinxin, and Gan Deqiang, "A Study on Gridconnected Distributed Generation System Planning and Its Operation Performance," Automation of Electric Power Systems, vol, 31, pp.26-31, May. 2007.
  6. Wang Xingwang, and Qiu Xiaoyan, "Distributed generation planning in distribution system based on modified particle swarm optimization algorithm," Power System Protection and Control, vol, 37, pp.16-20, July. 2009.
  7. N Sadati, T. Amraee, and A.M. Ranjbar, "A global Particle Swarm- Based-Simulated Annealing Optimization technique for under-voltage load shedding problem," Applied Soft Computing, vol, 9, pp 652-657, March, 2009.
  8. R Teodorescu, M. Liserre and P. Rodriguez, Grid Converters for Photovoltaic and Wind Power Systems. John Wiley & Sons, Ltd., 2011.
  9. IEEE Std 1547-2003, Standard for Interconnecting Distributed Resources with Electric Power Systems, IEEE, 2003.
  10. IEEE Std 1547.1-2005, IEEE standard conformance test procedures for equipment interconnecting distributed resources with electric power systems," IEEE, 2005.
  11. TBoutabba, S.Drid and M. E. H. Benbouzid,"A hybrid power generations system (Wind Turbine/Photovoltaic) to driving a DFIG fed by a three inverter," Sciences and
  12. Techniques of Automatic Control and Computer Engineering (STA), 2014 15th International Conference on, Hammamet, 2014, pp. 873-880.
  13. Ahmed Said Al Busaidi, Hussein A Kazem, Abdullah H Al-Badi, Mohammad Farooq Khan, "A review of optimum sizing of hybrid PV Wind renewable energy systems in oman," Renewable and Sustainable Energy Reviews, Volume 53, January 2016, Pages 185-193.
  14. D Rekioua and E. Matagne, Optimization of Photovoltaic Power Systems, Modelization, Simulation and Control. Springer, 2012.
  15. IEEE Std 1547-2003, Standard for Interconnecting Distributed Resources with Electric Power Systems, IEEE, 2003.
  16. R Teodorescu, M. Liserre and P. Rodriguez, Grid Converters for Photovoltaic and Wind Power Systems. John Wiley & Sons, Ltd., 2011.
  17. CIGRE Working Group B5.34, "The Impact of Renewable Energy Sources and Distributed Generation on Substation Protection and Automation," CIGRE, 2010.

International Journal of Scientific Research in Science and Technology

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Published

2018-12-30

Issue

Volume 4, Issue 11, November-December-2018

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
B. Manoj Kumar, P. Ramesh, " Modeling and Swarm Intelligence Based Control of Hybrid Wind-PV System for Grid Integration, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 4, Issue 11, pp.81-90, November-December-2018. Available at doi : https://doi.org/10.32628/IJSRST18401115