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Simulation of Controllers for AC Microgrid

Affiliations

  • Department of Electrical and Electronics Engineering, SRM University, Chennai – 603203, Tamil Nadu, India

Abstract


Objective: To design controllers for AC micro grid. To improve battery span, fuzzy control and energy management control the charging and discharging mode of the battery. Methods: A fuzzy controller can be used for the control of battery SOC of the renewable hybrid system and Energy Management Control is also used as above and to improve the performance of the system. Findings: The wind, solar hybrid power system plays a vital role today in renewable energy resources because it uses solar and wind power combined to create a stand-alone energy source that is both dependable and reliable. Conventional approach cannot provide with best way of energy management due to its non-linearity of battery charging process. So modern controllers are used in micro grid for battery SOC control. Improvement: In this work both fuzzy logic controller and EMC system is used for the hybrid system modeled using solar, wind and fuel cell system.

Keywords

Energy Management System, Fuzzy Logic Control, State of Charge.

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References


  • Zhang L, Zhou B, Cheng F, Zuo G. A Novel Maximum Power Point Tracking Control Method Suitable Doubly Salient Electro-Magnetic Wind Power Generator System. World Non Grid Connected Wind Power and Energy Conference Proceeding. 2009.
  • Rongxian H, Zhiwen L, Yaoming C, Fu W, Guoguang R. DC micro-grid simulation test platform. Conference proceeding of 9th Taiwan Power Electron Conference, Taiwan. 2010. p. 1361–6.
  • Wai RJ, Shih LC. Adaptive fuzzy-neural-network design for voltage tracking control of a DC–DC boost converter. IEEE Trans Power Electron. 2012 Apr; 27(4):2104–15.
  • Xu L, Ruan X, Mao C, Zhang B, Luo Y. An Improved Optimal Sizing Method for Wind Solar-Battery Hybrid Power System. Sustainable Energ IEEE Transactions. 2013 Jul; 4(3):774–78.
  • Jeong KS, Lee WY, Kim CS. Energy management strategies of a fuel cell/battery hybrid system using fuzzy logics. Journal of Power Sources. 2005; 145:319–26.
  • Vazquez S, Lukic SM, Galvan E, Franquelo LG, Carrasco JM. Energy Storage Systems for Transport and Grid Applications. IEEE Trans on Industrial Electronics. 2010 Dec; 57(12):3881–95.
  • Nunna HSVSK, Doolla S. Multiagent-Based Distributed-Energy- Resource Management for Intelligent Microgrids. IEEE Trans on Industrial Electronics. 2014 Apr; 60(4):1678–87.
  • Chen Y-K, Wu Y-C, Song C-C, Chen Y-S. Design and Implementation of Energy Management System with Fuzzy Control for DC Micro-grid Systems. IEEE Transactions on Power Electronics. 2013 Apr; 28(4).
  • Nehrir MH, Wang C, Strunz K, Aki R, Ramakumar H, Bing J, Miao Z, Salameh Z. A review of hybrid renewable/alternative energy systems for electric power generation: Configurations, control, and applications. IEEE Trans Sustain Energy. 2011 Oct; 2(4):392–403.
  • Ying H. Fuzzy Control and Modeling: Analytical foundations and applications. New York, IEEE Press, 2000.
  • Erdinc O, Vura B, Uzunoglu M, Ates Y. Modeling and analysis of an FC/UC hybrid vehicular power system using a wavelet-fuzzy logic based load sharing and control algorithm. International Journal of Hydrogen Energy .2009; 34:5223–33.
  • Pandey K, Banerjee P, Mathur D. Study and Modelling of Green Energy based Micro-Grid for Rural Area. Indian Journal of Science and Technology. 2016 Jun; 9(21).
  • Abo-Khalil AG, Lee D-C. MPPT control system based on estimated wind speed using SVR. IEEE Transactions on Industrial Electronics. 2008 Mar; 55(3):1489–90.
  • Fuzzy based optimal load management in stand alone hybrid solar PV/Wind/Fuel cell generation system. Available from: http://ieeexplore.ieee.org/document/7437965/. Date accessed:7/11/2015.

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