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Journal of Applied Mathematics
Volume 2014, Article ID 186360, 11 pages
http://dx.doi.org/10.1155/2014/186360
Research Article

Islanding Detection for Microgrid Based on Frequency Tracking Using Extended Kalman Filter Algorithm

Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China

Received 23 January 2014; Revised 31 March 2014; Accepted 12 April 2014; Published 18 May 2014

Academic Editor: Hongjie Jia

Copyright © 2014 Bin Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Islanding detection is essential for secure and reliable operation of microgrids. Considering the relationship between the power generation and the load in microgrids, frequency may vary with time when islanding occurs. As a common approach, frequency measurement is widely used to detect islanding condition. In this paper, a novel frequency calculation algorithm based on extended Kalman filter was proposed to track dynamic frequency of the microgrid. Taylor series expansion was introduced to solve nonlinear state equations. In addition, a typical microgrid model was built using MATLAB/SIMULINK. Simulation results demonstrated that the proposed algorithm achieved great stability and strong robustness in of tracking dynamic frequency.