Islanding Detection for Microgrid Based on Frequency Tracking Using Extended Kalman Filter Algorithm. (15th May 2014)

• Record Type: Journal Article
• Authors: Li, Bin; Wang, Jingpeng; Bao, Hailong; Zhang, Huiying
• Other Names: Jia Hongjie Academic Editor.
• Is Part Of: Journal of applied mathematics. Volume 2014(2014)
• Publication Date: 2014-05-15
• Subjects: Mathematics -- Periodicals; 519.05
• DOI: 10.1155/2014/186360
• Languages: English
• ISSNs: 1110-757X

Abstract

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.