Fuzzy inference ACO islanding detection and stability analysis of integrated power system

摘要

Islanding detection for integrated Solar Photo-Voltaic Energy System (SPVES) is described in this paper. Because islanding causes dangerous hazardous to human beings and also to apparatus, hence islanding detection techniques are essentially required. In this paper a new strategy is presented for islanding detection according to extraction of frequency variations at Point of Common Coupling (PCC). Rate of Change of Frequency (RCF) and its noise level is reduced by Low Pass Filter (LPF). Output of LPF is taken for detection of islanding with proposed method. The output of LPF and its derivative is considered for inputs for fuzzy systems. Fuzzy output signal is optimized for avoiding the misclassification of Islanding Data (ISD) and Non Islanding Data (NISD) at PCC. Using Ant Colony Optimization (ACO), optimized fuzzy control vector is obtained for fast detection of islanding condition. The proposed Fuzzy Inference Vector Ant colony Optimization (FIV-ACO) is also tested the stability system during anti-islanding.