Application of Islanding Detection and Classification of Power Quality Disturbance in Hybrid Energy System

2018 Asia Conference on Energy and Environment Engineering

能源学;生态环境科学

Sun, L.B.^1 ; Wu, Z.S.^1 ; Yang, K.K.^1

School of Electrical Engineering, Beijing Jiaotong University, Beijing

100044, China^1

关键词: Heuristic optimization method;    Hybrid energy system;    Hybrid power systems;    Islanding detection;    Multiple distributed generations;    Negative sequence components;    Power quality disturbances;    Renewable energy source;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/133/1/012020/pdf
DOI  :  10.1088/1755-1315/133/1/012020

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Islanding and power quality (PQ) disturbances in hybrid energy system become more serious with the application of renewable energy sources. In this paper, a novel method based on wavelet transform (WT) and modified feed forward neural network (FNN) is proposed to detect islanding and classify PQ problems. First, the performance indices, i.e., the energy content and SD of the transformed signal are extracted from the negative sequence component of the voltage signal at PCC using WT. Afterward, WT indices are fed to train FNNs midfield by Particle Swarm Optimization (PSO) which is a novel heuristic optimization method. Then, the results of simulation based on WT-PSOFNN are discussed in MATLAB/SIMULINK. Simulations on the hybrid power system show that the accuracy can be significantly improved by the proposed method in detecting and classifying of different disturbances connected to multiple distributed generations.