基于正弦状态估计模型的被动孤岛检测技术

Passive Islanding Detection Techniques Based on Sine State Estimated Model

以光伏发电系统多逆变器并网为研究对象,将现代状态估计理论引入孤岛效应检测中,提出一种基于公共耦合点(PCC)电压正弦状态估计的被动孤岛检测方法,推导出电压正弦波状态估计模型并离散化,利用强跟踪滤波器(STF)对该电压状态进行实时监测,通过BP神经网络对实时状态参数变化进行识别,从而区分正常、孤岛和伪孤岛现象。仿真和实验结果表明所提孤岛检测方法能有效、快速地检测出孤岛。

In multi-inverter photovoltaic system and network study,the modem state estimation theory is introduced to the detection of islanding, a passive islanding detection method based on sinusoidal estimates model of the point of common eoupling（PCC） voltage is proposed.The voltage sine wave discrete state estimation model is derived, the PCC voltage state is real-timely monitored by the strong tracking filter（STF）, the real-time status parameters island pheno- menon is identified by BP neural network to distinguish normal, island and pseudo-island phenomenon.Simulation and experimental results show that the proposed islanding detection methods can detect island effectively and quickly.