Machine Learning Approach to Islanding Detection for Inverter-Based Distributed Generation

Despite a number of economic and environmental benefits that integration of renewable distributed generation (DG) into the distribution grid brings, there are many technical challenges that arise as well. One of the most important issues concerning DG integration is unintentional islanding. Islanding occurs when DG continues to energize portion of the system while being disconnected from the main grid. Since the island is unregulated, its behavior is unpredictable and voltage, frequency and other power system parameters may have unacceptable levels, which may cause hazardous effect on devices and public. According to the IEEE Standard 1547 DG shall detect any possible islanding conditions and cease to energize the area within 2 sec. In this dissertation work, a new islanding detection method for single phase inverter-based distributed generation is presented. In the first stage of the proposed method, parametric technique called Autoregressive (AR) signal modeling is utilized to extract signal features from voltage and current signals at the Point of Common Coupling (PCC) with the grid. In the second stage, advanced machine learning technique based on Support Vector Machine (SVM) which takes calculated features as inputs is utilized to predict islanding state. The extensive study is performed on the IEEE 13 bus system and feature vectors corresponding to various islanding and non-islanding conditions, such as external grid faults and power system components switching, are used for SVM classifier training and testing. Simulation results show that proposed method is robust to external grid transients and able to accurately discriminate islanding conditions 50ms after the event begins

Testing and Evaluation of Wind Power Plant Protection System

Abstract. This paper discusses methodology and test set up which may be used for Wind Power Plant (WPP) planning and protection system evaluation. The test set up consists of a digital simulator, as well as a number of physical relays, recorders, software for system and relay modeling, signal editing, etc. Minimizing economic loss, in terms of using maximum output of wind generated power without interruption and causing minimum equipment damage due to faults, is the main benefit of having protection system that operates correctly. The correctness of operation is crucial during grid disturbances in preventing unwanted power plant disconnection and further system stability violation. Since there are no standardized requirements or methodology for WPP protection system testing, its evaluation is challenging and manly customized to fit a given solution. This paper discusses test requirements and test methodology to perform the evaluation in a comprehensive manner