ARIIDTM - A Research on Innovative Islanding Detection Technique for Microgrid - Research Thesis by Dr.V.Arivumani

 Abstract: 

Islanding detection is a way of protecting the renewable energy integrated Microgrid from the power grid network during abnormal conditions like hazards, faults, etc. Various islanding detection methods (Passive, Active, Hybrid and Remote methods) are implemented with new technologies to protect renewable energy-powered Microgrids integrated with the power grid network. However, among these methods, Passive methods are preferred and reported in most of the literature due to their known feasibility. These methods are straightforward to model with few processing elements, fewer computational requirements, and faster detection of islanding events without affecting the power quality. Yet, these methods have larger NonDetection Zone (NDZ) in which the islanding is not performed for minor power mismatches. Other than a voltage-frequency relay, most practices have less NDZ but more interrupted tripping, affecting the Microgrid's equipment. In this research, islanding detection is performed by sensing the voltage deviation (overvoltage and undervoltage) and voltage unbalance conditions using four proposed techniques. Angular symmetrical component (ASC) based islanding detection technique is performed using Delta Voltage Deviation (DVD) and Tangent Angle of Unbalance (TAU) parameters. Voltage and angle deviation (VAD) based islanding detection is performed by estimating absolute maximum deviation of voltage and phase angle from rated voltage and 1200 respectively. Voltage deviation and unbalance (VDU) based islanding detection is performed by estimating absolute maximum voltage deviation and voltage unbalance factor which is estimated from individual line voltage deviations. Finally, the islanding detection is simply performed using minimum and maximum line voltage (MMV) among three unequal line iv voltages in the unbalance conditions. The threshold setting of Voltage deviation is fixed as 10% as per IEC 62116. The threshold setting of tangent angle of unbalance, maximum phase angle deviation, voltage unbalance factor, and the % of minimum voltage with maximum voltage are set as 10 , 20 , 2% and 97% respectively. The proposed methods are validated in solar photovoltaic integrated Microgrid under various islanding and non-islanding events with the help of MATLAB/SIMULINK software. Performance of the proposed islanding detection methods are compared with the conventional methods available in the literature, such as Overvoltage / Undervoltage / Overfrequency / Underfrequency relay, Rate of Change of Frequency (ROCOF), and Voltage Unbalance and Total Harmonic Distortion (VUTHD) by simulation results. From the simulation results, it is evident that the proposed techniques effectively identify the islanding events under voltage deviation and unbalance conditions in microgrid. Also, the relays will not detect the islanding during internal events like linear and non-linear load switching. From the investigations made, it is found that Minimum and Maximum Voltage based islanding detection involves fewer computational requirements and hence it is found suitable for islanding detection in real time under any abnormal conditions.

 The Thesis is available in ShodhGanga: https://shodhganga.inflibnet.ac.in/jspui/handle/10603/564562

Citation Link: http://hdl.handle.net/10603/564562