Study on the Microgrid Fault Locating Combining with Load Forecasting

• Main Authors: Ping-Hsuan Hsieh, 謝秉烜
• Other Authors: Tsai-Hsiang Chen
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/t9bx9h

碩士 === 國立臺灣科技大學 === 電機工程系 === 105 === This thesis aims to study the microgrid fault locating based on load forecasting. The neural network technology is used to calculate the system load and renewable energy of each day. In order to improve the overall operation of the system reliability. This paper used the Particle Swarm Optimization (PSO) algorithm and the bus voltage variation by fault current which is Taiwan Power Company (TPC) and distributed generation provided to locate the fault. First, simulate the micro-grid system which is constructed by the Institute of Nuclear Energy Research Atomic Energy Council by using ETAP PowerStation software and the information including system structure, history load data and renewable energy data in order to execute fault location. Secondly, using MATLAB® software to build the matrix including system impedance matrix and bus voltage matrix and calculating the fault current when the fault occur. The simulation results by Particle Swarm Optimization show that the proposed method can be used to locate the fault based on load forecasting on the radial micro-grid.