Study on Location Identification Method of Power Line Outages Using PMU Measurements for Power System

• Main Authors: Wen-Tai Li, 李文泰
• Other Authors: Chao-Kai Wen
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/d7u556

博士 === 國立中山大學 === 通訊工程研究所 === 106 === Detecting and identifying power line outage events and locations quickly and accurately, which are providing the potential of preventing a large-scale blackout due to line outages as well as correct power network status for other monitoring and control tasks, e.g., state estimation and optimal power flow, are of paramount importance in the operation and maintenance of electric power systems.Recently, the widespread installation of phasor measurement units (PMUs) on transmission grids of most major power systems has attracted considerable attention for their potential to improve the reliability of power transmission.With the obtainment of wide-scale, real-time PMU data, the use of phasor angle measurements provided by PMUs in identifying locations of power line outages is regarded as a promising method, and thus a surge of interest in exploring applications with utilizing PMUs in line outages identification has been evident. The aim of this paper is to develop novel identification methods of power line outages with PMU measurements. Owing to the problem of power line outage identification has traditionally been formulated as a combinatorial optimization problem, the optimal solution of which can be found through an exhaustive search. However, the size of the search space grows exponentially with the number of outages and may thus pose a potential problem for the practical implementation of an exhaustive search, especially when multiple power line outages are considered in a power system. Hence, we propose a novel global stochastic optimization technique based on cross-entropy optimization to correctly and promptly identify multiple line outages. Then, we consider the cases of phasor angle measurements with bad data due to that communication errors or system malfunctions may introduce errors to the measurements and thus yield bad data. Most of the existing methods on line outage identification fail to consider such error. Hence, this paper further investigates the impact of identifying line outage using PMU measurements with bad data, and then develops a framework for identifying multiple power line outages based on the PMUs'' measurements in the presence of bad data. In particular, we design an algorithm to identify locations of line outage and recover the faulty measurements simultaneously. To validate the effectiveness and efficiency of the proposed approaches, case studies are carried on IEEE standard test systems.