Intelligent power systems: Detection and location of line outages
Li, Miao (2014) Intelligent power systems: Detection and location of line outages. Other thesis, Murdoch University.
In recent decades, the stability of large power system has attracted much attention. There are many different factors that leading to power system collapse and cause large area blackouts. For example, as demands of consumption grows, the influence of harmonic components and reactive power constraints may cause failure in the power system (Jiao 2011).These factors are usually very difficult to predict in the real world. One of the most important parts of modern power system is the transmission line. With the increased demand for electricity and the scale-up of power networks, the number of long distance transmission lines has increased. They are exposed to different environments such as different weather conditions such as high temperatures or lightning and different terrains such as mountains or canyons. When a line outage happens, it can be very hard to detect the fault’s location and searching and replacing the power line may take quite a long time. This can cause inestimable damage to customers and nations. Even after successfully restoring the power, continuous monitoring of the power system is still needed. Improved monitoring of the power system status could avoid future failure events that could render significant losses to the economy.
The recent method called synchronized phasor measurement allows for real-time monitoring of the entire power system and therefore can be used to detect faults as they occur. Actually, it is the only method that can observe multiple buses in the power system. One such application is the detection of line outages in remote or unobserved parts of the system (Mahoney 2011). A novel algorithm based on DC power flow which can detect line outages effectively will be introduced in this thesis report. Reviewing the concept of DC power flow is an essential part of this report. The simulation softwares used in the report are Power Factory and MATLAB. Finally, the efficiency of the novel algorithm will be assessed. Some suggestions for future works will be presented at the end of this report.
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