AbstractThis thesis details the approaches which aim to automatically optimize power system security schemes. In this research, power system security scheme includes two main plans. The first plan, which is called the defence plan scheme, is about preventing cascading blackouts while the second plan, which is called the restoration plan, is about rebuilding the power system in case of failure of the first plan. Practically, the defence plan includes under-frequency load shedding and under-frequency islanding schemes. These two schemes are always considered the last stage of the defensive actions against any severe incident. It is recognized that it is not easy for any power system’s operational planner to obtain the minimum amount of load shedding or the best power system islanding formation. In the case of defence plan failure, which is always possible, a full or partial system collapse may occur. In this situation, the power system operator is urgently required to promptly restore the system. This is not an easy task, since the operator must not violate many power system security constraints. In this research, genetic algorithms and expert systems are employed, as optimization methods, to identify the best amount of load shedding and island formation for the defence plan and the shortest path to rebuild the power system for the restoration plan. In the process of designing the power system security scheme, the majority of the electromechanical power system security constraints are considered. It is well known that power system optimization problems often have a huge solution space. In this regard, many successful techniques have been used to reduce the size of the solution spaces associated with the optimization of the power system security schemes in this work. The Libyan power system is used as an industrial case study to validate the practicality of the research approaches. The results clearly show that the new methods that have been researched in this PhD work have shown great success. Using the Libyan power system, the optimized defence plan has been compared to the current defence plan. The results of this comparison have shown that the optimized defence plan outperforms the current one. Regarding the optimized restoration plan, the results present the fact that the Libyan power system can be restored in reasonable time.
|Date of Award||1 Aug 2009|
|Supervisor||Roderick Dunn (Supervisor) & Haifeng Wang (Supervisor)|
Genetic Algorithms Applications to Power System Security Schemes
Elwerfelli, M. (Author). 1 Aug 2009
Student thesis: Doctoral Thesis › PhD