This 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 |
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Original language | English |
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Awarding Institution | |
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Supervisor | Roderick Dunn (Supervisor) & Haifeng Wang (Supervisor) |
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Genetic Algorithms Applications to Power System Security Schemes
Elwerfelli, M. (Author). 1 Aug 2009
Student thesis: Doctoral Thesis › PhD