M. Tech. Electrical Engineering. / Discusses the practical management of electrical networks, no perfect monitoring of an electrical power system state is available, either because it is expensive or technically unfeasible due to the poor quality of the available measurements in the control centre. To have a stable network, the control centre must receive the network information to be able to provide a proper security in unforeseen situation. As a power system network is a complex and a non-linear system, it is important to use more advanced methods for its analysis and control in a real time environment. The aim of this research work is therefore, to apply several state estimation algorithms using artificial intelligence by developing their mathematical models for the purpose of comparing their performances in estimating the state variable of the power system. The three types of state estimation algorithms investigated for this research work are: the Particle Swarm Optimisation (PSO), the Genetic Algorithm (GA) and the Newton method for state estimation (NSE).
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:tut/oai:encore.tut.ac.za:d1001381 |
| Date | January 2013 |
| Creators | Tungadio,Diambomba Hyacinthe-St, |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Text |
| Format |
Page generated in 0.0018 seconds