Title :
An Evolutionary Technique with Fast Convergence for Power System Topological Observability Analysis
Author :
Vázquez-Rodríguez, S. ; Faína, A. ; Neira-Duenas, B.
Author_Institution :
Univ. of La Coruna, Coruna
Abstract :
In this paper we use genetic algorithms for the determination of the observability of electrical power systems from the point of view of topological observability. The problem can be reduced to the determination of whether a spanning tree that fulfills certain conditions with regards to the use of available measurements exists. To this end we have developed a more appropriate encoding for handling graphs and a more efficient fitness function of low computational cost that is able to avoid local optima and accelerate convergence. The procedure was successfully applied to standard benchmark IEEE electrical power systems and we present some results for one of them.
Keywords :
electric power generation; genetic algorithms; observability; power markets; power systems; evolutionary technique; fast convergence; genetic algorithms; high voltage transportation lines; power system topological observability analysis; spanning tree; Acceleration; Computational efficiency; Convergence; Encoding; Genetic algorithms; Observability; Power system analysis computing; Power system measurements; State estimation; Tree graphs;
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9487-9
DOI :
10.1109/CEC.2006.1688699