Title :
Intelligent computational methods for power systems optimization problems
Author :
Pahwa, A. ; Chavali, S. ; Das, S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Kansas State Libr., Manhattan, KS, USA
Abstract :
Many power systems problems require optimization of an objective. Several of these problems are combinatorial and thus they have a discrete objective function. Various intelligent computational methods, some derived from nature, were used to solve such problems. This presentation provides a brief introduction to various intelligent computational methods. Results obtained for an example problem using a genetic algorithm and an ant colony optimization approach is presented and compared.
Keywords :
genetic algorithms; power system planning; ant colony optimization approach; discrete objective function; genetic algorithm; intelligent computational methods; power systems optimization problems; system planning; Ant colony optimization; Computational intelligence; Computational modeling; Genetic algorithms; Optimization methods; Power system planning; Power system reliability; Power systems; Simulated annealing; Solids;
Conference_Titel :
Power Engineering Society General Meeting, 2003, IEEE
Print_ISBN :
0-7803-7989-6
DOI :
10.1109/PES.2003.1267153
