Title :
Optimal Reactive Power Optimization by Ant Colony Search Algorithm
Author :
Oumarou, Ibrahim ; Jiang, Daozhuo ; Yijia, Cao
Author_Institution :
Coll. of Eletrcal Eng., Zhejiang Univ., Hangzhou, China
Abstract :
The paper presents an Ant Colony Search Algorithm (ACSA) for optimal reactive power optimization and voltage control of power systems. ACSA is a new co-operative agents´ approach, which is inspired by the observation of the behavior of real ant colonies on the topic of ant trial formation and foraging methods. Hence, in the ACSA a set of co-operative agents called ¿Ants¿ co-operates to find better solution for reactive power optimization problem. To analyze the efficiency and effectiveness of this search algorithms,the proposed methods is applied to the IEEE 30, 57, 191(practical) test bus system and the results are compared to those of conventional mathematical methods, genetic algorithm and adaptive genetic algorithm.
Keywords :
optimisation; power systems; reactive power control; search problems; voltage control; IEEE 191; IEEE 30; IEEE 57; ant colony search algorithm; cooperative agents; optimal reactive power optimization; power systems; test bus system; voltage control; Ant colony optimization; Costs; Genetic algorithms; Optimization methods; Power generation; Power systems; Propagation losses; Reactive power; Reactive power control; Voltage control; Ant colony Search Algorithm; Genetic Algorithm; Reactive Power Optimization;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.602
