Title :
Reactive power optimization in power system based on chaos ant colony algorithm
Author :
Liu, Zhe ; Zhao, Dongmei ; Zhang, Xu ; Dan, Baotao ; Guan, Fenghua
Author_Institution :
North China Electr. Power Univ., Beijing, China
Abstract :
A novel co-operative agents approach, ant colony optimization (ACO) algorithm, for solving problems of combinatorial optimization, is put forward by M. Dorigo. The main characteristics of ACO are positive feedback, distributed computation. Preliminary study has shown that it has many promising futures. This paper reviews recent work on ant algorithms and applications, the chaos ant colony optimization (CACO) algorithm is used in reactive power optimization problem in electric power system. The model of reactive power optimization is established taking the minimum network losses as the objective. Its validity is verified through arithmetic examples of IEEE30 node and a practical area network.
Keywords :
chaos; power engineering computing; power system control; IEEE30 node; chaos ant colony algorithm; power system; practical area network; reactive power optimization; Ant colony optimization; Chaos; Dynamic programming; Linear programming; Optimization methods; Power system modeling; Power system stability; Power systems; Reactive power; Voltage; Ant Colony Algorithm; Chaos sequence; Electric power system; Practical network; Reactive optimization;
Conference_Titel :
Sustainable Power Generation and Supply, 2009. SUPERGEN '09. International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4934-7
DOI :
10.1109/SUPERGEN.2009.5348366
