DocumentCode :
473607
Title :
Optimum allocation of generation for maximum loadability limit of power system using Multiagent Based Particle Swarm Optimization (MAPSO)
Author :
Shunmugalatha, A. ; Slochanal, S. Mary Raja
Author_Institution :
Electr. & Electron. Eng. Dept., K.L.N Coll. of Eng., Pottapalayam
fYear :
2007
fDate :
3-6 Dec. 2007
Firstpage :
1349
Lastpage :
1354
Abstract :
The problem of voltage stability is one of the main concerns in the operation of power systems. There are different approaches to estimate the voltage stability of the systems. Estimating the maximum loadability limit of power systems is one of the approaches. Maximum loadability limit is the margin between the operating point of the system and the maximum loading point. The optimum allocation of generation for maximum loadability limit of power system can be formulated as an optimization problem. The problem consists of two steps namely finding maximum loadability limit of power system and optimum cost of generation for the same. This paper utilizes the newly developed Evolutionary Multiagent Based Particle Swarm Optimization (MAPSO) in solving this optimization problem. Details of the implementation of the proposed method to IEEE- 30 bus system and IEEE-57 bus system are presented. Simulation results show that the proposed approach converges to better solution much faster, which prove the loadability and applicability of the proposed method.
Keywords :
load dispatching; multi-agent systems; particle swarm optimisation; power engineering computing; power system economics; power system stability; IEEE- 30 bus system; IEEE-57 bus system; maximum loadability limit; multiagent based particle swarm optimization; optimum generation allocation; voltage stability; Particle swarm optimization; Power engineering; Power generation; Power systems; economic load dispatch; maximum loadability limit; multiagent system; particle swarm optimization and voltage stability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Engineering Conference, 2007. IPEC 2007. International
Conference_Location :
Singapore
Print_ISBN :
978-981-05-9423-7
Type :
conf
Filename :
4510236
Link To Document :
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