DocumentCode :
2854374
Title :
A Self-Adaptive Improved Particle Swarm Optimization Algorithm and Its Application in Available Transfer Capability Calculation
Author :
Chen, Hou-he ; Li, Guo-qing ; Liao, Hai-liang
Author_Institution :
North China Electr. Power Univ., Beijing, China
Volume :
3
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
200
Lastpage :
205
Abstract :
A self-adaptive improved particle swarm optimization (IPSO) algorithm applied to available transfer capability (ATC) calculation is presented in this paper. Firstly, a new self-adaptive adjustment inertia-weighted strategy factor, which elevates the adaptability of particle swarm optimization (PSO) and accelerates convergence-speed of PSO, is proposed. Secondly, studying the search characteristics of PSO, penalty function is assigned dynamically. By this enhanced study behavior, the opportunity to find the global optimum is increased and the influence of the initial position of the particles is decreased. Thirdly, IPSO algorithm is adopted to solve the problem of ATC calculation. At last, the numeric simulation for IEEE 30-bus system demonstrates that this new IPSO is feasible and effective to solve the problem of ATC calculation.
Keywords :
algorithm theory; particle swarm optimisation; self-adjusting systems; global optimum; numeric simulation; penalty function; self-adaptive adjustment inertia-weighted strategy factor; self-adaptive improved particle swarm optimization algorithm; transfer capability calculation; Acceleration; Computational modeling; Convergence; Evolutionary computation; Iterative algorithms; Load flow; Neural networks; Numerical simulation; Particle swarm optimization; System identification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
Type :
conf
DOI :
10.1109/ICNC.2009.214
Filename :
5365602
Link To Document :
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