Title :
Improved Particle Swarm Optimization for Non-Convex Optimal Power Flow
Author :
Xia Shiwei ; Bai Xuefeng ; Guo Zhizhong ; Xu Ying
Author_Institution :
Dept. of Electr. Eng., Harbin Inst. of Technol., Harbin, China
Abstract :
This paper firstly proposes an improved particle swarm optimization (IPSO) by dynamically adjusting inertia weight, cognitive weight and social weight to strengthen the local and global search capability. Then the IPSO is applied for the non-convex optimal power flow (OPF) of the IEEE 6-genetor 30-bus system and New England 10-generator 39-bus system. All results verify the good convergence and global optimal performance of IPSO to solve the multi-minimum non-convex OPF problem in power system.
Keywords :
concave programming; load flow; particle swarm optimisation; power system simulation; IEEE 6-genetor; cognitive weight; global search capability; inertia weight; local search capability; multiminimum nonconvex OPF problem; nonconvex optimal power flow; particle swarm optimization; power system; social weight; Convergence; Fuels; Generators; Load flow; Optimization; Particle swarm optimization; Standards;
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2012 Asia-Pacific
Conference_Location :
Shanghai
Print_ISBN :
978-1-4577-0545-8
DOI :
10.1109/APPEEC.2012.6307503
