Title :
An improved particle swarm optimization algorithm for optimal power flow
Author :
Liu, Weibing ; Li, Min ; Wang, Xianjia
Author_Institution :
Sch. of Political Sci. & Public Manage., Wuhan Univ., Wuhan, China
Abstract :
This paper presents the solution of optimal power flow using particle swarm optimization algorithm. This paper proposes a novel improved particle swarm optimization for solving the optimal power flow problem. This method can be divided into two parts. In the first part a multi-start technique is introduced to overcome premature convergence, while the other part employs improved particle swarm optimization algorithm to obtain the optimal solution. IEEE 30-bus system is used to test the performance of this solution technique, and the numerical results show that the proposed algorithm is superior to genetic algorithm and conventional particle swarm optimization algorithm for the optimal power flow problem.
Keywords :
load flow; particle swarm optimisation; IEEE 30-bus system; multistart technique; optimal power flow; particle swarm optimization algorithm; Cost function; Energy management; Genetic algorithms; Linear programming; Load flow; Niobium; Particle swarm optimization; Power generation; Power generation economics; System testing;
Conference_Titel :
Power Electronics and Motion Control Conference, 2009. IPEMC '09. IEEE 6th International
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-3556-2
Electronic_ISBN :
978-1-4244-3557-9
DOI :
10.1109/IPEMC.2009.5157813