TY  - JOUR
T1  - A Particle Swarm Optimization with Random Particles and Fine-Tuning Mechanism for Nonconvex Economic Dispatch
AU - Yen, Chin-Wei AU - Tsai, Ming-Tang 
JO  - International Journal of Electrical and Power Engineering
VL  - 5
IS  - 1
SP  - 35
EP  - 41
PY  - 2011
DA  - 2001/08/19
SN  - 1990-7958
DO  - ijepe.2011.35.41
UR  - https://makhillpublications.co/view-article.php?doi=ijepe.2011.35.41
KW  - CF
KW  -Taiwan
KW  -particle swarm optimization
KW  -fine-tuning mechanism
KW  -Economic dispatch
KW  -valve-point effect
AB  - This study presents a new approach to the economic dispatch problems with valve-point effects. The practical economic dispatch problem has a nonconvex cost function with equality and inequality constraints that it is difficult to find the optimal solutions using any mathematical approaches. A Particle Swarm Optimization (PSO) with Random Particles and Fine-tuning mechanism (PSO-RPFT) is proposed to solve economic dispatch problem. The proposed developed in such a way that PSO with Constriction Factor (PSO-CF) is applied as a based level search which can give a good direction to the optimal global region. Random particles and fine-tuning mechanism is used as a fine tuning to determine the optimal solutions at the final. Effectiveness of the proposed method is demonstrated on 3 example systems and compared to that of SA, GA, EP. Results show that the proposed method is more effective in solving economic dispatch problem.
ER  -