Programmable Device Circuits and Systems

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Improved Particle Swarm Algorithm Applied to Optimal Real Power Loss Control


Affiliations
1 Department of Electrical and Electronics Engineering, VLB Janakiammal College of Engineering and Technology, Coimbatore, India
2 Akshaya College of Engineering and Technology, Coimbatore, India
3 VLB Janakiammal College of Engineering and Technology, Coimbatore, India
     

   Subscribe/Renew Journal


This paper presents an optimization algorithm to solve the optimal real power loss control problem. In PSO, particle studies from itself and the best one among the group only. In the proposed Improved Particle Swarm Optimization (IPSO) it studies from itself, the best one among the group and also from neighboring particles. By this enhanced behavior of IPSO, the opportunity to find the global solution is guaranteed and the speed of convergence is improved. The feasibility of the proposed method is demonstrated and results are compared with classical PSO. The developed IPSO has been tested on 6 bus Ward-Hale system and modified IEEE 14 bus system for optimal real power loss control problem.

Keywords

IEEE 14 Bus Systems, Improved Particle Swarm Optimization, Optimal Real Power Control, Ward-Hale 6 Bus System.
User
Subscription Login to verify subscription
Notifications
Font Size

Abstract Views: 181

PDF Views: 2




  • Improved Particle Swarm Algorithm Applied to Optimal Real Power Loss Control

Abstract Views: 181  |  PDF Views: 2

Authors

K. S. Chandragupta Mauryan
Department of Electrical and Electronics Engineering, VLB Janakiammal College of Engineering and Technology, Coimbatore, India
K. Thanushkodi
Akshaya College of Engineering and Technology, Coimbatore, India
C. K. Goghul Raman
VLB Janakiammal College of Engineering and Technology, Coimbatore, India

Abstract


This paper presents an optimization algorithm to solve the optimal real power loss control problem. In PSO, particle studies from itself and the best one among the group only. In the proposed Improved Particle Swarm Optimization (IPSO) it studies from itself, the best one among the group and also from neighboring particles. By this enhanced behavior of IPSO, the opportunity to find the global solution is guaranteed and the speed of convergence is improved. The feasibility of the proposed method is demonstrated and results are compared with classical PSO. The developed IPSO has been tested on 6 bus Ward-Hale system and modified IEEE 14 bus system for optimal real power loss control problem.

Keywords


IEEE 14 Bus Systems, Improved Particle Swarm Optimization, Optimal Real Power Control, Ward-Hale 6 Bus System.