Title
Hybrid particle swarm optimization with biased mutation applied to load flow computation in electrical power systems
Abstract
This paper presents the implementation of a Hybrid Particle Swarm Optimization with Biased Mutation (HPSOBM) algorithm to solve the load flow computation in electrical power systems. The load flow study obtains the system status in the steady-state and it is widely used in the power system operation, planning and control. The proposed methodology is applied in a different computational model, which is based on the minimization of the power mismatches in the system buses. This new model searches for a greater convergence, and also a larger application in comparison with traditional numerical methods. In order to illustrate the proposed algorithm some simulations were conducted using the IEEE 14 bus system.
Year
DOI
Venue
2011
10.1007/978-3-642-21515-5_70
ICSI (1)
Keywords
Field
DocType
electrical power system,bus system,system bus,new model search,power mismatches,load flow computation,hybrid particle swarm optimization,load flow study,system status,power system operation,different computational model,load flow,electrical power systems,evolutionary computation,artificial intelligence,particle swarm optimization
Particle swarm optimization,Convergence (routing),Mathematical optimization,Computer science,Electric power system,Evolutionary computation,Multi-swarm optimization,Minification,Numerical analysis,Computation
Conference
Volume
ISSN
Citations 
6728
0302-9743
0
PageRank 
References 
Authors
0.34
3
4