dc.contributor.author | Musau, Peter Moses | |
dc.contributor.author | Abungu, Nicodemus Odero | |
dc.date.accessioned | 2018-12-04T07:19:10Z | |
dc.date.available | 2018-12-04T07:19:10Z | |
dc.date.issued | 2013 | |
dc.identifier.issn | 2250-2459 | |
dc.identifier.uri | http://ir.mksu.ac.ke/handle/123456780/2096 | |
dc.description.abstract | Due to the increased importance of DFIGs in
optimization of real and reactive power losses and the
maintenance of voltage profile, the general methods of DG
placement and sizing in the existing literature cannot be of
practical importance in DFIG .In this paper a pure PSO
method used in general DG is compared with a HGAPSO in
the siting and sizing of DFIG with the objective of minimizing
power losses .The corresponding Combined participation
factors are assigned using the DFIG Domain Distributed
Slack Bus Model and a comparison made on the two schemes
of loss minimization. The obtained results for the real and
reactive power losses and voltage voltage profile illustrate the
DFIG need in the modern power system. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Distributed Generator (DG) | en_US |
dc.subject | Doubly Fed Induction generator (DFIG) | en_US |
dc.subject | Hybrid GAPSO (HGAPSO) | en_US |
dc.subject | Genetic Algorithm(GA), | en_US |
dc.subject | Particle Swarm Optimisation (PSO) | en_US |
dc.title | Power Loss Reduction in the Active Distribution Network by Doubly Fed Induction Generator (DFIG) Placement and Sizing Using Ordinary Particle Swarm Optimization (PSO) and an hybrid of Genetic Algorithm (GA) and PSO (HGAPSO) | en_US |
dc.type | Article | en_US |