dc.contributor.author | Nguyen, Thuan Thanh | |
dc.contributor.author | Nguyen, Thang Trung | |
dc.date.accessioned | 2023-04-14T08:33:46Z | |
dc.date.available | 2023-04-14T08:33:46Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Advances in electrical and electronic engineering. 2022, vol. 20, no. 4, p. 418 - 431 : ill. | cs |
dc.identifier.issn | 1336-1376 | |
dc.identifier.issn | 1804-3119 | |
dc.identifier.uri | http://hdl.handle.net/10084/149245 | |
dc.description.abstract | Power loss in the Distribution System (DS)
is often higher than that of other parts of the power
system because of its low voltage level. Therefore,
reducing losses is always an important task in de-
sign and operation of the DS. This paper aims to
apply a new approach based on Artificial Ecosystem
Optimization (AEO) for the Distributed Generation
Placement (DGP) and combination of DGP and net-
work REConfiguration (DGP-REC) problems to reduce
power loss of the DS to satisfy the technical constraints
including power balance, radial topology, voltage and
current bounds, and DG capacity limit. The AEO is
a recent algorithm that has no special control parame-
ters, inspired from the behaviours of living organisms
in the ecosystem including production, consumption,
and decomposition. The efficiency of the AEO is eval-
uated on two test systems including the 33-node and
119-node systems. The numerical results validated on
the 33-node and 119-node systems show that DGP-REC
is a more effective solution for reducing power loss com-
pared to the DGP solution. In addition, evaluation re-
sults on small and large systems also indicate that AEO
is an effective approach for the DGP and DGP-REC
problems. | cs |
dc.language.iso | en | cs |
dc.publisher | Vysoká škola báňská - Technická univerzita Ostrava | cs |
dc.relation.ispartofseries | Advances in electrical and electronic engineering | cs |
dc.relation.uri | https://doi.org/10.15598/aeee.v20i4.4535 | cs |
dc.rights | © Vysoká škola báňská - Technická univerzita Ostrava | |
dc.rights | Attribution-NoDerivatives 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nd/4.0/ | * |
dc.subject | artificial ecosystem optimization | cs |
dc.subject | distributed generation | cs |
dc.subject | distribution system | cs |
dc.subject | power loss | cs |
dc.subject | radial topology | cs |
dc.subject | REConfiguration | cs |
dc.title | Power Loss Minimization by Optimal Placement of Distributed Generation Considering the Distribution Network Configuration Based on Artificial Ecosystem Optimization | cs |
dc.type | article | cs |
dc.identifier.doi | 10.15598/aeee.v20i4.4535 | |
dc.rights.access | openAccess | cs |
dc.type.version | publishedVersion | cs |
dc.type.status | Peer-reviewed | cs |