Contingency based congestion management and cost minimization using bee colony optimization technique
Unexpected contingency occurrence in a power system network can lead to high current flow in the system. This has made the system to be in a stressed condition which causes congestion to the system, while instability can be the next unpredictable incident. High current flow may also impose high fuel...
Saved in:
Main Authors: | , , , |
---|---|
Other Authors: | |
Format: | Conference paper |
Published: |
2023
|
Subjects: | |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
my.uniten.dspace-30622 |
---|---|
record_format |
dspace |
spelling |
my.uniten.dspace-306222023-12-29T15:50:24Z Contingency based congestion management and cost minimization using bee colony optimization technique Rahim M.N.A. Musirin I. Abidin I.Z. Othman M.M. 55323600600 8620004100 35606640500 35944613200 Bee colony Congestion management Cost optimization Electrical Bandpass filters Electric lines Optimization Transmission line theory Bee colony Colony optimization Congestion management Control variable Cost minimization Cost optimization Current flows Electrical Fuel cost High currents Offline Power system networks Reliability test system System security Test systems Transmission constraint Transmission line Costs Unexpected contingency occurrence in a power system network can lead to high current flow in the system. This has made the system to be in a stressed condition which causes congestion to the system, while instability can be the next unpredictable incident. High current flow may also impose high fuel cost of the generators. Thus, congestion needs to be managed properly in order to reduce the undesired current flow in the transmission line for maintaining system security. This paper presents contingency based congestion management and cost minimization using bee colony optimization technique. In this study, bee colony optimization technique is applied to optimize the current flow in the system such that system security is preserved; considering transmission lines as the control variables. N-1 contingency is considered as the forecasted event, implemented offline so that the performance of the system can be evaluated. Cost minimization is also conducted by controlling the transmission constraints in the system. Validation through the IEEE 30-reliability test system and 6-Bus test system are conducted to simulate the scenarios. �2010 IEEE. Final 2023-12-29T07:50:24Z 2023-12-29T07:50:24Z 2010 Conference paper 10.1109/PECON.2010.5697705 2-s2.0-79951805150 https://www.scopus.com/inward/record.uri?eid=2-s2.0-79951805150&doi=10.1109%2fPECON.2010.5697705&partnerID=40&md5=6eb89f478e6ac2658dafedb9b3651b0a https://irepository.uniten.edu.my/handle/123456789/30622 5697705 891 896 Scopus |
institution |
Universiti Tenaga Nasional |
building |
UNITEN Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Tenaga Nasional |
content_source |
UNITEN Institutional Repository |
url_provider |
http://dspace.uniten.edu.my/ |
topic |
Bee colony Congestion management Cost optimization Electrical Bandpass filters Electric lines Optimization Transmission line theory Bee colony Colony optimization Congestion management Control variable Cost minimization Cost optimization Current flows Electrical Fuel cost High currents Offline Power system networks Reliability test system System security Test systems Transmission constraint Transmission line Costs |
spellingShingle |
Bee colony Congestion management Cost optimization Electrical Bandpass filters Electric lines Optimization Transmission line theory Bee colony Colony optimization Congestion management Control variable Cost minimization Cost optimization Current flows Electrical Fuel cost High currents Offline Power system networks Reliability test system System security Test systems Transmission constraint Transmission line Costs Rahim M.N.A. Musirin I. Abidin I.Z. Othman M.M. Contingency based congestion management and cost minimization using bee colony optimization technique |
description |
Unexpected contingency occurrence in a power system network can lead to high current flow in the system. This has made the system to be in a stressed condition which causes congestion to the system, while instability can be the next unpredictable incident. High current flow may also impose high fuel cost of the generators. Thus, congestion needs to be managed properly in order to reduce the undesired current flow in the transmission line for maintaining system security. This paper presents contingency based congestion management and cost minimization using bee colony optimization technique. In this study, bee colony optimization technique is applied to optimize the current flow in the system such that system security is preserved; considering transmission lines as the control variables. N-1 contingency is considered as the forecasted event, implemented offline so that the performance of the system can be evaluated. Cost minimization is also conducted by controlling the transmission constraints in the system. Validation through the IEEE 30-reliability test system and 6-Bus test system are conducted to simulate the scenarios. �2010 IEEE. |
author2 |
55323600600 |
author_facet |
55323600600 Rahim M.N.A. Musirin I. Abidin I.Z. Othman M.M. |
format |
Conference paper |
author |
Rahim M.N.A. Musirin I. Abidin I.Z. Othman M.M. |
author_sort |
Rahim M.N.A. |
title |
Contingency based congestion management and cost minimization using bee colony optimization technique |
title_short |
Contingency based congestion management and cost minimization using bee colony optimization technique |
title_full |
Contingency based congestion management and cost minimization using bee colony optimization technique |
title_fullStr |
Contingency based congestion management and cost minimization using bee colony optimization technique |
title_full_unstemmed |
Contingency based congestion management and cost minimization using bee colony optimization technique |
title_sort |
contingency based congestion management and cost minimization using bee colony optimization technique |
publishDate |
2023 |
_version_ |
1806427549800071168 |
score |
13.211869 |