Publication:
Congestion management based optimization technique using bee colony

Simple item page
dc.citedby12
dc.contributor.authorRahim M.A.en_US
dc.contributor.authorMusirin I.en_US
dc.contributor.authorAbidin I.Z.en_US
dc.contributor.authorOthman M.M.en_US
dc.contributor.authorJoshi D.en_US
dc.contributor.authorid58773347500en_US
dc.contributor.authorid8620004100en_US
dc.contributor.authorid35606640500en_US
dc.contributor.authorid35944613200en_US
dc.contributor.authorid55431909000en_US
dc.date.accessioned2023-12-29T07:49:08Z
dc.date.available2023-12-29T07:49:08Z
dc.date.issued2010
dc.description.abstractCongestion management problem is a popular issue in power system which can be due to line, voltage and thermal constraints. This phenomenon can possibly lead to voltage instability occurrence, loss increment and voltage drop in power system. Therefore, a proper management of congestion should be carried appropriately in order to maintain system operability considering all the available constraints. This paper presents congestion management problem using bee colony optimization approach. The aim of the study is to optimize the cost of generation in power system network within the given available constraints. The study involved the development of bee colony algorithm in addressing congestion management, considering cost optimization as the objective function. Line constraint is also taken into consideration in this study which depends on the electrical power provider to allow the power delivered to the customers. Tests conducted on the IEEE 30-Bus Reliability Test System for performance assessment revealed that the proposed bee algorithm technique is better than evolutionary programming technique in addressing this problem. �2010 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo5559247
dc.identifier.doi10.1109/PEOCO.2010.5559247
dc.identifier.epage188
dc.identifier.scopus2-s2.0-77958001041
dc.identifier.spage184
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-77958001041&doi=10.1109%2fPEOCO.2010.5559247&partnerID=40&md5=63effb4c58ac95a49219300c4f307c9f
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/30540
dc.pagecount4
dc.sourceScopus
dc.sourcetitlePEOCO 2010 - 4th International Power Engineering and Optimization Conference, Program and Abstracts
dc.subjectBee colony algorithm
dc.subjectCongestion management
dc.subjectCost optimization
dc.subjectElectrical
dc.subjectAlgorithms
dc.subjectComputer programming
dc.subjectCosts
dc.subjectManagement
dc.subjectBee Algorithm
dc.subjectColony algorithms
dc.subjectColony optimization
dc.subjectCongestion management
dc.subjectCost optimization
dc.subjectElectrical
dc.subjectElectrical power
dc.subjectEvolutionary programming
dc.subjectObjective functions
dc.subjectOptimization techniques
dc.subjectPerformance assessment
dc.subjectPower system networks
dc.subjectPower systems
dc.subjectReliability test system
dc.subjectThermal constraints
dc.subjectVoltage drop
dc.subjectVoltage instability
dc.subjectOptimization
dc.titleCongestion management based optimization technique using bee colonyen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
Files
Collections
SCOPUS