Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/14625
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSum-Im T.
dc.date.accessioned2021-04-05T03:36:01Z-
dc.date.available2021-04-05T03:36:01Z-
dc.date.issued2010
dc.identifier.other2-s2.0-79951615901
dc.identifier.urihttps://ir.swu.ac.th/jspui/handle/123456789/14625-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-79951615901&doi=10.1109%2fTENCON.2010.5685839&partnerID=40&md5=ea131bf89661ae7df25eca0493b1dbb8
dc.description.abstractIn this paper, a self-adaptive differential evolution algorithm (SaDEA) is proposed for solving conventional economic dispatch (ED) problem with transmission losses consideration. The purpose of ED problem is to minimize the total fuel cost of thermal power plants associated with the technical operation and economical constraints. The software development has been performed within the mathematical programming environment of MATLAB in this work. The efficiency of the proposed methodology is initially demonstrated via the analysis of IEEE 30-bus test case. A detailed comparative study among Lambda iteration, conventional genetic algorithm (CGA), tabu search/simulated annealing (TS/SA), ant colony search algorithm (ACSA) and the proposed method is presented. From the experimental results, the proposed method has achieved solutions with good accuracy, stable convergence characteristics, simple implementation and satisfactory computational time. ©2010 IEEE.
dc.subjectAnt colony search algorithms
dc.subjectComparative studies
dc.subjectComputational time
dc.subjectDifferential evolution algorithm
dc.subjectEconomic Dispatch
dc.subjectEconomic dispatch problems
dc.subjectFuel cost
dc.subjectPower system optimization
dc.subjectSelf-adaptive differential evolution algorithms
dc.subjectSoftware development
dc.subjectStable convergence
dc.subjectTechnical operations
dc.subjectTest case
dc.subjectThermal power plants
dc.subjectTransmission loss
dc.subjectAdaptive algorithms
dc.subjectArtificial intelligence
dc.subjectBiology
dc.subjectHeuristic algorithms
dc.subjectMathematical programming
dc.subjectSoftware design
dc.subjectTabu search
dc.subjectThermoelectric power plants
dc.subjectWave transmission
dc.subjectEvolutionary algorithms
dc.titleSelf-adaptive differential evolution algorithm for economic dispatch with transmission losses consideration
dc.typeConference Paper
dc.rights.holderScopus
dc.identifier.bibliograpycitationIEEE Region 10 Annual International Conference, Proceedings/TENCON. Vol , No. (2010), p.90-95
dc.identifier.doi10.1109/TENCON.2010.5685839
Appears in Collections:Scopus 1983-2021

Files in This Item:
There are no files associated with this item.


Items in SWU repository are protected by copyright, with all rights reserved, unless otherwise indicated.