DocumentCode :
1720093
Title :
Evolutionary Multi-Objective Optimization in Power Systems: State-of-the-Art
Author :
Rivas-Dávalos, F. ; Moreno-Goytia, E. ; Gutiérrez-Alacaraz, G. ; Tovar-Hernández, J.
Author_Institution :
Tecnol. de Morelia, Morelia
fYear :
2007
Firstpage :
2093
Lastpage :
2098
Abstract :
Electric utility industry is currently facing a market deregulated environment and many technological advances. In this context, the demand for electric power having higher network security, better power quality, improved system reliability, and availability is increasing every day. This complex scenario put the electric utilities under conflicting pressure between meeting the growth demands, reducing its operation cost, keeping maintenance and construction and try to provide lower rates for customers or to improve the company profits. Therefore, solutions for planning, design and operation of power systems involve the simultaneous optimization of multiple objectives, often conflicting between them. This work presents the state of the art of multi-objective evolutionary algorithms applications to electrical power systems, in order to provide the power system engineering community with the expertise about the development of multi-objective optimization paradigms and trends in the applications of multi-objective evolutionary algorithms, altogether useful for tackling down every-day electrical networks challenges.
Keywords :
evolutionary computation; power markets; power supply quality; power system economics; power system reliability; power system security; electric utility industry; evolutionary multiobjective optimization; network security; power markets; power quality; power systems; system reliability; Availability; Costs; Evolutionary computation; Maintenance; Power industry; Power quality; Power system planning; Power system reliability; Power system security; Power systems; Electric Power Systems; Evolutionary Algorithms; Multi-objective Optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power Tech, 2007 IEEE Lausanne
Conference_Location :
Lausanne
Print_ISBN :
978-1-4244-2189-3
Electronic_ISBN :
978-1-4244-2190-9
Type :
conf
DOI :
10.1109/PCT.2007.4538641
Filename :
4538641
Link To Document :
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