DocumentCode :
3509283
Title :
A genetic algorithm approach to optimization of power peaks in an automated warehouse
Author :
Cárdenas, J.J. ; Garcia, A. ; Romeral, J.L. ; Andrade, F.
Author_Institution :
Motion Control & Ind. Applic. Group, Tech. Univ. of Catalonia, Terrassa, Spain
fYear :
2009
fDate :
3-5 Nov. 2009
Firstpage :
3297
Lastpage :
3302
Abstract :
The simultaneous operation of the automated storage and retrieval machines (ASRs) in an automated warehouse can increase the likelihood that high power demand peaks turn unstable the electric system. Furthermore, high power peaks mean the need for more electrical power contracted, which in turns leads to more fixed operation cost and inefficient use of the electrical installations. In this context, we present a genetic algorithm approach to implement demand-side management (DSM) in an automated warehouse. It has been based on real data from ASRs and models of prognosis of load profile of ASRs. We took into account two main goals: minimize instantaneous power demand and keeping the performance of the system store and retrieval times.
Keywords :
demand side management; genetic algorithms; warehouse automation; automated retrieval machines; automated storage machines; automated warehouse; demand-side management; electric system; electrical power; genetic algorithm approach; power peak optimization; Costs; Genetic algorithms; Material storage; Motion control; Motion planning; Power demand; Power quality; Power system management; Production facilities; Storage automation; Genetic algorithm; automated warehouse; demand-side management; storage and retrieval machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics, 2009. IECON '09. 35th Annual Conference of IEEE
Conference_Location :
Porto
ISSN :
1553-572X
Print_ISBN :
978-1-4244-4648-3
Electronic_ISBN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2009.5415200
Filename :
5415200
Link To Document :
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