A multi-objective GA to demand-side management in an automated warehouse

  • Authors:

  • J. J. Cárdenas;A. García;J. J. Romeral;J. C. Urresty

  • Affiliations:

  • MCIA Group, Universitat Politècnica de Catalunya, Terrassa, Catalonya, Spain;MCIA Group, Universitat Politècnica de Catalunya, Terrassa, Catalonya, Spain;MCIA Group, Universitat Politècnica de Catalunya, Terrassa, Catalonya, Spain;MCIA Group, Universitat Politècnica de Catalunya, Terrassa, Catalonya, Spain

  • Venue:
  • ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
  • Year:
  • 2009

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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 tum 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 multi-objective genetic algorithm approach (MOGA) to implement demand-side management (DSM) in an automated warehouse. It works minimizing the total energy demand, but without increasing substantially the time for the operation. Simulations show the performances of the new approach.