Andrés Cacereño, David Greiner, Andrés Zuñiga, Blas J. Galván

Design and Maintenance Optimisation of Substation Automation Systems: A Multiobjectivisation Approach Exploration

  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Hardware and Architecture
  • Mechanical Engineering
  • General Chemical Engineering
  • Civil and Structural Engineering
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Substation automation systems (SAS) are critical infrastructures whose design and maintenance must be optimised to guarantee a suitable performance. In order to provide a collection of solutions that balance availability and cost, this paper explores the optimisation of the design and maintenance of a section of SAS. Multiobjective evolutionary algorithms are combined with discrete event simulation while the performance of two state-of-the-art multiobjective evolutionary algorithms is studied. On the one hand, the nondominated sorting genetic algorithm II (NSGA-II), and on the other hand, the S-metric selection evolutionary multiobjective optimisation algorithm (SMS-EMOA). Such a problem is solved from 2 and 3-objective approaches by attending to the multiobjectivisation concept. The robustness of the methodology is brought to light, and benefits were observed from the multiobjectivisation approach. Decision-makers can employ this knowledge to make informed decisions based on economic and reliability criteria.

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