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European Conference on the Applications of Evolutionary Computation

EvoApplications 2017: Applications of Evolutionary Computation pp 329–341Cite as

Adaptive Batteries Exploiting On-Line Steady-State Evolution Strategy

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10199))

Abstract

In energy distribution systems, uncertainty is the major single cause of power outages. In this paper, we consider the usage of electric batteries in order to mitigate it. We describe an intelligent battery able to maximize its own lifetime while guaranteeing to satisfy all the electric demand peaks. The battery exploits a customized steady-state evolution strategy to dynamically adapt its recharge strategy to changing environments. Experimental results on both synthetic and real data demonstrate the efficacy of the proposed solution.

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Notes

  1. 1.

    An area that never exceeds the part of energy assigned to it by the network is called independent; the more independent parts a network has, the more it is robust and do not risk a power outage see [3, 4].

  2. 2.

    See http://flexmeter.polito.it/.

  3. 3.

    https://bitbucket.org/EdoFadda/electricgame/.

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Author information

Authors and Affiliations

  1. Politecnico di Torino, Corso Duca Degli Abruzzi 24, Torino, Italy

    Edoardo Fadda, Guido Perboli & Giovanni Squillero

  2. CIRRELT, Montreal, Canada

    Guido Perboli

Authors
  1. Edoardo Fadda
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  2. Guido Perboli
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  3. Giovanni Squillero
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Corresponding author

Correspondence to Edoardo Fadda .

Editor information

Editors and Affiliations

  1. Politecnico di Torino, Turin, Italy

    Giovanni Squillero

  2. Edinburgh Napier University, Edinburgh, United Kingdom

    Kevin Sim

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Fadda, E., Perboli, G., Squillero, G. (2017). Adaptive Batteries Exploiting On-Line Steady-State Evolution Strategy. In: Squillero, G., Sim, K. (eds) Applications of Evolutionary Computation. EvoApplications 2017. Lecture Notes in Computer Science(), vol 10199. Springer, Cham. https://doi.org/10.1007/978-3-319-55849-3_22

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  • DOI: https://doi.org/10.1007/978-3-319-55849-3_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55848-6

  • Online ISBN: 978-3-319-55849-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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