Multi-objective Optimisation of Power Restoration in Electricity Distribution Systems

  • Alexandre Mendes
  • Natashia Boland
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7106)


This paper proposes a new multi-objective approach for the problem of power restoration in (n-1) contingency situations. It builds on a previous, mono-objective approach introduced in Mendes et al. (2010) [14]. Power restoration normally relies on network reconfiguration, and typically involves re-switching and adjustment of tap-changers and capacitor banks. In this work, we focus on re-switching strategies. The quality of the re-switching strategy is measured in terms of voltage deviations, number of consumers still affected after the reconfiguration, number of overloaded branches and number of switches changes. Due to the number of criteria and conflicting objectives, power restoration is a prime candidate for multi-objective optimisation. The method studied is based on a genetic algorithm and was tested using two real-world networks, with up to of 1,645 branches and 158 switches. We present a contingency example for each network and discuss the results obtained. Finally, we discuss the approach’s convergence by analysing the evolution of the solutions that compose the Pareto frontier.


Multi-objective optimisation genetic algorithms power distribution electricity networks 


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© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Alexandre Mendes
    • 1
  • Natashia Boland
    • 2
  1. 1.Centre for Intelligent Electricity Networks (CIEN), School of Electrical Engineering and Computer Science, Faculty of Engineering and Built EnvironmentThe University of NewcastleCallaghanAustralia
  2. 2.School of Mathematical and Physical Sciences, Faculty of Science and Information TechnologyThe University of NewcastleCallaghanAustralia

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