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Synchrony-optimized networks of Kuramoto oscillators with inertia

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  • Pinto, Rafael S.
  • Saa, Alberto

Abstract

We investigate synchronization in networks of Kuramoto oscillators with inertia. More specifically, we introduce a rewiring algorithm consisting basically in a hill climb scheme in which the edges of the network are swapped in order to enhance its synchronization capacity. We show that the synchrony-optimized networks generated by our algorithm have some interesting topological and dynamical properties. In particular, they typically exhibit an anticipation of the synchronization onset and are more robust against certain types of perturbations. We consider synthetic random networks and also a network with a topology based on an approximated model of the (high voltage) power grid of Spain, since networks of Kuramoto oscillators with inertia have been used recently as simplified models for power grids, for which synchronization is obviously a crucial issue. Despite the extreme simplifications adopted in these models, our results, among others recently obtained in the literature, may provide interesting principles to guide the future growth and development of real-world grids, specially in the case of a change of the current paradigm of centralized towards distributed generation power grids.

Suggested Citation

  • Pinto, Rafael S. & Saa, Alberto, 2016. "Synchrony-optimized networks of Kuramoto oscillators with inertia," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 77-87.
    • Handle: RePEc:eee:phsmap:v:463:y:2016:i:c:p:77-87
    DOI: 10.1016/j.physa.2016.07.009
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    Cited by:

    1. Zou, Yanli & Wang, Ruirui & Gao, Zheng, 2020. "Improve synchronizability of a power grid through power allocation and topology adjustment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 548(C).
    2. Arinushkin, P.A. & Vadivasova, T.E., 2021. "Nonlinear damping effects in a simplified power grid model based on coupled Kuramoto-like oscillators with inertia," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).

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