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Bio-inspired design for robust power grid networks

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  • Panyam, Varuneswara
  • Huang, Hao
  • Davis, Katherine
  • Layton, Astrid

Abstract

Technological advances have created a world where humans are highly dependent on an uninterrupted electric power supply, yet extreme weather events and deliberate attacks continue to disrupt power systems. Inherently robust ecological networks present a rich source of robust design guidelines for modern power grids. Analyses of ecosystem networks in literature suggest that this robustness is a consequence of a unique preference for redundant pathways over efficient ones. The structural similarity between these two system-types is exploited here through the application of ecological properties and analysis techniques to long-term power grid design. The level of biological similarity between these two system-types is quantitatively investigated and compared by computing ecological network metrics for a set of synthetic power systems and food webs. The comparison substantiates the use of the ecological robustness metric for optimizing the design of power grid networks. A bio-inspired optimization model is implemented, which restructures the synthetic power systems to mimic ecosystem robustness. The bio-inspired optimal networks are evaluated using N-1, N-2, and N-3 contingency analyses to assess system performance under the loss of 1, 2, and 3 components respectively. The bio-inspired grids all experienced significantly fewer violations in each loss scenario compared to traditional configurations, further supporting the application of the ecological robustness metric for power system robustness. The results provide insights into how ecological robustness can guide the design of power systems for improved infrastructural resilience to better survive disturbances.

Suggested Citation

  • Panyam, Varuneswara & Huang, Hao & Davis, Katherine & Layton, Astrid, 2019. "Bio-inspired design for robust power grid networks," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    • Handle: RePEc:eee:appene:v:251:y:2019:i:c:33
    DOI: 10.1016/j.apenergy.2019.113349
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