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Can graph properties determine future grid adequacy for power injection diversity?

Author

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  • Tio, Adonis E.
  • Hill, David J.
  • Ma, Jin

Abstract

Engineers need new tools to design future power grids able to accommodate an increasing diversity of power injection operating states. Graph-based grid expansion tools are an emerging approach that exploits the underlying graph properties of power grids to inform preliminary stages of decision-making. The simplicity of graph-based approaches circumvents the need for computationally-intensive operations modeling, but extensive testing on its effectiveness in capturing and improving actual grid performance is lacking. This work provides experimental results that explore the efficacy of four graph-based grid-expansion approaches in improving grid adequacy. We rank and compare grid expansion options using four graph metrics and three inadequacy metrics to see whether graph metrics are good predictors of grid adequacy. Results for a 6- and a 118-bus test system show that grid designs that are top-ranking in terms of the graph metrics are not necessarily top-ranking in terms of the grid inadequacy metrics, and vice versa. Nonetheless, high-ranking grid designs in terms of some graph metrics can be high-ranking as well in terms of some grid inadequacy metrics – an observation that can be useful in some applications. The case studies illustrate that using the four graph-based grid expansion heuristics explored may not necessarily lead to optimal grid adequacy. How prevalent this observation is to other test systems and actual grids and whether there exist special classes of grids wherein graph-based grid expansion result in optimal grid adequacy will be interesting areas for future work.

Suggested Citation

  • Tio, Adonis E. & Hill, David J. & Ma, Jin, 2020. "Can graph properties determine future grid adequacy for power injection diversity?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
  • Handle: RePEc:eee:phsmap:v:550:y:2020:i:c:s0378437120300182
    DOI: 10.1016/j.physa.2020.124165
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    References listed on IDEAS

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