An Operational Resilience Metric to Evaluate Inertia and Inverter-based Generation on the Grid

Phillips, Tyler; Alam, Samiul; Poudel, Bikash; Mosier, Thomas; McJunkin, Timothy R.

doi:10.1109/pesgm48719.2022.9916918

Cited by 3 publications

(2 citation statements)

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“…In order to add to the short-term resilience, the wind turbine generator can be ran below its maximum capability. The impact to resilience based on the dynamics of different generation assets has been demonstrated in [22]. Here, it was shown that the quick ramping capability of inverter-based generation can have a large impact to maintain frequency stability.…”

Section: Co-simulation Resilience Takeawaymentioning

confidence: 95%

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Scalable Resilience Analysis Through Power Systems Co-Simulation

et al. 2023

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The ability to robustly characterize transmission and distribution grid resilience requires the ability to perform time-scale analysis that interweaves communications, control, and power contributions. This consideration is important to ensuring an understanding of how each individual aspect can affect the resulting systemic resilience. The combination of co-simulation of these time-based characteristics and a resilience-specific metric provides a likely method to inform both design planning and implementation/operational goals to ensure resilience in power systems. The Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad co-simulation platform (MIRACL-CSP) has been developed to allow the modular integration of power grid models with control and metrics applications. This paper introduces MIRACL-CSP as a fundamental platform to study and improve the resilient operation of a microgrid. It offers a holistic investigation environment for systemically comparing the cyber-physical resilience to natural and manmade events. We emphasize the importance/advantage of intertwining the distribution system simulator GridLAB-D with the Power Distribution Designing for Resilience (PowDDeR) application to analyze the resilience of the St. Mary's microgrid in Alaska. The resilience is evaluated in both short-term (frequency stability) and long-term (energy constrained) metrics. The results of the analysis of the St. Mary's microgrid show that there is a trade-off between the two. As inertia-based generation assets are taken off-line, shortterm resilience drops. However, the long-term resilience is retained longer as less fuel is being used.

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Section: Co-simulation Resilience Takeawaymentioning

confidence: 95%

“…The short-term resilience in regards to the DIRE curve (Fig. 1) relates to the 'resist' phase and its derivation can be seen in more detail in [22].…”

Section: Power Distribution Designing For Resilience Applicationmentioning

confidence: 99%