Uncoordinated approaches to resilience assessment and mitigation strategies by transmission system operators (TSOs) and distribution system operators (DSOs) can lead to sub-optimal solutions. The report describes a surrogate model to efficiently simulate the flexibility services by storage systems, generation and load, connected to distribution networks, in transmission system resilience enhancement problems: the matching between the areas of surrogate model and complete model capabilities ranges from 83% (in high load hours with reduced network congestions) to 46% (in low load hours with limited flexibility margins).

To mitigate the degraded system performance caused by multiple contingencies arising from extreme weather events, the report customizes for quasi-real-time operation the general resilience control formulation developed in the previous research year. This formulation considers the recovery process for faulty components and the uncertainties in component vulnerabilities, while assuming negligible uncertainties in load and renewable generation. Various objective functions are applied to limit or minimize system degradation metrics (e.g. the conditional value at risk, CVAR, of the cost of energy not served, CENS).

Simulations on a medium-sized IEEE grid (118 buses) demonstrate that the CVAR limitation strategy results in lower overall costs for preventive and corrective actions but increases the risk of CENS: it requires lower or no preventive action costs but higher expected corrective action costs compared to the more conventional CVAR minimization approach, which is interesting for operators, who prefer corrective actions for economic reasons.

The costs for resilience boosting actions increase when the recovery time for the outaged components increases; the larger the CENS distribution tails the lower the degradation metrics (risk and CVAR of CENS) for the min CVAR strategy, while negligible effects on degradation metrics and on the action costs are found for the CVAR limitation strategy. Reducing the CVAR threshold set in the CVAR limitation strategy causes this strategy to shift the solution from corrective to preventive actions. In critical hours when the minimum achievable CVAR of CENS is higher than the CVAR threshold, the CVAR limitation strategy achieves the same CVAR value as in the min CVAR strategy.

The resilient control for quasi-real-time operation will be extended to include coordinated measures between DSOs and TSOs and enhance its applicability to realistic case studies.