The rising prevalence of flexible energy resources like electric vehicle chargers and heat pumps adds complexity to distribution grid operations. Concurrently, enhanced observability and controllability through advanced control systems offer ways to address these challenges. While automated systems manage routine operations, outlier scenarios with uncertainty or incomplete data require manual intervention.

This work introduces a concept for a decision support system designed to improve transparency and provide actionable recommendations, enabling operators to resolve incidents - non-routine situations beyond automated handling - efficiently and cost-effectively. Drawing from the DISEGO project and regulatory contexts such as the German §14a EnWG, the decision support system identifies critical issues, classifies incident types (e.g., communication failures, insufficient data), and suggests tailored actions.

The decision support system maps incidents to Smart Grid Architecture Model interoperability layers, ensuring both technical and organizational decision-making aspects are considered. It incorporates real-time data, forecasts, grid models, and regulatory constraints. Key functionalities include incident identification, real-time visualization, uncertainty overlays, prioritized action lists, and system diagnostics, all aimed at supporting operator decisions.

Scenario-based evaluation shows that structured decision support reduces operator workload, enhances grid stability, and accelerates responses during critical incidents, bolstering operational resilience.