Measuring the Resilience of Renewable Energy Communities: A Scenario Analysis of the Regenerative Capacity

The growing adoption of decentralized renewable energy systems highlights the need to assess their resilience to disruptions. Renewable Energy Communities (RECs), composed of consumers and prosumers, rely on rooftop solar, storage, and peer-to-peer (P2P) energy sharing to meet local demand. These communities form dynamic networks where resilience—defined as the ability to recover from disturbances—is critical, especially in low-prosumer-density settings.This study presents a framework to evaluate REC resilience under disruption scenarios. Using high-resolution energy data, we simulate P2P exchanges and construct directed, weighted energy-sharing networks. We compute centrality metrics to identify critical nodes and simulate both random failures and targeted attacks on the most connected users. Structural robustness is assessed by tracking changes in network connectivity and efficiency.Results show that RECs perform well under normal conditions, with greenhouse gas emissions reduced to 61% of the baseline and an average energy bill reduction (EBR) of 22.5%. Technical indicators such as the self-consumption rate (SCR = 1.07%) and self-sufficiency rate (SSR = 1.7%) confirm effective local energy use. However, resilience analysis reveals that removing a few highly connected users significantly reduces network efficiency. This underscores the need to expand user participation in RECs to increase redundancy, reduce vulnerability, and enhance overall robustness. Our framework offers a comprehensive method for evaluating both performance and resilience in decentralized energy-sharing systems.