Abstract

Abstract

Abstract

Abstract

Abstract

Abstract
Renewable Energy Communities (RECs) are emerging as key enablers of decentralized, sustainable, and consumer-driven energy systems. Beyond environmental benefits, RECs possess significant potential to enhance resilience against extreme weather, price volatility, and infrastructure fragility. This article integrates resilience and relia bility constraints directly into the planning and operation of RECs, assessing their impact on system cost, sizing, and dispatch. Two optimization models are developed: a design model that sizes community assets (PV and BESS) using varying resilience indicators, and an operational model that minimizes costs while monitoring reliability. The analysis introduces two resilience metrics, deterministic hourly autonomy and average autonomy, and eval uates them using real-world data from the Caxias Living Lab. Results demonstrate that average resilience can be increased with minimal cost impacts due to non-linear trade-offs, whereas strict hourly resilience requires signifi cant storage investment. Furthermore, a Value of Lost Load (VoLL) reliability indicator is shown to cost-effectively trigger maintenance events. This framework offers actionable guidance for designing sustainable, adaptive, and economically viable energy communities.