Climate change has increased the frequency and severity of natural disasters, disrupting power systems and disproportionately impacting socially vulnerable communities. While recent research has explored technical and socio-economic aspects of microgrid deployment, there remain limited work on designing microgrids that specifically enhance energy resilience for socially vulnerable communities during disasters. To address this gap, this study proposes an investment and resilience-oriented framework for planning and operation of renewable energy-integrated Residential Community Microgrid (RCMG). A two-stage stochastic programming model is developed to optimize long-term investment, operation, and capacity expansion under uncertainties in load demand, renewable generation, and outage duration. The framework also incorporates a load-curtailing demand response program (DRP) that incentivizes households through bill discounts. Results from case studies in three Texas communities demonstrate that integrating capacity expansion with DRP can reduce total system costs by up to 16\% while improving resilience by more than 60\% and increasing household bill savings by 13\%. The findings highlight the critical roles of DRP design, expansion timing, and differentiated electricity pricing in balancing financial accessibility and resilience. Scalability analysis shows that while expansion costs scale with demand, investment responses are shaped by social vulnerability, highlighting the need for proactive, community-specific planning and front-loaded funding to ensure equitable microgrid growth. These insights provide practical guidance for utilities and policymakers in planning equitable, community-specific microgrids that strengthen energy resilience under growing climate risks.


Keywords: Climate Change; Microgrids; Social Vulnerability; Resilience; Stochastic Programming.