Optimal Strategies for Coordinating Distributed Energy Resources in Active Distribution Networks

This thesis develops new frameworks to optimally coordinate and schedule Distributed Energy Resources (DERs)—including renewable generation, electric vehicles, community batteries, and other consumer energy assets—in active distribution networks. By addressing uncertainties such as fluctuating market prices and variable renewable outputs, the proposed models improve financial returns, manage risks, and maintain grid reliability. Key contributions include a risk-constrained scheduling approach for DER aggregators in energy and flexibility markets, and robust stochastic models that account for diverse DER types and evolving grid technologies. The research also explores dynamic pricing schemes and power exchange strategies to enhance social welfare and grid efficiency. Overall, the findings support a more flexible, resilient, and sustainable energy ecosystem, with practical implications for policymakers, grid operators, and market participants.