Robust load and energy management in smart grids with prosumer-integrated distributed energy resources

This study introduces the Resilient Prosumer-Centric Energy Optimization Framework (RPEOF), a robust two-stage optimization model developed using Mixed Integer Second-Order Conic Programming (MISOCP) to address uncertainties in load demand and renewable generation within smart grids with integrated prosumers. RPEOF effectively accommodates diverse prosumer resources, including electric vehicles, batteries, and photovoltaic (PV) systems, ensuring optimal energy scheduling across entities that both produce and consume energy. By leveraging a two-stage robust optimization approach, RPEOF ensures resilience against fluctuations in renewable generation and load variations, delivering stable energy management solutions under uncertain conditions. The framework integrates the Column-and-Constraint Generation (C&CG) algorithm to enhance computational efficiency, making it suitable for large-scale and real-time applications. Simulation results highlight significant advancements, including an 18% reduction in grid energy losses, a 15.2% decrease in voltage fluctuations, a 12% increase in prosumer electricity sales, and a zero load-shedding rate, alongside a 60% reduction in computation time compared to conventional methods. Extensive testing on a 33-node test network and an actual urban grid demonstrates RPEOF's scalability and real-world applicability, emphasizing its potential to advance smart grid efficiency and support sustainable energy systems.