Robust Load and Energy Management in Smart Grids with Prosumer-Integrated Distributed Energy Resources
CoI: Dr. Ali Al-Awami, Dr. Mujahed Al-Dhaifallah, Dr. Muhammad Khalid, Dr. Muhammad Gulzar
The increasing integration of renewable energy resources, coupled with the rise of prosumers (entities that both consume and produce energy), has introduced significant variability and uncertainty into modern smart grids. These challenges necessitate advanced energy management strategies that can ensure grid stability, minimize energy losses, and enhance the participation of prosumers in energy markets. Traditional optimization approaches often fall short in addressing the combined complexities of renewable integration, load fluctuations, and real-time operational requirements. This study introduces a novel optimization framework leveraging Mixed Integer Second-Order Conic Programming (MISOCP). The primary goal of the proposed method is to provide a robust and computationally efficient solution for energy scheduling in smart grids, particularly under uncertain conditions. By integrating prosumer-managed resources such as photovoltaic (PV) systems, energy storage systems (ESS), and electric vehicles (EVs), the method ensures optimal energy distribution and resilience against uncertainties in load demand and renewable generation.
