Enhancing Microgrid Sustainability Through Adaptive Energy Management Using Intelligent Control Algorithms

This study introduces an advanced control algorithm tailored for a bipolar DC microgrid to optimize the distribution of power among key resources, including wind energy generators (WEGs), solar photovoltaic (PV) systems, and battery energy storage (BES) units. The developed algorithm, a combination of intelligent load sharing and real-time monitoring, dynamically allocates power based on immediate demand. In this context, the main contributors of microgrid, such as wind energy, solar panels, and battery storage, collaborate seamlessly to share the load efficiently. By prioritizing renewable sources and adapting the battery's charge or discharge to meet diverse loads, this control algorithm ensures not only stability, but also sustainable and optimal performance in bipolar DC microgrid operations.