An Agent-Based Model of Microgrids with Distributed Renewable Energy Sources

The high penetration of renewable energy sources poses a challenge to stability of power systems, particularly microgrids, which are more vulnerable due to their small capacity and low inertia. To address instability, system components and their interactions need to be represented to more efficiently understand and optimize complex systems. Agent-based modeling enables autonomous operation and collaborative interaction, making the system adaptable to changes efficiently, making it ideal for microgrid management. In this paper, an agent-based microgrid simulation model is proposed. By independently representing microgrid components such as generators, energy storage systems (ESS), loads, environments and controllers, models can dynamically simulate the behavior of power systems, respond to system changes in real time. To validate the proposed model, experiments are conducted based on IEEE 13 bus system, and the results show that with the use of ESS, the frequency peak is reduced from over 62 Hz to around 60 Hz. In the case of sudden demand fluctuations, the frequency remains relatively stable, staying close to 60 Hz. The model demonstrates flexibility and robustness in managing renewable energy fluctuations and sudden load changes.