Optimal Control of an Autonomous Microgrid Integrated with Super Magnetic Energy Storage Using an Artificial Bee Colony Algorithm

Abstract

This article presents a microgrid that uses sustainable energy sources. It has a fuel cell (FC), wind energy production devices, and a superconducting magnetic energy storage (SMES) device. The performance of the suggested microgrid is improved by adapting an optimal control method using an artificial bee colony (ABC) algorithm. The ABC algorithm has many advantages, including simplicity, adaptability and resilience to handle difficult optimization issues. Under usual circumstances, wind and FC energies are typically appropriate for meeting load demands. The SMES, however, makes up the extra capacity requirement during transient circumstances. Using the ABC optimum controller, the load frequency and voltage are controlled. Measurements of the microgrid’s behavior using the newly developed optimal controller were made in response to step variations in wind power and load demand. To assess the performance of the suggested system, simulations in Matlab were run. The outcomes of the simulations demonstrated that the suggested microgrid supplied the load with AC power of steady amplitude and frequency for all disruptions. Additionally, the necessary load demand was precisely mitigated. Furthermore, even in the presence of variable wind speeds and SMES, the microgrid performed superbly. The outcomes under the same circumstances with and without the optimal ABC processor were compared. It was discovered that the microgrid delivered superior responses using the optimal ABC controller with SMES compared to the microgrid without SMES. The performance was also compared to the optimally controlled microgrid using particle swarm (PS) optimization.