Multi-microgrid intelligent load shedding for optimal power management and coordinated control with energy storage systems

This paper deals with optimal multi-stage power management and control coordinated with load shedding in interconnected microgrid (MG) with various renewable energy sources (RESs), namely: wind turbine, photovoltaic generator and concentrated solar power generator. Hybrid energy storage systems including electrical vehicles, fuel cells, redox flow batteries and superconducting magnetic energy storage have been introduced to improve the overall MG frequency dynamic performances in case of renewable energy integration and load disturbances. To improve the interconnected MG tie-lines power control, flexible alternating current transmission systems are added. For an optimal and robust solution, an artificial intelligence strategy is proposed, combining a load frequency control-based cascade Fuzzy-proportional-integral-derivative controller with filter (PIDN). In doing so, a recently meta-heuristic algorithm that mimics the social behavior of elephants in nature, named Elephant Herding Optimization, has been employed to optimize the Fuzzy-PIDN controller gains. To show the effectiveness and superiority of the proposed control strategy, various scenarios are carried out. A comparative study in view of a settling time and peak over/undershoot has been performed. The obtained results demonstrate that the proposed control strategy gives good performances for MG power management and control under RESs integration and load disturbances scenarios.

Automated summary

This paper discusses optimal multi-stage power management, control, and load shedding coordination in interconnected microgrids with various renewable energy sources. It introduces hybrid energy storage systems, flexible AC transmission systems, and an artificial intelligence strategy combining a fuzzy-proportional-integral-derivative controller with filter. The proposed control strategy shows good performance in managing and controlling microgrid power under renewable energy integration and load disturbances scenarios.