Optimal Load Frequency Control of a Hybrid Electric Shipboard Microgrid Using Jellyfish Search Optimization Algorithm

This paper examines the critical topic of load frequency control (LFC) in shipboard microgrids (SMGs), which face challenges due to low system inertia and intermittent power injection renewable energy sources. To maintain a constant (even under uncertainties), robust well-tuned controller is required. In this paper, study was conducted first by examining performance three different architectures, order determine most-appropriate for multi-energy SMG system. The time delays that occur communication links between sensors were also considered analysis. controllers tuned using very recent bio-inspired optimization algorithm called jellyfish search optimizer (JSO), has not been used until recently LFC problems. assess tuning efficiency proposed algorithm, SMG’s response results comprehensively compared obtained with other algorithms. showed gains provided JSO outperformed those counterparts, improvements ranging from 19.13% 93.49%. Furthermore, robustness selected evaluated various operational scenarios. clearly demonstrated controller’s established normal conditions do require retuning when parameters undergo significant variation.