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Description
Energy Management Strategy for Triple Hybrid Energy Storage Systems in Smart Grids This paper introduces an Energy Management Strategy for Triple Hybrid Energy Storage Systems in Smart Grids, overseeing a T-HESS that includes a Battery Energy Storage System (BESS), a supercapacitor, and a hydrogen fuel cell/electrolyzer integrated within a grid-connected
AC microgrid on the IEEE 33 bus radial distribution network. The suggested EMS functions across three tiers of escalating intelligence. Layer 1 employs an 11 state rule-based Finite State Machine featuring a priority-weighted greedy allocator and a dynamic hydrogen discharge limit. Layer 2 enhances dispatch with a 45 rule Mamdani-Sugeno fuzzy logic controller triggered near voltage regulation thresholds. Layer 3 utilizes a Soft Actor-Critic deep reinforcement learning agent with automated entropy adjustment, trained across a complete 8760 hour annual simulation cycle with LinDistFlow power flow for nodal voltage calculations at all 33 buses. The SAC agent demonstrates a load deficit of 10.21%, surpassing the rule-based EMS at 17.94%, while maintaining a final hydrogen reserve of 0.217, in contrast to total depletion observed in the naive baseline. Voltage control is sustained within ±5% at all buses during the simulated year. The suggested Energy Management Strategy for Triple Hybrid Energy Storage Systems in Smart Grids achieves a concurrent Pareto enhancement across all critical performance metrics, providing a physically based standard for intelligent multi-storage dispatch in smart distribution
networks.
| Topic Area | Smart Energy Storage, Integration and Utilization |
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