首页|Optimized distributed energy management for BESS incorporating time-varying delays with an improved bipartite grouping model simultaneously balancing SOH and SOC
Optimized distributed energy management for BESS incorporating time-varying delays with an improved bipartite grouping model simultaneously balancing SOH and SOC
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NSTL
Elsevier
To address the challenges of high lifespan loss, operational imbalance, poor robustness, and the lack of consideration for time-varying delays in conventional distributed energy management strategies for battery energy storage systems (BESS), this paper proposes a distributed energy management strategy for BESS incorporating time-varying delays with an improved bipartite grouping model, balancing state of health (SOH) and state of charge (SOC) simultaneously. Firstly, a BESS response capability evaluation model is developed to balance SOH and SOC. Building on this, the bipartite grouping model is further refined to maintain this balance. Next, state feedback predictive control (SFPC) is introduced into the distributed consensus algorithm (DCA) forming a new algorithm called SFPC-DCA, with its state-space equations adjusted for time-varying delays. Then, a hierarchical response principle is devised to determine which battery groups should engage in energy management, factoring in the maximum charge/discharge power. SFPC-DCA is used for balanced energy management across the battery groups, and BESS responds to the allocated power signals. Simulations and hardware experiments confirm that the proposed strategy improves SOC and SOH balance, reduces lifespan loss, and enhances operational robustness under time-varying delays.
Battery energy storage systemBipartite grouping modelSOH and SOC balancingDistributed consensus algorithmState feedback predictive controlTime delayBATTERYSTRATEGYWIND
Yu, Yang、Wang, Boxiao、Li, Menglu、Lv, Tingyan
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North China Elect Power Univ Baoding||North China Elect Power Univ Baoding