In summary, fully considering the cost and benefits of energy storage and the impact of the uncertainty of load forecast power on the energy scheduling of user systems with additional energy storage, this paper builds a user-side energy storage configuration optimization. . In summary, fully considering the cost and benefits of energy storage and the impact of the uncertainty of load forecast power on the energy scheduling of user systems with additional energy storage, this paper builds a user-side energy storage configuration optimization. . In order to reduce the impact of load power fluctuations on the power system and ensure the economic benefits of user-side energy storage operation, an optimization strategy of configuration and scheduling based on model predictive control for user-side energy storage is proposed in this study. . Based on this, this paper proposes an industrial user-side shared energy storage optimal configuration model, which takes into account the coupling characteristics of life and charge and discharge strategy. Firstly, the life loss model of lithium iron phosphate battery is constructed by using the. . To address these challenges, this study proposes a user-side cloud energy storage (CES) model with active participation of the operator. This CES model incorporates adjustable time-of-use (TOU) electricity pricing and state-of-charge (SOC) management. In the configuration process, the net load. .
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