A Joint Optimization Strategy for Demand Management and Peak-Valley Arbitrage of Industrial and Commercial Loads Based on Sodium-Ion Battery Energy Storage System

Demand reduction contributes to mitigate shortterm peak loads that would otherwise escalate distribution capacity requirements, thereby delaying grid expansion, improving asset utilization, and significantly reducing demand charges for electricity users. However, the high-rate discharge and low-rate charge characteristics of sodium-ion batteries introduce new constraints and optimization factors that challenge conventional scheduling strategies. To address this, this paper proposes a joint optimization strategy for demand management and time-of-use (TOU) arbitrage, specifically tailored to the highrate discharge capability of sodium-ion battery energy storage systems (BESS) in industrial and commercial (I&C) settings. First, the optimal depth of discharge (DoD) is determined based on the trade-off between the cycle life and calendar life of sodium-ion batteries. Then, the demand reduction capability of the storage system is defined by analyzing typical peak load characteristics of users. A mixed-integer linear programming (MILP) model is subsequently developed to jointly consider operational constraints, power balance constraints, and control strategy constraints, and is solved in a rolling real-time fashion. A key innovation of this work is the introduction of a variable time-scale average load perception mechanism, which enables effective reduction of sliding-window-based peak demand. Furthermore, by incorporating the probabilistic distribution of peak demand periods and the temporal characteristics of TOU price, a prioritybased operation scheduling framework is designed to fully exploit the benefits of sodium-ion BESS in both demand management and arbitrage applications. Case study demonstrates the effectiveness and robustness of the proposed strategy under realistic load scenarios.