计及阶梯式碳交易与需求响应的工业用户共享储能低碳经济调度

Low-Carbon Economic Dispatch of Shared Energy Storage for Industrial Users Considering Tiered Carbon Trading and Demand Response

摘要: 针对工业园区分布式可再生能源渗透率提升带来的调度挑战，文章提出了一种计及阶梯式碳交易与需求响应的工业用户共享储能低碳经济调度策略。首先，挖掘工业集群内部不同主体的用能异质性，利用各主体间净负荷的时空互补优势，构建了共享储能运行框架，以实现储能资源的集约化配置。其次，引入阶梯式碳交易机制作为引导系统减排的经济杠杆，并结合柔性需求响应机制，建立了源–荷–储协同优化调度模型，通过二次型平滑惩罚项约束负荷转移过程，保障生产连续性。再者，揭示了系统在阶梯碳价与分时电价等复杂约束下的低碳博弈机理，通过储能时空平移与负荷柔性重塑的深度耦合，实现碳排放与能量消耗的精准对齐，规避高额碳惩罚；并借助关键参数灵敏度分析，量化评估了所提策略在不同碳价与需求响应参与度下的适应性与降本效能。最后，以江苏省某工业园区为算例进行仿真验证。结果表明，所提策略通过共享模式使储能总规划容量由4233.81 kWh降低至2781.95 kWh，降幅达34.29%。在阶梯碳交易与价格信号的引导下，柔性负荷全天累计平移电量达925.42 kWh，实现了向夜间风电出力高峰等低碳时段的平滑平移，使集群净负荷的峰谷差由222.6 kW大幅收窄至76.7 kW，降幅达65.5%。在微观企业层面，系统总碳排放量由17.85吨降至15.57吨，下降12.77%，总运行成本由13540.20元优化至13394.98元，验证了所提策略在提升系统经济性与低碳治理水平方面的有效性。

Abstract: To address the scheduling challenges arising from the increasing penetration of distributed renewable energy in industrial parks, a low-carbon economic dispatch strategy for industrial users considering stepped carbon trading and demand response is proposed based on shared energy storage. First, by exploiting the energy-use heterogeneity of different entities within the industrial cluster and leveraging the spatiotemporal complementarity advantages of their net loads, a shared energy storage operational framework is constructed to achieve centralized configuration of energy storage resources. Second, the stepped carbon trading mechanism is introduced as an economic lever to guide system emission reduction, and combined with a flexible demand response mechanism, a source-load-storage collaborative optimal dispatch model is established, where a quadratic smoothing penalty term is employed to constrain the load shifting process and ensure production continuity. Then, the low-carbon gaming mechanism of the system under complex constraints, such as stepped carbon prices and time-of-use electricity prices, is revealed. Through the deep coupling of the spatiotemporal shifting of energy storage and the flexible reshaping of loads, precise alignment between carbon emissions and energy consumption is achieved, thereby avoiding high carbon penalties; furthermore, sensitivity analysis of key parameters is conducted to quantitatively evaluate the adaptability and cost-reduction effectiveness of the proposed strategy under different carbon prices and demand response participation levels. Finally, a case study simulation is conducted on an industrial park in Jiangsu Province. The results demonstrate that the proposed strategy reduces the total planned energy storage capacity from 4233.81 kWh to 2781.95 kWh through the shared mode, representing a reduction of 34.29%. Guided by stepped carbon trading and price signals, a cumulative total of 925.42 kWh of flexible load is shifted throughout the day. This realizes a smooth load shift toward low-carbon periods, such as the peak nighttime wind power output, thereby significantly narrowing the peak-to-valley difference of the cluster net load from 222.6 kW to 76.7 kW, yielding a 65.5% decrease. At the micro-enterprise level, the total system carbon emissions are reduced from 17.85 tons to 15.57 tons, yielding a 12.77% decrease, and the total operating cost is optimized from 13540.20 CNY to 13394.98 CNY. These findings verify the effectiveness of the proposed strategy in enhancing both the economic efficiency and the low-carbon operational management of the system.