Dynamic Containment Service from Industrial Demand Response Resources Coordinated with Energy Storage Systems

Industrial Demand Response Resources (DRRs) are widely used in the frequency response service market. A Virtual Energy Storage System (VESS) model is developed to enable industrial DRRs to participate in the Dynamic Cointainment (DC) service by coordinating with an Energy Storage System (ESS). The power and energy capacity of the ESS are determined by considering its complementary characteristics with industrial DRRs, enabling the VESS to successfully provide the DC service as a whole under the proposed control strategy. Meanwhile, the operational baseline of the ESS is updated based on the “state of energy” management rules for energy-limited units as defined in the DC service.“Numerical results and figures.xlsx” provides the numerical results of Fig. 6 - Fig. 11 of the paper. It contains seven sheets, providing the data behind Fig. 6 - Fig. 11 of the paper.In the “Fig. 6” sheet, the x-axis describes the time variable (unit: h), and the y-axis describes grid frequency variation (unit: Hz), delivery ratios of DC high service, related power curves (unit: MW), and state of charge (SOC) changing process of energy storage system-1 in scenario A.In the “Fig. 7” sheet, the x-axis describes the time variable (unit: h), and the y-axis describes delivery power curves of the virtual energy storage systems (unit: MW), steam power generation (unit: MW), and energy storage system-2 in scenario A.In the “Fig. 8” sheet, the x-axis describes the time variable (unit: h), and the y-axis describes grid frequency variation (unit: Hz), delivery ratios of DC high service, related power curves (unit: MW), and SOC changing process of energy storage system-1 in scenario B.In the “Fig. 9” sheet, the x-axis describes the time variable (unit: h), and the y-axis describes delivery power curves of the virtual energy storage systems (unit: MW), steam power generation (unit: MW), and energy storage system-2 in scenario B.In the “Fig. 10” sheet, the x-axis describes the time variable (unit: h), and the y-axis describes grid frequency variation (unit: Hz), delivery ratios of DC high service, related power curves (unit: MW), and SOC changing process of energy storage system-1 in scenario C.In the “Fig. 11” sheet, the x-axis describes the time variable (unit: h), and the y-axis describes delivery power curves of the virtual energy storage systems (unit: MW), steam power generation (unit: MW), and energy storage system-2 in scenario C. Moreover, the y-axis also describes recovery power curve (unit: MW), actual power curve (unit: MW), and SOC changing process of ESS-2.

工业需求响应资源（DRRs）在频率响应服务市场中得到了广泛应用。为使工业DRRs能够通过协调能源存储系统（ESS）参与动态包容（DC）服务，本研究开发了一种虚拟能源存储系统（VESS）模型。ESS的功率和能量容量是通过考虑其与工业DRRs的互补特性来确定的，从而使得VESS能够在所提出的控制策略下整体成功提供DC服务。同时，基于“能源状态”管理规则，针对能源受限单元在DC服务中的操作基准得到更新。“数值结果和图表.xlsx”文件提供了论文中图6至图11的数值结果。该文件包含七个工作表，提供了论文中图6至图11背后的数据。在“图6”工作表中，x轴描述了时间变量（单位：小时），y轴描述了电网频率变化（单位：赫兹）、直流高服务的交付比率、相关功率曲线（单位：兆瓦）以及能源存储系统-1在场景A中的状态变化过程。在“图7”工作表中，x轴描述了时间变量（单位：小时），y轴描述了虚拟能源存储系统的交付功率曲线（单位：兆瓦）、蒸汽发电（单位：兆瓦）以及场景A中的能源存储系统-2。在“图8”工作表中，x轴描述了时间变量（单位：小时），y轴描述了电网频率变化（单位：赫兹）、直流高服务的交付比率、相关功率曲线（单位：兆瓦）以及能源存储系统-1在场景B中的状态变化过程。在“图9”工作表中，x轴描述了时间变量（单位：小时），y轴描述了虚拟能源存储系统的交付功率曲线（单位：兆瓦）、蒸汽发电（单位：兆瓦）以及场景B中的能源存储系统-2。在“图10”工作表中，x轴描述了时间变量（单位：小时），y轴描述了电网频率变化（单位：赫兹）、直流高服务的交付比率、相关功率曲线（单位：兆瓦）以及能源存储系统-1在场景C中的状态变化过程。在“图11”工作表中，x轴描述了时间变量（单位：小时），y轴描述了虚拟能源存储系统的交付功率曲线（单位：兆瓦）、蒸汽发电（单位：兆瓦）以及场景C中的能源存储系统-2。此外，y轴还描述了恢复功率曲线（单位：兆瓦）、实际功率曲线（单位：兆瓦）以及ESS-2的状态变化过程。