安全与环境学报

传统评价方法无法全面地辨识涉及多个交互部件和复杂控制策略的压缩空气储能(Compressed Air Energy Storage, CAES)系统的潜在风险。为了更加全面地辨识CAES系统的潜在风险，研究将系统论过程分析(System-Theoretic Process Analysis, STPA)方法引入至先进绝热压缩空气储能系统中并进行风险分析。首先，通过对多种构型的压缩空气储能系统进行效率分析并确定研究对象；其次，定义系统储热过程中系统级事故和危害，构建控制结构模型，并识别可能导致事故的控制动作；最后，从系统控制、组件失效、系统协调不足、人为操作失误等多个维度，分析32个潜在的系统级危险场景，并提出109项针对性的控制措施。此外，选取危害与可操作性研究(Hazard and Operability Study, HAZOP)方法对STPA分析结果进行对比分析与可靠性验证，相比于HAZOP方法28.6%的识别率，STPA方法可有效识别61.5%的系统交互故障，在揭示储能系统复杂交互故障方面展现出了优越性。基于STPA的风险分析对于优化系统设计和提升系统稳定性与可靠性具有重要指导意义，研究为类似新兴能源系统的风险识别提供了参考和借鉴。

The promotion and implementation of Compressed Air Energy Storage(CAES) technology are becoming increasingly widespread. However, traditional evaluation methods fall short in comprehensively identifying the potential risks associated with CAES systems, which involve multiple interactive components and complex control strategies. To achieve a more comprehensive and systematic risk identification for energy storage systems and to ensure their safe and stable operation, this paper introduces the System-Theoretic Process Analysis(STPA) method for the first time to conduct a safety analysis of the Advanced Adiabatic Compressed Air Energy Storage(AA-CAES) system. First, this article examines various configurations of compressed air energy storage systems, emphasizing efficiency to select the optimal research subject. Subsequently, the STPA method is employed to qualitatively analyze the Advanced Adiabatic Compressed Air Energy Storage(AA-CAES) system and identify hazards at the system level. By analyzing the control processes of the system and establishing a control structure, 19 types of unsafe actions that may arise during system interactions were identified. The causes of 95 unsafe behaviors were investigated, leading to the proposal of 109 corresponding safety constraint measures. Finally, to verify the reliability of the STPA analysis results, the risk faults identified through the STPA method were compared with those identified by the Hazard and Operability Study(HAZOP) method. The classification and statistics of the fault types obtained from the analysis indicate that the STPA method achieves a recognition rate of 61% for system interaction faults, which is 5% higher than traditional HAZOP methods. This demonstrates that the STPA method has significant advantages in identifying complex interactive faults in energy storage systems. Risk analysis based on the STPA method can identify system risk factors during the design phase, facilitating the optimization of system design and operation while enhancing overall stability and reliability. This article is the first to apply the STPA method for risk analysis of the AA-CAES system, validating the effectiveness of the approach and offering valuable references and new insights for risk identification in similar systems.