Structured risk assessment for electrochemical energy storage system: Integrating consistency enhanced-FAHP and complex coupling relationship network

With the rapid deployment of Electrochemical Energy Storage Systems (EESS), effective risk management is essential for safe operation under complex conditions. However, existing EESS risk assessment studies still face several limitations. Expert opinions are often used for weight assignment without consistency correction, producing inaccurate weights and causing unreliable assessments. Suitable scoring methods that integrate real-time sensor data and supervisor opinions remain limited, making it difficult to reflect both real-time dynamics and diverse risk sources in EESS. In addition, causal relationships among risk factors are often neglected, leading to an absence of cascading effects and potential risks across systems. To address these issues, this paper proposes a structured risk assessment method for EESS. First, an EESS Risk Indexing (ERI) system organizes various risk factors hierarchically. Then, the Consistency-Enhanced Fuzzy Analytic Hierarchy Process (CE-FAHP) evaluates and corrects inconsistencies in expert opinions, thereby generating reliable weights. Next, a risk scoring method is established to integrate real-time sensor data and supervisor opinions. Finally, the Complex Coupling Relationship Network (CCRN) revises risk scores by modeling causal relationships among sub-factors. In this way, an assessment method is formed to capture both individual risks and causal relationships. A case study at six electrochemical energy storage stations in China shows that the proposed method effectively distinguishes stations with different risk levels and identifies critical risk contributors. The results indicate that TMS mechanical failure and BMS electrical failure are the dominant contributors to overall EESS risk. These findings support risk prioritization and decision-making for EESS safety.