安全与环境学报

面对西北地区集中式光伏项目建设及运维过程中多维度风险交互演化带来的系统性挑战，本文基于风险演化视角提出一种融合风险传递理论、价值工程理论和Monte-Carlo模拟技术的综合安全风险评估与决策方法。通过构建“固定风险–传递风险”双维度量化模型以及建立以价值工程为核心的多策略比选框架，实现了风险传播过程的动态仿真与系统风险水平的量化评估。为验证方法的有效性，进一步以西北地区集中式光伏项目为例进行实证研究，结果表明：所开发的综合安全风险评估与决策框架能够有效识别关键风险诱因，并筛选出平衡风险控制效能与成本效益的最优干预策略组合方案，为提升西北地区集中式光伏项目安全风险管理的系统性与精准性提供了理论依据与方法支持。

This paper proposes an integrated safety risk assessment and decision-making method for centralized photovoltaic projects in Northwest China from the perspective of risk evolution. The proposed method incorporates three core components. First， a dual-dimensional quantitative model consisting of “static risk” and “transmitted risk” is constructed based on Bayesian networks and information entropy theory. The static risk captures the inherent potential harm of each risk node given its parent nodes’ states， while the transmitted risk quantifies the amplifying effect of risk propagation along the network using Shannon entropy. Second， a data-driven threshold determination method is developed to identify the failure criterion for each risk node. This method employs second-order difference analysis on candidate threshold percentiles obtained from Monte-Carlo simulation results， and the optimal threshold is identified at the percentile where the system behavior exhibits a critical transition. Third， a multi-strategy decision-making framework is established by integrating sensitivity analysis and value engineering theory， enabling both the identification of critical risk triggers and the selection of optimal intervention strategy portfolios that balance risk control effectiveness and cost efficiency. The proposed framework is validated through an empirical study on a centralized photovoltaic project in Northwest China. A total of 38 risk factors are identified across the design， construction， and operation phases. The Monte-Carlo simulation with 5，000 iterations yields a baseline comprehensive safety risk level of 32.527， with the 5%， 50%， and 95% percentiles being approximately 16.000， 32.457， and 49.455， respectively， indicating a symmetric risk distribution. Sensitivity analysis identifies five key risk triggers that contribute most significantly to the overall system risk: lack of experience in regional risk perception， reduction of maintenance investment， improper contractor selection， incomplete emergency plans， and failure of safety supervision mechanisms. Among four categories of intervention strategies (organizational， managerial， technical， and economic)， the optimal combination of “organizational + managerial + technical” strategies achieves the highest value index of 2.698， outperforming other combinations including the four-strategy full combination (value index 1.925). The results demonstrate that the proposed framework can effectively identify critical risk triggers and select optimal intervention portfolios， providing both theoretical foundations and methodological support for systematic and precise safety risk management in centralized photovoltaic projects in Northwest China.