Operational Reliability Optimization: Integrated Petrochemical Logistics Systems Under Energy Transition via a Multi-Stage Collaborative Framework

The low-carbon transition is fundamentally reshaping the petrochemical industry, exposing integrated petrochemical logistics system to hazards arising from stochastic supply-demand uncertainty and operational vulnerabilities. To mitigate the risks of traditional static planning in this volatile environment, this paper develops the multi-stage collaborative reliability optimization framework. By integrating scenario generation and reduction techniques with stochastic programming, a multi-stage optimization model is established to ensure process safety and handle longterm planning adjustments. Taking a large-scale petrochemical network as a case study, the trade-off between economic expenditure and operational reliability is quantitatively evaluated across four fluctuation scenarios. The research findings demonstrate that the proposed multi-stage model outperforms static model in reliability indicators. Specifically: (i) the multi-stage model achieves a 39.25 % reduction in supply failure magnitude, representing a decrease of 18.13 ×10⁴ tons under the extreme failure scenario, and effectively curtails the average failure duration by 16.82 % under high fluctuation scenario; (ii) the service reliability level remains 1.88 % higher than that of the static model under extreme fluctuation scenario; and (iii) although the framework necessitates a 9.15 % safety premium in objective function value, this investment successfully transforms uncontrollable external hazards into manageable safety margins. These results provide critical decision support for maintaining operational safety and ensuring the continuous reliability of integrated petrochemical systems.

Keywords: Petrochemical system, Reliability optimization, Multi-stage collaborative programming, Supply and demand uncertainty, Risk mitigation.