Stochastic operation strategy for emerging industry development and information transmission in financial markets: Evidence from intermittent china renewable energy resources

The rapid growth of renewable energy sources introduces significant challenges for the economic and reliable operation of energy systems, necessitating advanced risk management strategies. Addressing the variability and uncertainty associated with renewables, this paper presents a stochastic dominance-constrained operation strategy tailored for Industrial Integrated Energy Systems (IIES). A novel risk factor-oriented benchmark selection method is proposed, which effectively manages risks by considering the complete profit distribution rather than focusing on specific risk metrics. Case studies using real-world data from U.S. electricity markets demonstrate that intermittent renewables can cause profit reductions exceeding 7 % in 50 % of scenarios. However, the proposed strategy mitigates such risks across all scenarios by leveraging both physical (e.g., energy storage) and financial (e.g., hedging) flexible resources. Furthermore, increasing financial trading resources by 33.33 % reduces fixed investment costs for energy storage by as much as 92.59 %, showcasing the cost-saving potential of the integrated approach. Compared to traditional stochastic methods, the proposed strategy improves economic performance and operational reliability under volatile market conditions and extreme weather scenarios. These findings underscore the robustness and adaptability of the proposed framework in managing multifaceted risks in IIES, paving the way for sustainable energy system operations.