Sustainable Electricity–Hydrogen–Coal-Chemical Coupled Systems Scheduling: A Structured Distributionally Robust Optimization Approach

Against the backdrop of low-carbon transition and the upgrading of the coal chemical industry, the coordinated operation between coal chemical processes and electricity–hydrogen systems has become increasingly important. However, the deep coupling and limited operational flexibility of energy–chemical processes, combined with the growing renewable penetration, pose significant challenges to achieving coordinated and reliable operation under uncertain conditions. To address these challenges, this article develops a distributionally robust optimal scheduling framework for an electricity–hydrogen–coal-chemical coupled system. The proposed framework jointly optimizes coal chemical processes and electricity–hydrogen systems within a unified modeling paradigm. To unleash the potential of operational flexibility in coal chemical production, an oxygen–carbon ratio regulation strategy is developed for the gasification process, enabling a flexible adjustment of production output within a constrained operating range. Furthermore, structured ambiguity sets are employed to delicately model high-dimensional and complex uncertainties in renewable generation and multiple energy demands. Based upon the ambiguity sets, we propose a multistage distributionally robust optimization model for sequential scheduling operation of the electricity–hydrogen–coal-chemical coupled systems. Because the resulting multilevel optimization structure cannot be handled by any off-the-shelf solvers, we exploit lifted decision rules (LDR) to enhance computational tractability and solution efficiency. Case studies demonstrate that the proposed method can effectively improve the economic performance as well as robustness of system operation, and validate the effectiveness of the oxygen–carbon ratio regulation in flexible methanol production.