Abstract: A distributionally robust optimization method was proposed for integrated energy systems with power-to-ammonia conversion and flexible coal-fired unit operation to enhance renewable accommodation and reduce carbon emissions. A two-stage power-to-ammonia model was developed considering dynamic response characteristics of electrolyzers and ammonia synthesis units, enabling green power-ammonia-power conversion via ammonia co-firing in thermal plants. To address the operational inflexibility of coal-fired units: (1) the oxygen by-product from water electrolysis was supplied to oxygen-enriched combustion systems, a flexible regulation model was established, forming an ammonia-oxygen dual-cycle mechanism comprising electrolyzers, ammonia synthesis, ammonia-blended coal-fired generation, and oxygen-enriched combustion; (2) cogeneration units, thermal storage, and electric boilers were coordinated to decouple the heat-electricity constraint in coal-fire plants. Accounting for wind and solar uncertainty, a distributionally robust optimization model was formulated to minimize operation costs under the worst-case probability distribution within an ambiguity set, and solved iteratively via the column-and-constraint generation algorithm. Comparative case studies demonstrate that the proposed strategy effectively reduces operating costs, promotes renewable energy utilization, and mitigates carbon emissions.