XGBoost-Assisted Effluent Ammonium Buffer-First Aeration Scheduling for Wastewater Treatment Under Influent Disturbances: A BSM2 Study.

Aeration is the dominant controllable energy demand in activated-sludge wastewater treatment, but peak-period aeration reduction can compromise dissolved oxygen supply, nitrification, and effluent NH₄-N compliance. This study develops an XGBoost-assisted effluent ammonium buffer-first aeration scheduling framework (XGB-WQBF-guarded) for flexible wastewater treatment under influent disturbances. Offline Benchmark Simulation Model No. 2 (BSM2) rollouts were used to train surrogate models for future maximum NH₄-N, violation probability, and aeration flexibility capacity (AFC) over an 8 h horizon. Online candidate KLa sequences were accepted only after predictive water-quality screening, and a transparent recovery guard overrode the data-driven action when the current NH₄-N buffer was low, or no predicted-safe schedule existed. XGB-WQBF-guarded maintained zero NH₄-N violations in the evaluated deterministic BSM2 scenarios, with peak-period aeration reductions of 17.86%, 9.92%, and 11.11% for dry-weather, high-ammonium-shock, and rain-disturbance cases, respectively. Under combined sensor noise and actuator mismatch, violation rates increased to 7.22% in the high-ammonium-shock case and 3.89% in the rain case; a conservative threshold reduced these rates to 3.89% and 2.22%, respectively, with lower PAR. Held-out shock tests further showed that zero-violation performance is conditional on disturbance patterns similar to the training rollouts. The framework should therefore be interpreted as a benchmark-supported, operator-facing scheduling concept that requires plant-specific validation before full-scale deployment.