This article aims to optimize the nitrogen removal of a sequencing batch reactor (SBR) through the use of the activated sludge model and iterative dynamic programming (IDP). Using a minimum batch time and a maximum nitrogen removal for minimum energy consumption, a performance index is developed on the basis of minimum area criteria for SBR optimization. Choosing area as the performance index makes the optimization problem simpler and a proper weighting in the performance index makes it possible to solve minimum time and energy problem of SBR simultaneously. The optimized results show that the optimal set-point of dissolved oxygen affects both the total batch time and total energy cost. For two different influent loadings, IDP-based SBR optimizations suggest each supervisory control of batch scheduling and set-point trajectory of dissolved oxygen (DO) concentration, and can save 20% of the total energy cost, while meeting the treatment requirements of COD and nitrogen. Moreover, it shows that the re-optimization of IDP within a batch can solve the modelling error problem due to the influent loading changes, or the process faults.