This paper investigates a practical steelmaking scheduling problem with batching decisions and energy constraints, in which batching is used to decide how to group and sequence a number of jobs to form job groups so as to meet batch production mode. Incorporating energy consideration into the scheduling is motivated by practical demand and the potential to reduce the energy bill through optimal scheduling. Based upon our proposed energy expressions, an MINLP model is formulated and solved using the spatial branch and bound (B&B) algorithm, which is enhanced by the proposed decomposition strategy working as a node heuristic. The benefits of the integrated scheduling and some sensitivity analysis experiments are reported on an illustrative example. Experiments on randomly generated instances show that the energy expressions are superior to the one of Haclera et al.(2015), the B&B outperforms the state-of-the-art commercial solvers and the decomposition strategy performs well running as an independent heuristic. (C) 2018 Published by Elsevier Ltd.