In this work, a mixed-integer linear programming (MILP) model is presented based on a discrete-time scheduling formulation that allows modeling and optimizing operational decisions for processes working under time sensitive energy prices. The main goal is to find an optimal production schedule, over a given time horizon, that satisfies product demand while minimizing total energy cost. This novel formulation, based on a new concept to model the transitions between alternative operating modes, is very efficient and robust. To illustrate the new capabilities of the model, a comprehensive comparison is performed with a previous alternative model. The model is also used to efficiently solve a real-world industrial case study. The obtained results show optimal solutions for the proposed methodology with modest computational effort.