This paper addresses a multistage batch plant scheduling problem under energy constraints. These reflect the limited availability of a thermal heating utility that is shared among parallel digesters of different capacities for the production of pulp. Depending on the processing sequence, more or less steam will be available for a given digester, which will affect the duration of its heating stage and the overall cycle time. Such integrated heating tasks resemble direct heat integration, which has been addressed through models based on generic frameworks for process representation (e.g., State-Task Network, Resource-Task Network, State-Sequence Network) and relying on a single time grid, either discrete or continuous. A new multiple time grid continuous-time model is now proposed where the complex energy constraints are derived from the higher level modeling framework that is Generalized Disjunctive Programming. The results show a considerable better performance compared to RTN discrete and continuous-time formulations, due to a substantially lower integrality gap and model size.