In today's energy markets, there is a growing effort toward the alignment of the industrial sector and the power grid for the sake of efficient energy distribution and consumption. In this paper, the resource-task network is used to provide a generic modeling framework for production scheduling under energy constraints. Three alternative process models for the energy-intensive melt shop of a steel plant are proposed and linked to a discrete-time formulation. The results show a trade-off between accurate representation of problem data and computational performance. By keeping track of the total energy and power consumption through time, we study the impact of fluctuating energy prices on the scheduling of operations and the economic benefits that can be obtained from the plant's participation in the price- and incentive-based industrial demand side management programs.