Production scheduling optimization for power-intensive processes with time-sensitive electricity prices

Abstract

Continuous power-intensive processes in air separation plant can take advantage of optimal production planning to reduce the consumption of electricity. In this work a solution approach is developed based on a discrete-time scheduling formulation that allows modeling and optimizing operating decisions either in a fixed or a rolling horizon scheme. The main goal of this contribution is to find an optimal hourly schedule for next week that minimizes total energy consumption cost while satisfying all operational constraints. The MILP model is tested on real-world electricity price and demand input data. The results show optimal solutions for the proposed methodology with a modest computational effort considering a one-hour time grid and one-week time horizon.