Abstract
Abstract Cryogenic air separation technology is used to produce large amounts of technical gases with high purity levels. It is an industrial energy-intensive technology consuming high volumes of electricity. The complexity in operating air separation processes increases since the volatile conditions (i.e., electricity prices and product demand) can hourly change. Thus, the use of computer-aided tools to obtain energy and economic savings becomes crucial. In this paper, we state a multiperiod and multiproduct mixed-integer linear programming (MILP) model to determine the optimal production schedule of an industrial cryogenic air separation process. The MILP model contributes to minimize the energy consumption in the network whereas the net profit is maximized. The model capabilities are developed and validated using an existing air separation plant.
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