The high energy demand in power-intensive processes and the possibility of reducing the energy bills by an optimal scheduling are the motivation for incorporating energy consideration in the production scheduling of air separation plants. Optimization opportunities exist at different time scales for day-ahead scheduling decisions and real-time decisions regarding all fluctuations in electricity prices. Consequently, this paper presents a reactive-iterative optimization approach, integrating the rolling horizon (RH) concept into an iterative solution algorithm, for optimizing production decisions when an industry participates in both the day-ahead electricity market and the spot electricity market. A novel discrete-time MILP formulation is used as a basis of the proposal, which allows adjusting production rates to electricity prices varying hourly or faster. Several scenarios from a real-life air separation industrial plant are solved to show interesting trade-offs between the predictive approach and the reactive-iterative strategy.

功率密集型过程中的高能源需求以及通过最佳调度来减少能源费用的可能性是将能源考虑因素纳入空分设备生产调度的动机。针对电价所有波动的日前调度决策和实时决策，在不同的时间尺度上存在优化机会。因此，本文提出了一种反应式迭代优化方法，该方法将滚动水平（RH）概念整合到迭代求解算法中，用于在行业同时参与日前电力市场和现货电力市场时优化生产决策。一种新颖的离散MILP公式被用作该提案的基础，可以根据每小时或更快的电价调整生产率。解决了现实生活中的空气分离工厂的几种情况，以显示预测方法和反应迭代策略之间的有趣折衷。