Increasingly volatile electricity prices make simultaneous scheduling optimization desirable for production processes and their energy systems. Simultaneous scheduling needs to account for both process dynamics and binary on/off-decisions in the energy system leading to challenging mixed-integer dynamic optimization problems. We propose an efficient scheduling formulation consisting of three parts: a linear scale-bridging model for the closed-loop process output dynamics, a data-driven model for the process energy demand, and a mixed-integer linear model for the energy system. Process dynamics is discretized by collocation yielding a mixed-integer linear programming (MILP) formulation. We apply the scheduling method to three case studies: a multiproduct reactor, a single-product reactor, and a single-product distillation column, demonstrating the applicability to multiple input multiple output processes. For the first two case studies, we can compare our approach to nonlinear optimization and capture 82% and 95% of the improvement. The MILP formulation achieves optimization runtimes sufficiently fast for real-time scheduling.

中文翻译：

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过程及其能源系统的同时混合整数动态调度

日益波动的电价使得生产过程及其能源系统需要同时进行调度优化。同时调度需要考虑能源系统中的过程动态和二进制开/关决策，从而导致具有挑战性的混合整数动态优化问题。我们提出了一个有效的调度公式，由三部分组成：闭环过程输出动态的线性尺度桥接模型、过程能量需求的数据驱动模型和能量系统的混合整数线性模型。过程动力学通过搭配产生一个混合整数线性规划 (MILP) 公式来离散化。我们将调度方法应用于三个案例研究：多产品反应器、单产品反应器和单产品蒸馏塔，证明对多输入多输出过程的适用性。对于前两个案例研究，我们可以比较我们的非线性优化方法并获得 82% 和 95% 的改进。MILP 公式为实时调度实现了足够快的优化运行时间。