Green Operation of an Air Separation Unit Using an Efficient MILP Optimal Scheduling Framework
Morgan Kelley, University of Texas
Greenhouse gas emissions in the United States increased by 7 percent from 1990 to 2014 and carbon dioxide accounted for 82 percent of greenhouse gas emissions in 20151. Electricity transmission and production accounts for 29 percent of these emissions and industry accounts for 21 percent1. In this work, we seek to lower both industrial and electricity sector emissions by changing the electricity demand profile of industrial plants. We seek to do this by performing optimal scheduling calculations for green operation of an air separation unit (ASU). Green operation of ASUs requires that the process dynamic characteristics and performance be included in production scheduling calculations to ensure that production rate changes (typically scheduled at hourly intervals) are feasible and do not violate product quality and operating safety constraints. However, the (first-principles) mathematical models that are needed to describe and optimize the green behavior of industrial facilities cover multiple time scales and are inevitably large-scale, nonlinear and stiff, posing computational challenges for simulation and optimization. We address this problem by utilizing a previously derived2 optimal scheduling framework and applying it to ASUs operating under greening conditions. We propose using low-order data-driven models of the plant's scheduling-relevant dynamics and present a set of reformulation and (exact) linearization techniques that allow us to cast the overall DR scheduling problem as Mixed Integer Linear Program (MILP). We show that green operation of an ASU can significantly reduce emissions, compared to a scenario where the production rate is kept constant. 1EPA: Overview of Greenhouse Gases. (2016). Retrieved October 4, 2017, from https://www.epa.gov/ghgemissions/overview-greenhouse-gases 2M.T. Kelley, R.C. Pattison, R. Baldick, and M. Baldea, "An MILP framework for optimizing demand response operation of air separation units," Appl. Energy, vol. 222, pp. 951-966, 2018.
Abstract Author(s): Morgan T. Kelley, Ross Baldick, Michael Baldea