Scheduling-informed optimal design of systems with time-varying operation: A wind-powered ammonia case study

The time-varying operation of chemical plants offers economic advantages, particularly in the presence of time-sensitive electricity markets and renewable energy generation. However, the uncertainty and short-timescale variability associated with renewable energy production, as well as the nonconvex process and cost models typically associated with chemical processes, make finding the optimal design of such systems challenging. In this work, a new approach is presented to finding the optimal design of systems with time-varying operation, called scheduling-informed design, whereby the optimal operation of many designs is determined and the resulting cost correlations into the optimal design problem are embedded. This method is applied to a case study of wind-powered ammonia generation and showed that it greatly improves the computational tractability of the optimal design problem and predicts with greater accuracy operating costs realized because of uncertainty in forecasting. (c) 2018 American Institute of Chemical Engineers AIChE J, 65: e16434 2019