A general optimization framework for designing chemical & energy systems subject to multi-scale temporal variability

We present a general optimization framework for designing chemical and energy systems that experience variability at multiple timescales. Motivated by an environmental need to decarbonize manufacturing, we seek to understand the viability of chemical and energy systems subject to temporal variability in physical and economic conditions. Our framework is based on a system specific superstructure and set of unit models, and it includes a representative time structure and the corresponding mathematical program for operation-informed design. The framework can be applied to determine the basic configuration and design of unit operations, associated time profiles of material and energy flows for flexible operation, and relevant thermodynamic variables (like temperature and pressure). It also allows us to identify how optimal design evolves over time. Understanding these behaviors is key to designing systems that successfully operate under variability. We apply our framework to study green ammonia synthesis, and identify optimal designs with distinct operational behavior at hourly, seasonal, and (multi-)yearly timescales. This includes charge/discharge decisions for energy storage, the behavior of mass storage tanks, and the seasonal purchase/sale of energy. We also observe transition points in design when considering different power grids.