A Mixed-Integer Linear Programming Formulation for Optimizing Multi-Scale Material and Energy Integration

This research presents a mathematical formulation for optimizing integration of complex industrial systems from the level of unit operations to processes, entire plants, and finally to considering industrial symbiosis opportunities between plants. The framework is constructed using mixed-integer linear programming (MILP) which exhibits rapid conversion and a global optimum with well-defined solution methods. The framework builds upon previous efforts in process integration and considers materials and energy with thermodynamic constraints imposed by formulating the heat cascade within the MILP. The model and method which form the fundamentals of process integration problems are presented, considering exchange restrictions and problem formulation across multiple time-scales to provide flexibility in solving complex design, planning, and operational problems. The work provides the fundamental problem formulation, which has not been previously presented in a comprehensive way, to provide the basis for future work, where many process integration elements can be appended to the formulation. A case study is included to demonstrate the capabilities and results for a simple, fictional, example though the framework and method are broadly applicable across scale, time, and plant complexity.