(216e) The Application of Stochastic Optimization in Lignin Depolymerization Process

Authors: 
Tong, Z., University of Florida
Bao, H., University of Florida
Zhu, Z., Georgia Institute of Technology
Lan, G., Georgia Institute of Technology
Biochemical refinery problems often involve uncertainty such as randomness in materials, reactions, and operations. In this work we establish a multistage stochastic programming model for the optimization and control of chemical processes under this type of uncertainty. We discuss the implementation of a stochastic dual dynamic programming (SDDP) algorithm to compute an optimal solution for this problem. We then applied the algorithm on a simulated lignin depolymerization process to test the efficiency under several conditions.