A multistage stochastic programming formulation to evaluate feedstock/process development for the chemical process industry

Abstract

Industry trends suggest that the feedstock and product portfolios along with utilized technologies of chemical process industry (CPI) may grow and be quite different compared to today’s in the near future. Incorporation of new feedstocks and technologies into the existing CPI infrastructure may require significant amounts of investments. Determining the investment decisions, i.e., how much to invest, which technologies to invest in, and when to invest in each technology for research and development and for capacity expansion, is a challenging task, because there are often many emerging technologies and the future performances of these technologies are uncertain. Here, we present a multistage stochastic programming (MSSP) formulation accounting for both endogenous and exogenous uncertain parameters associated with the new technology investment planning (NTIP) problem. The MSSP formulation is used to determine investment decisions for four case studies, including a biomass to ethylene production network. The solution for the biomass to ethylene case study suggests that, given the current market conditions, the investment in biomass technologies is not financially advantageous.