A stochastic programming approach for the integrated network with utility supply and carbon dioxide mitigation systems in uncertain utility demand

Abstract

A two-stage stochastic model is presented to develop the supply chain network and determine the optimal integrated network design by integrating CO2 mitigation and utility supply strategies with uncertain utility demand. The objective of this model is to decide the total network cost while meeting the utility demands and the targets of CO2 mitigation for each company over four seasons and uncertain demands for utilities. This model determines where and how much (1) utility (steam) to be transported among many companies, and (2) CO2 to be captured, transported from companies and stored, or (3) carbon credits to be levied for companies that emit excessive CO2. This model is assessed from the case study of Industrial Complex located at Yeosu in South Korea with uncertain utility demand. Optimized total costs estimated by the stochastic model (US$ 198.88 × 106/y) were slightly (0.68%) higher than that of the deterministic model (US$ 198.58 × 106/y). Variation in utility demand (stochastic model) affected both strategies, compared to the case of fixed utility demand (deterministic model). Steam transfer links decreases as utility demand increases, so carbon credits trading is a better option than carbon capture and storage system as a CO2 mitigation strategy.