Economic optimization of integrated network for utility supply and carbon dioxide mitigation with multi-site and multi-period demand uncertainties
Yuchan Ahn and
Applied Energy, 2018, vol. 220, issue C, 723-734
This study develops a two-stage stochastic model to design an integrated network that simultaneously optimizes utility supply and CO2 mitigation strategies under demand uncertainties. The objective of the proposed model is to minimize the expected total cost of the integrated network to meet both uncertain demands (utility supply and CO2 mitigation) for multi-site companies in an industrial complex over a multi-period planning horizon. This model determines the optimal locations and amounts of: (1) utility (steam) transferred between companies; (2) CO2 captured, transported, and stored; (3) carbon credits imposed on companies that exceed allowable CO2 emission. The proposed model is applied to Yeosu industrial complex in Korea to validate the model. Total cost for U2C2 stochastic model (US$ 189.92 × 106/y) is 0.71% (US$ 1.34 × 106/y difference) higher than the deterministic model (US$ 188.59 × 106/y). The variation of both uncertain demands in the stochastic model affects the cost and structure of integrated network compared to the fixed parameters in the deterministic model, and it confirmed that the uncertainty of demand for utility supply has a more considerable influence on the structure of the integrated network than the demand for CO2 mitigation.
Keywords: Supply chain network; Optimization; Stochastic programming; Utility supply; CO2 mitigation; Uncertainty (search for similar items in EconPapers)
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