Economic and environmental optimization of a multi-site utility network for an industrial complex.
Most chemical companies consume a lot of steam, water and electrical resources in the production process. Given recent record fuel costs, utility networks must be optimized to reduce the overall cost of production. Environmental concerns must also be considered when preparing modifications to satisfy the requirements for industrial utilities, since wastes discharged from the utility networks are restricted by environmental regulations. Construction of Eco-Industrial Parks (EIPs) has drawn attention as a promising approach for retrofitting existing industrial parks to improve energy efficiency. The optimization of the utility network within an industrial complex is one of the most important undertakings to minimize energy consumption and waste loads in the EIP. In this work, a systematic approach to optimize the utility network of an industrial complex is presented. An important issue in the optimization of a utility network is the desire of the companies to achieve high profits while complying with the environmental regulations. Therefore, the proposed optimization was performed with consideration of both economic and environmental factors. The proposed approach consists of unit modeling using thermodynamic principles, mass and energy balances, development of a multi-period Mixed Integer Linear Programming (MILP) model for the integration of utility systems in an industrial complex, and an economic/environmental analysis of the results. This approach is applied to the Yeosu Industrial Complex, considering seasonal utility demands. The results show that both the total utility cost and waste load are reduced by optimizing the utility network of an industrial complex.
Kim
Sang Hun
SH
Department of Chemical and Biomolecular Engineering, KAIST, Daejeon, Republic of Korea.
Yoon
Sung-Geun
SG
Chae
Song Hwa
SH
Park
Sunwon
S
D002617:Chemical Industry / Q000191:economics; D003246:Conservation of Energy Resources / Q000191:economics / Q000379:methods*; D011211:Electric Power Supplies / Q000191:economics; D007220:Industrial Waste / Q000191:economics; D008962:Models, Theoretical; D056910:Republic of Korea; D013227:Steam
D007220:Industrial Waste; D013227:Steam