Title: Optimisation of material and energy exchange in an eco-park network considering three fuel sources

Authors: Ivan Kantor; Ali Elkamel; Michael W. Fowler

Addresses: University of Waterloo, Waterloo, ON N2L 3G1, Canada ' University of Waterloo, Waterloo, ON N2L 3G1, Canada ' University of Waterloo, Waterloo, ON N2L 3G1, Canada

Abstract: This work represents a quantitative assessment of the eco-park theory and its application to a case involving the manufacture and export of several chemical products in addition to heat and electricity from an eco-industrial park comprised of a number of facilities or 'nodes'. The eco-industrial network is assessed in terms of environmental impact and profitability relative to existing facilities that do not interact directly with the exchange of material and energy streams amongst the nodes. GAMS software was employed to create the optimisation program with decision variables describing which of the network nodes should be constructed and what their associated production capacities should be in order to optimise an objective function focused on profit and environmental impact. Additionally, utilisation of three different fuels as the primary source of chemical reagents and energy are considered in various scenarios. These fuels are coal and biomass for gasification or a steam-methane reforming process for hydrogen production using natural gas as the fuel. The eco-park network with interacting production nodes is shown to be more profitable than the comparable non-integrated set of facilities and the network exports are produced with lower environmental impact in terms of criteria air contaminants.

Keywords: lifecycle analysis; LCA; GAMS; eco-parks; operations research; fuel comparison; industrial parks; multi-objective optimisation; fuel sources; material and energy exchange; operations management; environmental impact; profitability; chemical reagents; fuel use; coal; biomass; gasification; steam-methane reforming; hydrogen production; natural gas; air pollution; industrial clusters.

DOI: 10.1504/IJAOM.2014.066828

International Journal of Advanced Operations Management, 2014 Vol.6 No.4, pp.285 - 308

Received: 02 Feb 2013
Accepted: 08 Jan 2014
Published online: 14 Jan 2015 *

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