Water Integration of Eco-Industrial Parks Using a Global Optimization Approach

Abstract

This Article presents a mathematical programming model for the mass integration of eco-industrial parks. The model considers the reuse of wastewater among different industries and the constraints given by the process sinks and the environmental regulations for waste streams discharged to the environment. The model allows the optimal selection of treatment units to satisfy the process and environmental regulations. The objective function consists of the minimization of the total annual cost, including the treatment unit costs, the piping costs, and the cost of fresh water. A new discretization approach is proposed for the model reformulation to handle the bilinear terms of the model as part of a global optimization strategy. Results show that significant savings can be achieved for the design of an integrated eco-industrial park with respect to the integration of each individual industry.

Quantitative tools for cultivating symbiosis in industrial parks; a literature review

“…Zbontar and Glavic [153] performed a case study of a petrochemicals plant using some pinch analysis ideas which included water treatment costs and capital costs. Process and environmental regulations were used as constraints in a global optimization model proposed by Rubio-Castro et al [154,155] with annual costs, including water treatment and piping costs, where the problem of finding a global minimum was investigated further in [156]. Another model in which environmental and economic relationship were expanded, used LCA and Life Cycle Costing (LCC) to find designs which reduced both emissions and costs in remodelling an industrial park [157].…”

A novel application of genetic algorithm for synthesizing optimal water reuse network with multiple objectives

“…The first layer, which is based on a LP formulation, generates multiple starting points for the solution of the NLP model, which is the second layer of the optimization. Rubio- Castro et al (2010) applied a discretization approach by reformulating the MINLP model of a TWN superstructure to MILP and solved it for global optima. Guelli Ulson de Souza et al (2011) combined a heuristic method called waste source diagram and NLP algorithm for optimal synthesis of WUN.…”

“…where AR is the annualized investment factor (/yr); IC t is the investment cost coefficient for treatment unit t; F out,t is the flowrate of wastewater from treatment unit t (t/h); H is plant operating hours per annum (h/yr); OC t is the operating cost coefficient for treatment unit t (t/h); and PC is the piping cost expressed as (Rubio-Castro et al, 2010):…”

A multi-objective approach for property-based synthesis of batch water networks

“…In this context, several techniques for targeting the minimum wastewater discharge [4][5][6][7][8][9][10] and the minimum regeneration cost [11][12][13][14][15] have been proposed; these targeting techniques are very useful to identify targets before the design. In addition, in order to solve problems with multiple pollutants and to get optimal solutions with the corresponding design, some techniques for synthesizing water networks based on mathematical programming models have been reported [16][17][18][19][20][21][22][23][24][25][26]. Moreover, there have been reported several methodologies for synthesizing batch water networks based on the composition of the streams (see for example, Refs.…”