Faculty of Technology, University of Tuzla, Tuzla, Bosnia and Herzegovina, Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States, Faculty of Chemistry and Chemical Engineering, University of Maribor, Maribor, Slovenia, Swiss Federal Institute of Technology Lausanne, Lausanne, Switzerland, Sustainable Process Integration Laboratory—SPIL, NETME Centre, Faculty of Mechanical Engineering, Brno University of Technology—VUT BRNO, Brno, Czechia, CanmetENERGY, Natural Resources Canada, Varennes, QC, Canada, School of Chemical Engineering, Dalian University of Technology, Dalian, China

This work presents the synthesis of heat-integrated water networks (HIWNs) by using mathematical programming. A new superstructure is synthesised by combining a water network and a modified heat exchanger network. Based on the proposed superstructure, a mixed-integer nonlinear programming (MINLP) model is developed. The model is solved by using a one-step solution strategy enabling different initialisations and the generation of multiple solutions, from which the best one is chosen. The results show that the proposed model can be effectively used for solving HIWN problems of different complexities, including large-scale problems.

This work addresses the synthesis of heat-integrated water networks (HIWNs) by using a superstructure optimisation approach. A recently developed mixed-integer nonlinear programming (MINLP) model and an iterative solution strategy are applied in this work to a case study of HIWN. The objective function of the MINLP model is to minimise the network total annualised cost (TAC) comprising operating and investment costs. As there are trade-offs between operating and investment costs, good solutions can be obtained if the TAC is minimised by simultaneously exploring all water and heat integration opportunities within the network. A case study with sensitivity analysis is solved by analysing the impact of freshwater and utility costs on the network design and key performance indicators. The results indicate that in cases of low freshwater cost increased freshwater usage is forced and thus lowering wastewater regeneration/recycling and wastewater treatment cost. Increased freshwater flowrate is related to an increase of HEN investment. The high cost of freshwater could produce solutions with lower freshwater consumption compared to base case depending on utility cost and wastewater treatment cost. However, a decrease in freshwater consumption increases wastewater regeneration costs.