A Model for the Design of Optimal Total Water Network (OTWN)
Sujak, S.
Lim, J.S.
Wan Alwi, S.R.
Manan, Z.A.
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How to Cite

Sujak S., Lim J., Wan Alwi S., Manan Z., 2015, A Model for the Design of Optimal Total Water Network (OTWN), Chemical Engineering Transactions, 45, 697-702.
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Abstract

Water reuse network can reduce tremendously the freshwater consumption and wastewater generation. However, it requires major investment in the piping and pumping as well as reuse tank. Many industries still prefer to buy freshwater and treating all their wastewater as it is typically cheaper. However, this scenario is changing as the freshwater price, wastewater penalty to achieve the discharge standard, wastewater treatment cost and land price are increasing. There are many works in minimising water and wastewater cost in the industries. However, most of the work simplifies the wastewater treatment cost into simple equations that favours water reuse. The benchmarking methodologies focusing on measurements of wastewater treatment plant to achieve an establish output (contaminants removed) using the minimum of inputs (cost of energy, labour, maintenance, etc.). The wastewater treatment model is actually more complex as biological effects, detention time and many other factors should also be considered. The detention time and wastewater treatment plant volume will also affect the land price. This work presents a mixed-integer non-linear programming (MINLP) model for the synthesis of optimal total water network (OTWN). The aim is to find the minimum cost that considers all the trade-offs and considering a more detail calculations of the wastewater treatment plant and land area needed. The wastewater treatment is assumed to consist of primary and secondary treatment units. The model is applied to a synthetic fabric production in a textile plant and the result has shown that the OTWN model is able to determine the total cost of water and wastewater treatment network while accounting for the land cost when a water reuse has been included in the model.
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