The use of nonlinear programming to optimal water allocation

Environmental protection, shortage of fresh-water and rising costs for wast ewater treatment are all convincing motives for reducing fresh-water consum ption and wastewater discharge of the chemical, petrochemical, petroleum re fining and other process industries. Maximizing water reuse, regeneration r e-use, and regeneration recycling within the chemical plant, as well as opt imal distribution of waste streams for end-of-pipe treatment can reduce fre sh-water usage and wastewater discharge, while they are also significant in shrinking capital investment in wastewater treatment systems. Optimal assignment and design of water consuming, regenerating, and treatme nt systems is a complicated task that can be mathematically formulated as m ixed integer non-linear programming (MINLP). In the present article the sup erstructure based 'Cover and Eliminate' approach with NLP is applied with t he tools of the GAMS/MINOS/CONOPT package and compared to previous results. After introducing the problem in the context of chemical process synthesis , a mathematical model is described and the use of the methodology is expla ined. Experience with the use of GAMS is discussed. Several case studies ar e solved including basic examples from the literature and their variants. The main conclusion is that the application of the mathematical programming for the optimal water allocation problem is essential owing to the broad v ariety of the specification opportunities. The complex nature of re-use, re generation re-use, and recycling with multiple pollutants and multiple trea tment processes cannot be simultaneously taken into account by conceptual a pproaches. It is also shown that the assumption on the independency of cont amination rates, generally applied in earlier works, are nor necessarily va lid; and the NLP approach can deal with the more reliable specifications.