An Optimization-Based Computational Procedure for Retrofit of Refinery Water Network Systems Incorporating Water Reuse, Regeneration, and Recycle

Water is a key element for the normal functioning of refineries and petrochemical plants in the hydrocarbon processing industry. Scarcities in freshwater supply and increasingly stringent rules on wastewater discharges have emerged as issues of major concern in our time. Water has become an increasingly crucial resource to industrial plants due to increased requirements in operating efficiency and optimization, to avoid high demand of water, and the drive for sustainable development that may result in plants being vulnerable to interruptions in water supply and to water shortages in the future. It is a well-acknowledged fact that cost of water is low but its value is high, and that there is increased regulatory requirements for zero discharge from process plants. In line with these developments, this work has been undertaken with the goal of formulating and solving a mathematical optimization model for the optimal design of an integrated water network system for a typical oil refinery via combined knowledge of engineering heuristics and mathematical programming. The integrated model explicitly considers the incorporation of water minimization approaches and strategies that consist of the potential for water reuse, regeneration, and recycle (W3R), with the objective of minimizing freshwater consumption and wastewater flows while complying to the maximum allowable contaminant concentrations where it is concerned. The stipulated objective directly corresponds to minimizing the associated capital and operating costs of the facility, although cost is not explicitly considered in this work. The methodology includes data collection on flowrates and contaminant concentrations and the subsequent step of data reconciliation on the water balances. Next, a superstructure embedding all feasible alternatives for the implementation of the potential W3R opportunities are developed. A nonlinear programming (NLP) model is then formulated based on the superstructure with the addition of constraints on the maximum allowable contaminant concentrations to meet regulatory discharge requirements as well as for the evaluation of W3R opportunities. Computational studies are performed on the NLP model using GAMS algebraic modeling platform on an industrially-significant problem representative of industrial scale with six contaminants considered. The satisfactory numerical results show that our proposed approach is a promising tool to aid decision-making in the retrofit of refinery water network systems.