A mathematical formulation for robust targeting in heat integrated water allocation network. (1st February 2023)

• Record Type: Journal Article
• Authors: Haider, Md Alquma; Chaturvedi, Nitin Dutt
• Is Part Of: Energy. Volume 264(2023)
• Publication Date: 2023-02-01
• Subjects: HIWAN -- Uncertainty -- Robust optimization -- Process integration -- Targeting -- Mathematical modelling; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2022.126078
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Resource conservation strengthens a process industry's competitiveness and sustainability. Process integration (PI) strategies conserve resources. Heat-integrated water allocation networks (HIWANs) conserve energy and water. Process systems engineering optimizes synthesis, design, planning, scheduling, control, and supply chain. Recent developments promote robust optimization (RO) for uncertain optimization. RO optimizes for uncertain parameters to deal with data uncertainty. This research introduces a RO-based HIWAN resource-targeting model. Flow, concentration, and temperature uncertainties are modelled. The budget parameter reflects robustness. The budget restricts RO's conservatism and uncertainty, generating unduly cautious solutions. This model is explained with an example with different scenarios. Three of the scenarios have a single parameter uncertainty like source flow, source concentration, or inlet temperature, while one has multiple. Parameter behaviors are examined from nominal to worst-case scenarios. For scenario 1 where flowrate uncertainty is accounted, the robust flowrate target is 53.8% higher than the nominal value for the worst case. Similarly, for the second scenario where concentration uncertainty is accounted, robust flowrate target is 5.594% higher than nominal. In the last scenario with multiple uncertainties, the targeted flowrate increases by 59.44% compared to the nominal state. Nominal to worst-case scenarios can be handled by this model. Highlights: Concurrently minimization of heat and water incorporating parametric uncertainties. A linear programming based robust optimization framework is developed. Robust counterpart for various scenarios of uncertainties are presented. The objective is to minimize external resource requirements. Methodology can be used as per decision maker choice of budget for uncertainty.