Stochastic Pinch Analysis To Optimize Resource Allocation Networks

Abstract

Pinch analysis is a physical insight-based optimization technique, applicable to conservation problems for a wide range of resources (such as energy, water, hydrogen, cooling water, etc.). Principally, it has been applied to optimize the external resource, to satisfy unmet demands in source-sink allocation problems, with deterministic flows and deterministic quality parameters (such as contamination concentration in water and hydrogen conservation problems). However, in many applications, quality and flow parameters of different sources may not be deterministic due to changes in environmental as well as operational conditions (e.g., changes in product mix and/or feed characteristics). In this paper, the applicability of pinch analysis has been extended to resource conservation networks with uncertain qualities and flows for the operation of individual sources and demands with the desired reliability. The uncertainties in source quality and source flows are incorporated through different probability distributions with known means and standard deviations. The stochastic constraints, due to uncertainties associated with flow and quality parameters of the sources, are converted to deterministic equivalents by use of chance-constrained programming. The resultant deterministic problem is approximated to a linear programming problem in order to address it through pinch analysis techniques. Applicability of the proposed methodology is demonstrated for water and hydrogen conservation networks, and the results are verified through Monte Carlo simulations.

Robust resource targeting in continuous and batch process

“…Tan (2011) presented a fuzzy mathematical programming model for the synthesis of water networks when the model parameters exhibit fuzzy uncertainties. Arya et al (2018) proposed a stochastic pinch analysis approach to handle uncertainties associated with source qualities and flows while targeting resource requirement in a continuous process. Rodriguez-perez et al (2018), presented a stochastic model to control quality in sequencing batch reactors under uncertainty.…”

Optimal Targets of Two Parallel Regeneration Recycling Water Networks

“…Alnouri et al 9 gave a water network design strategy for zero-emission factories based on an MINLP model. Arya et al 10 studied the optimization of resource networks (including water networks) with uncertain concentrations or mass loads and then further discussed the situation under nonlinear conditions. 11 Mabitla and Majozi 12 proposed a hybrid method combining a graphical method and a mathematical programming method, which can effectively improve optimization efficiency.…”

Cascaded Design of Desalination Systems: A Graphical Approach

“…Many graphical tools that have been introduced in this regard provide simple and easy-to-use alternatives for wastewater targeting and were found to be very helpful in visualizing the system, especially in terms of optimal flow rate allocations. In fact, the applicability of graphical tools has been extended to resource conservation network design with uncertain qualities and flows, subject to desired reliability . Other work that involves the application of graphical tools to assist in the design of various water-using/water-producing systems has been attempted.…”

“…In fact, the applicability of graphical tools has been extended to resource conservation network design with uncertain qualities and flows, subject to desired reliability. 15 Other work that involves the application of graphical tools to assist in the design of various water-using/water-producing systems has been attempted. For instance, Skouteris et al 16 developed a rigorous analytical tool based on water footprint principles and water pinch analysis techniques that can be used to manage and optimize water consumption, in which the water consumption footprint and the theoretical water pollution footprint were quantified.…”