Multi-disciplinary Design Optimization for Large-scale Reverse Osmosis Systems

Large-scale desalination plants are complex systems with many inter-disciplinary interactions and different levels of subsystem hierarchy. Advanced complex systems design tools have been shown to have a positive impact on design in aerospace and automotive, but have generally not been used in the design of water systems. This work presents a multi-disciplinary design optimization approach to desalination system design to minimize the total water production cost of a 30,000m3/day capacity reverse osmosis plant situated in the Middle East, with a focus on comparing monolithic with distributed optimization architectures. A hierarchical multi-disciplinary model is constructed to capture the entire system’s functional components and subsystem interactions. Three different multi-disciplinary design optimization (MDO) architectures are then compared to find the optimal plant design that minimizes total water cost. The architectures include the monolithic architecture multidisciplinary feasible (MDF), individual disciplinary feasible (IDF) and the distributed architecture analytical target cascading (ATC). The results demonstrate that an MDF architecture was the most efficient for finding the optimal design, while a distributed MDO approach such as analytical target cascading is also a suitable approach for optimal design of desalination plants, but optimization performance may depend on initial conditions. INTRODUCTION Multidisciplinary design optimization (MDO) is a set of tools used by system engineers to optimize the design of a system that involves many disciplines or subsystems. The challenges that arise in MDO have largely been in the numerical complexity of performing system wide modeling [1]. To mitigate the numerical complexity, a number of strategies or methods for problem formulation and subsystem organization have been proposed, also known as MDO architectures [1–4]. An MDO architecture can be either monolithic or distributed. Examples of monolithic architectures include Multi-Disciplinary Feasible (MDF) and Individual Discipline Feasible (IDF) [2, 5, 6], where a single optimization problem is solved. In a distributed approach the problem is partitioned into multiple subproblems, examples include Collaborative Optimization (CO), Bi-Level Integrated Synthesis System (BLISS), and Analytical Target Cascading (ATC), to name a few [7–11]. A number of studies have been conducted to compare the effectiveness and limitations of different MDO architectures, and these studies have suggested 1 Copyright c © 2014 by ASME that the performance of an MDO architecture often depends on the nature of the problem [1, 12]. Therefore, it is imperative for engineers to test multiple architectures on a given problem. Desalination processes remove salt from saline water to produce fresh water. Large-scale desalination plants (with capacity of 30,000 m3/day or more) have been constructed in the Middle East since the early 1960’s to alleviate the region’s water shortage. As the cost of desalination technologies, especially reverse osmosis (RO) technology, continue to decrease, large-scale reverse osmosis desalination plants are being constructed in other areas around the world. The majority of reverse osmosis numerical optimization studies only consider the reverse osmosis process itself. As of today, designers in the field of desalination have not attempted to apply techniques developed in systems engineering, such as MDO, in the modeling and optimization of desalination systems. The reason for this may be that the RO process itself is of a scope that can be handled by a small design team. However, when considering the desalination system as a whole, including pre-treatment, life-cycle operation, and energy availability, the system becomes far more complex with major interactions between subsystems and components. As the world population continues to grow and fresh water supplies dwindle, there will be more desalination plants constructed around the world. Future desalination plant designers will face the problem of designing regional desalination networks, where a number of desalination plants must work together cohesively while sharing limited energy resources. These properties of desalination systems make them an ideal case example for studying systems engineering techniques such as multi-disciplinary design optimization. The objective of this study will be to investigate which type of MDO architectures are best suited for finding the optimal design of a reverse osmosis desalination system. The performances of several different MDO architectures are compared using a 30,000 m3/day reverse osmosis plant in the Middle East as a case study. This study also serves the purpose of presenting a real world test problem that will contribute to the on-going research of evaluating novel MDO architectures. RELATED WORK Optimization of Reverse Osmosis System A number of different studies have examined numerical optimization of RO processes, including optimization under different feed concentrations [13], optimization of energy costs based on electricity supply [14], optimization for both capital and operational costs [15], and optimization considering membrane fouling [16]. All of these works only considered the RO process itself in rather than a broader systems-oriented approach. Vince, et al. [17] considered both energy consumption and cost in a multi-objective optimization approach of RO plants, though their system model is also limited to the RO process alone. Kim, et al. [18] published an overview of systems engineering approaches for large-scale seawater desalination plant. They reviewed over 100 papers related to the different subsystems of a RO plant. However, they did not attempt to map the interactions between the major subsystems, nor propose methods for systemwide optimization. MDO Architectures A number of surveys and comparison studies of MDO architectures has been reported in the past decade. Martins, et al. [1] compiled a comprehensive list of all existing MDO architectures to date, and included descriptions of features, merits, and expected performance. Perez, et al. [19] performed an extended evaluation of five different architectures, based on metrics of simplicity, transparency, portability, efficiency and accuracy, using an aircraft conceptual design case study. de Wit and Keulen [20] compared six different distributed MDO methods based on performance and efficiency, using a simple two-beam truss structure as an example. Allison, et al. [5] compared the performance between MDF and IDF architectures with test problems of varying complexity. Honda, et al. [21] compared different information passing strategies in distributed MDO architectures. Brown, et al. [12] compared MDO methods with fixed-point iteration methods using a case example of a reusable launch vehicle. The limitations of these comparison studies include low dimensionality of test problems and inconsistency of programming skills between research groups. The consensus from these studies is that the most appropriate architecture will depend on the nature of the problem [1, 12, 19]. To the best of the authors’ knowledge, there has not been a study in which systems engineering tools are used to analyze an RO desalination plant, capture the interactions between pretreatment, the RO process, operations and energy consumption. Moreover, multi-disciplinary optimization has also not been applied to desalination technologies. This paper seeks to fill the gap by considering reverse osmosis plants at a systems level using MDO techniques. METHODOLOGY In this study several different MDO architectures are applied to the numerical design optimization of a reverse osmosis plant, to compare the performance of different architectures in desalination technology applications. This section outlines the methodologies associated with modeling of the desalination system and implementation of the MDO architectures. Reverse Osmosis System Model Development In this case study, a 30,000m3/day capacity seawater reverse osmosis plant is planned for a specific location on the coast of the Arabian Gulf. Actual cost and capacity numbers from an existing 2 Copyright c © 2014 by ASME Intake & Pre-treatment RO Process Flow Structure RO Unit feed water product water brine disposal HP pump