Optimization of integrated water and multiregenerator membrane systems

A thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy (Chemical Engineering), September 2017Water and energy are key resources in the process industry. The water-energy nexus considers the interdependence of water and energy resources and their effect on the environment. The increasing awareness of environmental regulations has heightened the need for process integration techniques that are environmentally benign and economically feasible. Process integration techniques within water network synthesis require a holistic approach for the sustainable use of water through reuse and recycle and regeneration reuse and recycle. Conventional methods for water minimisation through water network synthesis often use the “black-box” approach to represent the performance of the regenerators. The degree of contaminant removal and cost of regeneration are represented by linear functions. This, therefore, leads to suboptimal operating conditions and inaccurate cost representation of the regeneration units. This work proposes a robust water network superstructure optimisation approach for the synthesis of a multi-regenerator network for the simultaneous minimisation of water and energy. Two types of membrane regenerators are considered for this work, namely, electrodialysis and reverse osmosis. Detailed models of the regeneration units are embedded into the water network superstructure optimisation model to simultaneously minimise water, energy, operating and capital costs. The presence of continuous and integer variables, as well as nonlinear constraints renders the problem a mixed integer nonlinear program (MINLP). The developed model is applied to two illustrative examples involving a single contaminant and multiple contaminants and one industrial case study of a power utility plant involving a single contaminant to demonstrate its applicability. The application of the model to the single contaminant illustrative example lead to a 43.7% freshwater reduction, 50.9% decrease in wastewater generation and 46% savings in total water network cost. The multi-contaminant illustrative example showed 11.6% freshwater savings, 15.3% wastewater reduction, 57.3% savings in regeneration and energy cost compared to the water network superstructure with “black-box” regeneration model. The industrial case study showed a savings of up to 18.7% freshwater consumption, 82.4% wastewater reduction and up to 17% savings on total water network cost.XL201

Superstructure optimisation of a water minimisation network with a embedded multicontaminant electrodialysis model

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering, 2016The water-energy nexus considers the relationship between water and energy resources. Increases in environmental degradation and social pressures in recent years have necessitated the development of manufacturing processes that are conservative with respect to both these resources, while maintaining financial viability. This can be achieved by process integration (PI); a holistic approach to design which emphasises the unity of processes. Within the realm of PI, water network synthesis (WNS) explores avenues for reuse, recycle and regeneration of effluent in order to minimise freshwater consumption and wastewater production. When regeneration is required, membrane-based treatment processes may be employed. These processes are energy intensive and result in a trade-off between water and energy minimisation, thus creating an avenue for optimisation. Previous work in WNS employed a black box approach to represent regenerators in water minimisation problems. However, this misrepresents the cost of regeneration and underestimates the energy requirements of a system. The aim of the research presented in this dissertation is to develop an integrated water regeneration network synthesis model to simultaneously minimise water and energy in a water network. A novel MINLP model for the design of an electrodialysis (ED) unit that is capable of treating a binary mixture of simple salts was developed from first principles. This ED model was embedded into a water network superstructure optimisation model, where the objective was to minimise freshwater and energy consumption, wastewater productions, and associated costs. The model was applied to a pulp and paper case study, considering several scenarios. Global optimisation of the integrated water network and ED design model, with variable contaminant removal ratios, was found to yield the best results. A total of 38% savings in freshwater, 68% reduction in wastewater production and 55% overall cost reduction were observed when compared with the original design. This model also led to a 80% reduction in regeneration (energy) cost.GS201

Development of systematic technique for energy and property integration in batch processes

The increasing consumption of energy, generation of waste as well as higher cost of fresh resources and waste treatment systems are the important driving forces for developing efficient, environmentally friendly and economic resource conservation techniques in the process industries. Process integration is being recognized as an useful systematic strategy for resource conservation and waste minimization. Up to date, less research works have been investigated on heat and property integration and these works are only focused on continuous processes.Since the application of batch processes is increasingly popular due to the development of technology-intensive industries such as pharmacy, fine chemistry and foods, it is necessary to consider both heat and property integration in batch processes simultaneously. In this thesis, a new mixed integer nonlinear programming (MINLP) mathematical model is introduced to synthesize a property-based heat integrated resource conservation networks (HIRCNs) for batch processes. A source-HEN-sink superstructure is constructed to embed all possible network configurations. Then, an MINLP model that consists of propertybased resource conservation network (RCN) and heat exchanger network (HEN) models is developed.In the proposed model, the property-based RCN model is formulated based on supertargeting approach while HEN model is formulated via automated targeting method (ATM). The optimization objective is to minimize total annualized cost (TAC) for a batch process system. This includes the operating cost of fresh resources, hot and cold utilities as well as the capital cost of storage tanks. To demonstrate the proposed approach, three case studies were solved. Based on the optimized results, the proposed simultaneous targeting approach for property-based HIRCNs is more effective in term of TAC for HIRCNs than the presented sequential targeting approach

Chemical process optimization and pollution prevention via mass and property integration

The process industries such as petrochemicals, chemicals and pharmaceuticals, among others, consume large amounts of material and energy resources. These industries are also characterized by generating enormous amounts of waste that significantly contribute to the pollution of the environment. Integrated process design is a very effective technique in conserving process resources and preventing pollution. The design and environmental constraints may involve a variety of component- and property-based restrictions. To date, most techniques have been developed to handle process constraints which is either composition-based (via mass integration) or property-based. No work has been reported to handle the synthesis of resource conservation network that is governed by both constraints. The objective of this work is to develop a systematic and cost-effective design technique that is aimed at minimizing the consumption of fresh resources and the discharge of pollutants simultaneously. Because of the nature of the component- and property-based constraints, this approach is based on mass and property integration and takes into account the process constraints and also environmental regulations. In this research work, a new approach has been developed to simultaneously address component-based recycle constraints as well as property-based discharge constraints. The proposed optimization technique is intended to minimize the consumption of fresh resources, the pollutant content in the waste streams, and the operational and waste treatment costs. Additionally, a mixed-integer nonlinear programming (MINLP) formulation is solved for a case study of phenol production from cumene hydroperoxyde to illustrate the new problem and devised solution algorithm

Mass Integration for Hazardous Wastewater Reuse with Incorporation of Economic and Safety Objectives

With the development of society and the increasing population, the water crisis has been a severe problem for several regions in the world. Although various water-treatment technologies have been developed, water shortages continue to be on the rise. Due to the limited amount of available freshwater resources, maximizing the utilization of existing water resources has attracted much attention as a viable approach to addressing the water crisis. Among the factors contributing to the improvement of utilizing water, wastewater recycle plays a significant role. Wastewater is generally hazardous due to the presence of various pollutants. Therefore, wastewater reclamation and reuse can offer several economic, environmental, and health benefits. In this study, analysis of the existing water stream network is conducted to develop potential sinks and sources of wastewater recycle. Mass integration is used as an overarching framework for optimizing water treatment and reuse. In addition to techno-economic analysis, assessments on the inherent safety and sustainability of the candidate solutions are conducted to evaluate the proposed wastewater reutilization networks

Simultaneous process and molecular design/selection through property integration

The overall purpose of this work is to develop systematic methodology for the simultaneous design and selection of processes and molecules (materials). A propertybased approach is used to develop an interface between process and molecular design/selection. In particular, we focus on the problem of designing/selecting materials that are used in the context of a recycle/reuse system of process streams and for energy applications. Fresh and recycled resources (e.g., process streams, biomass, solvents, etc.) are integrated with the process to satisfy property-based constraints for the process units and to optimize the usage of the resources and the design of the process. For molecular design, property operators for mixing streams and group contribution methods (GCM) are used to consistently represent process sources, sinks, and different functional groups on the same property-base. For material selection, property based criteria (e.g., heat rate, high heating value, etc.) are used to bridge the process with material. This consistent representation enables the definition of the optimization problem formulation for product design while taking into consideration the recycle/reuse of process streams. In particular, this dissertation addresses four integrated topics. First, a new graphical approach for material targeting and substitution is presented. This graphical approach offers initial solutions and valuable insights that can be effectively used for conceptual design and for initializing mathematical programming techniques. Second, a mathematical optimization approach is developed along with a decomposition-based global solution procedure for material targeting and substitution using property integration. Third, an implementation approach is developed to synthesize the details of a recycle/reuse process network design based on the targets identified through the graphical and/or the mathematical approaches. Finally, property integration techniques are extended to a broader scope which deals with the lifecycle analysis of biomass utilization for energy generation. A generic model is developed to optimize the types and quantities of the feedstocks used to optimize power generation with biomass-fossil fuel co-fed system. Important issues of biomass growth, harvesting, transportation, processing, and disposal are included. Property-based tracking and constraints are included in the analysis. Also, the issues associated with greenhouse gas (GHG) emissions are incorporated in the analysis. Case studies are solved throughout the dissertation to demonstrate the applicability of the developed procedures