Integrated Approaches to Optimal Multi-Period Desalination Synthesis Involving Water-Energy Nexus

This work develops novel tools for the multi-period and multiscale synthesis of water desalination systems for systematically optimizing the benefits of the integration of emerging desalination technologies and the water-energy nexus. The research develops the optimization frameworks for the following problems: (1) optimization of multi-effect distillation (MED) design via MD brine treatment and process heat integration, (2) synthesis of desalination systems for multi-period capacity planning, and (3) synthesis and scheduling of solar-assisted membrane distillation (MD) for domestic water desalination. To solve the three problems, the water-energy nexus must be addressed in the planning, design, and operation of the water desalination system. In the first problem, an optimization approach to the design of MED-MD in the context of water-energy nexus with an industrial process is developed. The hybrid MED-MD desalination system is thermally integrated with industrial facility while any additional required thermal energy is supplied from external sources. The optimization framework targets optimizing the operating and design variables of the MED and MD units as well as the excess heat extracted from the industrial facility. In the second problem, an optimization approach was used to identify the optimal capacity planning of distressed water desalination systems considering the integration of emerging desalination technologies. Despite the economic challenges many emerging technologies face, some new desalination technologies such as MD demonstrate promising candidacy in the optimal expansion of desalination systems due to their modularity and other advantages. The developed framework also addresses the multiscale nature of the problem. Unit-specific decision variables such as the top brine temperature (TBT) and MD recycle ratio are simultaneously optimized with the synthesis of the multi-period flowsheet. In the third problem, a systematic approach for the design and scheduling of a skid-mounted solar-assisted membrane distillation system is developed. The problem targets domestic water demand in remote areas that are not supported by fresh water infrastructure. The proposed system consists of both thermal and photovoltaic (PV) solar systems to provide the energy required for desalination and system’s equipment. Storage tanks are used to collect thermal energy and to supply the feed to the MD system while PV cells are connected to electric-energy storage batteries to drive the pumping. Conventional fossil fuel is used to supplement the solar thermal energy as needed. The aim of the optimization framework is to determine the number and size of the storage tanks, the operating variables, the collection and dispatch times, the extent of solar and fossil-energy uses, and the operating schedule for the integrated system. The merits of the developed frameworks are illustrated in three distinct case studies with clear focus on MD as an example of emerging technologies integrated with conventional technologies. In all the three case studies, MD desalination as a standalone solution was suboptimal when compared to conventional desalination technologies. However, with the introduction of water-energy nexus with adjacent processing facilities and solar thermal heating, interesting results evolved with MD as a constituent of the global optimum. In addition, emerging technologies have shown economic merits when utilized at the end of the planning horizon in expanding systems, due to its modularity

Integrated Approaches to Optimal Multi-Period Desalination Synthesis Involving Water-Energy Nexus

This work develops novel tools for the multi-period and multiscale synthesis of water desalination systems for systematically optimizing the benefits of the integration of emerging desalination technologies and the water-energy nexus. The research develops the optimization frameworks for the following problems: (1) optimization of multi-effect distillation (MED) design via MD brine treatment and process heat integration, (2) synthesis of desalination systems for multi-period capacity planning, and (3) synthesis and scheduling of solar-assisted membrane distillation (MD) for domestic water desalination. To solve the three problems, the water-energy nexus must be addressed in the planning, design, and operation of the water desalination system. In the first problem, an optimization approach to the design of MED-MD in the context of water-energy nexus with an industrial process is developed. The hybrid MED-MD desalination system is thermally integrated with industrial facility while any additional required thermal energy is supplied from external sources. The optimization framework targets optimizing the operating and design variables of the MED and MD units as well as the excess heat extracted from the industrial facility. In the second problem, an optimization approach was used to identify the optimal capacity planning of distressed water desalination systems considering the integration of emerging desalination technologies. Despite the economic challenges many emerging technologies face, some new desalination technologies such as MD demonstrate promising candidacy in the optimal expansion of desalination systems due to their modularity and other advantages. The developed framework also addresses the multiscale nature of the problem. Unit-specific decision variables such as the top brine temperature (TBT) and MD recycle ratio are simultaneously optimized with the synthesis of the multi-period flowsheet. In the third problem, a systematic approach for the design and scheduling of a skid-mounted solar-assisted membrane distillation system is developed. The problem targets domestic water demand in remote areas that are not supported by fresh water infrastructure. The proposed system consists of both thermal and photovoltaic (PV) solar systems to provide the energy required for desalination and system’s equipment. Storage tanks are used to collect thermal energy and to supply the feed to the MD system while PV cells are connected to electric-energy storage batteries to drive the pumping. Conventional fossil fuel is used to supplement the solar thermal energy as needed. The aim of the optimization framework is to determine the number and size of the storage tanks, the operating variables, the collection and dispatch times, the extent of solar and fossil-energy uses, and the operating schedule for the integrated system. The merits of the developed frameworks are illustrated in three distinct case studies with clear focus on MD as an example of emerging technologies integrated with conventional technologies. In all the three case studies, MD desalination as a standalone solution was suboptimal when compared to conventional desalination technologies. However, with the introduction of water-energy nexus with adjacent processing facilities and solar thermal heating, interesting results evolved with MD as a constituent of the global optimum. In addition, emerging technologies have shown economic merits when utilized at the end of the planning horizon in expanding systems, due to its modularity

Optimal Multiscale Capacity Planning in Seawater Desalination Systems

The increasing demands for water and the dwindling resources of fresh water create a critical need for continually enhancing desalination capacities. This poses a challenge in distressed desalination network, with incessant water demand growth as the conventional approach of undertaking large expansion projects can lead to low utilization and, hence, low capital productivity. In addition to the option of retrofitting existing desalination units or installing additional grassroots units, there is an opportunity to include emerging modular desalination technologies. This paper develops the optimization framework for the capacity planning in distressed desalination networks considering the integration of conventional plants and emerging modular technologies, such as membrane distillation (MD), as a viable option for capacity expansion. The developed framework addresses the multiscale nature of the synthesis problem, as unit-specific decision variables are subject to optimization, as well as the multiperiod capacity planning of the system. A superstructure representation and optimization formulation are introduced to simultaneously optimize the staging and sizing of desalination units, as well as design and operating variables in the desalination network over a planning horizon. Additionally, a special case for multiperiod capacity planning in multiple effect distillation (MED) desalination systems is presented. An optimization approach is proposed to solve the mixed-integer nonlinear programming (MINLP) optimization problem, starting with the construction of a project-window interval, pre-optimization screening, modeling of screened configurations, intra-process design variables optimization, and finally, multiperiod flowsheet synthesis. A case study is solved to illustrate the usefulness of the proposed approach

Antenatal care packages with reduced visits and perinatal mortality: a secondary analysis of the WHO Antenatal Care Trial

BACKGROUND: In 2001, the WHO Antenatal Care Trial (WHOACT) concluded that an antenatal care package of evidence-based screening, therapeutic interventions and education across four antenatal visits for low-risk women was not inferior to standard antenatal care and may reduce cost. However, an updated Cochrane review in 2010 identified an increased risk of perinatal mortality of borderline statistical significance in three cluster-randomized trials (including the WHOACT) in developing countries. We conducted a secondary analysis of the WHOACT data to determine the relationship between the reduced visits, goal-oriented antenatal care package and perinatal mortality. METHODS: Exploratory analyses were conducted to assess the effect of baseline risk and timing of perinatal death. Women were stratified by baseline risk to assess differences between intervention and control groups. We used linear modeling and Poisson regression to determine the relative risk of fetal death, neonatal death and perinatal mortality by gestational age. RESULTS: 12,568 women attended the 27 intervention clinics and 11,958 women attended the 26 control clinics. 6,160 women were high risk and 18,365 women were low risk. There were 161 fetal deaths (1.4%) in the intervention group compared to 119 fetal deaths in the control group (1.1%) with an increased overall adjusted relative risk of fetal death (Adjusted RR 1.27; 95% CI 1.03, 1.58). This was attributable to an increased relative risk of fetal death between 32 and 36 weeks of gestation (Adjusted RR 2.24; 95% CI 1.42, 3.53) which was statistically significant for high and low risk groups. CONCLUSION: It is plausible the increased risk of fetal death between 32 and 36 weeks gestation could be due to reduced number of visits, however heterogeneity in study populations or differences in quality of care and timing of visits could also be playing a role. Monitoring maternal, fetal and neonatal outcomes when implementing antenatal care protocols is essential. Implementing reduced visit antenatal care packages demands careful monitoring of maternal and perinatal outcomes, especially fetal death