Flexibility analyses and their applications in solar-driven membrane distillation desalination system designs

Vincentius Surya Kurnia Adi, Chuei-Tin Chang

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Owing to the rapidly growing world population and the alarming effects of global warming, there appears to be an ever-increasing demand for freshwater almost everywhere. For this reason, considerable effort has been devoted in recent years to develop an efficient and sustainable desalination technology. Among various alternatives, the air gap membrane distillation (AGMD) is widely considered as a promising candidate since the energy consumed per unit of water generated by this method is the lowest (Cabassud and Wirth, 2003; Ben Bacha et al., 2007; Bui et al., 2010). Many researchers have already constructed rigorous mathematical models to simulate and analyze the underlying transport phenomena so as to identify the key variables affecting the water flux in an AGMD module (Koschikowski et al., 2003; Meindersma et al., 2006; Ben Bacha et al., 2007; Chang et al., 2010). Particularly, Ben Bacha et al. (2007) and Chang et al. (2010, 2012) have built models of all units embedded in a solar-driven membrane distillation desalination system (SMDDS), that is, (1) the solar absorber, (2) the thermal storage tank, (3) the counter-flow shell-and-tube heat exchanger, (4) the AGMD modules, and (5) the distillate tank, and then discussed various operational and control issues accordingly. The process flow diagram of a typical SMDDS design can be found in Figure 10.1. Gálvez et al. (2009) meanwhile designed a 50 m3/day desalination setup with an innovative solar-powered membrane, and Guillen-Burrieza et al. (2011) also assembled a solar-driven AGMD pilot plant. These two studies were performed with the common goal of minimizing energy consumption per unit of distillate produced. Note that SMDDS should be operated in batch mode since the solar energy can only be supplied intermittently and periodically. Furthermore, the freshwater demand of SMDDS is assumed to be time variant, thus the traditional continuous operation is almost out of the question in this study.

Original languageEnglish
Title of host publicationSynthesis, Design, and Resource Optimization in Batch Chemical Plants
PublisherCRC Press
Pages233-263
Number of pages31
ISBN (Electronic)9781482252422
ISBN (Print)9781138893306
DOIs
Publication statusPublished - 2015 Jan 1

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Desalination
Distillation
Systems analysis
Membranes
Air
Solar absorbers
Water
Tubes (components)
Global warming
Pilot plants
Solar energy
Energy utilization
Mathematical models
Fluxes

All Science Journal Classification (ASJC) codes

  • Chemistry(all)
  • Chemical Engineering(all)
  • Engineering(all)

Cite this

Adi, V. S. K., & Chang, C-T. (2015). Flexibility analyses and their applications in solar-driven membrane distillation desalination system designs. In Synthesis, Design, and Resource Optimization in Batch Chemical Plants (pp. 233-263). CRC Press. https://doi.org/10.1201/b18200
Adi, Vincentius Surya Kurnia ; Chang, Chuei-Tin. / Flexibility analyses and their applications in solar-driven membrane distillation desalination system designs. Synthesis, Design, and Resource Optimization in Batch Chemical Plants. CRC Press, 2015. pp. 233-263
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Adi, VSK & Chang, C-T 2015, Flexibility analyses and their applications in solar-driven membrane distillation desalination system designs. in Synthesis, Design, and Resource Optimization in Batch Chemical Plants. CRC Press, pp. 233-263. https://doi.org/10.1201/b18200

Flexibility analyses and their applications in solar-driven membrane distillation desalination system designs. / Adi, Vincentius Surya Kurnia; Chang, Chuei-Tin.

Synthesis, Design, and Resource Optimization in Batch Chemical Plants. CRC Press, 2015. p. 233-263.

Research output: Chapter in Book/Report/Conference proceedingChapter

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Adi VSK, Chang C-T. Flexibility analyses and their applications in solar-driven membrane distillation desalination system designs. In Synthesis, Design, and Resource Optimization in Batch Chemical Plants. CRC Press. 2015. p. 233-263 https://doi.org/10.1201/b18200