Modeling and optimization of solar thermal-photovoltaic vacuum membrane distillation system by response surface methodology

Hongling Deng, Xiaohong Yang, Rui Tian, Junhu Hu, Bo Zhang, Fangda Cui, Guangyu Guo

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Response surface methodology is used in this study to model and optimize a solar thermal-photovoltaic vacuum membrane distillation (STPVMD) system with PVDF hollow fiber membrane. Regression models have been developed to forecast the effect of various operation factors on the permeate flux and the energy consumption. The operation factors in the model include the feed inlet temperature, the feed flow rate and the vacuum pressure. Analysis of variance is used to statistically validate the regression models. With permeate flux as the objective function of optimization, the optimal operation parameters are found to be 63 °C for the feed inlet temperature, 237 L/h for the feed flow rate, and 750 kPa for the vacuum pressure. Experimental tests show that the resulting permeate flux is 6.26 L/m2·h, which is slightly higher than the predicted value of 6.05 L/m2·h. The corresponding energy consumption is predicted to be 12.52L/kW·h, demonstrating the effectiveness and reliability of the models.

Original languageEnglish (US)
Pages (from-to)230-238
Number of pages9
JournalSolar Energy
Volume195
DOIs
StatePublished - Jan 1 2020

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Materials Science(all)

Keywords

  • Energy consumption
  • Membrane distillation
  • Permeate flux
  • Regression models
  • Response surface methodology
  • Solar thermal-photovoltaic system

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