Optimal sizing of an off-grid, renewable energy reverse osmosis desalination system based on a genetic algorithm

Daming Xu, Tom Acker

Research output: Contribution to journalArticle

Abstract

The purpose of this work was to find the optimal configuration for an off-grid, renewable energy reverse osmosis desalination (RO) system. The objective was to find the lowest levelized cost of energy (LCOE), with power reliability as the constraint. A genetic algorithm was used to solve the nonlinear integer programming problem. A site with brackish groundwater in Arizona, USA, was selected. The capacity of the RO system was 11.36 m3/d (3,000 gal/d), requiring a constant power consumption of 2.366 kW. The results showed that the optimal configuration was a hybrid photovoltaic/ wind/diesel/battery system with LCOE 0.527 USD/kWh and the corresponding levelized cost of water 3.585 USD/m3, which were about half of the 7.9 USD/m3 currently paid by residents in the area. Sensitivity analyses showed that: (a) the LCOE was fairly insensitive to photovoltaic panel tilt angle over a range; (b) the optimal tilt angle for the hybrid system must be found in the context of the performance of the entire system; (c) the “more hybrid” the renewable energy system, the lower the LCOE; (d) the LCOE value was monotone increasing as diesel price or discount rate increasing, respectively, and different diesel price or discount rate could bring different optimal configurations with diesel generators.

Original languageEnglish (US)
Pages (from-to)67-82
Number of pages16
JournalDesalination and Water Treatment
Volume163
DOIs
StatePublished - Sep 2019

Fingerprint

Reverse osmosis
Desalination
genetic algorithm
desalination
Genetic algorithms
diesel
energy
Costs
cost
discount rate
tilt
Integer programming
Hybrid systems
sizing
reverse osmosis
Groundwater
Electric power utilization
groundwater
Water

Keywords

  • Brackish water desalination
  • Genetic algorithm
  • Optimal sizing
  • Renewable energy
  • Reverse osmosis

ASJC Scopus subject areas

  • Water Science and Technology
  • Ocean Engineering
  • Pollution

Cite this

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