Optimal sizing of a standalone renewable energy reverse osmosis desalination system using an ant system

Daming Xu, Thomas L. Acker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

The purpose of this work was to find the optimal configuration for an off-grid, renewable energy reverse osmosis (RO) desalination system using an ant system (AS), where the objective was to find the lowest annualized cost of the renewable energy system. This nonlinear integer programming was transferred to finding the shortest route on the construction graph by artificial ants. A well on the Navajo Nation in Arizona, USA was selected as the candidate site and real-world data were used. The capacity of the RO system was 18.93 m^{3}/d (5000\ gal/d), requiring a constant power consumption of 3.95 kW. The results of the AS optimization showed that the optimal configuration with the smallest annualized cost of the renewable energy system was a hybrid wind/photovoltaic/battery system, although a diesel generator was a candidate. The cost of energy was 0.46 USD/ kWh and cost of water was 3.35 USD/m^{3}, which was less than half of the 7.9 USD/m^{3} currently paid by residents that live in the area.

Original languageEnglish (US)
Title of host publication2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728169293
DOIs
StatePublished - Jul 2020
Event2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Virtual, Glasgow, United Kingdom
Duration: Jul 19 2020Jul 24 2020

Publication series

Name2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings

Conference

Conference2020 IEEE Congress on Evolutionary Computation, CEC 2020
Country/TerritoryUnited Kingdom
CityVirtual, Glasgow
Period7/19/207/24/20

Keywords

  • ant colony optimization
  • brackish water desalination
  • optimal sizing
  • renewable energy
  • reverse osmosis

ASJC Scopus subject areas

  • Control and Optimization
  • Decision Sciences (miscellaneous)
  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture

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