System-Level Optimisation of Combined Power and Desalting Plants

Houd Al-Obaidli, S. Namany, Rajesh Govindan, T. Al-Ansari

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

10 Citations (Scopus)

Abstract

Nations in the Gulf Cooperation Council (GCC) utilise their vast oil and natural gas resources in order to satisfy the demand for water and power, which continues to increase due to population and economic growth. The abundance in fossil fuels and relatively low O&M costs make fuel-based technologies a de-facto choice when planning new power or desalting facilities which are proven to have the lowest levelized cost compared to other alternatives. However, energy intensive desalination systems have contributed to high greenhouse gas (GHG) emissions and increased costs. Recently, several facilities have been designed to include renewable energy in order to mitigate GHG emissions and improve the overall environmental welfare. This study evaluates different power and desalting configurations using both fossil-based and renewable energy sources to determine an optimal configuration that minimises CO2 emissions at a relatively low levelized cost. Using the current utilities infrastructure in Qatar as a basis, six configurations were devised where three of them mimic current configurations and three were proposed. The technologies selected were limited to existing configurations: open cycle gas turbine (OCGT), combined cycle gas turbine (CCGT), multi-stage flash (MSF), and seawater reverse osmosis (SWRO), and three renewable technologies concentrated solar power (CSP), solar PV, and biomass integrated gasification combined cycle (BIGCC). At a system-level, optimisation of levelized costs vs global warming potential (GWP) was conducted using a stochastic programming framework. The findings conclude that current configurations are suboptimal and the infusion of renewable energy sources (RES) into the combined power and desalting plant (CPDP) infrastructure significantly improves CO2 emissions with a reduction ranging between 52% and 67% and overall system levelized cost decrease between 8% and 32%.

Original languageEnglish
Title of host publicationComputer Aided Chemical Engineering
PublisherElsevier B.V.
Pages1699-1704
Number of pages6
DOIs
Publication statusPublished - 2019

Publication series

NameComputer Aided Chemical Engineering
Volume46
ISSN (Print)1570-7946

Keywords

  • Portfolio optimisation
  • environmental impact
  • levelized costs
  • renewable energy
  • stochastic processes

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