Transactions on Machine Intelligence

Transactions on Machine Intelligence

Economic Analysis of Off-Grid Reverse Osmosis Desalination: A Case Study in Chabahar, Iran

Document Type : Original Article

Authors
S. Rasi Ershadi 1
R. Miremadi 2
H. Shayanfar 1
1 Department of Electrical Engineering, Iran University of Science And Technology, Tehran, Iran
2 Department of Mechanical Engineering, Shahid Beheshti University, Tehran, Iran
10.47176/TMI.2018.31
Abstract
Accessing fresh water in Chabahar, Iran’s only oceanic port, poses significant challenges due to both geographic and infrastructural constraints. Situated along the Gulf of Oman, Chabahar faces acute water scarcity, making the deployment of a water desalination system an attractive and necessary solution to meet the city’s growing water demands. Among available technologies, reverse osmosis (RO) desalination stands out as an efficient and widely adopted method for seawater purification. However, the successful implementation of such a system requires careful consideration of its power supply, especially given the lack of a reliable local power infrastructure. This paper presents a comprehensive techno-economic analysis of an RO water desalination system tailored for Chabahar’s unique conditions. To address the energy needs, various distributed generation (DG) options are evaluated to ensure continuous and cost-effective electrical supply to the desalination units. System design and optimal component sizing are conducted using the HOMER software, which allows for detailed modeling under different operational scenarios. The technical findings are then integrated into a financial analysis using COMFAR software, enabling assessment of investment feasibility, operating costs, and long-term sustainability. Notably, real-world regional data are incorporated throughout the analysis to enhance the study’s practical relevance and applicability, offering valuable insights for policymakers and planners.
Keywords
COMFAR
Diesel generator
HOMER
Photovoltaic
Reverse osmosis
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Transactions on Machine Intelligence
Volume 1, Issue 1
Winter 2018
Pages 31-38

  • Receive Date 09 January 2022
  • Revise Date 15 February 2022
  • Accept Date 09 March 2022