Multi-objective analysis of an influence of a geothermal water salinity on optimal operating parameters in low-temperature ORC power plant. (1st July 2020)

• Record Type: Journal Article
• Authors: Jankowski, Marcin; Borsukiewicz, Aleksandra; Wiśniewski, Sławomir; Hooman, Kamel
• Is Part Of: Energy. Volume 202(2020)
• Publication Date: 2020-07-01
• Subjects: ORC -- Multi-objective optimization -- Genetic algorithm -- Geothermal energy; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.117666
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The effects of geothermal brine salinity on optimal operating parameters of an organic Rankine cycle (ORC) power plant are investigated. For a more comprehensive understanding of the problem, a multi-objective optimization study is conducted aiming at minimizing the total heat transfer area while maximizing the exergy efficiency of the ORC. The optimization problem is solved using Non-dominated Sorting Genetic Algorithm-II. The multi-criteria decision making results show that an increase in the salinity (from 0.00 kgkg −1 to 0.12 kgkg −1 ) lowers the total heat transfer area and exergy efficiency by 4.39% (from 82.0 m 2 to 78.4 m 2 ) and 7.72% (from 28.5% to 26.3%), respectively. An adverse impact of the salinity on the exergy efficiency is dominant resulting in higher system size (reaching 8.00%) for obtaining the same exergy efficiency. For the same reason, a lower exergy efficiency (up to 5.00%) is reported for a system with the predefined heat exchangers size. A sensitivity analysis reveals that the salinity influence on the heat transfer area and exergy efficiency is mainly associated with a decrease in the mass flow rate of the working fluid. Moreover, salinity can increase the exergy flow rate of the brine thereby impacting the exergy efficiency. It is concluded that the salinity of the geothermal water should be considered in designing the ORC for a geothermal power plant because of its significant impact on the performance of the system. Highlights: The effects of brine salinity on optimal parameters of ORC are investigated. The total heat transfer area and exergy efficiency are objective functions. The Non-dominated Sorting Genetic Algorithm-II is applied as optimization tool. An increase in salinity lowers the total heat transfer area and exergy efficiency. An increase in salinity results in suboptimal design points of the ORC.