Optimizing Solar Energy Harvesting through Integrated Organic Rankine Cycle–Reverse Osmosis Systems: A Techno–Economic Analysis
Lina Wang,
Chunyu Zhou () and
Hamid Reza Rahbari
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Lina Wang: School of Marine Technology and Environment, Dalian Ocean University, Dalian 116023, China
Chunyu Zhou: Information Office, Dalian Ocean University, Dalian 116023, China
Hamid Reza Rahbari: AAU Energy, Aalborg University, 6700 Esbjerg, Denmark
Sustainability, 2023, vol. 15, issue 18, 1-20
Abstract:
When it comes to seawater desalination in the small- to medium-electricity ranges, the organic Rankine cycle (ORC) powered by solar energy stands out as the most energy-efficient technology currently available. Various solar techniques have been developed to capture and absorb solar energy. Among them, the parabolic trough collector (PTC) has gained recognition as a low-cost solar thermal collector with a long operating life. This study investigates the thermodynamic performance and economic parameters of a PTC-powered ORC using Dowtherm A and toluene as working fluids for the solar cycle and ORC cycle, respectively. Thermo-economic multi-objective optimization and decision-making techniques are applied to assess the system’s performance. Four key parameters are analyzed for their impact on exergy efficiency and total hourly cost. Using TOPSIS decision-making, the best solution from the Pareto frontier is identified, featuring an ORC exergy efficiency of 30.39% and a total hourly cost of 39.38 US$/h. The system parameters include a mass flow rate of fresh water at 137.7 m 3 /h, a total output net power of 577.9 kJ/kg, and a district heating supply of 1074 kJ/kg. The cost analysis reveals that the solar collector represents approximately 68% of the total hourly cost at 26.77 US$/h, followed by the turbine, thermoelectric generator, and reverse osmosis (RO) unit.
Keywords: techno–economic optimization; exergy efficiency; ANN; NSGA-II; TOPSIS (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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