Energy, Exergy, and Exergoeconomic Analysis of Solar Thermal Power Plant Hybrid with Designed PCM Storage

被引:21
作者
Fani, Maryam [1 ]
Norouzi, Nima [1 ]
Ramezani, Molood [2 ]
机构
[1] Amirkabir Univ Technol, Energy Engn & Phys Dept, Tehran Polytech, 424 Hafez Ave Tehran, Tehran 158754413, Iran
[2] Islamic Azad Univ Shahroud, Engn Dept, Shahrud, Iran
关键词
Parabolic trough; phase change material; exergy; exergoeconomic; genetic algorithm; PHASE-CHANGE MATERIALS; SYSTEM; OPTIMIZATION; PERFORMANCE; CONDUCTIVITY; METHODOLOGY; COST;
D O I
10.1142/S2010132520500303
中图分类号
O414.1 [热力学];
学科分类号
摘要
The tendency of renewable energies is one of the consequences of changing attitudes towards global energy issues. As a result, solar energy, which is the leader among renewable energies based on availability and potential, plays a crucial role in thoroughly filing global needs. Significant problems with the solar thermal power plants (STPP) are the operation time, which is limited by daylight and is approximately half of the power plants with fossil fuels, and the capital cost. In the present study, a new suggested sketch of adding latent heat storage (LHS) filled with commercial phase change material (PCM) to a 500-kW STPP case study has been investigated. Solar system details and irradiation amounts for a case study, including total and beam radiation have been determined. Also, the theoretical energetic and exergetic analysis of adding PCM storage to STTP is conducted, which showed a 19% improvement in the exergetic efficiency of the power plant to reach 30%. Besides, an optimized storage tank and appropriate PCM material have been investigated and selected concerning the practical limitations of the case study. By designing a new cycle, the LHS will be charged during daylight and will be discharged at night, doubling power plant operation time up to 2500 h. Finally, exergoeconomic survey of STPP hybrid with PCM storage was carried out using Engineering Equation Solver (EES) program with genetic algorithm (GA) for three different scenarios, based on eight decision variables, which led us to decrease final product cost (electricity) in optimized scenario up to 30% compared to base case scenario from 28.99 to 20.27 $/kWh for the case study. Also, a comparison is made to demonstrate the effectiveness of the proposed new cycle on 250, 500, 1000, and 2000 kW STTPs.
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页数:14
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