期刊
RENEWABLE ENERGY
卷 183, 期 -, 页码 283-293出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.renene.2021.10.089
关键词
Salinity gradient energy; Capacitance mixing; Capacitive salinity; heat engine; Thermodynamic analysis; Performance evaluation; Parametric optimization
资金
- National Natural Science Foundation of China [51876181]
- Science and Technology Planning Projects of Fujian Province, China [2018H0036]
A novel cycle model of the capacitive salinity/heat engine using nano-porous super-capacitors has been established, showing significantly higher energy conversion efficiency compared to traditional capacitive heat engines. By optimizing the temperature of the heat reservoir and the salt concentration of seawater, the efficiency of the engine is improved, providing potential for reducing fossil fuel consumption in real-life applications.
A novel cycle model of the capacitive salinity/heat engine mainly consisting of nano-porous super -capacitors is established for harvesting mixed free energy caused by salinity difference between the river water and the seawater, and the thermal energy due to the temperature difference. The heat engine is charged and discharged in the cycle of a low temperature brine and a high temperature fresh water, respectively. The analytical expressions of the cyclic work output and efficiency are given. General performance characteristics of the capacitive salinity/heat engine are analyzed. The temperature of the heat reservoir and salt concentration of seawater are optimized to improve the efficiency of the capacitive salinity/heat engine. The optimal selection ranges of several main parameters are provided. When the Stern distance is equal to 1 nm and the charging voltage is equal to 3.5V, the energy conversion efficiency of the capacitive salinity/heat engine is about 40%, while the pure thermal efficiency in the cycle is about 16.9%. The energy conversion efficiency of the capacitive salinity/heat engine is signifi-cantly larger than that of the capacitive heat engine. The results obtained can facilitate the application of this technology to real life, which can reduce the consumption of fossil fuels. (c) 2021 Elsevier Ltd. All rights reserved.
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