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Energy Efficiency and Performance Limiting Effects in Thermo-Osmotic Energy Conversion from Low-Grade Heat

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journal contribution
posted on 12.10.2017, 00:00 by Anthony P. Straub, Menachem Elimelech
Low-grade heat energy from sources below 100 °C is available in massive quantities around the world, but cannot be converted to electricity effectively using existing technologies due to variability in the heat output and the small temperature difference between the source and environment. The recently developed thermo-osmotic energy conversion (TOEC) process has the potential to harvest energy from low-grade heat sources by using a temperature difference to create a pressurized liquid flux across a membrane, which can be converted to mechanical work via a turbine. In this study, we perform the first analysis of energy efficiency and the expected performance of the TOEC technology, focusing on systems utilizing hydrophobic porous vapor-gap membranes and water as a working fluid. We begin by developing a framework to analyze realistic mass and heat transport in the process, probing the impact of various membrane parameters and system operating conditions. Our analysis reveals that an optimized system can achieve heat-to-electricity energy conversion efficiencies up to 4.1% (34% of the Carnot efficiency) with hot and cold working temperatures of 60 and 20 °C, respectively, and an operating pressure of 5 MPa (50 bar). Lower energy efficiencies, however, will occur in systems operating with high power densities (>5 W/m2) and with finite-sized heat exchangers. We identify that the most important membrane properties for achieving high performance are an asymmetric pore structure, high pressure resistance, a high porosity, and a thickness of 30 to 100 μm. We also quantify the benefits in performance from utilizing deaerated water streams, strong hydrodynamic mixing in the membrane module, and high heat exchanger efficiencies. Overall, our study demonstrates the promise of full-scale TOEC systems to extract energy from low-grade heat and identifies key factors for performance optimization moving forward.

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