Power cycles for waste heat recovery from medium to high temperature flue gas sources – from a view of thermodynamic optimization

Chengyu Li and Huaixin Wang

Applied Energy, 2016, vol. 180, issue C, 707-721

Abstract: Large quantities of waste heat generated during industrial production offer an opportunity for waste heat recovery (WHR). Several case studies are selected using flue gas as heat source, which are representative of a fairly wide range of source temperature (200–700°C). The objective function of WHR refers to maximization of net power output. With a view to seeking an optimal combination of cycle configuration, fluid and cycle parameters under different heat source condition, the following researches have been performed. Different types of power cycles (e.g., Rankine cycle, transcritical cycle and combined cycle) as well as different cycle configurations (e.g., saturated or superheating, with or without regenerator) are evaluated. In order to compensate the defects of conventional cycles in some case studies, a novel improved transcritical CO2 cycle and two combined cycle designs are presented. Working fluid selection among the organics is performed. After the parametric optimization, comparison and analysis are carried out among different cycles. Results indicate that the regenerative organic transcritical cycle produces the maximum power output at source temperatures up to about 500°C, and different optimum working fluids are obtained under different heat source temperature. The improved transcritical CO2 cycle shows satisfying performance in source temperature range of 500–600°C. One combined cycle produces the largest work at source temperature above 600°C. The traditional steam Rankine cycle shows bad performance at source temperature below 500°C due to its bad thermal matching with sensible source. At source temperature of 700°C, steam Rankine cycle shows satisfying performance, and produces a power output close to that of the combined cycle.

Keywords: Waste heat recovery; Cycle design; Working fluid selection; Parametric optimization (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (16)

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DOI: 10.1016/j.apenergy.2016.08.007

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