Low-temperature thermal energy(<130°C)recycling and utilization can significantly increase energy efficiency and reduce CO_(2)emissions.Among various technologies for heat-to-electricity conversion,thermally r...Low-temperature thermal energy(<130°C)recycling and utilization can significantly increase energy efficiency and reduce CO_(2)emissions.Among various technologies for heat-to-electricity conversion,thermally regenerative electrochemical cycle(TREC)has garnered significant attention for remarkable efficiency in thermal energy utilization.The thermally regenerative electrochemical cycled flow battery(TREC-FB)in this paper offers several advantages,including continuous power output and operating without an external power supply.The goal of this investigation is to enhance the understanding of how various parameters affect system performance through simulation,thus optimizing cell performance.In this work,based on the conservation equations and electrochemical equations,the two-dimensional steady models coupled with the flow field and electrochemical field of high-temperature cell and low-temperature cell are constructed separately by COMSOL Multiphysics.The diffusion coefficient and kinetic parameters in the model were obtained by cyclic voltammetry(CV),chronoamperometry(CA)and Tafel electrochemical measurements for subsequent application in the models.Experimental results have confirmed the validity of this model.The main focus of this work is to examine how the system performance is impacted by various factors including current density,electrolyte flow rate,temperature coefficient,porous electrode geometry,heat recuperation efficiency,and temperature difference between hot and cold cells.The results indicate that a larger electrolyte flow rate leads to larger power density,but reduces system efficiency.Smaller porous electrode thickness,higher temperature coefficient,higher heat recuperation efficiency and larger temperature difference between the cells can enhance the system performance.This work offers a new guide for further enhancing TREC-FB performance.展开更多
基金the National Natural Science Foundation of China(No.51921004)the National Natural Science Foundation of China(No.52206020)the special support from China Postdoctoral Science Foundation(2021TQ0236).
文摘Low-temperature thermal energy(<130°C)recycling and utilization can significantly increase energy efficiency and reduce CO_(2)emissions.Among various technologies for heat-to-electricity conversion,thermally regenerative electrochemical cycle(TREC)has garnered significant attention for remarkable efficiency in thermal energy utilization.The thermally regenerative electrochemical cycled flow battery(TREC-FB)in this paper offers several advantages,including continuous power output and operating without an external power supply.The goal of this investigation is to enhance the understanding of how various parameters affect system performance through simulation,thus optimizing cell performance.In this work,based on the conservation equations and electrochemical equations,the two-dimensional steady models coupled with the flow field and electrochemical field of high-temperature cell and low-temperature cell are constructed separately by COMSOL Multiphysics.The diffusion coefficient and kinetic parameters in the model were obtained by cyclic voltammetry(CV),chronoamperometry(CA)and Tafel electrochemical measurements for subsequent application in the models.Experimental results have confirmed the validity of this model.The main focus of this work is to examine how the system performance is impacted by various factors including current density,electrolyte flow rate,temperature coefficient,porous electrode geometry,heat recuperation efficiency,and temperature difference between hot and cold cells.The results indicate that a larger electrolyte flow rate leads to larger power density,but reduces system efficiency.Smaller porous electrode thickness,higher temperature coefficient,higher heat recuperation efficiency and larger temperature difference between the cells can enhance the system performance.This work offers a new guide for further enhancing TREC-FB performance.
