Publication

Power-to-methane via co-electrolysis of H2O and CO2: The effects of pressurized operation and internal methanation

Abstract

This paper presents a model-based investigation to handle the fundamental issues for the design of co-electrolysis based power-to-methane at the levels of both the stack and system: the role of CO2 in co-electrolysis, the benefits of employing pressurized stack operation and the conditions of promoting internal methanation. Results show that the electrochemical reaction of co-electrolysis is dominated by H2O splitting while CO2 is converted via reverse water-gas shift reaction. Increasing CO2 feed fraction mainly enlarges the concentration and cathode-activation overpotentials. Internal methanation in the stack can be effectively promoted by pressurized operation under high reactant utilization with low current density and large stack cooling. For the operation of a single stack, methane fraction of dry gas at the cathode outlet can reach as high as 30 vol.% (at 30 bar and high flowrate of sweep gas), which is, unfortunately, not preferred for enhancing system efficiency due to the penalty from the pressurization of sweep gas. The number drops down to 15 vol.% (at 15 bar) to achieve the highest system efficiency (at 0.27 A/cm(2)). The internal methanation can serve as an effective internal heat source to maintain stack temperature (thus enhancing electrochemistry), particularly at a small current density. This enables the co-electrolysis based power-to-methane to.achieve higher efficiency than the steam-electrolysis based (90% vs 86% on higher heating value, or 83% vs 79% on lower heating value without heat and converter losses).

About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.