Design and Operation of PEM-Electrolyzers Considering Cost and Efficiency

Abstract

The design and operation of electrolyzers are always a trade-off between parameters that contrarily affect performance and operational goals. This talk will discuss some of those.Compression of the product gases within an electrochemical process is often discussed as an alternative to subsequent mechanical compression. On the one hand, the electrochemical compression is advantageous in terms of energy efficiency; on the other hand, elevated gas pressure is responsible for increased gas loss due to permeation across the membrane. This can be prevented by using thicker membranes; in return, it impairs the proton transport in the electrolyzer and ultimately reduces its performance. It is therefore advisable to discuss an energetically sensible gas pressure level. As gas permeation is a crucial impact on this trade-off, it needs to be discussed how it is affected through operating conditions. Aside from the gas pressure difference between anode and cathode, the diffusion rate increases exponentially with temperature. However, lowering the stack temperature diminishes the electrochemical reaction kinetics as well as the ion conductivity of the ionomer. Hence, the influence of gas pressure, stack temperature and polarization curves on the plant efficiency are inextricably linked. Simulation results indicate that the energetically optimal design and operating conditions are functions of the applied cell voltage. As the design of the electrolysis plant is determined by its installation, only the operating conditions can be chosen flexibly. Economically, investment costs are best allocated to the cost of hydrogen when using high current density in order to have a high production capacity. On the contrary, a high current density also means a high cell voltage, which in turn results in a low plant efficiency and is responsible for high operating costs. Considering all these effects, the complexity of dependencies between parameters will be illustrated in this talk and how modeling can be used to access them. The results will outline challenges as well as directions how the technology can be further developed in future. Figure 1