Towards upscaling the Battolyser- An Integrated Ni-Fe Alkaline Battery and Electrolyser: A combined modeling and experimental study

Electrochemical cells and systems have been around for a few centuries. Lately, these technologies have been attracting attention. Although the technology to generate electricity from renewable sources is well developed and widely available -such as photovoltaic and wind energy- this is not always available. Because of this, it is necessary to store produced surplus electricity to be able to use it at moments when the sun is not shining or the wind is not blowing. Many different electrochemical technologies can be used to store electricity or transform it to a useful energy carrier- such as hydrogen. However, the energy transition will also need to address the optimal usage of critical materials. Integrating functionalities and optimizing energy storage can help bridge the gap between electricity production and consumption using only a limited amount of critical materials. New innovative technologies that use less critical materials will be key to sustainably transition to a fossil-fuel free future. It will be necessary to move forward and upscale technologies at a quick pace. A combined modeling and experimental approach can help move through the TRL development stages quickly, optimizing the use of resources and experimental work required. The battolyser is a new integrated battery and electrolyser system that provides flexibility in energy storage. During periods of high availability of renewable energy it can be charged indefinitely, filling up the battery capacity first and producing hydrogen from there on out. A battolyser system can be used to guarantee access to cheap electricity and green hydrogen, all in one device and using the materials required for one device. Modeling the electrochemical reactions of the battolyser and optimizing the cell design parameters when moving towards an upscaled system is a tool that can be used for the continuous development of a better prototype and scaling up. Chapter 3 describes the modeling studies performed on the battolyser system, including the relevant experimental validation. Here, a 1D COMSOL model was developed to study the cell parameters and understand the effect of electrode and gap thickness, electrode porosity, and electrolyte conductivity. Testing experimentally at larger scales is challenging and often not done. Highly alkaline KOH electrolytes are usually not tested in lab conditions, and therefore the effect of higher concentrations than 5M KOH is unknown on new electrode material developments. To optimize an integrated device, the effect on both the electrolysis function and the battery function need to be reconciled and designed for the specific application. In Chapter 4, extensive lab scale experiments on the electrolyte concentration are described, including different alkali metal cation concentrations. To optimize for different functionalities of the battolyser, different cations can be used at specific concentrations. A flow cell was designed and built, and different flow configurations were tested. 3D printing technology allows for quick iterations and modifications of the design, however the proprietary resins are usually not tested at highly alkaline conditions which could potentially cause degradation of the cell components. Working with higher than 5MKOH concentrations results in practical difficulties that will only scale with plant capacity. In Chapter 5, the preliminary results of a flow cell configuration are included. The results of this work can be applied directly to predict the optimal design and operating parameters of an up-scaled battolyser cell. This will allow for quicker iterations of up-scaled designs to further develop the prototype technology. For this, it is important to verify simulation results with experimental data. Using a combined approach including simulations and experimental work allows testing various setups and optimizing the energetic efficiency of the device. 3D printing manufacturing technology can also help speed up this iterative process to generate design modifications and quickly manufacture experimental setups to validate the simulation data.