Analysis of Electrochemical Ammonia Production Rate via Smoothing Filters for Solar Energy Storage

Solar power is a widely used renewable energy technology that is going to play a key role in the clean energy transition. To address the solar power intermittency problem, battery energy storage systems are integrated into the grid such that the excess photovoltaic energy can be stored for later use. However, batteries suffer from energy degradation and therefore storing energy in the form of a chemical fuel helps in overcoming this challenge. Energy storage in the form of hydrogen is an option, but hydrogen is linked with high flammability, poor volumetric density, and high storage costs. Alternatively, ammonia addresses several issues associated with hydrogen. Excess solar energy can be stored in the form of ammonia via the direct electrochemical ammonia synthesizer (EAS). Accordingly, it is crucial to assess the ammonia production requirements as it directly determines the EAS capacity requirements and the overall system costs. Additionally, there is a loss of efficiency with an increase in ammonia production. This study proposes the utilization of power smoothing filters to assess the ammonia production rates of the EAS as well as the nitrogen and hydrogen input requirements. Sliding window filters such as the moving average, moving mean, and moving regression (MR) filters have been utilized to determine the excess solar power available for ammonia production. Simulation results conclude that the power tracking capability of the smoothing filters has a direct impact on the EAS ammonia production rates. Overall, the MR filter has superior power tracking thereby resulting in lower EAS capacity requirements and thus reduced system costs.