A framework for the design of battery energy storage systems in Power-to-X processes

Energy storage has become increasingly crucial as more industrial processes rely on renewable power inputs to achieve decarbonization targets and meet stringent environmental standards. Storage systems are essential for mitigating the fluctuations in plant operations that result from the discontinuity of renewables, allowing for a smooth reconciliation of renewable power with the steadiness of the process. This paper introduces a general and systematic framework, qualifying as a self-consistent analytical tool rather than a competitive alternative to traditional optimization techniques, to identify the optimal delivery policies minimizing the capacity of battery energy storage systems in Power-to-X processes. Specifically, we propose an optimal supply schedule that converts the arbitrarily fluctuating electric power availability from renewable sources into an optimally fluctuating electric power output. This way, the required storage capacity is minimized while concurrently meeting various operating requirements, such as ramping rates and load flexibility constraints. The main novelty of this framework lies in its numerically explicit formulation, which requires little effort to be implemented and a short computational time to be run, making it a handy shortcut method for designing battery storage systems. Finally, the framework's effectiveness is validated through a case study involving the design optimization of a renewable-powered industrial facility for green hydrogen production: precisely, the optimal configuration attains a levelized cost of hydrogen equal to 2.92 USD/kg, featuring solar and wind installed capacities of 50 MW and 150 MW, respectively; an electrolyzer capacity of 69.88 MW; and an electricity storage capacity of 28.20 MWh (California, 2023).