Abstract:
The digital twin which supports data-based decision making, optimization, control and anomaly detection and diagnosis, can contribute to the improvement of sustainability, agility and productivity in water electrolysis system, which is expected to provide to reduce green hydrogen production cost. In this study, we propose a digital twin for a 500kW alkaline water electrolysis (AWE) to be built at the Saemangeum Renewable Energy National Demonstration Complex in Korea to reduce green hydrogen production cost through optimal operation of AWE system. A simulation model, which is the basis of the digital twin, was developed with Python and gPROMS, and the system efficiency of the AWE process according to pressure was analyzed comparing between excluding the compression process and including the process of hydrogen compression to 200 bar. The optimum operating pressure with the compression showed at 10-30 bar. At high pressure, process equipment cost becomes higher, therefore, it is essential to consider hydrogen compression to the storage pressure in order to decide the optimal operating conditions. Β© 2022 Elsevier B.V.
