Modeling alkaline water electrolysis for power-to-x applications: A scheduling approach

The flexible operation of alkaline water electrolyzers enables power-to-x plants to react efficiently to different energy scenarios. In this work, a novel scheduling model for alkaline water electrolysis is formulated as a mixed-integer linear program. The model is constructed by implementing operational states (production, standby, idle) and transitions (cold/full startup, shutdown) as integer variables, while the power loading and hydrogen flowrate are set as continuous variables. The operational characteristics (load range, startup time, ramp rates) are included as model constraints. The proposed model allows finding optimal number of electrolyzers and production schedules when dealing with large data sets of intermittent energy and electricity price. The optimal solution of the case study shows a balance between hydrogen production, energy absorption, and operation and investment costs. The optimal number of electrolyzers to be installed corresponds to 54% of the ones required to absorb the highest energy peak, being capable of loading 89.7% of the available energy during the year of operation, with an overall plant utilization of 93.7% and 764 startup/shutdown cycles evenly distributed among the units. (c) 2020 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

Automated summary

A novel scheduling model for alkaline water electrolysis is formulated as a mixed-integer linear program, allowing for efficient reaction to different energy scenarios. The model enables finding the optimal number of electrolyzers and production schedules when dealing with large data sets of intermittent energy and electricity price, achieving a balance between hydrogen production, energy absorption, and operation costs.