Workshop for the funding module WELMO
14. February 2019E-Metrobus Kick-Off
21. February 2019Optimized electrolyzer operation: Employing forecasts of wind energy availability, hydrogen demand, and electricity prices (Grüger et al. 2018)
Fabian Grüger, Oliver Hoch, Jörn Hartmann, Martin Robinius, Detlef Stolten
Paper, submitted and published in International Journal of Hydrogen Energy, Vol.44 (9) February 2019
Abstract
One of the main advantages of fuel cell based mobility over other sustainable mobility concepts is the flexible production of hydrogen via electrolysis. To date, it is unclear how electrolysis at hydrogen refueling stations should be operated in order to achieve the lowest possible costs despite the constraints of hydrogen demand. This study proposes and evaluates an intelligent operating strategy for electrolysis capable of exploiting times of low electricity prices while participating in the spot market and maximizing wind energy utilization when combined with a wind farm. This strategy is based on a simulation model considering imperfect forecasts (e.g. of wind availability or energy prices) and non-linear electrolyzer behavior. Results show that this approach reduces hydrogen production costs by up to 9.2% and increases wind energy utilization by up to 19%, respectively.
One of the main advantages of fuel cell based mobility over other sustainable mobility concepts is the flexible production of hydrogen via electrolysis. To date, it is unclear how electrolysis at hydrogen refueling stations should be operated in order to achieve the lowest possible costs despite the constraints of hydrogen demand. This study proposes and evaluates an intelligent operating strategy for electrolysis capable of exploiting times of low electricity prices while participating in the spot market and maximizing wind energy utilization when combined with a wind farm. This strategy is based on a simulation model considering imperfect forecasts (e.g. of wind availability or energy prices) and non-linear electrolyzer behavior. Results show that this approach reduces hydrogen production costs by up to 9.2% and increases wind energy utilization by up to 19%, respectively.