The technologies for future energy systems must be developed now, but they will be deployed into energy systems very different from those of today. This is a challenge for Power-to-X technologies, which rely on the fluctuating production of renewable energies. Dynamic analysis is indispensable to achieve ideal integration of Power–to–X into the energy system. Thereby dynamic requirements for Power-to-X plants become clear and can be fed back to plant operators and component manufacturers. This allows to develop key components of Power-to-X today in a way that they match future energy systems perfectly. Using linear programming, this study optimizes a large-scale energy system completely coupled with the components of a Power-to-X plant. This Power-to-X plant produces hydrogen and synthetic natural gas. The results reveal that in the considered scenario Power-to-X plants are installed in almost all regions and are used for multi-day to seasonal energy storage. Electrolysis must be operated very dynamically and has about 200 starts a year in every region, whereas methanation is much more decoupled from the fluctuations of renewables and only has about 40 starts a year in every region. This is made possible by a hydrogen storage system which, if ideally designed, can store the hydrogen production of the electrolysis for an average of 17 h. Furthermore, this study investigates other flexibility requirements for Power-to-X plants including their scheduling, full load hours, average uptimes, and average downtimes.
«
The technologies for future energy systems must be developed now, but they will be deployed into energy systems very different from those of today. This is a challenge for Power-to-X technologies, which rely on the fluctuating production of renewable energies. Dynamic analysis is indispensable to achieve ideal integration of Power–to–X into the energy system. Thereby dynamic requirements for Power-to-X plants become clear and can be fed back to plant operators and component manufacturers. This a...
»