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Abstract

H2 production through water electrolysis for power-to-X applications is being investigated by comparing different bidding strategies on the electricity spot market in Sweden. For that, a price independent order (PIO) strategy was developed assisted by forecasting electricity prices with neural networks (NN). For comparison, a price dependent order (PDO) with a fixed bid price was used. The optimization of the NN showed that increasing the number of neurons in the hidden layer did not reduce error in forecasting due to possible overlapping of data making the model unnecessarily complex. By using different combinations of data for insample training and data from 2016-2018 for out-ofsample testing, preliminary results showed similar trends for PIO and PDO when bid prices are increased. However, the PIO marginally reduced the average cost of electricity when compared to PDO in all scenarios, but this was at the expense of increased non-operating hours (cold and warm mode). Further investigations with a mathematical optimization approach will reveal ideal conditions to run the system with low H2 production costs and increased profitability.

Keywords

dayahead market; hydrogen production; Nord Pool; process optimization; Variable renewable energy; water electrolysis

Published in

Energy proceedings
2019, volume: 2
Title: Innovative Solutions for Energy Transitions: Part I
Publisher: Scanditale AB

Conference

11th International Conference on Applied Energy, ICAE 2019

SLU Authors

UKÄ Subject classification

Energy Systems

Publication identifier

  • DOI: https://doi.org/10.46855/energy-proceedings-1592

Permanent link to this page (URI)

https://res.slu.se/id/publ/142864