Hystar Unveils HyPilot Demonstration Project for Safer and Efficient Electrolyser Technology in Norway
Key Ideas
- Hystar has inaugurated the HyPilot project at the Kårstø Gas Processing Plant in Norway, showcasing a safer and more efficient 1.5MW containerised PEM electrolyser.
- The project, supported by partners like Equinor and Enova, aims to collect performance data under various operating scenarios, including intermittent power supply, for green hydrogen production.
- With a €26 million grant from the EU Innovation Fund, Hystar plans to expand its electrolyser stack production capacity, aiming for 1.5 GW annually by 2027 and 4.5 GW by 2031.
- Equinor's SVP highlights the significance of HyPilot in testing Hystar's novel electrolyser design for renewable energy applications, emphasizing its role in advancing green hydrogen technology.
Hystar has launched its HyPilot demonstration project at the Kårstø Gas Processing Plant in Rogaland, Norway, introducing a cutting-edge 1.5MW containerised PEM electrolyser. Collaborating with partners such as Equinor, Yara Clean Ammonia, Gassco, and ABB, the project aims to showcase the safety and efficiency of Hystar's electrolyser technology, integrating expertise from the fuel cell sector to enhance performance. By gathering performance data from different operational scenarios, including intermittent power supply, the project intends to advance green hydrogen production methods. Hystar's CEO expressed gratitude to Enova and the project partners for their support. The EU Innovation Fund recently granted Hystar €26 million to boost its electrolyser stack production, enabling the company to establish an automated factory with a capacity of 1.5 GW annually by 2027, scaling up to 4.5 GW annually by 2031. Andreas Jagtøyen, Equinor's SVP for Renewable & Low Carbon Technology, highlighted the project's role in evaluating Hystar's innovative electrolyser design for renewable energy applications. The project signifies a critical step towards enhancing operational efficiency and gaining valuable data for system modeling and technology validation.
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