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Green Hydrogen H2 News

New cooperative initiative to improve electrolysis system efficiency

Anela DoksoBy Anela Dokso23/12/20222 Mins Read
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A new worldwide cooperative initiative at the University of Bayreuth Center for Energy Technology (ZET) aims to improve electrolysis system efficiency and dependability.

To lower green hydrogen production costs, a German industrial partner and four Canadian partners from industry and science are developing novel models, hardware, and software. The University of Bayreuth will receive 250,000 euros from the Federal Ministry of Education and Research (BMBF) for three years.

Thus, the EU aims to produce and import 10 million tons of green hydrogen by 2030. This requires effective, dependable, and competitive technologies.

PEM-based electrolysis devices are ideal for large-scale green hydrogen production. Megawatt-scale PEM electrolysis systems are commercially employed. They operate quickly and flexibly. Thus, PEM electrolysis systems can directly couple highly variable power generation from renewable energy sources like sun or wind.

This strong dynamic can prematurely age electrolytic cell stacks. Thus, system performance and service life decrease. Electrolysis processes are complex and long-term operational experience is limited, making industrial-scale prediction impossible. Thus, system performance and service life decrease.

Electrolysis processes are complex and long-term operational experience is limited, making industrial-scale prediction impossible. Thus, system performance and service life decrease. Electrolysis processes are complex and long-term operational experience is limited, making industrial-scale prediction impossible.

“Hyer,” the BMBF-funded German-Canadian collaborative initiative, addresses this. The research partners intend to create a digital techno-economic model of a dynamic, renewable energy-linked PEM electrolysis facility. This model will accurately anticipate aging and performance decline with hardware and software applications. Thus, service life can optimize operating methods. The model will also feature a stack’s digital twin, which accurately maps dynamic operation’s effects on electrolysis cells.

The University of Victoria’s Institute for Integrated Energy Systems and the NRC will use artificial intelligence and machine learning to create the digital twin. The Hydrogen Research Institute of the Université du Québec à Trois-Rivières builds, analyzes, and characterizes innovative stacks with the NRC to offer experimental data for modeling.

SEGULA Technologies GmbH in Rüsselsheim tests and ages these stacks on a “Hyer” test bench. Pulsenics Inc., a Toronto startup, will deliver electrochemical stack characterization solutions.

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