Hydrogen 4:0 Design and Development of Cyber-Physical Systems for an Interoperable Renewable Hydrogen Plant (21.RP2.0062) – Completed

Hydrogen is increasingly recognised as a key energy source for a sustainable future. With vast renewable resources, access to coastal transport ports, and advanced research infrastructure, Australia is well-positioned to become a global hydrogen exporter. Despite the environmental benefits of green hydrogen – produced via electrolysis powered by renewable energy – its current share in the overall hydrogen market remains small.

The challenge

Key challenges in scaling producing include energy inefficiencies, complex compliance monitoring, and safety concerns. This project, Hydrogen 4.0, aimed to leverage emerging digital technologies such as the Internet of Things (IoT), advanced data analytics, and cyber-physical systems to address these challenges, improve operational safety and efficiency, and ensure compliance within lab-scale renewable hydrogen plants.

 

The objectives

The main objectives of the Hydrogen 4.0 project were:

  1. Data Requirements: Identify and define the data necessary to monitor and ensure the safe, efficient operation of lab-scale renewable hydrogen plant equipment.
  2. Cyber-Physical Systems: Design and implement cyber-physical systems for lab-scale hydrogen plants at QUT and SUT, enabling communication between physical components and their digital twins.
  3. Data Analytics for Safety and Compliance: Develop advanced data analytics methods to detect anomalies in critical equipment, ensure operational safety, monitor and report regulatory and standards compliance.
  4. Demonstration Plant: Design and construct a lab-scale hydrogen plant to demonstrate research outcomes and serve as a platform for ongoing research, education, and training.
  5. Platform Evaluation: Evaluate the performance and capabilities of the Hydrogen 4.0 platform through practical application in a lab-scale hydrogen plant.

 

The outcome

The project identified key challenges in maintaining operational safety, and a lack of real-time, data-driven insights into plant performance. To address these challenges, the project introduces the Hydrogen 4.0 framework – an innovative approach that integrates renewable hydrogen production with digital technologies inspired by Industry 4.0, such as the Internet of Things (IoT), digital twins (DT), and advanced data analytics. Through the design and implementation of lab-scale cyber-physical hydrogen plant, the project demonstrates the potential of Hydrogen 4.0 to improve operational efficiency, enhance safety, and streamline compliance monitoring. Key achievements include the identification of data requirements, deployment of predictive maintenance and safety assurance analytics, and the successful construction of a prototype lab-scale hydrogen plant, validating the viability of the Hydrogen 4.0 platform in a controlled research setting.

The future of Hydrogen 4.0 lies in the development of a comprehensive implementation and evaluation framework that can be adapted to industrial-scale hydrogen production facilities. As the hydrogen economy matures, there is a unique opportunity to embed the principles of Industry 4.0 into its foundational infrastructure.

 

Next steps

Future work should prioritise the standardisation of digital interfaces and protocols to enable interoperability between diverse hydrogen production systems and their associated digital platforms. Establishing uniform schemas for data collection, communication protocols, and software-hardware interfaces will be crucial to ensuring seamless integration across different vendors, facilities, and geographical locations. In addition, there is an urgent need to develop robust cybersecurity frameworks specifically tailored to Hydrogen 4.0 systems. As hydrogen plants become increasingly connected through IoT and digital twins, they also become more vulnerable to cyber threats. Future research should explore secure data transmission, threat detection, access control, and resilience strategies that safeguard critical infrastructure. Additionally, the integration of advanced artificial intelligence and machine learning techniques presents and opportunity to significantly enhance system performance, reliability, and adoption.

Project researchers

  • A/Prof. Ali Yavari
  • A/Prof. Mahnaz Shafiei
  • Prof. Ian MacKinnon
  • Dr. Saman Ashgahri Gorji
  • Prof. Jonathan Love

Project status

Complete