University of Auckland Power System Group

About

Power Systems Group operates within the Faculty of Engineering and Design at one of New Zealand’s leading research-intensive universities. The group brings together strong academic foundations and extensive industry engagement to address critical challenges in energy systems, renewable integration, and power system resilience. The group’s research focuses on the development and deployment of smart grids, cyber-physical energy systems, and digital twins for modern power networks. Core activities include AI-enabled monitoring, control, and optimization of critical infrastructure, advanced energy storage integration, and system-level approaches to enhance reliability, flexibility, and security of future energy systems, closely aligned with Horizon Europe priorities on climate neutrality and infrastructure resilience.

The University of Auckland offers state-of-the-art experimental and digital infrastructure for power system analysis, real-time simulation, and validation, including OPAL-RT, RTDS, MATLAB/Simulink, PyPSA, and cloud-enabled IoT platforms. These facilities support end-to-end research from modelling and digital twin development to real-time testing and deployment of AI driven smart grid solutions.

The Power Systems Group works closely with leading electricity sector organisations, including Vector, Transpower, Powerco, Mercury, Counties Energy, WEL Networks, Horizon Networks, Alpine Energy, Unison, PowerNet, Orion, Network Waitaki, Meridian, Northpower, TransNet, Mitton ElectroNet, and Electrix, as well as engineering and technology partners such as Contact, AECOM, ETEL, Hiko and Power Engineering. These collaborations support joint research, innovation, and policy-relevant projects aimed at enhancing power system resilience, renewable integration, and grid modernisation.

The Power Systems Group also has a strong track record in international collaboration, knowledge exchange, and policy-relevant research dissemination. The group has led and contributed to high-impact global forums, including the IEEE Power & Energy Society (PES), CIGRE, and the IET, and has organized major international conferences such as IEEE PES APPEEC 2025, CIGRE AORC 2025, ISGT Asia 2017, IEEE eGRID 2022, and ISGT Asia 2023. These activities have significantly influenced regional and international dialogue on energy transition pathways, grid digitalization, and evidence-based policy development for sustainable power systems.

For more information about the Power Systems Group, click here:

https://www.auckland.ac.nz/en/engineering/our-research/engineering-research/research-areas-and-facilities/power-systems.html

Strategic Keywords (Horizon Europe Alignment)

Energy Systems • Renewable Integration • Power System Resilience • Digital Twins • AI for Critical Infrastructure • Smart Grids • Cyber-Physical Systems • Policy Impact

Destination 4. Efficient, sustainable and inclusive energy use

HORIZON-CL5-2026-09-D4-01: Researching the technical, social & economic factors impacting the energy performance of Smart Buildings (Built4People Partnership)

Destination 3. Sustainable, secure and competitive energy supply

HORIZON-CL5-2026-04-Two-Stage-D3-02: Next generation of renewable energy technologiesHORIZON-CL5-2026-03-D3-13: Industrial scale up and circularity pathway for IPV technologies (EUPI-PV Partnership)HORIZON-CL5-2026-11-D3-14: Improved system design for innovative PV applications (EUPI-PV Partnership)HORIZON-CL5-2026-03-D3-18: Grid-forming capabilities for more resilient and RES-based electricity gridsHORIZON-CL5-2026-03-D3-19: Affordable and sustainable primary equipment for Future-Ready multi-terminal HVDC SystemsHORIZON-CL5-2026-03-D3-20: Hybrid AI-Control Framework for a next-generation grid-scale energy storage and system integrationHORIZON-CL5-2026-03-D3-21: Novel solutions for off-grid storage of renewable energy for critical infrastructuresHORIZON-CL5-2026-03-D3-22: AI-driven forecasting algorithms for Grid and Consumer friendly Energy Sharing – Societal Readiness pilotHORIZON-CL5-2026-11-D3-23: Data sharing to support the training and development of AI foundation models in the energy sector

Representatives

Research Fellow

University of Auckland Power System Group