ViPES2X

The purpose of the project is to demonstrate methods to reduce the cost of hydrogen and the extension of the lifetime of batteries. This will be brought about by bidding the batteries and electrolysis units into the relevant markets in a portfolio with slower units such as heat pumps and district heating network elements.

As the complexity of the energy system grows, so does the need for dimensioning assets such as batteries, electrolysers, and other types of energy storage, as well as the need to operate them efficiently in the grid to keep CO2 emissions and energy costs as low as possible.

The project has developed a fully AI-driven Virtual Power Plant (VPP) using self-improving algorithms for operating energy storage and Power-to-X (P2X) systems in the most optimal way. The VPP can forecast in real time the cost of operations (energy costs, losses, and degradation) and compare with income (energy import savings and revenue from balancing markets). The project has demonstrated a 15% cost reduction for hydrogen production by predicting system degradation, a 15-20% increase in battery life- time by predicting long term degradation, and a 45% reduction in the degradation of batteries by co-aggregating and optimizing battery systems with slower reacting loads such as district heating and heat pumps.

Project owner Hybrid Greentech has developed and demonstrated the VPP using cutting-edge research at DTU Energy, DTU Wind Energy and Energy Systems, and Imperial College London. Green Hydrogen Systems and Lhyfe expects to implement the VPP in their electrolysers and Dynelectro to aggregate their electrolyser systems with the VPP.

Results from Dynelectro show that ancillary services to both the FRR, FCR, aFFR, mFFR markets. This has been achieved with using a real life wind turbine power profile and substantiates one of our differentiators – dynamic operation.

More details: ViPES2X