Hydrogen has the potential to be a key element in the process of displacing fossil fuels for our future energy needs. As hydrogen is not a freely occurring element in nature, a process is required to release it, one of which is by electrolysis. It is proposed in this project to investigate the risks and opportunities from the connection of electrolysers to the distribution network. This will inform the development of a subsequent project which would, in conjunction with a range of partners, connect an electrolyser and wind turbine to the local network and produce hydrogen for transport applications. The expected benefits are in the reduction of potential reinforcement costs and the potential to create new generation capacity on constrained sections of network.

Objectives

This project provides the initial analysis to understand the opportunities and risks that exist for DNOs from the uptake of hydrogen technologies. Analysis from the UK H2 Mobility Project gives potential uptake figures of 1.6m hydrogen fuelled vehicles by 2030. In this scenario annual hydrogen consumption would be 254,000 tonnes, with a little over half of this coming from electrolysis. This would represent between 350-800MW of new demand being connected to the electricity network. This demand would potentially require significant and expensive network re-enforcement, but it also introduces a new demand which has substantial potential for flexible operation.

This project is developing learning in the following areas:

• Identification of appropriate learning and baseline data from other hydrogen electrolyser, DSM, and ANM projects;

• From the projects identified in above, extraction and collation of useful assessment criteria and baseline data sets;

• From the projects identified above, identification of ‘lessons learnt’ which would influence the potential uptake of this approach and inform a proposed trial;

• Understanding of the technology which could be used for this application and a commercial arrangement for utilising the service to remove network constraints;

• Potential operational profiles for a demonstration system which would utilise the above learning and provide quantifiable evidence of system performance.