Completed Clean Energy Engineering

SHARED (Smart Hydrogen and Resilient Energy Decarbonisation)

In plain English

AI plain-English summary

Rural homes and businesses could store their own clean energy as hydrogen gas, bypassing the need for expensive grid upgrades. The problem is stark: rural communities are often the last to benefit from energy decarbonisation, yet they face the highest vulnerability to climate impacts and power outages. Strengthening electricity cables to remote areas is prohibitively expensive and slow. This project tests whether small-scale hydrogen production and storage—made locally from renewable electricity—can provide a cheaper, faster alternative. Instead of relying entirely on a strained grid, a village could produce hydrogen when renewable power is abundant, store it, and burn it for heat or electricity when demand spikes or the grid fails. If the approach works, the impact would be invisible but vital: a more resilient energy system that keeps lights on and homes warm during extreme weather, without forcing rural households to bear the highest costs of the green transition. The project also identifies what specific infrastructure and support these communities actually need—something often assumed rather than measured.

View original technical description
Rural communities face challenges in decarbonising heating systems are more vulnerable to climate change impacts and more likely to be Worst Served Customers (WSCs). Decarbonising these areas could increase electricity demand, exacerbating resilience issues, especially for WSC. Strengthening the electricity network in these areas would be expensive and take time, so alternative solutions are needed. SHARED will explore the potential of low-cost hydrogen production and storage as a solution to improve the resilience of these communities. The project will assess how effective this approach could be and identify the specific needs of rural communities.

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Related Research

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Original classification

Feasibility Studies

Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.