Many organisations are starting to take practical steps to decarbonise their assets, processes, transport requirements, support services and supply chains to enable the UK to meet its Net Zero obligation by 2050. This emphasis on total decarbonisation across all sectors has led to increasing interest in deploying infrastructure to produce, store and distribute hydrogen and in hydrogen-fuelled technologies as a part of the Net Zero mix of energy solutions. Since hydrogen is such a versatile energy vector that can be used to decarbonise many applications, such infrastructure projects have become known as hydrogen hubs.
When scoping a hydrogen hub project, scale is often not certain at the outset, as investment budgets are influenced by the relative novelty of the solutions being proposed and the carbon saved by them, the uncertainty over future market support mechanisms and a desire to scale up investment, once technologies and markets mature and project costs come down with increased scale. Therefore, a range of potential solutions needs to be considered to best achieve the project objectives within the available budget, both now and in future.
This interest in developing local infrastructure, which can be scaled up to regional and national level as market conditions allow, limits the choice of production solutions at each stage to those that make best use of the available resources to achieve the project’s decarbonisation ambitions. For example, an urban/industrial area may have limited access to renewable energy resources but plentiful access to biogas or heat from industrial processes that are suitable for carbon capture and usage/storage (CCUS). Such a hub could be expanded later to incorporate greener sources of hydrogen at a regional or national scale as market conditions allow.
Perhaps more challenging is the choice of which combination of potential hydrogen applications should be supplied by the hydrogen produced and how this might change as the hub is scaled up. This conundrum can only be resolved by quantifying and comparing demand with supply and storage combinations to guarantee a secure supply whilst optimising resources. The complexity of this problem requires modelling which considers system performance in operational (in some cases per second), seasonal, annual and worst case design scenarios.
Kiwa solves these challenges using detailed time-series modelling to forecast how intermittent and variable combinations of energy resource will affect the generation and supply of hydrogen, and understand how a varying demand will further test the capabilities of the energy system. This allows us to optimise the cost of the system whilst maintaining security of supply in a series of stress tests using, for example, 1-in-20 year weather events.
In this presentation, James Thomas, Kiwa UK's Data Science Lead, examines how in recent projects Kiwa has used a combination of engineering, modelling and technical leadership to help bridge the gap between concept stage and reality. They will use as an example, a recent feasibility study for an integrated energy system that includes renewable generation, hydrogen supply and storage, and distribution to various demands.