In Scotland, wind energy is sometimes significantly higher than the transmission network’s capacity to transport the electricity to the rest of Great Britain. When this happens, payments are made to wind farms operators to compensate them for having to reduce their site’s power output to the level the network can absorb. This reduction is known as curtailment.

To prevent zero-carbon renewable energy going unused, curtailed energy could be an attractive source of electricity. It can reduce the overall cost of hydrogen production, through installing electrolyser units, which can utilise this power that would otherwise be curtailed.

The hydrogen produced can then be used for a variety of applications, including industry, heat and transport.

This report looks at whether curtailed energy from large-scale renewables in Scotland could be used to produce hydrogen economically. For further details, please read the report attached.

Key findings 

• The deployment of electrolysis will potentially lead to a significant decrease in curtailment of renewable energy due to increased electricity load behind network constraints. This will depend on the location of deployment and revenue mechanisms.
• Given that wind generation in Scotland is likely to grow faster than network reinforcement, there is likely to be a significant volume of curtailed energy in the late 2020s and possibly into the 2030s. Having facilities co-located with electricity generation may make the production of hydrogen from curtailed energy cost-competitive with other sources.
• However, these volumes of curtailed energy may be transitory in both timing and location due to expansion of the transmission network. As the transmission network is reinforced, there will be less network-related curtailment.
• The frequency of curtailed energy is generally higher in northern Scotland due to additional network constraints, so electrolysers used for hydrogen storage located further north will have potentially higher load factors and a lower cost of hydrogen production, at least in the near-term.
• If curtailed energy is used for other options and less for hydrogen production, hydrogen production might not be cost-competitive.
• Substantial hydrogen storage will be needed to buffer between production and demand. Near-term hydrogen electrolysis deployments are likely to be dependent on individual customers such as local heating systems or transport providers. In the absence of a wider hydrogen network, hydrogen will need to be stored either by the supplier or the customer.
• By the early 2030s, transmission-connected wind capacity is likely to significantly exceed off-peak electricity demand, meaning that curtailment will likely remain an ongoing feature of system operation. The availability of curtailed energy will depend on the wider context for energy system management and electrolysis will compete with a broad range of options, such as interconnection, battery storage, demand-side response and new pumped hydroelectricity capacity. The business case for using electrolysis for hydrogen storage will depend on the general growth of the hydrogen economy, transition of gas networks and broader market mechanisms that may be implemented across Great Britain’s electricity and gas systems. The near-term use of curtailed energy for electrolysis can generate significant learning and preparation for a future where hydrogen may be used as a large-scale energy vector for system balancing.

The Scottish Government has set very ambitious targets and policies in its Climate Change Plan to decarbonise the energy system. The Scottish TIMES model is as a key tool informing these new climate change policies.

TIMES is a well-known, widely used model. However, the adequacy of TIMES for energy efficiency policy analysis has not been assessed in the literature. This report sets out the potential for using TIMES to understand the system impacts of energy efficiency improvements.

The main challenges identified in the specific context of using TIMES for energy efficiency analysis are:

• Energy efficiency implementation in TIMES is not straightforward. Several approaches could be followed, delivering potentially different results.
• Decisions are cost driven. The cost minimisation algorithm would lead to outcomes involving extreme specialisation (corner solutions), if not prevented by user determined constraints (e.g. imposing maximum shares for different technologies).
• Energy demands and actions and reactions across the wider economy impacts are not modelled within TIMES. More generally, market “problems” and other drivers for consumer behaviour are not captured.

From a policy analysis perspective, TIMES is a very powerful tool that could be used to support decision making. Therefore, building on the model’s strengths, the report discusses possible TIMES uses and ways to go forward, grouped as:

• using TIMES as it is;
• developing TIMES improvements; and
• soft-linking with other models.