The newly developed spatial heat model (https://smarter.energynetworks.org/projects/nia_nggt0154) provides a powerful, peer reviewed platform for generating future GB building heat scenarios at high levels of granularity. The quality of outputs is however dependent on credible data about technology costs and fuel prices that account for whole energy market and policy interactions. Because there’s little precedence for the kind of energy system architectures that net zero would require, the input assumptions that go into the existing model must continue to be revised and benchmarked against the latest available data and insight. The project will focus on the Decarbonisation of Heat, specifically heat demand, technology, markets, networks, and policy implications.
Benefits
NA
Learnings
Outcomes
A detailed internal report and more concise external summary report with insights and implications for stakeholders, policy and regulation were produced and are available on the Smarter Networks Portal.
The key recommendations contained in these reports were compiled based on the modelling and analysis conducted:
- Phasing out gas boilers is crucial for the decarbonisation of heat: banning gas boiler replacements by 2035 could put Britain on track towards zero carbon heating by 2050, but delaying a ban to 2040 would leave us in 2050 with 15Mt of CO2emissions from residential heating, about a quarter of today’s total; to make a gas boiler ban in 2035 practical, action is needed now to ramp up deployment of low carbon alternatives
- Without policy change, gas boiler replacements are expected to remain attractive to households: heat pumps are a technology that can start being deployed today, but today’s air source heat pumps (ASHPs) have typically twice the up-front cost of gas boilers; even after accounting for heat pumps’ higher efficiency, and declining costs over time, they could still be 50% more expensive on an annualised lifetime cost basis in 2030
- Achieving deployment of 600k heat pumps per year by 2028 will require policy intervention: both cost and non- cost barriers need removing; costs could be addressed through a combination of grants, carbon taxes and reallocation of policy costs away from electricity (for example, onto gas or onto general taxation); an awareness of impacts on low-income households will be important for policy design
- Decarbonisation of heat will drive higher electricity demand: electricity demand from heating could quadruple by 2050 to over 100TWh per year, accounting for more than a quarter of the increase in total electricity demand
- Not all electric heating is equal: technologies like networked ground source heat pumps and thermal batteries can provide greater efficiency and flexibility, and in scenarios with greater deployment of these technologies it is expected that energy system costs could be lower by around £1bn a year on average to 2050, which is roughly 2% of total system costs
- Household economics won’t lead to an optimal system: without targeted policy intervention, it is not expected that the more efficient or flexible electrical heating systems will be economically attractive to householders, which could lead to over-dependence on ASHPs; although they are likely to be an important part of the mix, a system with only ASHPs would have unnecessarily high peak power demand and system costs
- Scenarios using hydrogen for a share of heating have lower peak power demand: using hydrogen in some homes means lower demand for electricity at peak times and in extremely cold weather events (assuming flexible electrolysis) and could lower power network costs by £0.5bn per year by 2050
- Green hydrogen could drive higher electricity prices: if around 30% of hydrogen is produced by electrolysis in the 2030s, baseload power prices could be up to £8/MWh higher in scenarios with hydrogen heating, as flexible electrolysers reduce the occurrence of low-price periods
Lessons Learnt
- As a large multi-stakeholder project. regular updates were useful to keep up to date with the project progress
- Regular meetings allowed questioning on the modelling methods and gain insight into other participants’ perspectives.