The large-scale uptake of heat pumps to decarbonise the GB residential heat sector is expected to significantly impact the magnitude and shape of the electricity demand profiles at different spatial scales. Aggregate electricity demand profiles of heat pumps for regions are different due to varying characteristics of the housing stock that affect number and size of heat pumps that can be installed. This will lead to different level of network reinforcement needs at different Bulk Supply Points (BSPs).
Key objectives of this projects are:
- To estimate half-hourly electricity demand profiles for heat pumps at different spatial scales such as LA and national, for selected future scenarios.
- To quantify technically available flexibility from electrified residential heat
Benefits
- Improved temporally and spatially resolved data on electricity demand needed for heating residential buildings in future years. This will be used to inform the ESO Future Energy Scenarios (FES).
- Flexibility that can be exploited due to thermal inertia of buildings will be quantified. We don’t currently have the ability to model this.
- More robust heat pump demand profiles, informed from observed trial data. Our current heat pump profiles are derived from gas boiler thermal demand profiles, evidence suggests these are not optimal.
- Improved analysis and insights of peak demands and flexibility.
Learnings
Outcomes
Project Achievements
The project successfully delivered intended outputs, fulfilling the objectives outlined in the scope. Key achievements included the delivery of the following:
- A comprehensive dataset of half-hourly demand profiles was produced for each Local Authority. This dataset covered multiple technologies, including ASHP, GSHP, gas boilers, and electric resistive heating, along with dwelling type, FES scenario, and year.
- An associated dataset was developed, providing estimations for the magnitude and duration of flexibility resulting from electrified heating systems across different temperature scenarios.
- The modelling tool and supporting documentation were successfully delivered as part of the project outcomes.
Project Impact and Changes
The completion of the project resulted in several significant improvements and changes. These included enhancements to data granularity and modelling capabilities, as well as a more accurate representation of real-world heat pump operation.
- Data granularity of demand profiles was increased both temporally and regionally, enabling more detailed analysis and insights.
- The ability to model various weather conditions and years was enhanced, providing a better understanding of how demand may respond to changing weather patterns.
- Representation of heat pump operation was improved, reflecting real-world behaviour more accurately than previous NESO models.
- A more robust method for estimating flexibility from heat pumps was established, with the capacity to break down results regionally and for different outdoor temperatures.
Application of Results and Future Opportunities
The profile data generated by the project has already been utilised in this year’s Ten Year Forecast modelling of normalised heat demand profiles (to be published at the end of July, 2026). These profiles have proved to be more representative of real-world heat pump operation compared to previous profiles, as evidenced by comparisons with other studies and stakeholder feedback.
Reliable profile and peak demand modelling are essential for our electricity supply modelling and for Electricity Market Reform, which underpins the future security of electricity supply. With further analysis and integration into NESO’s current FES processes, we can expect the model to further improve our heat demand profiles, thereby enhancing the reliability of our peak demand outputs. The outputs could also inform regional capacity requirements via RESP, providing a clearer understanding of regional variations in heat pump demand.
Future analysis may include quantifying the effects of specific weather years and weather scenarios on demand and supply. This could involve investigating flexibility from pre-heating under different heat pump roll-out scenarios and how these vary with weather conditions. There is also scope for further exploration of regional differences in demand and flexibility.
The above opportunities have potential to feed into better planning capability and therefore into longer term consumer and system value.
Lessons Learnt
Previous FES heat pump profiles have shown amplified peaks. This project indicates that heat pumps tend to operate more continuously, with less amplified peaks. The highest peak is seen in the morning, with a second lower peak in the evening.
Work Package 3 showed there could be significant potential for flexibility from air source heat pumps. Using the FES 2022 levels of heat pump uptake in 2050, it was indicated that up to 13GW of downward flexibility for a one hour duration, and up to 10GW for a two hour duration, could be achieved at an outdoor temperature of -5C, assuming all air source heat pumps participated.
With the model delivered as part of this project, NESO can now do further analysis using updated FES data and varied input assumptions. This is expected to provide significant insight which we can use to inform our modelling and analysis.
This could include:
- More detailed analysis of the demand profiles. E.g., under what weather conditions and time of day are the highest peaks likely.
- How will this demand vary regionally. E.g., where are the highest peaks likely to occur.
- Following on from the above, how will variability in heat pump demand temporally and regionally coincide with supply and network constraints.
Although significant flexibility potential was shown, future studies may need to assess how this flexibility could be carried out without creating new peaks and new system stresses. This may need to involve a dynamic optimisation of heat pump flexibility to align with supply constraints. This could be particularly important at regional levels.
