Project Summary
Heat pumps are essential for reducing the UK's building emissions, but their widespread use could strain local electricity networks. HeatNet will demonstrate how coordinating heat pump operations with advanced algorithms can address these challenges.
HeatNet will develop innovative machine-learning tools to manage heat pump power loads to help regulate voltage drops at the grid edge and ensure customer warmth. Our aim is to develop an independent service to accelerate the electrification of heat with new strategies that improve voltage quality and network reliability.
Innovation Justification
HeatNet is a highly innovative solution designed to increase the number of heat pumps connected to the network without requiring additional reinforcement. While smart control systems can remotely manage distributed energy resources to reduce network stress and enhance grid stability, our unique approach uses machine learning to optimise the interdependence between localised groups of heat pumps to minimise voltage drop. We believe this technique is unprecedented globally.
Managing domestic heat pumps presents unique challenges compared to electrical loads like EVs or batteries. HeatNet controls must minimise consumer discomfort and meet pre-agreed service levels by balancing heat pump performance factors, external weather conditions, and thermal inertia, all while supporting grid stability. HeatNet uses network modelling and machine learning control algorithms, to improve the management of clusters of heat pumps on LV subnetworks. We aim to develop a market-led service that uses innovative optimisation tools to coordinate localised groups of heat pumps to regulate voltage and minimise the need for reinforcement. Alpha will help us develop our innovation in two key areas:
Technical: processes for integrating voltage drop data with heat pump optimisation and coordination algorithms to improve network management
Commercial: understanding the overall value proposition, regulatory considerations, and mechanisms to maintain consumer protection and DNO oversight
Despite the complexity and early conceptual state of HeatNet, we have already started to engage with two innovation projects tackling similar themes: Market Signals for the Electrification of Heating and Demand Diversification Service for LMAs. We anticipate that these early connections will help pave the way for shared learning and collaboration during Alpha. Passiv also bring insights from UKPN’s projects Watt Heat and Heatropolis. The positive feedback from our Show & Tell webinar underscores interest and potential for HeatNet and we plan significantly wider stakeholder engagement during Alpha.
Currently, network reinforcement is the counterfactual alternative for addressing load growth and voltage drop issues caused by localised concentrations of heat pumps. Coordinating electrical loads from large numbers of heat pumps on a single subnetwork to ensure diversity and stability remains largely theoretical due to limited real-world data. HeatNet aims to address these challenges using advanced modelling tools in Alpha, and plans to test these outcomes through a large-scale demonstration trial during Beta.
Due to the technical complexity of HeatNet, it is well-suited to the phased nature of the SIF to de-risk the project, as demonstrated by early success during Discovery. There is a level of high commercial potential and the project is now ready for more technical development during Alpha, ahead of further trial or deployment in Beta. The network innovation process is a critical catalyst for technology-led innovations such as HeatNet, which would not otherwise be realised through more incremental, business-as-usual, commercial activities.
The six-month scale of Alpha will enable HeatNet to rapidly progress in tackling Challenge 1, Theme 2, by testing data integrations and optimisation scenarios, engaging widely with stakeholders to identify barriers and enablers, and developing suitable business models. This approach allows for engagement with relevant stakeholders, including network designers, heat pump manufacturers, and regulators, to address the technical barriers relating to interoperability and uncertainties associated with consumer protection identified during the Discovery.
Readiness levels have been summarised as follows:
Technology readiness: Alpha will enable progression from (TRL4-5) to (TRL5-6)
· Integration readiness: Initial levels are low (1), but with scope to transpose existing specifications (e.g. smart heat mandate, PAS1879 (5)
· Commercial readiness: Alpha will support initial market understanding (CRL 2-3)
Impacts and Benefits
Impacts and benefits description
HeatNet delivers consumer benefits by optimising load shifting between clusters of heat pumps on a local LV network. Using smart controls can help to reduce seasonal network stress and voltage drop challenges.
During Discovery, Imperial College London completed a cost-benefit analysis (CBA) using their Integrated Whole Energy System model (IWES). This model quantifies the impact of future demand growth and calculates thermal and voltage-driven asset upgrades, reinforcement costs and the impact of demand diversity effects in LV networks. The CBA used growth rates in heat pumps UKPN’s 2023 Consumer Transformation DFES and assumed full participation of HeatNet residential smart heat pump control in network management to help regulate network voltages and flows. Imperial College estimated that the 30-year NPV of benefits from the HeatNet approach across UKPN’s licence regions could be about £541m from avoided distribution network reinforcement. When including the potential benefits of transmission and generation systems this value proposition increases to £3,048m. The corresponding whole-life NPV values were £832m and £5,030m, respectively.
Financial - Future reduction in the cost of operating the network.
Average avoided cost to the DNO due to the HeatNet solution, compared to uncoordinated and unmanaged heat pump installations requiring conventional reinforcement (M/£).
Discovery validated a high-level proof of concept of using advanced heat pump controls and machine-learning coordination algorithms to increase heat pump uptake within the same network infrastructure by almost 30%.
Better-informed voltage management will lead to a reduction in cost from reduced voltage issues, associated site visits, and obtaining a more resilient network.
Early modelling during Discovery achieved a 15% reduction in peak voltage drop and a 14% reduction in peak demand.
Analysis by Imperial College during Discovery identified that distribution level savings of £7,179 of MW per year are achievable.
Financial - cost savings per annum on energy bills for consumers
Long-term savings by reduced distribution use of system (DUoS) costs from reduced socialised costs for network upgrades.
Environmental - carbon reduction -- indirect CO2 savings
HeatNet can help accelerate the adoption of higher -volume heat pump installations compared to traditional reinforcement-led approaches. This will contribute to broader societal benefits by reducing reliance on gas-heating boilers and their associated emissions.
Although CO2 savings from avoided infrastructure has not yet been quantified, initial analysis by Imperial College using IWES suggests carbon storage could be reduced by 0.7 MtCO2/year using HeatNet.
Metric: Number of HeatNet-optimised homes adopted over time (number of households).
New to market – services
The business models and opportunities for commercialising the HeatNet service will be explored in detail during Alpha. We intend to evaluate the key value drivers and regulatory barriers for this new type of service as well as, the roles of service providers (suppliers, aggregators), end users (DNO/DSO) any emerging consumer protection issues.
In addition to distribution level savings highlighted above, HeatNet could result in transmission level savings and wider energy system benefits including a reduced need for low carbon power generation, smaller heating appliances, and a lower reliance on other flexibility technologies such as battery storage systems. Early analysis suggests that by 2050, this technology could result in a net value of £2.46 billion per year across the whole GB energy system compared to the counterfactual Consumer Transformation National Grid FES projection.
The details of potential cost savings to the network, consumer savings, environmental benefits, and opportunities for realising the value form a HeatNet service will be explored further and quantified during Alpha and Beta. All benefits are linked to the deployment of the HeatNet solution as a commercial proposition following Beta.
