GigaMap In Numbers
Introduction
More public charge points are needed across Great Britain to meet increasing demand from Electric Vehicles (EVs). Government targets to install 300,000 charge points by 2030 highlight the scale of the challenge; but what are these numbers based on? Should chargers be distributed evenly and what power should these be? Robust, granular data is required to ensure we install the right hardware in the right place at the right time.
With the release of GigaMap 2.0., Field Dynamics make a significant step forward in solving these challenges. We’ve refreshed our analysis of 95 million MOT records to identify spatial variations in vehicles and mileages and built a hyper-granular view of energy demand (kWh) to 2050. Crucially, we’ve supplemented these with the most up to date view of public charging infrastructure (Zapmap) and regional EV Uptake Curves (FES 2024) to offer unparalleled insights into the regions that most urgently require attention.
This not only empowers government and local authorities in long-term planning for EV infrastructure but also provides Charge Point Operators (CPOs) and Distribution Network Operators (DNOs) with the insights needed to strategically deploy charging assets in high-demand areas.
How much energy will GB need for EV charging?
By 2050, assuming all vehicles are electric and there is no reduction in the overall car parc, total energy demand across GB (England, Scotland and Wales) from electric cars and vans will be ~80 TWh (Fig. 1 – based on today’s battery efficiencies).
This demand grows rapidly between 2030 and 2040, increasing from 18 TWh to 69 TWh, reflecting an annual increase of over 4.6 TWh / year. For context, electricity consumption from EVs (cars and vans) in 2023 was just ~ 2.9 TWh (FES), whilst total domestic electricity consumption across UK was 92.6 TWh (ECUK). Clearly, there is a way to go to achieve these levels.
Who Drives the most?
On average, cars and vans across Great Britain travel ~137 miles a week, or 7,137 miles a year. The spatial variations in both mileage and total energy demand are highlighted by postcode area in Figure 2.
Mileages tend to be highest in less built-up areas such as Northampton (NN) and Inverness (IV) as well as some key commuter areas north of London i.e. East (E) or Uxbridge (UB). In contrast, the lowest mileages are observed in the postcode areas south of London, i.e. Bromley (BR), South-West London (SW) and Sutton & Morden (SM).
Total vehicle counts directly scale up the level of demand, so in contrast to mileage trends, the total energy demand tends to be higher in built up areas due to higher population densities. The postcode areas with highest total demand are Birmingham, Sheffield and Peterborough. At the country level, vehicle numbers and thus energy demand are far higher in England (32.1 million vehicles, 69TWh), than in Scotland (2.9 million vehicles, 7TWh) or Wales (2 million vehicles, 5TWh)
Who is reliant on public charging infrastructure?
Whilst total energy demand is crucial for understanding eventual load on the electricity network, many EV drivers can charge at home and require limited use of public charging infrastructure. In contrast, as adoption grows, demand from EV drivers that cannot charge at home (on-street residents) will see huge growth; this latter component is crucial for Councils and CPOs to understand.
To enable this, Field Dynamics has mapped over 28 million households in Great Britain and assessed whether there is enough space to park and charge a car on their property. Those without space are considered on-street (32.7% of households) and will be reliant on public charging.
Applying this on-street percentage to total energy demand within a given geography allows us to calculate the total demand from on-street households (Figure 3). By 2050, this will have grown to 21 TWh; 18.2TWh in England, 1.8 TWh in Scotland and 1 TWh in Wales.
The 10 local authorities across GB with the greatest on-street demand are shown in Figure 4. Birmingham has the highest level of demand (337 MWh), followed by Glasgow (279 MWh) and Edinburgh (237 MWh) which are some ways behind.
Why no London? It is worth noting that local authorities vary in size and population. Larger authorities are likely to have more demand simply due to their size and the associated number of vehicles. Local authorities in London are split into smaller areas so they do not appear in the Top 10, although Barnet has the highest, with 143 MWh.
Are we ahead of the curve?
One of the most significant additions for this report is the inclusion of existing public charging infrastructure. Zapmap have generously shared their dataset covering the locations of all chargers across Great Britain.
With this, Field Dynamics can now accurately identify areas where infrastructure has been deployed ahead of demand, but also areas that require additional and immediate development. Simply put, we analyse total demand against current capacity, for every year out to 2050, and we share that here for each local authority.
Click for more details on calculating supply and demand
Total Demand: We use the on-street energy demand calculated in the section above, but we recognise that EV users with a home charger still utilise public charging 15% of the time (Zapmap insights). Therefore, total public demand is on-street plus an additional 15% of off-street demand. Across GB, this equates to around 30TWh by 2050.
EV Uptake: We’ve used projections from the latest National Grid Future Energy Scenarios (2024) at the Grid Supply Point level and applied these down to each individual LSOA.
Current Capacity: We’ve partnered with Zapmap to identify all public chargers in GB, as at the end of February 2025.
Every charger has a theoretical maximum charge that it can deliver over a set period. At its most basic, for a single day this would be the maximum charge speed multiplied by 24 hrs. However, chargers are not used 24/7, and they unable to deliver consistently at their top speeds. This is, therefore, not representative of actual capacity.
Alternatively, current energy-based utilisation rates vary from just c. 3.9 to 8.1% (Q1 2024), depending on the power (GFI); this equates to a much lower utilisation. However, if EV uptake increased and the number of charge points remained constant, utilisation would inevitably increase at a similar rate, until it reached its maximum practical limit. Therefore, current utilisation is also not representative of the maximum capacity.
Instead, we want to model a real-world output for each charger based on the power of the unit, but also accounting for standard human behaviours. Effectively, if an average device were used efficiently, without requiring users to connect/disconnect in the middle of the night, how many sessions could we reasonably expect to deliver.
To derive this, we have modelled a Theoretical Maximum Annual Capacity (TMAC) for each charger (Table 1). We’ve detailed the underlying assumptions in the Methodology and have created an explainer video here but, in short, the TMACs reflect an effective energy-based utilisation between 44% and 72% (calculated assuming constant use at average charge speed for absolute maximum). Whilst this is high compared to levels observed today, it reflects the fact that utilisation would grow if no further units were installed.
Zapmap have supplied the locations of every Electric Vehicle Supply Equipment (EVSE) point, split by power group, across GB. We assume that every EVSE can charge a vehicle, and therefore apply the respective TMAC to each, thus, calculating total capacity across GB .
Zapmap have supplied the locations of every Electric Vehicle Supply Equipment (EVSE) point, split by power group, across GB. We assume that every EVSE can charge a vehicle, and therefore apply the respective TMAC to each, thus, calculating total capacity across GB .
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Surplus Demand
Based on the input assumptions outlined in the boxes below, GB currently has a Theoretical Maximum Annual Capacity (TMAC) of 7.3 TWh; this is theoretically capable of meeting EV demand until 2031 if everyone could use any charge point. By 2050, even with the modelled efficient use, current infrastructure will have a charge deficit of 22.7 TWh by 2050. To meet this demand, the system would need over 313% growth in charger numbers of the same configuration. Conversely, if Ultra-Rapids were the sole method of future delivery, we would require an additional 92,647 charge points.
Spatial Variations
However, demand is not spatially consistent across all regions, and neither is existing infrastructure (Figure 5).
In fact, North-East Derbyshire will theoretically run out of capacity in 2025, with an additional seven local authorities in 2026, and more in each subsequent year. In contrast, three local authorities including Westminster (2,819 EVSEs), Hammersmith & Fulham (2,848 EVSEs), and City of London (115 EVSEs) have enough capacity to cover demand beyond 2050.
Clearly, the significant spatial variations in demand and supply mean creating a highly efficient system using a ‘small’ number of chargers will be practically challenging to deliver. Despite this, our analysis suggests the scale of the challenge is far from insurmountable, and that the government targets of 300,000 by 2030 are a sizeable step towards meeting the demand across GB.
Moreover, the report highlights the immense value with the latest release of GigaMap 2.0. Whilst we’ve shared the results at local authority level, we have calculated it from the ground up, allowing us to view results by individual LSOA (lower super output area). This will enable Councils to identify area where support is required but also enable CPOs to identify areas where chargers are likely to see higher levels of utilisation.
With the release of GigaMap 2.0., Field Dynamics have taken a significant step forward in modelling the future energy demand from electric vehicles.
Our latest analysis suggests over 80 TWh of charging demand by 2050, with a combined total of 30 TWh of public demand (21 TWh from on-street households). Current capacity of GB charging infrastructure is around 7.3 TWh, enough to last till ~2031 at the national level. However, pronounced spatial variations in both demand and existing supply mean some local authorities will run out as early as 2025.
These new insights should help support the likes of CPOs, Councils and DNOs to install the right infrastructure in the right place at the right time.
Methodology
To create GigaMap 2.0., Field Dynamics have refreshed the underlying GigaMap data product but have also supplemented this with additional contextual datasets.
Regional EV Uptake: The National Electricity System Operator publishes an annual forecast for the energy system (Future Energy Scenarios, FES). This includes EV uptake curves for each of the 364 relevant Grid Supply Points within Great Britain. We’ve applied these EV uptake curves to the LSOAs that reside within each GSP.
GigaMap: We have created a highly granular view of EV energy demand through a comprehensive analysis of over ~ 95 million MOT records.
The MOT dataset, an annual test of vehicle safety, allows us to calculate actual miles driven, as well as the make and model for each anonymised vehicle by Postcode Area. We compare each vehicle to the New Car Assessment Programme (NCAP) data to group the vehicles into standard classifications (i.e. Supermini, Small Family Car, Large Family Car, etc.) and we use the current fleet of available battery electric vehicles (BEVs) to assign a battery efficiency to each NCAP classifications.
Each vehicle exhibits a different demand profiles (Figure 6). For example, a large LGV travels 236 miles a week at 2 miles / kwh, requiring 6,161 kWh / year. In contrast, a large family does just 164 miles a week at 3.8 miles / kwh, requiring 2,253 kWh / year. By assessing the geographical spread of these vehicle types and combining them together, we calculate the energy demand of every car and van on the road in Great Britain.
When compared to GigaMap 1.0., overall demand in the latest release has increased by around ~9 TWh (~13%) which reflects i) the diminished impact of Covid related changes to typical mileage and ii) incremental improvements in our methodology. The increase in mileage is broadly consistent across England, Scotland and Wales.
Theoretical Maximum Annual Capacity (TMAC): To calculate the theoretical maximum output from a given charger we can make a set of reasonable assumptions to account for typical charging speed and human behaviour.
We’ve assumed a standard charge is 32kWh (based on the GFI utilisaton report, but supported by real-world observations), and have taken average charge speeds from Zapmaps analysis of ZapPay sessions. For each device power group, we calculate an average charge time, but we also account for ‘clip in / out’ (5-mins per session), as well as overstay for Slow / Fast AC sessions, and an assumed time between sessions (less for more powerful chargers). We also assume that a typical driver is unlikely to start a session in the middle of the night, apart from on Rapid or Ultra Rapid devices where night-time activity is higher (Fleet / in-transit etc.).
A detailed breakdown of the input assumptions for each charger type are highlighted in Figure 7.
Zapmap have supplied the locations of every Electric Vehicle Supply Equipment (EVSE) point, split by power group, across GB. We assume that every EVSE can charge a vehicle, and therefore apply the respective TMAC to each, thus, calculating total capacity across GB .
