EVInsight
Free White Paper · April 2026 England

EV Risk Intelligence
in England 2026

A postcode-level analysis of electric vehicle infrastructure risk and demand across English local authorities. Over 1.4 million postcodes scored across 35+ factors using government and statutory data.

English Postcodes Scored
1.4M+
EVs per Rapid (Windsor)
50,237
Max Risk Score (Westminster)
100
Local Authorities Analysed
309
HM Land RegistryEnvironment AgencyDfT STATS19ONS IMDPolice.ukDVLA VEH0132DfT NaPTANONSPD May 2025Ofcom Connected NationsNHS ODS
About This Report

Risk, demand, and the infrastructure gap

England presents two distinct EV infrastructure challenges. In urban centres, risk is high and deployment is complex. In suburban and rural areas, risk is low but demand is rising fast and infrastructure has not kept pace. This report introduces a new metric — EVs per rapid charger — that reframes the conversation from where it is safe to deploy to where the market is being missed.

Windsor
Windsor and Maidenhead

The most acute demand gap in England. With 254,264 registered EVs and an average of just 22.7 chargers within 5km, Windsor and Maidenhead has the highest EVs per rapid charger ratio in the country at 50,237. The highest EV adoption rate in England is served by some of its worst rapid charging provision.

50,237
EVs per Rapid
254,264
Registered EVs
2.3km
Avg Nearest Rapid
Stockport
Greater Manchester

202,752 registered EVs and 24,875 per rapid charger. Stockport's commuter population has adopted EVs at a rate that far outstrips public charging provision. With residents dependent on routes into Manchester, the absence of reliable rapid charging is a structural barrier to continued adoption.

24,875
EVs per Rapid
202,752
Registered EVs
2.0km
Avg Nearest Rapid
Wiltshire
South West England

70,396 registered EVs but only 9.3 chargers within 5km on average and 27,042 EVs per rapid charger. A large rural county with strong EV adoption driven by affluent market towns, yet rapid charging has not followed. Somerset, its neighbour, has secured £3.78 million of LEVI funding to address an identical pattern.

27,042
EVs per Rapid
70,396
Registered EVs
3.8km
Avg Nearest Rapid
Peterborough
Cambridgeshire

118,976 registered EVs and 15,974 per rapid charger. Average risk score of 9.2 — the highest of any area in this group — yet rapid charging remains inadequate. A city with strong logistics and commuter demand for rapid charging and a significant deployment opportunity for operators willing to accept moderate risk.

15,974
EVs per Rapid
118,976
Registered EVs
1.7km
Avg Nearest Rapid
West Devon
Devon

Only 1,704 registered EVs but an average of 13.3km to the nearest rapid charger and 17,885 EVs per rapid charger. A rural area where even modest EV ownership creates acute charging pressure. Commercial operators will not deploy here without public subsidy. LEVI funding exists to address exactly this pattern.

17,885
EVs per Rapid
13.3km
Avg Nearest Rapid
1.9
Avg Chargers (5km)
Somerset
South West England

17,106 registered EVs, 7,398 per rapid charger, and 4.4km average to nearest rapid. Somerset secured £3.78 million of LEVI funding in 2025, committing to a minimum of 1,606 slow chargepoints and 20 rapids. The council has explicitly stated that without LEVI, rural deployment would not happen. Somerset validates the case for targeted public investment.

7,398
EVs per Rapid
17,106
Registered EVs
4.4km
Avg Nearest Rapid
Highest Risk Postcodes

Where risk is concentrated in England

Risk in England is concentrated in inner London. Westminster scores 100 at WC2N postcodes — the Trafalgar Square area. Outside London, risk drops sharply. No English postcode outside Greater London reaches the Critical band for the same combination of factors.

PostcodeAreaScoreBandIMD DecileCollisionsChargers (5km)
WC2N 5DUTrafalgar Square, Westminster100Critical54712,400+
W8 4PLKensington, RBKC74Critical6315,200+
W5 2NXEaling75Critical428980+
B1 1AYBirmingham City Centre75Critical324320+
SS14 1EJBasildon, Essex55High51912
The Demand Gap

EVs per rapid charger — a new measure of underservice

EVInsight has developed a new metric to quantify where infrastructure deployment has failed to keep pace with adoption: EVs per rapid charger. Calculated by dividing registered EV counts by average rapid chargers within 5km at postcode level, it identifies areas where EV drivers face the greatest practical pressure from inadequate provision.

The metric reveals a pattern that risk scores alone cannot capture. Windsor and Maidenhead has a moderate average risk score of 6.8 — far below London's urban centres — yet its 50,237 EVs per rapid charger ratio is the highest in England. The market has grown far faster than infrastructure.

This is not a coincidence. Commercial operators deploy where risk is acceptable and footfall is high. In suburban areas with affluent, EV-adopting populations and limited high-density retail, the commercial case for rapid charging is weaker despite genuine and growing demand. Public intervention through LEVI is the only mechanism that corrects this gap.

Key Finding

Windsor and Maidenhead has 254,264 registered EVs — the highest adoption in England — and 50,237 EVs per rapid charger. The area with the most EVs has among the worst rapid charging access relative to demand.

EVs per Rapid Charger — Most Underserved Areas

Windsor and Maidenhead
50,237
Wiltshire
27,042
Greater Manchester
24,875
West Devon
17,885
Cheshire West and Chester
16,835
Peterborough
15,974
North Yorkshire
15,916
Somerset
7,398
Full Local Authority Data

England by local authority

All 309 English local authorities scored by average EV risk, infrastructure provision, and EVs per rapid charger. Sorted by average risk score descending.

Local AuthorityAvg ScoreMax ScoreAvg Chargers (5km)Avg Nearest Rapid (km)Avg IMDEV DensityEVs per Rapid
Westminster25.61004,1680.75.581,7161,329
Barking and Dagenham24.8601401.23.25,468310
City of London23.1573,6190.87.91,78426
Thurrock21.560162.85.15,008772
Hackney19.2522,6110.73.43,74664
Haringey18.1538270.83.86,136126
Basildon17.555112.55.36,8042,238
Brent16.8591,8451.13.514,118412
Kensington and Chelsea16.4745,4470.96.05,800133
Harlow15.939152.24.62,448646
Waltham Forest15.7591,5391.24.46,268294
Bristol, City of15.753571.25.211,376554
Hillingdon15.689811.35.316,576845
Enfield15.6652781.14.17,970335
Sefton15.438482.35.07,5082,024
Newham15.0621,4971.13.35,178206
Islington14.8492,3880.64.14,59064
Ealing14.4751,0701.04.116,720453
Hammersmith and Fulham14.3614,7650.85.113,804327
Hounslow14.0619290.94.49,418294
Lewisham14.0441,4790.94.05,036129
Blackpool13.858201.52.72,742542
Luton13.854531.83.84,362828
Camden13.6653,1090.94.67,468118
Birmingham13.3752001.43.320,4681,515
Walsall13.159201.63.96,096524
Slough12.847451.04.470,2987,413
Barnet12.8555431.25.417,322620
Tower Hamlets12.8543,1460.83.44,848107
Greenwich12.8606520.84.55,800175
Middlesbrough12.747441.53.52,706331
Sandwell12.561831.42.911,928978
Harrow12.5461441.25.99,608628
Wolverhampton12.257281.33.55,788426
Coventry12.0522801.34.37,174488
Peterborough9.256231.74.6118,97615,974
Milton Keynes9.1621251.36.2171,3645,345
Leeds8.968451.45.5112,7826,459
Sheffield9.959191.84.715,6682,212
Portsmouth9.854431.34.423,5164,052
South Gloucestershire5.948302.07.294,2927,073
Swindon4.535431.46.381,2626,576
Windsor and Maidenhead6.842232.38.3254,26450,237
Wiltshire3.53293.86.870,39627,042
Stockport2.424252.06.2202,75224,875
Cheshire West and Chester3.534103.66.441,99816,835
North Yorkshire3.53465.36.424,47415,916
West Devon2.625213.35.11,70417,885
Cornwall2.72873.64.716,3588,696
Shropshire3.12846.25.710,3768,071
County Durham6.33894.84.114,9947,812
Somerset4.03374.45.417,1067,398
East Riding of Yorkshire4.03156.06.711,5186,911
Buckinghamshire5.243192.97.527,5466,053
Cheshire East3.73483.27.019,4966,004
Dorset3.53973.86.112,8725,113
North Norfolk2.02036.94.72,8227,255
Northumberland4.63784.55.511,3464,047
Policy Implications

What the data tells operators and planners

01
The demand gap is the most urgent deployment signal

Risk scores tell operators where deployment is complex. EVs per rapid charger tells them where the market is being missed. Windsor and Maidenhead, Stockport, and Wiltshire are not high-risk areas. They are areas where EV adoption has far outpaced charging provision. For operators seeking commercially viable sites with low risk and genuine demand, these local authorities represent the most significant untapped opportunity in England.

02
LEVI funding must target the demand gap, not just the rural gap

The Local Electric Vehicle Infrastructure fund is designed for areas where commercial deployment is unlikely. Somerset is the right kind of target — rural, low EV density, low commercial viability. But the data reveals a different category of underserved area: suburban local authorities with high EV adoption, moderate risk, and inadequate rapid charging. Windsor and Maidenhead, Cheshire West, and Peterborough are not rural. They are prosperous, high-adoption areas where rapid charging has simply not followed demand. LEVI allocation criteria should be broadened to capture this pattern.

03
Urban risk does not preclude urban deployment

Westminster scores 100 and has over 4,000 chargers within 5km. High risk and high infrastructure coexist in urban England because operators accept elevated risk in exchange for high utilisation. The data supports this: London boroughs have the highest risk scores and the most chargers. The risk model identifies where mitigation is required, not where deployment is impossible. Operators deploying into high-risk urban environments should use postcode-level data to inform physical security, insurance, and maintenance contracts.

04
Rural isolation requires a different metric entirely

West Devon has 1,704 registered EVs and a nearest rapid charger distance of 13.3km. The EVs per rapid charger metric does not fully capture this — the absolute journey distance is the more relevant figure for residents who cannot reach a charger without significant detour. Local authorities in rural Devon, Lincolnshire, and Northumberland require investment justified not by demand density but by geographic equity. LEVI funding at current levels cannot close this gap without a dedicated rural rapid charging programme.

05
Procurement capability is the operational barrier

Somerset secured £3.78 million of LEVI funding and is still appointing contractors. The gap between allocation and deployment reflects a consistent challenge across English local authorities: procurement processes for EV charging are complex, site selection criteria are poorly defined, and officers frequently lack the technical grounding to make confident investment decisions. Postcode-level risk and demand data gives procurement teams a defensible, auditable basis for site selection and business case development.

06
Infrastructure should follow adoption trajectory, not just current EV density

EV registrations in areas like Windsor and Maidenhead, South Gloucestershire, and Milton Keynes grew by 25 percentage points between 2020 and 2025. Areas with fast-rising adoption today will have significantly higher demand in 3 to 5 years. Infrastructure planning that responds only to current EV density will always lag the market. Forward-looking deployment should weight adoption growth rate alongside current demand.

07
Use postcode-level data at every stage of the deployment pipeline

Risk scores, EV density, IMD decile, flood risk, collision counts, and rapid charger proximity are all available at postcode level through the EVInsight API. Operators can use this data to screen sites, model utilisation, inform insurance, and justify grant applications. Local authorities can use it to prioritise ward-level investment and satisfy procurement requirements for evidence-based site selection.

Data
All Data from Government Sources

Every factor in this analysis derives from Environment Agency, ONS, DfT, Police.uk, HM Land Registry, and DVLA vehicle registration data. All sources are licensed under the Open Government Licence v3. EVInsight is an ICO Registered Data Controller (ZC106985).

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Published April 2026 · EVInsight · evinsight.co.uk · ICO ZC106985