Shell Recharge EV Charging Station Locations Dataset – Denmark
Shell Recharge EV Charging Station Locations Dataset – Denmark
Shell Recharge is the global EV charging brand of energy major Shell plc, offering public charging points (many at Shell fuel stations), a roaming app, and home/workplace charging solutions. It operates in Denmark alongside Shell's traditional fuel retail business.
There are 57 Shell Recharge EV Charging Stations as of 15 July 2026 in Denmark. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Shell Recharge locations, including full address details, administrative divisions, and precise WGS84 latitude/longitude coordinates - structured for GIS, retail analytics, mapping, and AI/RAG workflows.
Dataset Summary
- Dataset Coverage: 57 Shell Recharge ev charging stations in Denmark
- Contents: Coordinates, addresses, postal codes, and administrative divisions
- File Format: Fully geocoded CSV dataset (UTF-8)
- Free Sample: Instantly accessible dataset to verify structure and data quality
- Use Cases: Suitable for GIS, retail analytics, site selection, and AI/RAG workflows
- Last Updated: 15 July 2026
Dataset Methodology:
This dataset is compiled from publicly available business listings, official company sources, and geospatial validation workflows. Automated quality checks and manual analyst reviews are applied to improve coordinate precision, address standardisation, duplicate detection, and overall analytical consistency.
It is periodically reviewed and updated to reflect known network changes, closures, relocations, and newly identified locations.
Dataset fields included in the CSV:
- GUID
- Title
- Latitude
- Longitude
- Street No
- Street
- City
- Kommune
- Region
- Population
- Postal Code
- Address
Require additional attributes such as charging points, charger types, or charging speed? Contact us to request a custom data enrichment.
Data Preview: Sample geospatial records from the Shell Recharge dataset in Denmark
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| 888b069... | Shell Recharge Charging Station | 56.093974 | 8.243528 | 6700 | 25 Enghavevej, Ringkøbing, 6700, Denmark |
| cc864bf... | Shell Recharge Charging Station | 55.524842 | 8.590166 | 6705 | 8 Korskrovej, 6705, Esbjerg, Denmark |
| 8f61a75... | Shell Recharge Charging Station | 56.025983 | 12.586735 | 3000 | 115 Kongevejen, Helsingør, 3000, Denmark |
| cc8abfb... | Shell Recharge Charging Station | 54.849594 | 9.405044 | 6340 | 8A Sønderborgvej, Kruså, 6340, Denmark |
| c7fa7ea... | Shell Recharge Charging Station | 55.688541 | 11.856120 | 4070 | Ejby, 4070, Denmark |
Note: Only a subset of the full dataset fields are displayed here. Download the free sample (option above) to view all fields and verify the data structure.
Why download from Geolocet?
- Instant download - full dataset available immediately after purchase, no waiting, no manual fulfilment
- Free sample first - verify structure, fields, and coordinate precision before you commit
- Analysis-ready CSV - clean, standardised, and compatible with Excel, Python, QGIS, Power BI, and PostgreSQL out of the box
- Regularly updated - last updated 15 July 2026
✅ Data looks right? Add to cart ↑ - or download the free sample first.
Regional Distribution Breakdown
Looking at the geographic distribution, the highest concentration of Shell Recharge locations in Denmark is found in Region Hovedstaden (17 sites, equivalent to 0.88 Shell Recharge ev charging stations per 100,000 residents). This is followed by Region Syddanmark (13 sites; 1.05 per 100,000) and Region Midtjylland (12 sites; 0.87 per 100,000). From a market-penetration perspective, Region Sjælland has the highest brand density at 1.05 locations per 100,000 people (population: 855,000), making it the most saturated region for Shell Recharge in Denmark. By contrast, Region Midtjylland records only 0.87 locations per 100,000 residents (population: 1,380,000), indicating a potential white-space opportunity for network expansion or competitor analysis.
Also available for Denmark
Brand bundle
Top 14 EV Charging Stations Brands in Denmark - €380
All major chains in one standardised dataset. Best for competitive benchmarking, network analysis, and market sizing across the leading brands.
View Top Brands dataset →Full market coverage
All EV Charging Stations Locations in Denmark - complete POI dataset
Includes everything in the brand bundle plus independent operators, smaller chains, and local businesses not covered by the top brands. Best for full market mapping, territory planning, and white-space analysis.
View full POI dataset →Related geospatial datasets
- Administrative boundaries and full polygon dataset for Denmark: Map these Shell Recharge locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Denmark: Overlay demographic indicators to deeply understand the population structures and household types surrounding these Shell Recharge locations.
- Explore demographics data insights for Denmark: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Income indicators dataset for Denmark (small-area income analysis): Download an analysis-ready dataset on income distribution across small geographic units - ideal for segmentation, customer analytics, location planning, and socio-economic scoring.
- Income distribution and socio-economic patterns in Denmark - expert analysis: A detailed blog post explaining income geography, disparities, and how income-based indicators can support location intelligence and market analytics.
- Explore a rich library of Denmark-specific datasets on our dedicated country page: detailed demographics, wealth indicators, multi-level boundaries, and a broad spectrum of retail POIs. View demographics, retail POI, and administrative boundary datasets for Denmark
Need the data in another format?
We can deliver this dataset in alternative formats upon request (GeoJSON, Shapefile, Excel, PostgreSQL import files, etc.). Contact us at contact@geolocet.com.
Who uses this data?
- Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
- Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
- Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.
- Vendor Distribution: FMCG and wholesale suppliers identifying specific retail locations for direct-store-delivery (DSD) pitching.
- Catchment Area Analysis: Analysts mapping 15-minute drive times to understand localized customer reach and accessibility.
- Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
- Urban Planning: City government agencies studying retail accessibility, neighborhood walkability, and commercial infrastructure.
Frequently Asked Questions
Q: Are the datasets suitable for machine learning workflows?
A: Yes. The structured tabular format and standardized coordinates make the datasets suitable for machine learning and predictive analytics applications.
Q: Can I request custom enrichment fields?
A: Yes. Custom enrichment services may be available depending on the project scope and geographic coverage requirements.
Q: Is this dataset useful for accessibility studies?
A: Yes. Analysts can combine the coordinates with mobility, transport, and demographics datasets to evaluate accessibility and service coverage.
Q: Can this dataset be imported into Power BI or Tableau?
A: Yes. The CSV structure is compatible with Power BI, Tableau, Looker Studio, and other business intelligence platforms.
Q: Is this dataset suitable for market analysis?
A: Yes. The dataset is designed for retail analysis, competitor benchmarking, site selection, market coverage studies, and geospatial intelligence workflows.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this Shell Recharge dataset to identify underserved regions in Denmark for potential market expansion.""Calculate the total population coverage for Shell Recharge in Denmark using a 10km catchment radius around each coordinate.""Compare the spatial distribution of Shell Recharge locations against major competitor clusters to identify overlap and whitespace opportunities in Denmark."
Disclaimer: All brand logos and trademarks displayed are the property of their respective owners and are used strictly for identification purposes. This product consists of geospatial location data only; no images, logos, or trademark rights are included in the downloadable files.