Kople EV Charging Station Locations Dataset – Norway
Kople EV Charging Station Locations Dataset – Norway
One of Norway's largest EV charging operators, building and running rapid, fast and normal chargers nationwide at hotels, shops, housing cooperatives and municipalities. Kople grew out of energy group Ringerikskraft's charging activities (started in 2012, unified under the Kople brand in 2019) and is now majority-owned by investment fund Cube III alongside Ringerikskraft.
There are 776 Kople EV Charging Stations as of 16 July 2026 in Norway. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Kople 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: 776 Kople ev charging stations in Norway
- 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: 16 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
- Town
- Admin_level_1
- Admin_level_2
- Municipality
- 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 Kople dataset in Norway
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| 2cb39d5... | Kople Charging Station | 60.199286 | 5.487447 | 5211 | 342 Hegglandsdalsvegen, 5211, Bjørnaf... |
| 3f9ee4c... | Kople Charging Station | 59.139354 | 11.285822 | 1788 | 10 Justisveien, 1788, Halden, Norway |
| 4440d2d... | Kople Charging Station | 60.508935 | 5.347379 | 5109 | 1 Hylkjebakken, 5109, Bergen, Norway |
| 3930f38... | Kople Charging Station | 58.718016 | 9.212291 | 4950 | 1 Furumoveien, 4950, Risør, Norway |
| e7836d7... | Kople Charging Station | 66.319655 | 14.194899 | 8610 | 36 Revelheigata, 8610, Rana, Norway |
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 16 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 Kople locations in Norway is found in Oslo Og Viken (382 sites, equivalent to 18.45 Kople ev charging stations per 100,000 residents). This is followed by Agder Og Sør-Østlandet (114 sites; 14.9 per 100,000) and Vestlandet (106 sites; 7.39 per 100,000). From a market-penetration perspective, Nord-Norge has the highest brand density at 18.78 locations per 100,000 people (population: 490,000), making it the most saturated region for Kople in Norway. By contrast, Trøndelag records only 4.9 locations per 100,000 residents (population: 490,000), indicating a potential white-space opportunity for network expansion or competitor analysis.
Also available for Norway
Brand bundle
Top 12 EV Charging Stations Brands in Norway - €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 Norway - 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 Norway: Map these Kople locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Norway: Overlay demographic indicators to deeply understand the population structures and household types surrounding these Kople locations.
- Explore demographics data insights for Norway: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Explore a rich library of Norway-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 Norway
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?
- Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
- Consumer Behavior Analytics: Researchers correlating local demographics, foot traffic data, and proximity to physical stores.
- Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
- Last-Mile Delivery Routing: E-commerce and food-delivery planners optimizing localized courier routes and dispatch proximity.
- Urban Planning: City government agencies studying retail accessibility, neighborhood walkability, and commercial infrastructure.
- B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
- Territory Management: Field sales directors partitioning regional territories and routing field agents efficiently using exact addresses.
Frequently Asked Questions
Q: Are postal codes included for all locations?
A: Postal codes are included wherever available and validated as part of the standardization workflow.
Q: Can I analyze this dataset with AI tools?
A: Yes. The dataset is structured for compatibility with AI workflows including ChatGPT, Claude, Gemini, RAG pipelines, and Python-based analytics.
Q: Is this dataset useful for franchise analysis?
A: Yes. The dataset can support franchise territory planning, network expansion analysis, and regional performance benchmarking.
Q: Can I use this dataset in GIS software?
A: Yes. The dataset is suitable for GIS platforms including QGIS, ArcGIS, GeoPandas, CARTO, and other spatial analysis environments.
Q: Does the dataset include all locations in the country?
A: The dataset is designed to provide a complete and standardized list of known Kople locations operating in Norway as of 16 July 2026.
Q: Can this dataset support territory optimization?
A: Yes. The dataset is suitable for defining service territories, balancing regional coverage, and optimizing operational footprints.
Q: How are addresses standardized?
A: Addresses are cleaned and normalized through automated formatting and validation workflows to improve consistency and usability.
Q: Can this data be combined with demographics datasets?
A: Yes. Many customers combine these locations with demographics, income, mobility, and administrative boundary datasets for deeper spatial analysis.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this Kople dataset to identify underserved regions in Norway for potential market expansion.""Identify isolated Kople sites in Norway that may face operational inefficiencies due to low regional clustering.""Analyze proximity between Kople locations and major highways, ring roads, or arterial transport corridors in Norway."
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.