ORLEN EV Charging Station Locations Dataset – Poland
ORLEN EV Charging Station Locations Dataset – Poland
ORLEN is a major multi-energy corporation based in Poland, operating the country's largest network of fuel stations. It heavily invests in alternative energy through the ORLEN Charge network, offering high-speed electric vehicle charging facilities accessible via a dedicated mobile app.
There are 550 ORLEN EV Charging Stations as of 2 June 2026 in Poland. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all ORLEN 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: 550 ORLEN ev charging stations in Poland
- 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: 2 June 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
- 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 ORLEN dataset in Poland
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| 679894a... | Stacja ładowania ORLEN Charge | 53.781965 | 20.450861 | 10-160 | 4 Żeglarska, Olsztyn, 10-160, Powiat ... |
| 5d60766... | ORLEN Charging Station | 54.349156 | 18.589920 | 80-126 | 12 Stanisława Lema, Gdańsk, 80-126, P... |
| 282675c... | ORLEN Charging Station | 53.027197 | 18.693581 | 87-100 | 7 Kosynierów Kościuszkowskich, Toruń,... |
| 8ddb69b... | ORLEN Charging Station | 52.495142 | 19.680034 | 09-401 | Płock, 09-401, Powiat Płock, Poland |
| 22387ec... | Orlen Charging Station | 54.526660 | 18.513110 | 81-225 | 48 Morska, Gdynia, 81-225, Powiat Gdy... |
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 2 June 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 ORLEN locations in Poland is found in Pomorskie (140 sites, equivalent to 5.94 ORLEN ev charging stations per 100,000 residents). This is followed by Warmińsko-Mazurskie (83 sites; 6.17 per 100,000) and Kujawsko-Pomorskie (78 sites; 3.94 per 100,000). From a market-penetration perspective, Warmińsko-Mazurskie has the highest brand density at 6.17 locations per 100,000 people (population: 1,345,000), making it the most saturated region for ORLEN in Poland. By contrast, Podkarpackie records only 0.15 locations per 100,000 residents (population: 2,060,000), indicating a potential white-space opportunity for network expansion or competitor analysis.
Also available for Poland
Brand bundle
Top 21 EV Charging Stations Brands in Poland - €240
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 Poland - 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 Poland: Map these ORLEN locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Poland: Overlay demographic indicators to deeply understand the population structures and household types surrounding these ORLEN locations.
- Explore demographics data insights for Poland: Methodology, use cases, and definitions explaining how demographic metrics support your location intelligence workflows.
- Income indicators dataset for Poland (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.
- Explore a rich library of Poland-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 Poland
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.
- Geofencing & Targeted Advertising: Media buyers executing hyper-local, location-based mobile ad campaigns around specific brand locations.
- Trade Area Marketing: Agencies planning direct-mail or localized out-of-home (OOH) billboard campaigns near high-density retail clusters.
- Supply Chain Strategy: Distribution analysts evaluating competitor logistics networks and regional warehouse accessibility.
- Smart City Research: Academic researchers analyzing commercial density, urban growth patterns, and spatial economics.
- CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
Frequently Asked Questions
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.
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: What coordinate reference system is used?
A: Coordinates are provided in the global WGS84 geographic coordinate system (EPSG:4326).
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 request custom enrichment fields?
A: Yes. Custom enrichment services may be available depending on the project scope and geographic coverage requirements.
Q: Can this dataset be used for academic or research purposes?
A: Yes. Researchers and universities frequently use these datasets for urban studies, geography, economics, and spatial analytics projects.
Q: Is the dataset standardized for analytics workflows?
A: Yes. Address formatting, administrative areas, and geospatial fields are standardized to improve consistency across analytical environments.
Q: How accurate are the coordinates?
A: Coordinates undergo automated validation and manual quality review processes to improve positional accuracy and analytical reliability.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this ORLEN dataset to identify underserved regions in Poland for potential market expansion.""Compare the spatial distribution of ORLEN locations against major competitor clusters to identify overlap and whitespace opportunities in Poland.""Analyze the relationship between ORLEN site distribution and regional economic activity across Poland."
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.