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Description
Petrom EV Charging Station Locations Dataset – RomaniaQuick links: Dataset Summary Methodology Download Regional Distribution Brand Bundle Related Datasets Use Cases FAQ Analyze with AI Petrom is Romania's most recognised fuel retail brand, operated by OMV Petrom, the largest integrated energy company in the country. As part of its transition toward a lower carbon future, OMV Petrom has been expanding EV charging infrastructure at Petrom branded filling stations across Romania and the wider South East
Petrom is Romania's most recognised fuel retail brand, operated by OMV Petrom, the largest integrated energy company in the country. As part of its transition toward a lower-carbon future, OMV Petrom has been expanding EV charging infrastructure at Petrom-branded filling stations across Romania and the wider South-East European region, offering charging alongside conventional fuel services.
There are 78 Petrom EV Charging Stations as of 2 June 2026 in Romania. This dataset is compiled and maintained by Geolocet and provides a complete, geocoded list of all Petrom 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: 78 Petrom ev charging stations in Romania
- 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
- County
- 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 Petrom dataset in Romania
| ID | Location Title | Latitude | Longitude | Postal Code | Full Address |
|---|---|---|---|---|---|
| f6ad6bc... | Petrom Electric Charging Station | 47.036329 | 21.945634 | 410583 | 28A Strada Nufărului, Oradea, 410583,... |
| 68dc64c... | Petrom Charging Station | 45.843351 | 26.157853 | 525200 | 1E Strada Ștefan cel Mare, Covasna, 5... |
| 81e51be... | Petrom Charging Station | 46.925791 | 26.908671 | 611052 | Șoseaua de Centură, Roman, 611052, Mu... |
| 5f29850... | Petrom Charging Station | 45.615797 | 22.956424 | 335500 | 1 Strada Viilor, Hațeg, 335500, Oraș ... |
| 62a8642... | Petrom Charging Station | 45.399135 | 27.046663 | 125300 | Strada Focșani, Râmnicu Sărat, 125300... |
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 Petrom locations in Romania is found in Timiș (7 sites, equivalent to 1.05 Petrom ev charging stations per 100,000 residents). This is followed by Bihor (4 sites; 0.72 per 100,000) and București (4 sites; 0.23 per 100,000). From a market-penetration perspective, Covasna has the highest brand density at 1.54 locations per 100,000 people (population: 195,000), making it the most saturated region for Petrom in Romania. By contrast, Cluj records only 0.14 locations per 100,000 residents (population: 695,000), indicating a potential white-space opportunity for network expansion or competitor analysis.
Also available for Romania
Brand bundle
Top 15 EV Charging Stations Brands in Romania - €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 Romania - 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 Romania: Map these Petrom locations against highly precise administrative polygons for territory analysis and spatial structuring.
- Demographics dataset for Romania: Overlay demographic indicators to deeply understand the population structures and household types surrounding these Petrom locations.
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 [email protected].
Who uses this data?
- Franchise Expansion: Network development teams assessing market saturation and mapping open territories for new franchisees.
- Commercial Brokerage: Real estate brokers validating commercial property valuations based on proximity to major retail anchors.
- 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.
- Mobility Analysis: Transport consultants evaluating retail proximity to major transit corridors and parking infrastructure.
- B2B Telemarketing & Outreach: Sales teams using verified phone numbers to pitch localized services (e.g., POS systems, commercial cleaning, security).
- CRM Data Enrichment: RevOps teams appending accurate, standardized contact details and coordinates to existing Salesforce/HubSpot records.
- Economic Development: Agencies identifying underserved neighborhoods or "retail deserts" for targeted commercial investment.
Frequently Asked Questions
Q: Does the dataset include opening hours?
A: Yes, opening hours are included where publicly available and validated during the data standardization process.
Q: Does the dataset contain duplicate locations?
A: Duplicate detection and validation workflows are applied during processing to improve consistency and reduce redundant records.
Q: Can I combine this dataset with administrative boundaries?
A: Yes. The coordinates can be spatially joined with municipalities, census units, postal areas, and other administrative polygons.
Q: How recent is this dataset?
A: This dataset was last updated on 2 June 2026 and is periodically refreshed through automated collection and validation workflows.
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 dataset support expansion planning?
A: Yes. Analysts often use the dataset to identify underserved areas, evaluate regional density, and support retail expansion decisions.
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.
Analyze this data with AI
Use these prompts with ChatGPT, Claude, or Gemini to extract strategic insights from this dataset:
"Analyze this Petrom dataset to identify underserved regions in Romania for potential market expansion.""Identify the most central Petrom locations in Romania to serve as hubs for a last-mile delivery network.""Detect clusters where Petrom sites are in close proximity to analyze potential self-cannibalization in Romania."
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.
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