Portfolio Case Study · Business Analytics
EV Charging Station Demand & Location Intelligence
Evaluating station utilization, charging demand, revenue performance and peak-hour behavior using Python to inform capacity-planning decisions.
Portfolio note: this dataset is synthetic, built around real EV-charging business questions and dimensions used in public datasets (e.g. CHARGED, IEA EV Charging & Grid Integration Tool). It does not represent actual company data.
Business Scenario
An EV charging operator wants to improve station utilization and decide where additional charging capacity should be considered. This case study analyzes 12 stations to answer: which stations have the highest utilization, what the peak charging hours are, which stations generate the most revenue, which are under-utilized, and which profiles management should prioritize for expansion.
Key Metrics (12 stations)
Total Sessions
1.17M
Energy Delivered
30.4M kWh
Total Revenue
₹455M
Peak Demand Hour
21:00
Top Station
Airport Corridor
Capacity Priority
3 stations
Demand Patterns
Charging demand by hour of day
Insight: Demand peaks around 21:00, with a smaller secondary bump in the morning — evening hours are the highest-pressure window for capacity and staffing.
Demand heatmap — station × hour
Insight: Airport Corridor, Shopping Mall and Central Business District show consistently high demand across most hours, not just peak times — these are the highest-priority sites for capacity upgrades.
Station Utilization & Revenue
Average utilization rate by station
Insight: Utilization ranges from 34% (Metro Station) to 76% (Airport Corridor) — a 42-point spread showing significant imbalance in how the network is used.
Revenue by station
Insight: The top 3 stations by revenue (Airport Corridor, Shopping Mall, Central Business District) generate roughly 42% of total network revenue.
Energy delivered vs. utilization rate
Insight: Energy delivered scales closely with utilization rate, confirming utilization as a reliable proxy for load — useful for quick capacity-planning triage without needing full revenue data.
Station Priority Ranking
| Station | Location | Utilization | Revenue | Priority |
|---|---|---|---|---|
| EV002 | Airport Corridor | 75.9% | ₹68.0M | Capacity Priority |
| EV005 | Shopping Mall | 72.3% | ₹62.7M | Capacity Priority |
| EV001 | Central Business District | 69.3% | ₹58.1M | Capacity Priority |
| EV011 | Industrial Area | 63.2% | ₹33.6M | Growth Opportunity |
| EV007 | Highway Exit | 52.5% | ₹40.2M | Growth Opportunity |
| EV010 | Metro Station | 34.5% | ₹26.1M | Growth Opportunity |
Business Recommendations
- Capacity planning — 3 stations fall into the Capacity Priority group. Review these locations for additional chargers, queue monitoring, or charger-capacity upgrades.
- Peak demand — Charging demand peaks around 21:00. Staffing, maintenance and dynamic pricing can be evaluated around high-demand periods.
- Under-utilization — Low-utilization stations should be reviewed for location fit, visibility, pricing, partnerships and customer acquisition.
- Revenue growth — Prioritize high-utilization stations for cross-selling, membership programs and premium fast-charging options.
- Expansion strategy — Expansion should combine utilization, energy delivered, revenue and local demand — not revenue alone.