⚡ EV Charging Station Utilization Dashboard

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📌 Project Summary

This dashboard helps urban planners and EV companies track and optimize charging station performance.
It uses Python and Power BI to identify utilization gaps, peak demand zones, and idle/overloaded locations to drive smarter deployment decisions.

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🎯 Business Problem

EV infrastructure expansion often faces inefficiency due to:

• Underutilized or overloaded stations
• Uneven demand across geographies
• Lack of real-time usage monitoring

This project aims to solve this by providing insights into location-level utilization trends, enabling optimized rollout strategies.

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🔍 Key Features

• 🗺️ Location-wise utilization analysis
• 🔋 Peak hour and idle station detection
• 📍 Demand clustering by city/region
• ⚡ Overload flagging for maintenance planning
• 📈 Deployment recommendations for new zones

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🛠 Tech Stack

• Language: Python
• Libraries: pandas, geopandas, datetime
• Data: CSV + geo-tagged station logs
• Visualization: Power BI
• File Format: .pbix

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🧠 Architecture

flowchart TD
    subgraph KPIs
        KPI1["Station Utilization %"]
        KPI2["Peak Hours by City"]
        KPI3["Location-Wise Demand"]
        KPI4["Overloaded Stations"]
        KPI5["Idle Stations Detected"]
    end

    SRC["📥 EV Station Log Data (Geo CSV)"] --> PY["🐍 Python Script"]
    PY --> PD["🧹 Pandas + Geo Cleanup"]
    PD --> DB["📊 Excel Table / DB"]
    DB --> BI["📈 Power BI Dashboard"]
    BI --> OUT["💡 Deployment & Efficiency Insights"]
    BI --> KPI1 & KPI2 & KPI3 & KPI4 & KPI5

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📊 KPIs Tracked

Charging Station Utilization %

Peak Demand Hours per Region

Geographic Demand Concentration

Overloaded vs Idle Stations

Deployment Suggestions

📸 Dashboard Preview

🚧 Challenges & Learnings

Cleaning inconsistent geo-coordinates

Mapping idle stations and clustering usage

Visualizing overloads using conditional formatting

Enhancing user experience via tooltip filters

🚀 Future Enhancements

Add live integration from IoT station APIs

Build alert system for idle/overload zones

Deploy as web app with live map interactivity

Integrate cost efficiency analytics by zone

👨‍💻 About Me

Hi, I'm B. Sunil Kumar Reddy, a Data Analyst who builds real-world dashboards from real-world data. Focused on APIs, automation, and business value through analytics.

🔗 LinkedIn Profile(https://www.linkedin.com/in/sunilreddy-data-analyst/)

💻 Explore More Projects(https://github.com/Sunil5411)

⭐ Support

If you found this project helpful, feel free to give it a ⭐ — it motivates me to keep building and sharing more real-world analytics projects.