EV Charging Network Optimization Dashboard
The EV Charging Network Optimization Dashboard identifies optimal charging station locations across urban regions by balancing accessibility, demand, and grid capacity.
Overview
With the growing adoption of electric vehicles, uneven charging infrastructure creates accessibility gaps. This project leverages open data and optimization algorithms to recommend new charging station placements that maximize coverage while minimizing redundancy.
Data
- NREL Alternative Fuel Station Dataset
- Washington State EV Population Data
- Demographic & Traffic Flow Statistics
Methodology
- Weighted K-Means and p-Median optimization to identify ideal candidate locations.
- Scoring Model combines distance, demand, and density factors.
- Built an interactive D3.js & Folium dashboard visualizing demand clusters, grid constraints, and accessibility.
Results
- Identified underserved “charging gap” zones across Washington State.
- Provided an interpretable location-allocation map aiding policymakers and urban planners.
Tech Stack
Python · Pandas · GeoPandas · scikit-learn · Folium · D3.js