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EV Charging Network Optimization

1st place at the IE Business School Datathon. The challenge, proposed by Iberdrola, was to design the optimal electric vehicle charging network for Spain's interurban routes for a 2027 operational horizon, subject to electrical grid capacity constraints.

Problem

Spain's interurban road network needs a strategically placed EV charging infrastructure to support mass EV adoption by 2027. The placement must respect:

  • Existing electrical grid capacity at candidate locations
  • Driver range anxiety (maximum distance between chargers)
  • Budget and installation constraints

Approach

  1. Data collection – road network topology, traffic flow data, grid capacity at candidate sites
  2. Optimization model – formulated as a facility location / set cover problem
  3. Solver – mixed-integer linear programming (MILP) with coverage and capacity constraints
  4. Validation – simulated EV trips across major Spanish corridors

Results

  • Achieved optimal coverage of interurban routes within grid constraints
  • Solution selected as best among all competing teams

Tech Stack

Python · PuLP / OR-Tools · pandas · geopandas · matplotlib

About

A Datathon i participated (and won) when i was doing my Master's in IE. The challengewas to design the optimal charging network for Spain's interurban routes for a 2027 operational horizon, subject to electrical grid capacity constraints.

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