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Local Chapter project

Harnessing AI for Renewable Energy Access in Mexico

Satellite ImageryMachine Learning
Start date
July 12, 2021
Finish date
September 12, 2021
Project status
completed
Harnessing AI for Renewable Energy Access in Mexico

Challenge background

In Mexico, the electricity production given by renewable energy is around 31%, where 4.3% comes from solar energy according to the Energy Secretariat (2020). Mexico’s government objective for 2050 is to generate 50% of the electricity from renewable energy.

The problem

The main objective of this project is to locate with data science the best solar energy spots with public spatial demographic data and satellite images.

The project results will be made open source. The deliverables of the projects will be useful for further research and decision-making for private companies, public institutions, and policymakers like SENER, ANES, ASOLMEX, Solar Power Europe, Tesla, GIZ, etc.

Goal of the project

  • Comparison of nighttime satellite imagery against the geographic location of the population.
  • Grid coverage analysis and machine-learning-driven heatmaps to identify sites that are most suitable for solar panel installation.
  • An interactive map with a list of the top Mexico regions with a high demand for electricity.

What you'll learn

1. Extract satellite images.

2. Analyze spatial demographic data.

3. Create heat maps that interpret insights of solar energy spots.

4. Create an interactive map with satellite images.

Get involved

What to expect from a Local Chapter project

First project

  • Welcomes beginners and experienced practitioners.
  • Focuses on education and collaborative delivery.
  • Produces open-source project work.

Benefits

  • Address a significant real-world problem with your skills.
  • Build your project portfolio.
  • Demonstrate your work to organizations and project partners.

Requirements

  • Working English communication.
  • A learning mindset.
  • Commitment to collaborative project work.