Voltanex-Carbon-Credit-Calculator

This project simulates carbon credit tokenization using real energy generation data from Brazil’s ONS. It parses generation data from a monthly .csv file and calculates the carbon credits produced.

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InspirationCarbon

Facing a climate crisis, we wanted to create something that bridges real-world environmental impact with blockchain transparency. Inspired by the need for accurate, verifiable carbon credit systems, we built a project that uses Brazil’s official energy data to calculate emissions offsets and tokenize carbon credits.

What it does

  • Fetches real monthly power generation data from Brazil’s ONS (Operador Nacional do Sistema Elétrico)
  • Filters and calculates renewable energy output (in MWh) from a chosen power plant
  • Converts that output into an estimate of avoided carbon emissions

How we built it

  • Data is sourced from this public dataset: https://dados.ons.org.br/dataset/geracao-usina-2
  • We use Python and Pandas to clean, parse, and aggregate the CSV data
  • Emission savings are calculated by multiplying the total MWh by a CO2 factor
  • We used a CLI-based approach to pass plant names and time ranges

Challenges we ran into

  • Monthly CSV files are too large to upload directly to GitHub and must be downloaded manually
  • The dataset changes column names between months, requiring flexible handling of fields like date and energy
  • Some plant names are inconsistent, making filtering unreliable without normalization

Accomplishments that we're proud of

  • We calculated carbon credits from real national-scale energy data
  • Built a modular pipeline that could scale to include more power plants or additional months

What we learned

  • Working with public data means being ready to handle inconsistencies and manual edge cases
  • Real-time carbon credit systems depend on reliable energy input, which is not always standardized

What's next for Voltanex-Carbon-Credit-Calculator

  • Automate CSV downloads from the ONS platform using scripts or their API (if exposed)
  • Add dynamic plant selection and validation via UI or metadata lookup
  • Deploy credit tokens fully on Avalanche and publish a smart contract interface
  • Add historical tracking and a visualization dashboard for plant-by-plant or region-by-region analysis

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