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Predicting Belgium’s future solar PV generation: Part II

This is part two of a two-part series. Part one covered collecting and processing the data, then assessing the forecasts in the dataset. It also contains the link to the dataset and repo. This part covers my predictions, using machine learning. Intro OK, we’ve looked at the data, and we’ve seen how accurate their predictions are/were. Can I do any better? I’m taking three approaches: SARIMA, TensorFlow, and Prophet. A quick aside: Why do we want to predict the future energy generation? There are a number of reasons.

  • Data Science
  • Data Analysis
  • Time Series
  • Python
  • Energy
Friday, November 8, 2024 | 15 minutes Read
Hero Image
Predicting Belgium’s future solar PV generation: Part I

This is part one of a two-part series. This part covers collecting and processing the data, then assessing the forecasts in the dataset. Part two covers my predictions. Intro I have a friend who owns a solar management platform, and he asked me to investigate some solar PV generation data provided by Elia, one of Belgium’s transmission system operators. The data includes measured solar PV generation by region, along with their various forecasts.

  • Data Science
  • Data Analysis
  • Time Series
  • Python
  • Energy
Sunday, November 3, 2024 | 15 minutes Read
Contact me:
  • james@gibbins.me
  • jamgib

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