/energy-weather-modelling

Use of time series modelling tools including ARIMA, LSTM, and Monte Carlo simulation to model electricity consumption, rainfall and temperature data.

Primary LanguageJupyter Notebook

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Energy and Weather Modelling: Time Series Analysis

This project the use of time series models in forecasting electricity, temperature and rainfall patterns.

Data is sourced from Met Éireann, the UK Met Office, and data.gov.ie.

Techniques used include:

  • ARIMA and Prophet for temperature forecasting
  • LSTM for rainfall forecasting
  • Monte Carlo simulations for extreme weather modeling
  • PyFlux for probability-based analysis of temperature forecasts