Electricity demand forecasting for Austin, TX, using a combination of timeseries methods and regression models

This repo contains the code for my postgraduate thesis dealing with Short-term Load Forecasting, predicting the electric load demand per hour in Greece, developed in R, RStudio, R-markdown and R-Shiny using daily load datasets provided by the Greek Independent Power Transmission Operator (I.P.T.O.). A presentation of the thesis' results can be f…

Multi-User-Personality-Electricity-Load-Forecasting

A PyTorch-based, end-to-end energy time-series forecasting demo with LSTM/GRU models, strong seasonal baselines, residual learning, and a CLI for reproducible train/eval runs on OPSD (with run logging + notebooks).

An educational application to predict the grid balance in Alberta. Capstone project for my Machine Learning and AI Bootcamp.

Forecasting System for Continual Learning Scenarios based on Hoeffding Trees With Change Point Detection Mechanism

Multi-User-Personality-Electricity-Load-Forecasting

Machine learning model for forecasting short-term electricity demand in the UK.

The Northern Benghazi Electrical Load & Weather Dataset combines historical electricity consumption records with meteorological data for Benghazi, Libya.

Electricity Load Forecasting

⚡ An advanced time-series forecasting pipeline designed to predict electricity load demand. By leveraging machine learning models and exploratory data analysis, this project aims to optimize energy grid management, reduce operational costs, and ensure efficient power distribution. 🔋📈

📈 Generate accurate demand forecasts with Python using synthetic data, featuring ARIMA/SARIMA modeling, evaluation metrics, and reproducible visualizations.