energy-forecasting

Automated Machine Learning pipelines. Builds the Open Short Term Energy Forecasting package.

A curated list of awesome energy forecasting resources such as, code libraries, datasets, courses, tutorials, research papers, competitions and communities.

This study considers the prediction and forecasting of solar and wind power generation on a country-wide basis for the Greek energy grid.

Comparison of LSTM models and FCNN on Energy forecasting project using ASHRAE's data base for the Great Energy Predictor III competition on Kaggle.

Multi-model ML forecasting for Home Assistant — benchmark, promote, and publish calibrated forecasts as HA sensors. Pi 5 ready.

A benchmark for energy forecasting with PatchTST, Autoformer, Informer, and classical baselines using the ETT Dataset

Kernel quantile regression

Zero-shot multivariate power grid load, market price and renewable energy forecasting for the Polish Power System (PSE) using Google TimesFM and weather covariates.

Home Assistant integration for Energy Price Forecast – electricity price forecasts for European bidding zones.

End-to-end energy consumption forecasting for Portugal — XGBoost + conformal prediction (MAPE 1.44%), FastAPI, React/Vite, Prometheus metrics, deployed on HF Spaces.

AI-powered monitoring, forecasting, simulation and decision support for hybrid solar and wind energy systems.

An IoT-based Mobile App built with Flutter and Dart for real-time electrical energy monitoring, consumption analytics, and remote circuit control on Android and iOS devices.

AI-powered energy consumption forecasting system using machine learning, anomaly detection, and interactive dashboard for smart city and energy optimization applications.

⚡ Production-grade demand forecasting & live electricity dashboard: Prophet + LightGBM + SARIMA ensemble (10% MAPE). 36-feature engineering, TimescaleDB, FastAPI, Docker-ready. Real-time Brazilian electricity monitoring with HuggingFace data, Chart.js streaming, smart API/HuggingFace fallback.

⚡ Short-term load forecasting using machine learning on the UK-DALE dataset. Predicts household power usage with scalable ML models.

Time-series forecasting of hourly energy consumption using Long Short-Term Memory (LSTM) neural networks. This project explores deep learning models for energy forecasting and compares their performance to traditional statistical models like ARIMA and SARIMA. Part of my transition into computational energy systems research.

Overview of how the market operates and EDA of some of the variables in it

Solar power production calculator from forecast data.

This repository is about Hybrid Energy Forecasting and Trading Competition results performed by NICE_forecast.