Here, the most popular Electric Load Forecasting datasets are collected centrally. Feel free to support this work. 🔥
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Updated
Apr 27, 2026 - Python
Here, the most popular Electric Load Forecasting datasets are collected centrally. Feel free to support this work. 🔥
This repo contains data and code for Task-Aware Machine Unlearning with Application to Load Forecasting.
Grid-Aware STGNN for Multi-horizon Power Load Forecasting
This is the official repo for the paper E2E-AT: A Unified Framework for Tackling Uncertainty in Task-aware End-to-end Learning, to be appeared in AAAI-24.
Implementation of two different models (TF2/Keras) from literature and a custom model for day-ahead load forecasting (short term load forecasting) on two different datasets.
Official repository for the ParDeeB framework and the Shahrekord Energy Dataset: A high-resolution 4-year hourly benchmark (30,000+ samples) featuring 23 meteorological and temporal determinants for short-term load forecasting.
Hourly electricity load forecasting (AEP) with XGBoost - calendar + lag features, baseline comparison, recursive 24h forecast, and a Streamlit demo.
AI-powered electricity load forecasting and grid demand planning for Southern California. SARIMA time series forecasting, EV adoption and solar penetration scenario builder, and executive capacity planning dashboard.
Professional energy data science portfolio — wildfire risk modeling, grid investment optimization, load forecasting, and energy economics research tools built for utility infrastructure analytics.
Public model cards (Voltcrown v7.9 + lineage) and a dependency-light forecasting toolkit for the ENTSO-E load-forecast challenge — with OpenSSF Scorecard hardening.
Hybrid quantum-classical XGBoost experiments for short-term electricity load forecasting in power systems.
Context-aware power load forecasting system using XGBoost + Optuna hyperparameter tuning. Predicts 15-minute interval electricity consumption by training separate models per season, time-of-day period, and day type (weekday/weekend). Outputs results to formatted Excel with per-day sheets and tuning history.
Climate, Energy and Green Microbiology portfolio covering weather prediction, renewable optimization, electricity pricing, load forecasting, and sustainable transition modeling.
Production XGBoost quantile forecasters for the German day-ahead market. The load model beats the TSO's published forecast by 21 % across a 14-month holdout.
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