Python package for working with demand-side grid projects, datasets and queries
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Updated
Oct 30, 2026 - Python
Python package for working with demand-side grid projects, datasets and queries
Life Cycle Assessment of Technical Building Services of Large Residential Building Stocks using Semantic 3D City Models
A rigorous benchmark of 11 time-series forecasting models on hourly energy demand data — from a seasonal naive baseline to gradient-boosted trees, deep recurrent networks, and a stacking ensemble.
🔋 Time Series Forecasting for Energy Demand Spike Prediction 🔋
Code written for a co-op term on Integrated Assessment Models
LSTM-based hourly electricity demand forecasting model with 3.95% MAPE, using PGCB data to enable proactive grid management.
Dashboard and data processing routines for European green fuel demand projections developed in the PtX Markets Project
A module to prepare demand profiles for Europe at arbitrary spatial resolution, based on ENTSO-E historical load data.
This project seeks to analyze the behavior of solar energy generation in Spain and how this generation is affected by various climatic/atmospheric variables.
End-to-end time series analysis of hourly electricity consumption across 4,400+ London households using smart meter data
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.
30-day hourly electricity demand forecasting on PJM West data. Compares ARIMA, SARIMAX, Prophet, Random Forest & XGBoost, with a Streamlit dashboard. Includes honest recursive back-testing.
Interactive dashboard displaying the latest trends in publicly reported data center energy use.
En este proyecto se busca analizar el comportamiento de la generación de energía solar en España y como dicha generación es afectada por diversas variables climáticas/atmosféricas.
Academic AI/Data Science project analysing the relationship between climate variables and electricity demand.
pull PSE data into Python
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