Materials of WiDS Texas 2021 Hackathon
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Updated
Jun 20, 2021 - Python
Materials of WiDS Texas 2021 Hackathon
Python based data collection tool which currently supports PJM but will eventually cover everyone else....
Tiny fully-typed python client for the ERCOT Public API
Multi-agent RAG system using LangGraph over ERCOT protocols with retrieval optimization, memory, and web fallback.
PowerConnection.AI applications — energy sales and customer portal
ERCOT plan comparison demo: simulate electricity bill costs from 15-minute usage and weather scenarios, then rank plans (MVP, extensible lakehouse roadmap).
End-to-end hourly ERCOT electricity demand forecasting: EIA + Open-Meteo data, leakage-safe features, walk-forward backtest (2.67% MAPE, 69% over baseline), CQR-calibrated 80% intervals, and a live interactive Streamlit Grid Planner.
ERCOT BESS arbitrage: LightGBM dispatch adds +$2.6M/yr (100 MW battery) over persistence on 2-year held-out test (77% of ceiling).
Live nodal LMP price map across US ISOs
Solar supply forecasting model training and MLflow deployment
Free, open-source TypeScript/JavaScript client for US ISO/RTO energy data. No API key required.
ERCOT's 434 GW interconnection queue analyzed in PostgreSQL/PostGIS: trigram POI geolocation, county queue pressure, cohort attrition, and the cost factor
Daily solar and wind curtailment across US ISOs - CAISO, ERCOT. Open source.
End-to-end analysis of 5 years of ERCOT hourly grid load data, featuring a Winter Storm Uri case study. Built in Python, SQL, and Power BI.
Time-series forecasting of hourly electricity demand in ERCOT regions.
Developmental Phase of EnergyHack2026
Constructing and pricing ERCOT wind index swaps and floor options using ERA5 weather data, cross-validation, and Monte Carlo simulation.
ERCOT hourly load + Texas weather data pipeline for energy demand correlation analysis.
Python optimization framework for municipal water utility demand response. Models a three-facility system (GWTP, WWTP, lift station) as a triple-battery against ERCOT day-ahead prices using MILP (Pyomo/GLPK) and NMPC (do-mpc/CasADi/Ipopt). ENG 573 Capstone, UIUC MEng Energy Systems, Spring 2026.
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