Python based data collection tool which currently supports PJM but will eventually cover everyone else....
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Updated
Oct 22, 2024 - Python
Python based data collection tool which currently supports PJM but will eventually cover everyone else....
Materials of WiDS Texas 2021 Hackathon
Tiny fully-typed python client for the ERCOT Public API
PowerConnection.AI applications — energy sales and customer portal
Multi-agent RAG system using LangGraph over ERCOT protocols with retrieval optimization, memory, and web fallback.
ERCOT plan comparison demo: simulate electricity bill costs from 15-minute usage and weather scenarios, then rank plans (MVP, extensible lakehouse roadmap).
Solar supply forecasting model training and MLflow deployment
ERCOT BESS arbitrage: LightGBM dispatch adds +$2.6M/yr (100 MW battery) over persistence on 2-year held-out test (77% of ceiling).
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.
Live nodal LMP price map across US ISOs
Free, open-source TypeScript/JavaScript client for US ISO/RTO energy data. No API key required.
Daily solar and wind curtailment across US ISOs - CAISO, ERCOT. Open source.
ERCOT's 434 GW interconnection queue analyzed in PostgreSQL/PostGIS: trigram POI geolocation, county queue pressure, cohort attrition, and the cost factor
Time-series forecasting of hourly electricity demand in ERCOT regions.
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.
Electricity market analysis and grid stress prediction using Python, machine learning, and transmission system insights
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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