Time-Series-Prediction for joint capstone project at Data Science Bootcamp neuefische GmbH.
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Updated
Dec 16, 2020 - Jupyter Notebook
Time-Series-Prediction for joint capstone project at Data Science Bootcamp neuefische GmbH.
Real-time grid digital twin for Germany's energy transition. Features <50ms physics loop, VDE-AR-N 4110 compliance validation, Monte Carlo robustness testing (n=50 AR(1) uncertainty), and production-ready CI/CD architecture.
Redispatch volumes forecasting using ARIMAX models and LSTM
Cloud-native grid compliance automation using AWS Lambda and Pandapower. Validates VDE-AR-N 4110 voltage stability through serverless AC power flow simulations for Redispatch 3.0 operations.
Das Projekt strebt die Entwicklung eines marginalen zonalen CO2-Emissionsmodells für das deutsche Stromnetz an. Durch die genaue Erfassung und Analyse lokaler Emissionsdaten soll eine zeitliche bzw. räumliche Verschiebung von Lasten ermöglicht werden, um die Abregelung erneuerbarer Erzeugungseinheiten im Redispatch zu minimieren.
A Python tool for validating and parsing BDEW Redispatch 3.0 XML data for German grid congestion management. Features strict XSD schema validation and Pandas integration.
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