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energy-analytics

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AI system for energy demand forecasting and grid optimization. Uses time series analysis and weather data to predict energy consumption, optimize renewable energy integration, and prevent grid failures.

  • Updated Nov 7, 2025
  • Python

Complete data architecture and machine learning project for industrial cost analysis. Includes a modern ETL pipeline (Bronze-Silver-Gold), validations with Great Expectations, Prefect orchestration, in-depth EDA, predictive models (Random Forest and Gradient Boosting), and deployment via Streamlit.

  • Updated Nov 21, 2025
  • Python

Learn how to visualize power consumption trends using Syncfusion WPF Surface Charts. This guide covers creating interactive 3D charts, binding energy data, customizing chart appearance, and optimizing performance to display annual power usage patterns across countries.

  • Updated Nov 14, 2025
  • C#

Data-driven analysis of solar farm data from Benin, Sierra Leone, and Togo, using statistical analysis and EDA to identify high-potential regions for solar installations. Delivers actionable insights to enhance operational efficiency and support sustainable energy investments.

  • Updated Aug 24, 2024
  • Python

An end-to-end AI forecasting system designed to predict hourly energy consumption for commercial buildings. Developed using Python and Random Forest to optimize grid efficiency, reduce operational costs, and support sustainable energy management.

  • Updated Apr 12, 2026
  • Jupyter Notebook

AC power flow and N-1 contingency analysis of the Lucknow 132kV transmission network using PyPSA. Built with real UPPTCL substation data and ACSR Zebra parameters to evaluate voltage profile, line loading, transmission losses, and contingency performance. Identifies congestion hotspots and critical corridors under peak load conditions.

  • Updated Apr 18, 2026
  • Python

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