Applied machine learning toolkit implementing Double Machine Learning for Energy Analytics.

Multi-AI Agent Energy Management System with HILS simulation, Hybrid AI (ML+LLM), and MCP Runtime - Real-time visualization demo for smart grid optimization

Global EV charging & EV models (2025) EDA tutorial: infrastructure density vs adoption, manufacturer/model dynamics, and regional gap insights.

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.

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.

UK day-ahead electricity price prediction using weather-driven renewables forecasting + ML (XGBoost/SVR), including spike detection + battery arbitrage evaluation.

Machine learning and time-series forecasting for smart grid demand response analysis.

Repository of the paper "Detecting and interpreting faults in vulnerable power grids with machine learning".

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.

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.

Data-driven analysis of Nigeria’s electricity system (2000–2024) using Python, Sql, Power BI.

🔋⚡ Professional LOAD OUTPUT monitoring for Victron MPPT solar chargers - Real-time kWh tracking of load consumption with ESP82XX + ioBroker + MQTT

Reproducible energy data pipeline with layered warehouse design, dbt transformations, and Spark-based batch analytics.

⚡ Simulate and visualize energy management with a multi-agent AI framework for real-time insights and efficient resource utilization.

Smart Grid ETL + Real-Time Energy Anomaly Analytics Dashboard

Solar plant performance monitoring dashboard built using Power BI and DAX

Scenario-based analysis of global oil market supply–demand balances, OPEC+ policy sensitivity and geopolitical risk drivers, using OPEC, EIA and OEUK data.

Python ML system forecasting India's hourly grid electricity demand — Ridge Regression (R²>0.90), time-series feature engineering, and live Streamlit dashboard

Machine learning project for predicting residential electricity consumption using building and occupancy features. Implements seasonal ML models (monsoon & summer) with CatBoost, regression analysis, cross-validation, and model interpretability for smart city and energy efficiency applications.