Full Stack Project: Wind Forecast Monitoring (React, Node.js, Data Analysis)

This video demonstrates my full-stack Wind Forecast Monitoring and Analysis project. The goal of this project is to analyze the accuracy of wind power forecasts in the UK and estimate how much wind energy can be reliably expected for grid planning. 🚀 Project Overview: This solution consists of three main components: 1. Frontend (React + Tailwind CSS) - Interactive dashboard - Date range selection - Forecast horizon slider - Line chart comparing actual vs forecast data 2. Backend (Node.js + Express) - Fetches data from BMRS APIs - Implements horizon-based forecast selection logic - Ensures no future data leakage - Returns clean, aligned datasets 3. Data Analysis (Jupyter Notebook) - Forecast error calculation (MAE, RMSE, P90, P95, P99) - Error vs horizon analysis - Time-of-day error patterns - Error distribution analysis - Reliability estimation using percentiles 📊 Key Insight: Using historical data, I estimated a reliable wind power baseline using the P10 percentile, which represents a conservative and realistic expectation for grid planning. 🧠 Key Concept Explained: Forecast Horizon → The time gap between when a forecast is made and the target time. This ensures we evaluate forecasts that were actually available at decision time. 🛠 Tech Stack: - Frontend: React, Tailwind CSS, Recharts - Backend: Node.js, Express - Data Analysis: Python, Pandas, NumPy, Matplotlib 📁 GitHub Repo: https://github.com/manishtmtmt/wind-forecast-monitoring 🌐 Live Demo: https://wind-forecast-monitoring-omega.vercel.app/ Thanks for watching!