iEldesouky/Predicting-Power-Output-of-Solar-Panels-in-Egypt-

Predicting Power Output of Solar Panels in Egypt # ☀️ Solar Power Prediction for Aswan, Egypt **Accurate solar panel power output prediction using machine learning for Egypt's renewable energy sector.** ## 📋 Project Overview This project develops a machine learning system to predict solar panel power output in Aswan, Egypt using weather data. With **83.8% accuracy** (50.4% improvement over baseline), our system helps Egyptian energy companies optimize solar energy generation and grid management. ### 🎯 Key Features - **83.8% prediction accuracy** using K-NN Manhattan distance - **Egypt-specific feature engineering** for local climate patterns - **8 machine learning models** compared and evaluated - **Statistical validation** of all results (ANOVA, Z-tests, Chi-square) - **Complete data pipeline** from raw data to predictions - **Practical applications** for Egyptian energy companies ### 🌍 Why This Matters for Egypt Egypt aims for **42% renewable energy by 2035**, but unpredictable solar generation costs millions annually. This project provides: - Better energy planning for solar farms - Reduced reliance on fossil fuel backups - Support for Egypt's Vision 2030 renewable goals - Climate change adaptation for energy sector ## 📊 Results Summary | Metric | Value | Improvement | |--------|-------|-------------| | **Best Model Accuracy** | **83.8%** | +50.4% over random baseline | | **Best Model** | K-NN Manhattan Distance | | | **Features Used** | 10 engineered features | | | **Statistical Significance** | p < 0.001 for all key findings | | | **Overfitting** | Minimal (0.5% gap train vs test) | | ## 📁 Project Structure