solar-power-generation-predictor

A web application that predicts solar power generation based on real-time weather data using machine learning.

Features

• Real-time Weather Integration: Fetches current weather conditions from OpenWeatherMap API
• Machine Learning Model: Uses a pre-trained Random Forest Regressor to predict solar power output
• Dynamic Tips: Generates personalized optimization recommendations based on weather conditions
• Interactive Visualization: Displays prediction results with charts and detailed metrics
• Responsive Design: Works on both desktop and mobile devices

Technologies Used

Frontend: HTML ,CSS ,JavaScript ,Bootstrap 5 (UI framework) ,Chart.js (Data visualization)

Backend: python, flask

Dataset: solar_power_generation.csv

Machine Learning

• Random Forest Regressor
• Feature engineering:
• Time proxies from solar position
• Weather interactions (temperature × humidity, radiation × cloud cover)
• Seasonal indicators

Installation & Setup

Prerequisites

• Python 3.8+
• pip package manager

Steps

1. Clone the repository
2. Install dependencies
3. Set up your OpenWeatherMap API key from OpenWeatherMap
4. Replace the API key in app.py
5. Run the application