📊 A simple yet powerful tool to optimize energy distribution between Solar, Battery, and Gas sources while meeting renewable energy targets.

• 📥 Takes total power demand as input (MW).
• 🌞 Ensures 90% renewable energy (solar + battery).
• 🔋 Splits renewable energy between solar (8 parts) and battery (1 part).
• 🛢 Remaining demand is met with gas energy.
• 💰 Calculates total cost based on per MW prices.
• 📄 Clean, user-friendly output.

1. Calculate Renewable Energy
   renewable_energy = TOTAL_DEMAND × RENEWABLE_TARGET

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2. Split into Solar & Battery
   solar_energy = renewable_energy × (8/9) battery_energy = renewable_energy × (1/9)

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3. Gas Energy for the Rest
   gas_energy = TOTAL_DEMAND − renewable_energy

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4. Total Cost
   total_cost = (solar_energy × SOLAR_COST) + (battery_energy × BATTERY_COST) + (gas_energy × GAS_COST)

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• Python 3.x installed

# Clone the repository
git clone https://github.com/your-username/energy-planning-optimization.git

# Navigate into the folder
cd energy-planning-optimization

# Run the program
python energy_planner.py
💡 Example Output
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Enter the total power demand in MW: 100

Energy Planning Optimization Results:
Total Demand: 100.00 MW
Solar Energy: 80.00 MW
Battery Energy: 10.00 MW
Gas Energy: 10.00 MW
Total Cost: ₹430000.00
📈 Future Improvements
🎯 Make solar-to-battery ratio user-adjustable.

🔢 Allow renewable target percentage customization.

🛠 Add more non-renewable sources for comparison.

📊 Visualize results with charts & graphs.

🛠 **Made with ❤️ by Kartik Bhardwaj**
👨‍💻 Author
Kartik Bhardwaj
💼 Aspiring Generative AI Engineer | Full Stack Developer | Data Scientist