🌱 EcoMPC4Greenhouse: Education Platform

🌍 Overview

EcoMPC4Greenhouse is an interactive, web-based platform aimed at enhancing education in Nonlinear Economic Model Predictive Control (NEMPC) applied to greenhouse climate management. By integrating real-time data and dynamic simulations, the platform enables students and researchers to explore how to optimize greenhouse systems for sustainability, balancing plant growth, energy use, and CO₂ emissions.

Developed to support the publication "Carbon Neutral Greenhouse: Economic Model Predictive Control Framework for Education," the platform provides hands-on learning with advanced control techniques, bridging theory and practical agricultural applications.

🚀 Features

• Greenhouse Climate Model: Simulates lettuce growth dynamics influenced by external weather data, temperature, light, and CO₂ concentration.
• Economic MPC Framework: Optimizes climate conditions to balance crop yield, energy consumption, and CO₂ emissions.
• Real-Time Data Integration: Fetches 🌦️ weather forecast, 😶‍🌫️ carbon intensity forecasts and ⚡️ electricity price to adjust the greenhouse control strategy.
• User-Friendly Interface: Intuitive design for students to visualize simulations, analyze results, and experiment with control parameters.
• Educational Focus: Aimed at bridging the gap between control theory and real-world applications, enhancing problem-solving skills through interactive learning.

📜 Citation

If you use this platform for academic purposes, please cite our publication:

@misc{wadinger2024carbonneutralgreenhouseeconomic,
  author        = {Marek Wadinger and Rastislav Fáber and Erika Pavlovičová and Radoslav Paulen},
  note          = {Submitted to European Control Conference (ECC)},
  title         = {Carbon Neutral Greenhouse: Economic Model Predictive Control Framework for Education},
  url           = {https://arxiv.org/abs/2410.23793},
  year          = {2024},
}

👐 Contributing

Feel free to contribute in any way you like, we're always open to new ideas and approaches.

• Feel welcome to open an issue if you think you've spotted a bug or a performance issue.

Please check out the contribution guidelines if you want to bring modifications to the code base.

🛠 For Developers

Installation (for Local Use)

If you wish to run the platform locally, follow the steps below:

1. Clone the repository:

   git clone https://github.com/MarekWadinger/ecompc-greenhouse-platform.git

2. Navigate to the project folder:

   cd ecompc-greenhouse-platform

3. Create a virtual environment:

   python -m venv --upgrade-deps .venv
   source .venv/bin/activate

4. Install the required dependencies:

   pip install -r requirements.txt

5. Run the platform locally:

   streamlit run app.py