Introduction to GreenLightPlus


Project Statement: GreenLightPlus is a Python library developed by Daidai Qiu (opens in a new tab), based on the original MATLAB version of the GreenLight model by David Katzin. This project aims to provide open-source tools for greenhouse simulation research, solely for academic and educational purposes. For detailed information on the original model, please refer to David Katzin's GitHub repository (opens in a new tab).

GreenLightPlus is an advanced greenhouse simulation library based on Python, designed to revolutionize greenhouse environment modeling and control strategy research. It integrates complex greenhouse climate models, crop growth models, and energy consumption simulations, providing researchers and practitioners with a powerful and comprehensive tool.

GreenLightPlus not only migrates and optimizes the original model to Python but also adds new features such as modeling and simulation of different greenhouse structures, a training environment for AI reinforcement learning models, and integration with EnergyPlus, greatly enhancing its usability and application range. It significantly expands the functionality, offering users a more powerful and flexible greenhouse simulation tool.

Project GitHub: GreenLightPlus (opens in a new tab)

Key Features

  • Accurate Climate and Crop Simulation: Simulates greenhouse microclimate and crop growth, providing a highly realistic simulation environment.
  • Diverse Greenhouse Structures: Quickly generate and analyze different types of greenhouse geometric models through parametric modeling tools, supporting diversified scenario studies.
  • Energy Consumption Analysis: Accurately calculate and optimize the energy use of heating, cooling, and lighting systems, aiding in sustainable greenhouse design.
  • Integration with EnergyPlus: Conduct detailed energy and climate simulations, evaluate the performance of different greenhouse structures, and provide comprehensive performance analysis.
  • AI Model Training Environment: Built-in reinforcement learning environment compliant with the OpenAI Gymnasium API standard, providing a simulated training environment for AI algorithms.
  • Data Visualization: Generate intuitive charts and reports, facilitating the analysis of simulation results and AI model performance.
  • Open Source Flexibility: Fully open-source codebase and detailed documentation, allowing users to customize and extend functionality according to specific needs.

All code is fully open-source and comes with detailed documentation, providing users with great flexibility and extensibility. Whether for academic research or practical applications, GreenLightPlus is an ideal choice.

Why Use It?

GreenLightPlus is not just a powerful greenhouse simulation tool but also an ideal simulation training environment for developing and testing advanced AI control strategies. It provides greenhouse managers, agricultural researchers, and technical experts with a comprehensive solution for:

  • Optimizing Resource Utilization: Achieve maximum yield and minimal resource consumption through fine-tuned greenhouse operations.
  • Accurate Prediction: Simulate crop yields and energy demands under various scenarios, providing data support for decision-making.
  • Advanced Research Platform: Provide a reliable simulation environment for agricultural research and education, promoting innovation and knowledge dissemination.
  • Reducing Development Risk: Test different greenhouse designs and strategies in a virtual environment, significantly reducing the cost and risk of actual implementation.
  • Promoting Sustainable Development: Optimize design and operation to support sustainable and efficient greenhouse agricultural practices.
  • AI Control Strategy Development: Provide a standardized reinforcement learning environment to accelerate the development of intelligent greenhouse control systems.

Whether your goal is to optimize existing greenhouse operations, design new facilities, or conduct cutting-edge research, GreenLightPlus offers the necessary simulation, analysis, and optimization tools to help you achieve breakthrough progress in the field of smart greenhouses.

Who Can Benefit?

  • Greenhouse managers and operators
  • Agricultural researchers and scientists
  • Horticulture students and educators
  • Agricultural technology companies and innovators
  • Sustainable agriculture enthusiasts

Whether you want to optimize existing greenhouse operations, design new facilities, or conduct advanced research in controlled environment agriculture, GreenLightPlus provides the tools and insights you need for success. Let's explore how to use GreenLightPlus and further develop its capabilities, embarking on your GreenLightPlus journey!


David Katzin, Simon van Mourik, Frank Kempkes, and Eldert J. Van Henten. 2020. “GreenLight - An Open Source Model for Greenhouses with Supplemental Lighting: Evaluation of Heat Requirements under LED and HPS Lamps.” Biosystems Engineering 194: 61–81. https://doi.org/10.1016/j.biosystemseng.2020.03.010 (opens in a new tab)