A Python–EnergyPlus Co-simulation and Optimization Framework with Expedited Computation using ML-based Surrogate Modeling

PyE+ is a flexible and extensible framework designed to integrate EnergyPlus with Python to enable co-simulation, multi-objective optimization (via NSGA-II), and machine learning–based surrogate modeling for expedited evaluation of building energy performance and occupant comfort.

• ✅ Co-simulation interface between Python and EnergyPlus
• ✅ Parametric control of U-values, lighting/plug loads, infiltration, and HVAC setpoints
• ✅ Integrated NSGA-II optimization (with optional surrogate acceleration)
• ✅ GUI built with Tkinter for user-friendly execution
• ✅ Live plotting of Pareto front and RMSE trends
• ✅ Citation-aware licensing and CITATION.cff metadata

• Python ≥ 3.8
• EnergyPlus ≥ v9.5
• eppy
• DEAP
• scikit-learn
• matplotlib, numpy, pandas
• tkinter (standard in Python)

1. Clone the repository:

   git clone https://github.com/MubashirWani/PyE-Plus.git
   cd PyE-Plus

2. Set your EnergyPlus path and ensure Energy+.idd is accessible.

3. Activate your virtual environment and install dependencies:

   • pip install -r requirements.txt

4. Run the GUI:

• python Graphics.py

Two EnergyPlus Input Data Files (IDFs) are included in this package:

• Baseline_IDF_Modified.idf
• RealBuilding_Test_MoreParameters_Wellington_Python.idf

These files provide reference building models for baseline and measure simulations, respectively.

🧠 Tip: Users are encouraged to explore the second IDF file—especially the Python Plugin and related object definitions—to better understand how PyE+ leverages the EnergyPlus Python API for real-time control and optimization.

📄 License

This project is licensed under the MIT License.

🧠 Acknowledgements

• Developed as part of research on building energy optimization and smart grid integration.

• EnergyPlus® is a product of the U.S. Department of Energy.

Academic Use and Citation Notice
If you use this software, in whole or in part, for academic research, publication, or derivative work, you are kindly requested to cite the original creator:

Mubashir Hussain Wani. "PyE+: A Python-EnergyPlus Co-simulation and Optimization Framework with Expedited Computation using ML-based Surrogate Modeling", 2025. GitHub: https://github.com/MubashirWani/PyE-Plus

This is not a legal requirement but a scholarly courtesy.