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pye-plus

Multi-Criteria Decision Making (MCDM) Framework for Building Energy Systems with Expedited Computation using Machine Learning (ML) Techniques

https://github.com/mubashirwani/pye-plus

Science Score: 57.0%

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    Found 2 DOI reference(s) in README
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    Low similarity (17.0%) to scientific vocabulary

Keywords

bems building-energy-model co-simulation digital-twin-application energy energyplus gaussian-processes intelligent-algorithms machine-learning mcdm mlp-regressor nsga-ii optimization-algorithms python random-forest smart-building surrogate-modelling
Last synced: 6 months ago · JSON representation ·

Repository

Multi-Criteria Decision Making (MCDM) Framework for Building Energy Systems with Expedited Computation using Machine Learning (ML) Techniques

Basic Info
  • Host: GitHub
  • Owner: MubashirWani
  • License: mit
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 1.04 MB
Statistics
  • Stars: 1
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 2
Topics
bems building-energy-model co-simulation digital-twin-application energy energyplus gaussian-processes intelligent-algorithms machine-learning mcdm mlp-regressor nsga-ii optimization-algorithms python random-forest smart-building surrogate-modelling
Created 9 months ago · Last pushed 7 months ago
Metadata Files
Readme License Citation

README.md

PyE+

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

🔍 Overview

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.

⚙️ Features

  • ✅ 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

🧪 Dependencies

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

🚀 Getting Started

  1. Clone the repository: ```bash 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
  1. Run the GUI:
  • python Graphics.py

📂 Included IDF Files

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.

📚 Citation

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. Available: https://doi.org/10.5281/zenodo.15877753

This is not a legal requirement but a scholarly courtesy.

Owner

  • Login: MubashirWani
  • Kind: user

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use PyE+ in your research, please cite it as below."
title: "PyE+: A Python-EnergyPlus Co-simulation and Optimization Framework with Expedited Computation using ML-based Surrogate Modeling"
authors:
  - family-names: Wani
    given-names: Mubashir Hussain
    orcid: https://orcid.org/0000-0001-9246-9583
date-released: 2025-05-24
version: "1.0.0"
license: MIT
repository-code: https://github.com/MubashirWani/PyE-Plus
doi: 10.5281/zenodo.15877753
keywords:
  - EnergyPlus
  - Python
  - optimization
  - NSGA-II
  - surrogate modeling
  - machine learning
  - building simulation

GitHub Events

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Dependencies

requirements.txt pypi
  • deap *
  • eppy *
  • matplotlib *
  • numpy *
  • pandas *
  • pillow *
  • scikit-learn *