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An open-source optimization model for the design and operation of hybrid renewable energy systems.

Project description

VY4E logo

VY4E-OptModel is the core optimization engine of the VY4E ecosystem. It provides the fundamental modelling framework for integrated zero-carbon energy systems, supporting electricity, heat, hydrogen, and storage.


🚀 Features

  • Modular formulation for multi-vector energy systems

  • Compatible with deterministic, stochastic, and equilibrium approaches

  • Flexible temporal structure: hours, days, representative periods

  • Built on JuMP / Pyomo (depending on module choice)

  • Interfaces with VY4E-data (datasets) and VY4E-examples (notebooks)


📂 Structure

  • src/: Core source code for the optimization model.

  • data/: Sample case studies.

  • docs/: Documentation and formulation notes.

  • tests/: Validation and regression tests.


📦 Prerequisites

  • Python 3.12 or higher.

  • A supported solver: Gurobi, CBC, or CPLEX. Make sure the solver is installed and accessible in your system’s PATH.


🚀 Installation

  1. Clone the repository:

git clone https://github.com/VY4E-nexus/VY4E-OptModel.git
cd VY4E-OptModel
  1. Create and activate a virtual environment (recommended):

python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`
  1. Install the required Python packages:

pip install -r requirements.txt

Usage

To run the optimization model, use the oM_Main.py script from the src directory.

python src/oM_Main.py --case <case_name> --solver <solver_name>

Command-line Arguments

  • --dir: Directory containing the case data (defaults to the current directory).

  • --case: Name of the case to run (e.g., Home1).

  • --solver: Solver to use (e.g., gurobi, cbc, cplex).

  • --date: Model run date in “YYYY-MM-DD HH:MM:SS” format.

  • --rawresults: Save raw results (True/False).

  • --plots: Generate plots (True/False).


🤝 Contributing

Contributions are welcome! If you want to contribute to VY4E-OptModel, please follow these steps:

  1. Fork the repository.

  2. Create a new branch for your feature or bug fix.

  3. Make your changes and commit them with a clear message.

  4. Push your changes to your fork.

  5. Create a pull request to the main branch of this repository.


📄 License

This project is licensed under the terms of the GNU General Public License v3.0.

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