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flixOpt: Energy and Material Flow Optimization Framework

flixOpt is a Python-based optimization framework designed to tackle energy and material flow problems using mixed-integer linear programming (MILP). Combining flexibility and efficiency, it provides a powerful platform for both dispatch and investment optimization challenges.

🚀 Introduction

flixOpt was developed by TU Dresden as part of the SMARTBIOGRID project, funded by the German Federal Ministry for Economic Affairs and Energy. Building on the Matlab-based flixOptMat framework, flixOpt also incorporates concepts from oemof/solph.

Although flixOpt is in its early stages, it is fully functional and ready for experimentation. Feedback and collaboration are highly encouraged to help shape its future.

🌟 Key Features

  • High-level Interface with low-level control

    • User-friendly interface for defining energy systems
    • Fine-grained control for advanced configurations
    • Pre-defined components like CHP, Heat Pump, Cooling Tower, etc.

  • Investment Optimization

    • Combined dispatch and investment optimization
    • Size and discrete investment decisions
    • Integration with On/Off variables and constraints

  • Multiple Effects

    • Couple effects (e.g., specific CO2 costs)
    • Set constraints (e.g., max CO2 emissions)
    • Easily switch optimization targets (e.g., costs vs CO2)

  • Calculation Modes

    • Full Mode - Exact solutions with high computational requirements
    • Segmented Mode - Speed up complex systems with variable time overlap
    • Aggregated Mode - Typical periods for large-scale simulations

🛠️ Getting Started

See the Getting Started Guide to start using flixOpt.

See the Examples section for detailed examples.

⚙️ How It Works

See our Concepts & Math to understand the core concepts of flixOpt.

🛠️ Compatible Solvers

flixOpt works with various solvers:

  • HiGHS (installed by default)
  • CBC
  • GLPK
  • Gurobi
  • CPLEX

📝 Citation

If you use flixOpt in your research or project, please cite: