# FlixOpt: Energy and Material Flow Optimization Framework
[](https://flixopt.github.io/flixopt/latest/)
[](https://github.com/flixOpt/flixopt/actions/workflows/python-app.yaml)
[](https://pypi.org/project/flixopt/)
[](https://pypi.org/project/flixopt/)
[](https://opensource.org/licenses/MIT)
---
## 🚀 Purpose
**flixopt** is a Python-based optimization framework designed to tackle energy and material flow problems using mixed-integer linear programming (MILP).
**flixopt** bridges the gap between high-level energy systems models like [FINE](https://github.com/FZJ-IEK3-VSA/FINE) used for design and (multi-period) investment decisions and low-level dispatch optimization tools used for operation decisions.
**flixopt** leverages the fast and efficient [linopy](https://github.com/PyPSA/linopy/) for the mathematical modeling and [xarray](https://github.com/pydata/xarray) for data handling.
**flixopt** provides a user-friendly interface with options for advanced users.
It was originally developed by [TU Dresden](https://github.com/gewv-tu-dresden) as part of the SMARTBIOGRID project, funded by the German Federal Ministry for Economic Affairs and Energy (FKZ: 03KB159B). Building on the Matlab-based flixOptMat framework (developed in the FAKS project), FlixOpt also incorporates concepts from [oemof/solph](https://github.com/oemof/oemof-solph).
---
## 🌟 Key Features
- **High-level Interface** with low-level control
- User-friendly interface for defining flow systems
- Pre-defined components like CHP, Heat Pump, Cooling Tower, etc.
- Fine-grained control for advanced configurations
- **Investment Optimization**
- Combined dispatch and investment optimization
- Size optimization and discrete investment decisions
- Combined with On/Off variables and constraints
- **Effects, not only Costs --> Multi-criteria Optimization**
- flixopt abstracts costs as so called 'Effects'. This allows to model costs, CO2-emissions, primary-energy-demand or area-demand at the same time.
- Effects can interact with each other(e.g., specific CO2 costs)
- Any of these `Effects` can be used as the optimization objective.
- A **Weigted Sum** of Effects can be used as the optimization objective.
- Every Effect can be constrained ($\epsilon$-constraint method).
- **Calculation Modes**
- **Full** - Solve the model with highest accuracy and computational requirements.
- **Segmented** - Speed up solving by using a rolling horizon.
- **Aggregated** - Speed up solving by identifying typical periods using [TSAM](https://github.com/FZJ-IEK3-VSA/tsam). Suitable for large models.
---
## 📦 Installation
Install FlixOpt via pip.
`pip install flixopt`
With [HiGHS](https://github.com/ERGO-Code/HiGHS?tab=readme-ov-file) included out of the box, flixopt is ready to use..
We recommend installing FlixOpt with all dependencies, which enables additional features like interactive network visualizations ([pyvis](https://github.com/WestHealth/pyvis)) and time series aggregation ([tsam](https://github.com/FZJ-IEK3-VSA/tsam)).
`pip install "flixopt[full]"`
---
## 📚 Documentation
The documentation is available at [https://flixopt.github.io/flixopt/latest/](https://flixopt.github.io/flixopt/latest/)
---
## 🛠️ Solver Integration
By default, FlixOpt uses the open-source solver [HiGHS](https://highs.dev/) which is installed by default. However, it is compatible with additional solvers such as:
- [Gurobi](https://www.gurobi.com/)
- [CBC](https://github.com/coin-or/Cbc)
- [GLPK](https://www.gnu.org/software/glpk/)
- [CPLEX](https://www.ibm.com/analytics/cplex-optimizer)
For detailed licensing and installation instructions, refer to the respective solver documentation.
---
## 📖 Citation
If you use FlixOpt in your research or project, please cite the following:
- **Main Citation:** [DOI:10.18086/eurosun.2022.04.07](https://doi.org/10.18086/eurosun.2022.04.07)
- **Short Overview:** [DOI:10.13140/RG.2.2.14948.24969](https://doi.org/10.13140/RG.2.2.14948.24969)
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