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# Multi-use optimization tool for energy storage systems (mu_opt)
This stand-alone tool generates the optimized operating strategy for energy storage systems. Due to its flexible structure, this optimization framework enables the simultaneous use of multiple storage applications (dynamic multi-use).

The tool was created by [Stefan Englberger](https://www.ei.tum.de/en/ees/staff/mitarbeiter-liste/englberger-stefan/) at the Institute for Electrical Energy Storage Technology at the Technical University of Munich. For efficient optimization, the tool was designed in Mathworks Matlab and also supports the Gurobi solver.

### **Highlights & Features:**

#### Maximization of profit from multi-use operation
- Dynamic allocation of energy and power of physical energy storage system
- Segmentation into virtual energy and power partitions
- Behind-the-meter and front-the-meter applications

#### Optimization
- Mixed-integer linear programming
- Problem-based optimization framework
- Linearization of non-linear internal processes

#### Supporting state-of-the-art applications
- Frequency containment reserve
- Peak shaving
- Self-consumption improvement
- Spot market trading

#### Technical considerations include
- Component efficiencies and system peripherals
- Degradation model for well-established cell chemistry
- Self-discharge of storage system

#### Regulatory constraints include
- System topology
- Application's degrees of freedom
- Spot market regulations

### **How to cite:**

[Stefan Englberger, Andreas Jossen, Holger Hesse. (2020). Unlocking the Potential of Battery Storage With the Dynamic Stacking of Multiple Applications. Cell Reports Physical Science, 1(11).](https://doi.org/10.1016/j.xcrp.2020.100238)

![alt text](https://gitlab.lrz.de/open-ees-ses/mu_opt/raw/master/logo.png "mu_opt / Englberger")