SimSES (Simulation of stationary energy storage systems) is an open source modeling framework for simulating stationary energy storage systems. The tool, initially developed in MATLAB by Maik Naumann and Nam Truong, was 2019 converted to Python and improved by Marc Moeller and Daniel Kucevic at the Institute for Electrical Energy Storage Technology - Technical University of Munich.

SimSES enables a detailed simulation and evaluation of stationary energy storage systems currently with the current main focus on lithium-ion batteries. Future releases will include redox-flow batteries and power-to-gas systems. The core component of this simulation tool is a modular, flexible and abstract energy storage model, which allows a user-defined combination of system structure and technology for the energy storage systems. Furthermore, stress characterization enables the estimation of the energy storage degradation. Various aging models are integrated into the simulation tool that are based on the degradation test conducted at the institute, thus guaranteeing reliability and practicality of the developed tool.

In order to optimize the utilization of the energy storage in different applications, numerous operating strategies are implemented. Time step based simulations and built-in evaluation tool allow to calculate and monitor technical parameters for simulated storage operation. Furthermore, technical and economic key performance indicators (characteristics) are derived which enable the assessment and comparison of the simulation results.

The open source code can be found here: https://gitlab.lrz.de/open-ees-ses/simses

SES Optimization Tool Boxes

• Linear Programming Optimization Tool lp_opt https://gitlab.lrz.de/open-ees-ses/lp_opt

Open Data Profiles:

Standard Battery Energy Storage System Profiles: Analysis of various Applications for Stationary Lithium-Ion Battery Energy Storage Systems using a Holistic Simulation Framework
D.Kucevic, B.Tepe, S.Englberger, A.Parlikar, M.Muehlbauer, O.Bohlen, A.Jossen, H.Hesse
Parts of the input as well as a set of open data storage profiles can be found at the servers of TU Munich: https://mediatum.ub.tum.de/1510254

The above mentioned tool has been used for several publications, including the following papers:

Englberger, S.; Hesse, H.; Kucevic, D.; Jossen, A. A Techno-Economic Analysis of Vehicle-to-Building: Battery Degradation and Efficiency Analysis in the Context of Coordinated Electric Vehicle Charging 2019, 12, doi:10.3390/en12050955.

Naumann, M.; Karl, R.Ch.; Truong, C.N.; Jossen, A.; Hesse, H.C. (2015): Lithium-ion Battery Cost Analysis in PV-household Application. In: Energy Procedia 73, S. 37–47. DOI: 10.1016/j.egypro.2015.07.555.

Truong, C.; Naumann, M.; Karl, R.; Müller, M.; Jossen, A.; Hesse, H. (2016): Economics of Residential Photovoltaic Battery Systems in Germany. The Case of Tesla’s Powerwall. In: Batteries 2 (2), S. 14–30. DOI: 10.3390/batteries2020014.

M. Naumann, C. N. Truong, M. Schimpe, D. Kucevic, A. Jossen and H. C. Hesse, "SimSES: Software for techno-economic Simulation of Stationary Energy Storage Systems," International ETG Congress 2017, Bonn, Germany, 2017, pp. 1-6. URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8278770&isnumber=8278714
If you use SimSES in your work, please cite this paper and the code using its DOI: 10.14459/2017mp1401541
The source code, load profiles for example simulations, and a documentation are available at Bitbucket under the BSD 3-clause License: https://bitbucket.org/Team_SES/opensimses

For further information or comments, please contact simses.ees@ei.tum.de.