SimSES

Latest revision as of 20:31, 9 July 2022

Simulation of stationary energy storage systems

Authors:
Marc Möller, Daniel Kucevic, Nils Collath, Anupam Parlikar, Petra Dotzauer, Benedikt Tepe, Stefan Englberger, Martin Cornejo, Andreas Jossen, Holger Hesse, Maik Naumann, Nam Truong

Contact:
Martin Cornejo

SimSES provides a library of state-the-art energy storage models by combining modularity of multiple topologies as well as the periphery of an ESS. This paper summarizes the structure as well as the capabilites of SimSES. Storage technology models based on current research for lithium-ion batteries, redox flow batteries, as well as hydrogen storage-based electrolysis and fuel cell are presented in detail. In addition, thermal models and their corresponding HVAC systems, housing, and ambient models are depicted. Power electronics are represented with AC/DC and DC/DC converters mapping the main losses of power electronics within a storage system. Additionally, auxiliary components like pumps, compressors, and HVAC are considered. Standard use cases like peak shaving, residential storage, and control reserve power provisions through dispatch of storage are discussed in this work, with the possibility to stack these applications in a multi-use scenario. The analysis is provided by technical and economic evaluations illustrated by KPIs.

Based on Python. Using Python for data processing.

Website / Documentation
Download

Open Source
BSD 3-Clause "New" or "Revised" License (BSD-3-Clause)

Directly downloadable

Input data shipped

Model Scope

Model type and solution approach

Model class	Electrical energy storage system
Sectors	Electricity
Technologies	Renewables
Decisions	dispatch
Regions	World
Geographic Resolution
Time resolution	Minute
Network coverage

Model type	Simulation
	Power flow and state of charge calculation based on time series profiles
Variables	>50
Computation time	27 minutes (20 years with 5 minute time step resolution)
Objective
Uncertainty modeling
Suited for many scenarios / monte-carlo	Yes

References

Scientific references

Naumann, Maik; Truong, Cong Nam (2017): SimSES - Software for techno-economic simulation of stationary energy storage systems.
https://dx.doi.org/10.14459/2017mp1401541

Reports produced using the model

Naumann, M; Truong, C.N.; Schimpe, M.; Kucevic, D.; Jossen, A.; Hesse, H.C. (2017): SimSES: Software for techno-economic Simulation of Stationary Energy Storage Systems. In: VDE-ETG-Kongress 2017. Bonn. Preprint accepted for publication in IEEE Conference Proceedings. http://ieeexplore.ieee.org/document/8278770/

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

Example research questions

Optimal system sizing and operation due to battery aging or economic results

◀ back to model list

@@ Line 3: / Line 3: @@
 |Acronym=SimSES
 |author_institution=Technical University of Munich
-|authors=Maik Naumann, Nam Truong
+|authors=Marc Möller, Daniel Kucevic, Nils Collath, Anupam Parlikar, Petra Dotzauer, Benedikt Tepe, Stefan Englberger, Martin Cornejo, Andreas Jossen, Holger Hesse, Maik Naumann, Nam Truong
-|contact_persons=Maik Naumann, Nam Truong
+|contact_persons=Martin Cornejo
-|contact_email=simses.ees@ei.tum.de
+|contact_email=simses.ees@ed.tum.de
-|website=www.simses.org
+|website=https://www.ei.tum.de/ees/simses/
-|source_download=https://bitbucket.org/Team_SES/opensimses
+|source_download=https://gitlab.lrz.de/open-ees-ses/simses
-|text_description=SimSES (Simulation of stationary energy storage systems) is an open source modeling framework for simulating stationary energy storage systems. The tool has been developed in MATLAB, mainly by Maik Naumann and Nam Truong at the Institute for Electrical Energy Storage Technology.
+|text_description=SimSES provides a library of state-the-art energy storage models by combining modularity of multiple topologies as well as the periphery of an ESS. This paper summarizes the structure as well as the capabilites of SimSES. Storage technology models based on current research for lithium-ion batteries, redox flow batteries, as well as hydrogen storage-based electrolysis and fuel cell are presented in detail. In addition, thermal models and their corresponding HVAC systems, housing, and ambient models are depicted. Power electronics are represented with AC/DC and DC/DC converters mapping the main losses of power electronics within a storage system. Additionally, auxiliary components like pumps, compressors, and HVAC are considered. Standard use cases like peak shaving, residential storage, and control reserve power provisions through dispatch of storage are discussed in this work, with the possibility to stack these applications in a multi-use scenario. The analysis is provided by technical and economic evaluations illustrated by KPIs.
-|User documentation=https://bitbucket.org/Team_SES/opensimses
+|User documentation=https://gitlab.lrz.de/open-ees-ses/simses
-|Code documentation=https://bitbucket.org/Team_SES/opensimses
+|Code documentation=https://gitlab.lrz.de/open-ees-ses/simses
-|Number of developers=2
+|Number of developers=6
 |open_source_licensed=Yes
 |license=BSD 3-Clause "New" or "Revised" License (BSD-3-Clause)
 |model_source_public=Yes
-|Link to source=https://bitbucket.org/Team_SES/opensimses
+|Link to source=https://gitlab.lrz.de/open-ees-ses/simses
 |data_availability=all
 |open_future=No
-|modelling_software=Matlab
+|modelling_software=Python
-|processing_software=Matlab
+|processing_software=Python
-|Additional software=Matlab
 |GUI=No
 |model_class=Electrical energy storage system
 |sectors=Electricity,
 |technologies=Renewables
 |Demand sectors=Households, Industry, Commercial sector, Other
 |Energy carriers (Renewable)=Sun, Wind
-|Storage (Electricity)=Battery
+|Storage (Electricity)=Battery, Chemical
 |Storage (Gas)=No
 |Storage (Heat)=No
@@ Line 47: / Line 46: @@
 |computation_time_hardware=Workstation
 |computation_time_comments=20 years with 5 minute time step resolution
-|citation_references=Naumann, M; Truong, C.N.; Schimpe, M. ; Kucevic, D.; Jossen, A.; Hesse, H.C. (2017): SimSES: Software for techno-economic Simulation of Stationary Energy Storage Systems. In: VDE-ETG-Kongress 2017. Bonn. Preprint accepted for publication in IEEE Conference Proceedings
+|citation_references=Naumann, Maik; Truong, Cong Nam (2017): SimSES - Software for techno-economic simulation of stationary energy storage systems.
-|citation_doi=http://doi.org/10.14459/2017mp1401541
+|citation_doi=10.14459/2017mp1401541
-|report_references=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
+|report_references=Naumann, M; Truong, C.N.; Schimpe, M.; Kucevic, D.; Jossen, A.; Hesse, H.C. (2017): SimSES: Software for techno-economic Simulation of Stationary Energy Storage Systems. In: VDE-ETG-Kongress 2017. Bonn. Preprint accepted for publication in IEEE Conference Proceedings. http://ieeexplore.ieee.org/document/8278770/
+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

Author institution	Technical University of Munich +
Authors	Marc Möller, Daniel Kucevic, Nils Collath, Anupam Parlikar, Petra Dotzauer, Benedikt Tepe, Stefan Englberger, Martin Cornejo, Andreas Jossen, Holger Hesse, Maik Naumann, Nam Truong +
Citation doi	10.14459/2017mp1401541 +
Citation references	Naumann, Maik; Truong, Cong Nam (2017): SimSES - Software for techno-economic simulation of stationary energy storage systems.
Computation time comments	20 years with 5 minute time step resolution
Computation time minutes	27 +
Contact email	simses.ees@ed.tum.de +
Contact persons	Martin Cornejo +
Data availability	all +
Decisions	dispatch +
Example research questions	Optimal system sizing and operation due to battery aging or economic results
Full Model Name	Simulation of stationary energy storage systems +
Georegions	World +
Is suited for many scenarios	true +
License	BSD 3-Clause "New" or "Revised" License (BSD-3-Clause) +
Math modeltype	Simulation +
Math modeltype shortdesc	Power flow and state of charge calculation based on time series profiles +
Model class	Electrical energy storage system +
Model source public	true +
Modelling software	Python +
Number of variables	50 +
Open future	false +
Open source licensed	true +
Processing software	Python +
Report references	Naumann, M; Truong, C.N.; Schimpe, M.; Kuc … Naumann, M; Truong, C.N.; Schimpe, M.; Kucevic, D.; Jossen, A.; Hesse, H.C. (2017): SimSES: Software for techno-economic Simulation of Stationary Energy Storage Systems. In: VDE-ETG-Kongress 2017. Bonn. Preprint accepted for publication in IEEE Conference Proceedings. http://ieeexplore.ieee.org/document/8278770/ 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), S. 14–30. DOI: 10.3390/batteries2020014
Sectors	Electricity +
Source download	https://gitlab.lrz.de/open-ees-ses/simses +
Technologies	Renewables +
Text description	SimSES provides a library of state-the-art … SimSES provides a library of state-the-art energy storage models by combining modularity of multiple topologies as well as the periphery of an ESS. This paper summarizes the structure as well as the capabilites of SimSES. Storage technology models based on current research for lithium-ion batteries, redox flow batteries, as well as hydrogen storage-based electrolysis and fuel cell are presented in detail. In addition, thermal models and their corresponding HVAC systems, housing, and ambient models are depicted. Power electronics are represented with AC/DC and DC/DC converters mapping the main losses of power electronics within a storage system. Additionally, auxiliary components like pumps, compressors, and HVAC are considered. Standard use cases like peak shaving, residential storage, and control reserve power provisions through dispatch of storage are discussed in this work, with the possibility to stack these applications in a multi-use scenario. The analysis is provided by technical and economic evaluations illustrated by KPIs. economic evaluations illustrated by KPIs.
Timeresolution	Minute +
Website	https://www.ei.tum.de/ees/simses/ +

About

Help

Search

Navigation

Search

Interaction

Toolbox

Namespaces

Variants

Views

Actions

SimSES

Latest revision as of 20:31, 9 July 2022

References

Scientific references

Reports produced using the model

Example research questions

Log in / create account

About

Help

Search

Navigation

Search

Interaction

Toolbox

Namespaces

Variants

Views

Actions

SimSES

Latest revision as of 20:31, 9 July 2022

References

Scientific references

Reports produced using the model

Example research questions