=Paper=
{{Paper
|id=Vol-2262/ekaw-poster-15
|storemode=property
|title=Ontology-Based Development of Smart Grid Co-Simulation Scenarios
|pdfUrl=https://ceur-ws.org/Vol-2262/ekaw-poster-15.pdf
|volume=Vol-2262
|authors=Jan Sören Schwarz,Sebastian Lehnhoff
|dblpUrl=https://dblp.org/rec/conf/ekaw/SchwarzL18
}}
==Ontology-Based Development of Smart Grid Co-Simulation Scenarios==
https://ceur-ws.org/Vol-2262/ekaw-poster-15.pdf
Ontology-Based Development of Smart Grid
Co-Simulation Scenarios
Jan Sören Schwarz1 and Sebastian Lehnhoff1
Department of Computing Science, University of Oldenburg, Germany
jan.soeren.schwarz@uni-oldenburg.de
Abstract. As the transition of the power system to renewable energies
leads to a rise in complexity, co-simulation is used to test new tech-
nologies with interdisciplinary simulation models. For this, experts from
different domains have to cooperate in the development, execution, and
evaluation of co-simulation scenarios. To assist the stakeholder in this
process, we propose to integrate domain knowledge and structure the
process based on ontologies. This approach aims to allow the high-level
development of simulation and automated integration of its information
in the specification and execution of concrete co-simulation scenarios.
Keywords: Co-Simulation · Energy scenarios · Information model ·
Smart grid · Ontology
1 Introduction
The transition of the power system towards more decentralized plants and in-
telligent devices in a smart grid leads to a demand for new technologies and
increasing dependencies between different domains. Thus, the power system can
be considered neither detached from the ICT system nor ecological, economic,
or sociotechnical systems. In these different domains, specific software, program-
ming languages, and paradigms are typically used. Co-simulation is an important
approach in order to handle this complexity in the development of new technolo-
gies . It permits the execution of diverse simulation models, which are developed
in different tools, in individual runtime environments and synchronizes them in
a joint simulation scenario [2]. In this paper the following two challenges of the
development and specification of co-simulation scenarios are addressed.
Firstly, simulation experts work together with experts from the different sim-
ulation models in the development of co-simulation scenarios. This collaboration
of simulation and domain experts can be a complex task, because in discussions
the used terminology may be unclear. Therefore, it would be a benefit to directly
integrate external domain knowledge.
Secondly, co-simulation scenarios are developed manually by simulation and
domain experts. Central elements of this process are the parameters, dependen-
cies, and data flows of simulation models. An increasing number of simulation
models make the development more complex and error-prone. Therefore, it is
essential for the specification of complex large-scale co-simulation scenarios to
gain assistance in terms of automation and validation.
2 J. Schwarz and S. Lehnhoff
2 Approach
To deal with the previously stated challenges, we propose to use ontologies for
knowledge integration and also for representation and structuring of the devel-
opment process in co-simulation. An overview of the approach is shown in figure
1. To deal with the first challenge, the integration of existing ontologies allows
the reuse of existing definitions and descriptions of terms. For example, in the
energy domain the Common Information Model (CIM) can be used as vocabu-
lary for the definitions of terms used in co-simulation. Another example of the
integration is the Ontology of units of Measure (OM) [1], which can be used for
the definition of units. The structure for the development process addressing the
second challenge is shown as follows.
2.1 Information Model
The approach is based on the information model of the Sustainability Evaluation
Process (SEP) described in [3]. It supports the information exchange in the
process of development and evaluation of co-simulation scenarios, as it allows
the modeling of dependencies and data flows.
The structure of the information model is depicted in figure 2. On the left-
hand side the domains of interest are modeled with objects, which are described
by attributes. On the right-hand side the evaluation function is categorized into
facets and criteria. The connection between the two sides is established through
transformation functions from attributes to the evaluation criteria.
The information model is modeled in a mind map to facilitate the partici-
pation of domain experts without previous knowledge of ontologies. The use of
a mind map has a twofold effect: the implementation of brainstorming within a
project team, and the systematic collating of information in the structure of the
information model. For the ontological representation a base ontology represent-
ing the information model structure has been developed. In addition, the mind
map tool XMind1 was extended to transform the content of the mind map to
RDF, based on the base ontology. For this transformation the structure of the
mind map has to comply with the specific structure of the information model.
1
https://www.xmind.net/
External Semantic Diagram Information Model Semantic Media
Ontologies (Mind Map) Base Ontology Wiki (SMW)
CIM
Instantiated SPARQL Queries Simulation
OM Information Model Scenarios
Fig. 1: Overview of the approach.
Ontology-Based Development of Smart Grid Co-Simulation Scenarios 3
Fig. 2: Structure of the SEP information model.
2.2 Semantic Media Wiki
To specify concrete simulation scenarios, applicable simulation models have to be
selected and coupled based on the high-level scenarios modeled in the information
model. To support this process, a Semantic MediaWiki (SMW) is used to collect
available simulation models in a catalog. The catalog in the SMW is used to
facilitate the participation of users without experiences in ontologies.
2.3 Example Query
The use of ontologies provides the structure for querying the content of the
information model and the catalog in the SMW with SPARQL. Thus, the devel-
opment of simulation scenarios can be assisted in several ways.
?imAttribute wikiCategory:FMIVariable wikiCategory:Component
rdf:type rdf:type rdf:type
?attribute imDB:unit ?unit fmi:unit ?fmiVar wiki:fmiVariables ?component
information model wiki
Fig. 3: Visualization of example query.
In figure 3 an example query is visualized. It assists the user in finding simula-
tion models suitable for the high-level scenario defined in the information model.
Manually done, this can be a complex task because there may be a vast amount
of simulation models available which are usually developed by the domain ex-
perts and not the simulation experts. For this query, the attributes defined in
the information model (?attribute) have to be annotated with a unit (?unit) to
4 J. Schwarz and S. Lehnhoff
find matching FMI variables (?fmiVar ) and the corresponding simulation models
(?component) from the catalog in the SMW.
Based on the information model structure the user can also be assisted in the
planning of the evaluation of the high-level scenario. Especially, in a large sce-
nario with many objects, queries can show objects with missing in- and outputs
and offer recommendations. Additionally, the simulation models in the SMW can
be queried to assist the coupling. For this, the technical interfaces and charac-
teristics of the simulation models stored in the catalog in the SMW are checked
for compatibility.
3 Conclusion
In this paper we proposed an approach for the use of ontologies for development
of smart grid co-simulation scenarios to assist the stakeholder in this process.
Our approach provides ontology-based structures for the modeling in an inter-
disciplinary context and allows the reuse of existing knowledge from external
ontologies. It can be instantiated in a mind map in collaboration of interdisci-
plinary domain experts and permits the integration of external ontologies for
definition of terms and referencing external works. Additionally, a catalog of
simulation components in the SMW has been developed, which can also be in-
tegrated for querying in order to assist the simulation expert in finding suitable
simulation models for the specification of co-simulation scenarios.
This approach was developed and used in the project NEDS. It was used to
assist the development of interdisciplinary future scenarios for the power supply
of the German federal state Lower Saxony and the following simulation and
sustainability evaluation of the scenarios [3].
ACKNOWLEDGEMENTS
The work is part of the research project ’NEDS – Nachhaltige Energieversorgung
Niedersachsen’, which is supported by the Lower Saxony Ministry of Science and
Culture through the ’Niedersächsisches Vorab’ grant program (grant ZN3043).
References
1. Rijgersberg, H., Van Assem, M., Top, J.: Ontology of units of measure and related
concepts. Semantic Web 4(1), 3–13 (2013). https://doi.org/10.3233/SW-2012-0069
2. Schlögl, F., Rohjans, S., Lehnhoff, S., Velasquez, J., Steinbrink, C., Palensky, P.:
Towards a Classification Scheme for Co-Simulation Approaches in Energy Systems.
International Symposium on Smart Electric Distribution Systems and Technologies.
IEEE/IES pp. 2–7 (2015). https://doi.org/10.1109/SEDST.2015.7315262
3. Schwarz, J.S., Witt, T., Nieße, A., Geldermann, J., Lehnhoff, S., Sonnenschein,
M.: Towards an integrated sustainability evaluation of energy scenarios with au-
tomated information exchange. In: Proceedings of the 6th International Confer-
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