An Approach to Design Smart Grids and Their IT System by Cosimulation

Oudart, David; Cantenot, Jérôme; Boulanger, Frédéric; Chabridon, Sophie

doi:10.5220/0007407003720379

Cited by 2 publications

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“…All FMUs produced by the different teams must provide interoperable data structures, namely each input should match an output, in type and meaning. An example of a cosimulation approach for smart grids [11] identified several steps and actors involved in such a process. The first step is to define all the connections between the simulation models in order to define the interface of the models for each modeling team.…”

Section: An Approach Based On Model Refinementmentioning

confidence: 99%

The Smart Grid Simulation Framework: Model-Driven Engineering Applied to Cyber-Physical Systems

Oudart

Cantenot

Boulanger

et al. 2021

Communications in Computer and Information Science

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Section: An Approach Based On Model Refinementmentioning

confidence: 99%

The Smart Grid Simulation Framework: Model-Driven Engineering Applied to Cyber-Physical Systems

Oudart

Cantenot

Boulanger

et al. 2021

Communications in Computer and Information Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…An example of a cosimulation approach for smart grids (Oudart et al, 2019) identified several steps and actors involved in such a process. The first step is to define all the connections between the simulation models in order to define the interface of the models for each modeling team.…”

Section: An Approach Based On Model Refinementmentioning

confidence: 99%

A Model based Toolchain for the Cosimulation of Cyber-physical Systems with FMI

Oudart

Cantenot

Boulanger

et al. 2020

Proceedings of the 8th International Conference on Model-Driven Engineering and Software Development

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Smart Grids are cyber-physical systems that interface power grids with information and communication technologies in order to monitor them, automate decision making and balance production and consumption. Cosimulation with the Functional Mock-up Interface standard allows the exploration of the behavior of such complex systems by coordinating simulation units that correspond to the grid part, the communication network and the information system. However, FMI has limitations when it comes to cyber-physical system simulation, particularly because discrete-event signals exchanged by cyber components are not well supported. In addition, industrial projects involve several teams with different skills and methods that work in parallel to produce all the models required by the simulation, which increases the risk of inconsistency between models. This article presents a way to exchange discrete-event signals between FMI artifacts, which complies with the current 2.0 version of the standard. We developed a DSL and a model-based toolchain to generate the artifacts that are necessary to run the cosimulation of the whole system, and to detect potential inconsistencies between models. The approach is illustrated by the use case of an islanded grid implementing diesel and renewable sources, battery storage and intelligent control of the production.

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An Approach to Design Smart Grids and Their IT System by Cosimulation

Cited by 2 publications

References 0 publications

The Smart Grid Simulation Framework: Model-Driven Engineering Applied to Cyber-Physical Systems

The Smart Grid Simulation Framework: Model-Driven Engineering Applied to Cyber-Physical Systems

A Model based Toolchain for the Cosimulation of Cyber-physical Systems with FMI

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