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

被引:1
作者
Oudart, David [1 ,2 ]
Cantenot, Jerome [1 ]
Boulanger, Frederic [3 ]
Chabridon, Sophie [2 ]
机构
[1] EDF R&D, Palaiseau, France
[2] Inst Polytech Paris, Telecom SudParis, CNRS, SAMOVAR, Paris, France
[3] Univ Paris Saclay, CentraleSupelec, CNRS, LRI, Paris, France
来源
PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON MODEL-DRIVEN ENGINEERING AND SOFTWARE DEVELOPMENT (MODELSWARD) | 2020年
关键词
Cosimulation; FMI; IT; MDE; Smart Grid; Cyber-physical System;
D O I
10.5220/0008875400150025
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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.
引用
收藏
页码:15 / 25
页数:11
相关论文
共 22 条
[1]   Engineering Smart Grids: Applying Model-Driven Development from Use Case Design to Deployment [J].
Andren, Filip Proestl ;
Strasser, Thomas I. ;
Kastner, Wolfgang .
ENERGIES, 2017, 10 (03)
[2]  
Awais M.U., 2013, P 2013 WORKSHOP MODE, P1
[3]  
Blochwitz T., 2011, Proceedings of the 8th International Modelica Conference, DOI 10.3384/ecp11063105.
[4]  
Broman David., 2015, Proceedings of the 18th International Conference on Hybrid Systems: Computation and Control, P179, DOI DOI 10.1145/2728606.2728629
[5]   Hybrid co-simulation: it's about time [J].
Cremona, Fabio ;
Lohstroh, Marten ;
Broman, David ;
Lee, Edward A. ;
Masin, Michael ;
Tripakis, Stavros .
SOFTWARE AND SYSTEMS MODELING, 2019, 18 (03) :1655-1679
[6]   High level architecture for simulation: An update [J].
Dahmann, JS ;
Morse, KL .
2ND INTERNATIONAL WORKSHOP ON DISTRIBUTED INTERACTIVE SIMULATION AND REAL-TIME APPLICATIONS, PROCEEDINGS, 1998, :32-40
[7]  
Evora-Gomez J., 2019, P 13 INT MOD C, V157, P785, DOI DOI 10.3384/ECP19157785
[8]   Co-Simulation: A Survey [J].
Gomes, Claudio ;
Thule, Casper ;
Broman, David ;
Larsen, Peter Gorm ;
Vangheluwe, Hans .
ACM COMPUTING SURVEYS, 2018, 51 (03)
[9]   Semantic adaptation for FMI co-simulation with hierarchical simulators [J].
Gomes, Claudio ;
Meyers, Bart ;
Denil, Joachim ;
Thule, Casper ;
Lausdahl, Kenneth ;
Vangheluwe, Hans ;
De Meulenaere, Paul .
SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL, 2019, 95 (03) :241-269
[10]  
Guermazi S., 2015, EXE MODELS