Dominik Vereno, Katharina Polanec, Jounes-Alexander Gross, Christoph Binder, Christian Neureiter
{"title":"Introducing a Three-Layer Model Taxonomy to Facilitate System-of-Systems Co-Simulation","authors":"Dominik Vereno, Katharina Polanec, Jounes-Alexander Gross, Christoph Binder, Christian Neureiter","doi":"10.1002/iis2.13264","DOIUrl":null,"url":null,"abstract":"<p>The growing demand for efficient, resilient, and sustainable electricity infrastructure has led to the emergence of smart grids as cyber-physical systems of systems. Co-simulation has proven an effective tool for their analysis and validation by coordinating independent subsystem simulations. However, the reuse and integration of diverse models in co-simulation poses challenges, requiring compatibility and integration efforts. In response, this paper proposes a model taxonomy with the purpose of facilitating co-simulation; it comprises three layers: concrete-instance models, abstract-instance models, and type models. The taxonomy contributes to the creation of independently developed models that can be seamlessly integrated into a coupled co-simulation. Furthermore, it reflects the emergence of digital twins in smart grid engineering by the explicit distinction of abstract and concrete instances. The three-layer taxonomy was derived and validated through a case study on co-simulation of electric-vehicle charging infrastructure. The research further analyzes and formalizes three modeling-and-simulation challenges framed through the lens of the taxonomy: the integration of models across all three layers, the merging of layers, and the consolidation of instance models to craft joint co-simulation scenarios. Finally, three concrete recommendations for research and industrial practice are given. Thereby, the study contributes to the efficient and effective model-based validation of cyber-physical systems of systems using co-simulation.</p>","PeriodicalId":100663,"journal":{"name":"INCOSE International Symposium","volume":"34 1","pages":"2202-2216"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"INCOSE International Symposium","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/iis2.13264","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The growing demand for efficient, resilient, and sustainable electricity infrastructure has led to the emergence of smart grids as cyber-physical systems of systems. Co-simulation has proven an effective tool for their analysis and validation by coordinating independent subsystem simulations. However, the reuse and integration of diverse models in co-simulation poses challenges, requiring compatibility and integration efforts. In response, this paper proposes a model taxonomy with the purpose of facilitating co-simulation; it comprises three layers: concrete-instance models, abstract-instance models, and type models. The taxonomy contributes to the creation of independently developed models that can be seamlessly integrated into a coupled co-simulation. Furthermore, it reflects the emergence of digital twins in smart grid engineering by the explicit distinction of abstract and concrete instances. The three-layer taxonomy was derived and validated through a case study on co-simulation of electric-vehicle charging infrastructure. The research further analyzes and formalizes three modeling-and-simulation challenges framed through the lens of the taxonomy: the integration of models across all three layers, the merging of layers, and the consolidation of instance models to craft joint co-simulation scenarios. Finally, three concrete recommendations for research and industrial practice are given. Thereby, the study contributes to the efficient and effective model-based validation of cyber-physical systems of systems using co-simulation.