Simulating Modelica models with a Stand-Alone Quantized State Systems Solver

Bergero, Federico; Floros, Xenofon; Pastor, Joaquı́n; Kofman, Ernesto; Cellier, François E.

doi:10.3384/ecp12076237

Cited by 16 publications

(14 citation statements)

References 8 publications

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“…At this point, other QSS versions of the literature [54,55] which can simulate hybrid Modelica models deserve to be cited. Our solver can also simulate models written in Modelica, as soon as they are exported into an FMU-ME.…”

Section: Discussionmentioning

confidence: 99%

Co-simulation of cyber-physical systems using a DEVS wrapping strategy in the MECSYCO middleware

et al. 2018

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Most modeling and simulation (M&S) questions about cyber-physical systems (CPS) require expert skills belonging to different scientific fields. The challenges are then to integrate each domain's tools (formalism and simulation software) within the rigorous framework of M&S process. To answer this issue, we give the specifications of the MECSYCO co-simulation middleware which enables to interconnect several pre-existing and heterogeneous M&S tools, so they can simulate a whole CPS together. The middleware performs the cosimulation in a parallel, decentralized and distributable fashion thanks to its modular multi-agent architecture. In order to rigorously integrate tools which use different formalisms, the co-simulation engine of MECSYCO is based on DEVS. The central idea of MECSYCO is to use a DEVS wrapping strategy to integrate each tool into the middleware. Thus, heterogeneous tools can be homogeneously co-simulated in the form of a DEVS system. By using DEVS, MECSYCO benefits from the numerous scientific works which have demonstrated the integrative power of this formalism and gives crucial guidelines to rigorously design wrappers. We demonstrate that our discrete framework can integrate a vast amount of continuous M&S tools by wrapping the FMI standard. To this end, we take advantage of DEVS efforts of the literature (namely, the DEV&DESS hybrid formalism and QSS solvers) to design DEVS wrappers for FMU components. As a side-effect, this wrapping is not restricted to MECSYCO but can be applied in any DEVS-based platform. We evaluate MECSYCO with the proof of concept of a smart-heating use-case, where we co-simulate non DEVS-centric M&S tools.

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Section: Discussionmentioning

confidence: 99%

Co-simulation of cyber-physical systems using a DEVS wrapping strategy in the MECSYCO middleware

et al. 2018

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“…Later on, the same research group developed a standalone QSS solver with a interface based on a small subset of Modelica (µ-Modelica), and a back-end module for OpenModelica that generates µ-Modelica code from regular Modelica code, see (Bergero et al, 2012).…”

Section: Qss Algorithmsmentioning

confidence: 99%

Simulation of Large-Scale Models in Modelica: State of the Art and Future Perspectives

Casella¹

2015

Linköping Electronic Conference Proceedings

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State-of-the-art Modelica tools are very effective at converting declarative models based on differentialalgebraic equations into ordinary differential equations. However, when confronted with large-scale models of distributed systems with a high number of states (1000 or more) or with large algebraic systems of equations (1000 or more unknowns), they face a number of serious efficiency issues, that hamper their practical use for system design. The paper analyses these issues in detail, points out strategies for improvement, and also introduces a library of scalable test models that can be used to assess existing tools, as well as to help developing advanced solution methods for large-scale systems.

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“…Being a subset of the complete language, µ-Modelica is accepted by all Modelica simulation tools enabling us to simulate the same model both in OpenModelica and in the QSS stand-alone solver. For more information regarding the transformation of Modelica to µ-Modelica models, we refer the reader to [3].…”

Section: Case Studiesmentioning

confidence: 99%

“…The application of QSS methods to Modelica models was studied in [3,10,11], showing the benefits of QSS methods for problems with frequent discontinuities. Also the use of QSS methods (not using Modelica) for a large hybrid sparse load management problem was studied in [18].…”

Section: Related Workmentioning

confidence: 99%

Simulation of Smart-Grid Models using Quantization-Based Integration Methods

Floros¹,

Bergero²,

Ceriani³

et al. 2014

Linköping Electronic Conference Proceedings

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Concepts such as smart grids, distributed generation and micro-generation of energy, market-driven as well as demand-side energy management, are becoming increasingly important and relevant as emerging trends in the design, management and control of energy systems. Appropriate modeling and design, efficient management and control strategies of such systems are currently being studied. In this line of research a very important enabling component is efficient and reliable simulation. However those energy models are typically large, stiff and exhibiting heavy discontinuities, and at the same time consist of interconnected multi-domain subsystems encompassing electrical, thermal, and thermo-fluid models. Object-Oriented (O-O) languages such as Modelica are obviously well-suited for the modeling of such systems; however, traditional state-ofthe-art hybrid differential algebraic equation solvers cannot efficiently simulate these systems especially when their size grows to the order of hundreds, thousands, or even more interconnected units.The goal of this paper is to show, through a couple of exemplary case studies, that Quantized State System (QSS) integration methods are ideally suited to solve models of such systems, as they scale up better than traditional methods with the system size, and provide time savings of several orders of magnitude, while achieving comparable numerical precision.

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Simulating Modelica models with a Stand-Alone Quantized State Systems Solver

Cited by 16 publications

References 8 publications

Co-simulation of cyber-physical systems using a DEVS wrapping strategy in the MECSYCO middleware

Co-simulation of cyber-physical systems using a DEVS wrapping strategy in the MECSYCO middleware

Simulation of Large-Scale Models in Modelica: State of the Art and Future Perspectives

Simulation of Smart-Grid Models using Quantization-Based Integration Methods

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