Multi-agent Multi-Model Simulation of Smart Grids in the MS4SG Project

Vaubourg, Julien; Presse, Yannick; Camus, Benjamin; Bourjot, Christine; Ciarletta, Laurent; Chevrier, Vincent; Tavella, Jean-Philippe; Morais, Hugo

doi:10.1007/978-3-319-18944-4_20

Cited by 18 publications

(17 citation statements)

References 13 publications

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“…Hence, every MECSYCO cosimulations and every DEVS wrappers must be carefully validated and verified in order to bring exploitable results. The verification of the MECSYCO implementation was done empirically through several use cases (notably in collaboration with EDF which was able to check the results against a real system [44], and when studying green cloud computing [43]), but no formal verification were performed.…”

Section: Discussionmentioning

confidence: 99%

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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%

“…GNU/Linux, Mac OS, Microsoft Windows). It is currently used to study green cloud computing [43] and for the M&S of smart electrical grids in the context of a partnership between LORIA/Inria 3 and EDF R&D (main French electric utility company) [44].…”

Section: Generalitiesmentioning

confidence: 99%

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

et al. 2018

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“…Here, the MAS paradigm enables to study how the organisation of a set of agents may affect a decision process. Another example of MAS usage in the context of Smart City is the work of Vaubourg et al [32] that shows how the multi-agent paradigm can be successfully applied for smart grids multi-model simulation. -Problem solving: The MAS paradigm partly emerged from the community working on distributed problem solving.…”

Section: Multi-agents Usage In Smart Citiesmentioning

confidence: 99%

Smart Is a Matter of Context

Nigon¹,

Verstaevel²,

Boes³

et al. 2017

Modeling and Using Context

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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 18916The contribution was presented at CONTEXT 2017 :http://context17.lip6.fr/ Abstract. Smart cities involve, in a large scale, a wide array of interconnected components and agents, giving birth to large and heterogeneous data flows. They are inherently cross-disciplinary, provide interesting challenges, and constitute a very promising field for future urban developments, such as smart grids, eco-feedback, intelligent traffic control, and so on. We advocate that the key to these challenges is the proper modelling and exploitation of context. However, said context is highly dynamic and mainly unpredictable. Improved AI and machine learning techniques are required. Starting from some of the main smart cities features, this paper highlights the key challenges, explains why handling context is crucial to them, and gives some insights to address them, notably with multi-agent systems.

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“…As shown in previous work [6], the platform also supports multi-level modeling. It is currently used for the M&S of smart electrical grids in the context of a partnership between Inria (French IT research institute) and EDF R&D (leading French electric utility company) [24].…”

Section: Presentation Of Mecsyco a Multi-agent Environment For Mandsmentioning

confidence: 99%

“…In previous works on MECSYCO like [24], the authors have created model artifacts for FMUs solely based on the FMI for co-simulation specifications. However as discussed in the following section, wrapping the two FMUs in DEVS in our more complex hybrid context requires defining a sound DEV&DESS model artifact.…”

Section: Operational Specificationsmentioning

confidence: 99%

Hybrid Co-simulation of FMUs using DEV&DESS in MECSYCO

2016

TMS/DEVS Symposium on Theory of Modeling &Amp; Simulation (TMS/DEVS 2016)

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Co-simulation is a key tool in the design and operation of a growing number of complex cyber-systems. But efficiently yet accurately combining continuous time components (such as FMUs) with event-based ones can be challenging, both from a modeling perspective and an operational, tools-oriented one. We propose a platform to tackle this problem building up on MECSYCO, a MAS-based DEVS wrapping platform dedicated to co-simulation. Relying on the ability of DEVS to integrate the DEV&DESS formalism -which offers a sound framework for describing hybrid models-we propose a DEV&DESS wrapper for FMU. This wrapper encapsulates a version of the DEV&DESS simulation algorithm for FMU components which is notably composed of: (1) a forecast strategy which searches for the next state-event; (2) a bisectional algorithm to approach the location of the state-change in an FMU. Our solution is implemented using Java and JavaFMI to control the FMU. Our sample case is the co-simulation of a barrel-filler factory implemented in different FMUs and event-based models. Compared to related works, our proposal is functional, generic, yet evolutionary, and benefits from the strong foundations of

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Multi-agent Multi-Model Simulation of Smart Grids in the MS4SG Project

Cited by 18 publications

References 13 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

Smart Is a Matter of Context

Hybrid Co-simulation of FMUs using DEV&DESS in MECSYCO

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