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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Smart grids are the oncoming generation of power grids, which rely on information and communication technologies to tackle decentralized and intermittent energy sources such as wind farms and photovoltaic plants. They integrate electronics, software information processing and telecommunications technical domains. Therefore the design of smart grids is complex because of the various technical domains and modeling tools at stake. In this article, we present an approach to their design, which relies on model driven engineering, executable models and FMI based cosimulation. This approach is illustrated on the use case of an insular power grid and allows to study the impact of power production decisions.
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