Jean-Philippe Tavella

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

This paper illustrates how the multi-agent approach, or paradigm, can help in the modeling and the simulation of smart grids in the context of MS4SG (a joint project between LORIA-INRIA and EDF RD for example modeling tools of the power grids, of telecommunication networks, and of the information and decision systems. This paper describes the use of MECSYCO as a valid approach to integrate these heterogeneous models in a multi-agent smart grid simulation platform. Several use cases show the ability of MECSYCO to effectively take into account the requirements of smart grids simulation in MS4SG.

Toward an accurate and fast hybrid multi-simulation with the FMI-CS standard

Multi-simulation in the context of future smart electrical grids consists in associating components modeling different physical domains, but also their local or global control. Our DACCOSIM multi-simulation environment is based on the version 2.0 of the FMI-CS (Functional Mock-up Interface for Co-Simulation) standard maintained by the Modelica Association. It has been specifically designed to run large-scale and complex systems on a single PC or a cluster of multicore nodes. But it is quite challenging to accurately simulate FMUs-composed systems involving predictable and unpredictable events while preserving the system overall performance. This paper presents some additions to the FMI-CS standard aiming to improve the accuracy and the performance of distributed multi-simulations involving a mix of both time steps and various kinds of events. The proposed FMI-CS primitives are explained, as well as the Master Algorithm strategies to exploit them efficiently.

Scaling of Distributed Multi-simulations on Multi-core Clusters

DACCOSIM is a multi-simulation environment for continuous time systems, relying on FMI standard, making easy the design of a multi-simulation graph, and specially developed for multi-core PC clusters, in order to achieve speedup and size up. However, the distribution of the simulation graph remains complex and is still the responsibility of the simulation developer. This paper introduces DACCOSIM parallel and distributed architecture, and our strategies to achieve efficient multi-simulation graph distribution on multi-core clusters. Some performance experiments on two clusters, running up to 81 simulation components (FMU) and using up to 16 multi-core computing nodes, are shown. Performances measured on our faster cluster exhibit a good scalability, but some limitations of current DACCOSIM implementation are discussed.

Smart Grids Simulation with MECSYCO

These demonstrations show the current results of the DEVS-based platform called MECSYCO (Multi-agent Environment for Complex SYstems CO-simulation), formerly named AA4MM (Agents & Artifacts for Multi-Modeling [1]), in the context of smart grids simulation with different use cases based on real scenarios.