Efficient Co-simulator Integration with Application to Smart Grids

Abstract

The evolution of the electric power grid towards a"smart grid"is an example of an emerging large-scale cyber-physical system. To study the potential of cyberattacks or other sources of extreme events, high-fidelity co-simulation is the only realistic strategy. In this work, we demonstrate a practical and high-performance co-simulation strategy for smart grids, which provides lessons about co-simulation integration that can be carried over to other cyber-physical systems. Specifically, we present a co-simulation platform based on the Mosaik framework that integrates several federates including OpenDSS for power flow, a refined NS-3 for communication networks, and custom Python-based simulators for on-load tap changer control, distributed state estimation, and data collection. We compare synchronization strategies -- exhaustive lock-step time advancement versus an optimized event-driven approach that exploits lower-bound time stamps (LBTS) and next-event prediction -- and introduce targeted refinements to NS-3 event handling and relevance filtering of internal events. Performance is evaluated on two standard IEEE benchmark systems: the 13-node test feeder with tap-changer voltage regulation and a large-scale 33-bus system augmented with 32 European low-voltage feeders (1,793 nodes total) performing distributed state estimation with thousands of phasors and smart meters. Experimental results demonstrate that the refined event-based synchronization that uses LBTS-based NS-3 event filtering reduces execution time by up to 50% (and more than 4$\times$ in smaller scenarios) compared to na\"ive lock-step methods, while strictly preserving temporal correctness and simulation accuracy. We additionally summarize a domain ontology that standardizes multi-simulator configuration and entity mapping across power, communication, and control domains.