Work Package JRA2 has developed advanced simulation-based methods to check and validateSmart Grid scenarios, configurations and applications. The required models cover the various partsof Smart Grids, such as power system infrastructures, control algorithms, communication systems,market aspects or/and external factors like weather and people. The challenge is that the individualmodels of these parts are of very different nature (continuous, discrete, stochastic, etc.). From thetechnical perspective, this challenge has been overcome with the help of offline co-simulation, wherethe most suitable simulation tools for all considered domain can be coupled via the Functional Mockup Interface specification. From the methodological perspective, this challenge has been addressedby basing the work in JRA2 on ERIGrid’s holistic testing procedure.@en

This report summarizes the work conducted within ERIGrid related to an integrated simulation environment for large-scale systems.The main goal of the JRA2 is to develop advanced simulation-based tools and methods to validate Smart Grid scenarios, configurations and applications in con-text of co-simulation. The work done in D-JRA2.1 involved assessment of specialized simulation packages for Smart Grids and to develop tools to couple these simulation packages for co-simulation. New tools and models were also developed as some of the existing tools were not sufficient enough to achieve the appropriate couplings. In D-JRA2.2 co-simulation-based assessment methods were developed to compare the performance between monolithic and co-simulations. In D-JRA2.3 we aim to combine all the work done under WP JRA2 to present an integrated simulation package that can be applied to Large Scale systems. The assessment methods developed in D-JRA2.2 have been tested initially in small systems to measure the performance and identify possible flaws. How-ever, the complexity increases significantly in large scale realistic systems. This report documents the challenges faced when the systems and their models grow larger (i.e., upscaled) and how different large scale specific phenomena and issues were identified. After the identification of the challenges, the assessment methods were modified and packaged into an in-tegrated simulation environment which can be used for scaled out systems. The simulation pack-ages are provided as an addendum along with this report while their details are concisely docu-mented in this report.@en