With the transition towards a smart grid, the power system has become strongly intertwined with the information and communication technology (ICT) infrastructure. The interdependency of both domains requires a combined analysis of physical and ICT processes, but simulating these together is a major challenge due to the fundamentally different modeling and simulation concepts. After outlining these challenges, such as time synchronization and event handling, this manuscript presents an overview of state-of-the-art solutions to interface power system and ICT simulators. Due to their prominence in recent research, a special focus is set on co-simulation approaches and their challenges and potentials. Further, two case studies analyzing the impact of ICT on applications in power system operation illustrate the necessity of a holistic approach and show the capabilities of state-of-the-art co-simulation platforms.@en

The energy system of the future is expected to be composed of a large variety of technologies and applications. However, the diverse nature of these components, their interlinked topology, and the sheer size of the system lead to an unprecedented level of complexity. Industry is confronted with severe problems in designing interoperable grid components, analyzing system stability, and improving efficiency. This paper describes the main challenges of continuous time-based and discrete event-based models of such cyber-physical energy systems. Using a characteristic test model, the scalability of the two approaches is analyzed. The results show the strengths and weaknesses of these two fundamentally different modeling principles that need to be considered when working with large scale cyber-physical energy systems.@en

Worldwide, cities are nowadays formulating their own sustainability goals, including ambitious targets related to the generation and consumption of energy. In order to support decision makers in reaching these goals, energy experts typically rely on simulation models of urban energy systems, which provide a cheap and efficient way to analyze potential solutions. The availability of high-quality, well-formatted and semantically structured data is a crucial prerequisite for such simulation-based assessments. Unfortunately, best practices for data modelling are rarely utilized in the context of energy-related simulations, so data management and data access often become tedious and cumbersome tasks. However, with the steady progress of digitalization, more and more spatial and semantic city data also become available and accessible. This paper addresses the challenge to represent these data in a way that ensures simulation tools can make use of them in an efficient and user-friendly way. Requirements for an effective linking of semantic 3D city models with domain-specific simulation tools are presented and discussed. Based on these requirements, a software prototype implementing the required functionality has been developed on top of the CityGML standard. This prototype has been applied to a simple yet realistic use case, which combines data from various sources to analyze the operating conditions of a gas network in a city district. The aim of the presented approach is to foster a stronger collaboration between experts for urban data modelling and energy simulations, based on a concrete proof-of-concept implementation that may serve as an inspiration for future developments. @en

Due to the increased deployment of renewable energy sources and intelligent components the electric power system will exhibit a large degree of heterogeneity, which requires inclusive and multi-disciplinary system assessment. The concept of co-simulation is a very attractive option to achieve this; each domain-specific subsystem can be addressed via its own specialized simulation tool. The applicability, however, depends on aspects like standardised interfaces, automated case creation, initialisation, and the scalability of the co-simulation itself. This work deals with the inclusion of the Functional Mock-up Interface for co-simulation into the DIgSILENT PowerFactory simulator, and tests its accuracy, implementation, and scalability for the grid connection study of a wind power plant. The coupling between the RMS mode of PowerFactory and MATLAB/Simulink in a standardised manner is shown. This approach allows a straightforward inclusion of black-boxed modelling, is easily scalable in size, quantity, and component type.@en

Simulation-based assessments are a cost- and time-effective way of evaluating various aspects of large energy systems. For instance, they can help in the design process of energy systems, where they provide insights into technical or economic questions. Or they can be used for developing operational strategies and controllers to increase the efficiency of energy systems. In the case of integrated urban energy systems, simulation-based assessments still remain challenging due to their complex requirements, from both a methodological as well as a technical perspective. This is not only due to the size of the considered systems but also due to the fact that they comprise and integrate subsystems that are related to different engineering domains (e.g., electric grids and heat networks) and different stakeholders. Nevertheless, recent work has demonstrated how innovative simulation approaches can be successfully utilized in this context, enabling detailed multi-domain assessments for urban energy systems. However, not only models and tools are necessary for such complex simulation based assessments. Issues related to data availability and reproducibility are of equal importance, in order to set up simulations and compare results. And, with the help of proper methodologies, it is possible to exploit synergies between complementary simulation approaches for holistic assessments. Within this context, this paper highlights recent developments from research projects that target these issues. The examples demonstrate how these new approaches help in understanding the associated risks and potentials, paving the way for early adopters to implement innovative concepts in the context of integrated urban energy systems.@en

Distributed computing offers many advantages for all types of computational applications. Realizing heterogeneous simulation platforms may benefit from many facilities of distributed computing. However, distributing simulation components over a network raises many challenges concerning communications, data exchange, numerical stabilities and others. A well-known solution that addresses some of these challenges is the High Level Architecture (HLA). The HLA is an industry standard for distributed simulation and interoperability. So far the HLA has been used in industry for Discrete Event Simulations (DES). In this paper it is presented how the HLA can also be employed for continuous simulations. Two HLA specific algorithms for distributing explicitly coupled continuous simulation components over the network are presented. The simulation components follow the Functional Mock-up Interface (FMI) specification. The FMI is a specification for model exchange and co-simulation among simulation tools. Any simulation component conforming to FMI, generated from any of the more than forty simulation tools1 that are supporting or planning to support the FMI, can be considered in the proposed architecture.@en

In recent years, co-simulation and model exchange approaches have become ever more popular within the context of model-based design and analysis. This trend has led to the development of the Functional Mock-up Interface (FMI) specification—the de facto standard for model exchange and cosimulation— and a growing number of FMI-compliant tools. This paper addresses the FMI-based co-simulation of hybrid models representing closed-loop control systems, where a continuous time-based plant model is connected to a discrete event-driven controller model. The semantics of execution and data flow of such models are discussed and demonstrated with the help of a model that has been inspired by real-world applications. An example illustrates that popular proprietary simulation environments are not necessarily able to properly capture the semantics of these models. Furthermore, it is shown how existing concepts and tools can be successfully applied to implement such simulations properly.@en

In recent years, co-simulation and model exchange approaches have become ever more popular within the context of model-based design and analysis. This trend has led to the development of the Functional Mock-up Interface (FMI) specification—the de facto standard for model exchange and cosimulation— and a growing number of FMI-compliant tools. This paper addresses the FMI-based co-simulation of hybrid models representing closed-loop control systems, where a continuous time-based plant model is connected to a discrete event-driven controller model. The semantics of execution and data flow of such models are discussed and demonstrated with the help of a model that has been inspired by real-world applications. An example illustrates that popular proprietary simulation environments are not necessarily able to properly capture the semantics of these models. Furthermore, it is shown how existing concepts and tools can be successfully applied to implement such simulations properly.@en

The complexity and dynamic nature of laboratory configurations pose a challenge when undertaking joint experiments, involving multiple Research Infrastructures (RIs). In this context, this paper presents an approach towards the automation of Configuration Management (CM) for joint experiments between multiple labs. The objective is to develop a CM workflow, based on the automated generation of individual local signal configurations from a single global experiment configuration. For this reason, a global experiment configuration file which defines signals, their exchange patterns between RIs, and the data transport packages used for the actual exchange is created. Furthermore, typical use cases based on static and dynamic lab configuration are defined and demonstrated using the proposed approach.@en

The complexity and dynamic nature of laboratory configurations pose a challenge when undertaking joint experiments, involving multiple Research Infrastructures (RIs). In this context, this paper presents an approach towards the automation of Configuration Management (CM) for joint experiments between multiple labs. The objective is to develop a CM workflow, based on the automated generation of individual local signal configurations from a single global experiment configuration. For this reason, a global experiment configuration file which defines signals, their exchange patterns between RIs, and the data transport packages used for the actual exchange is created. Furthermore, typical use cases based on static and dynamic lab configuration are defined and demonstrated using the proposed approach.@en

Smart grid systems are characterized by high complexity due to interactions between a traditional passive network and active power electronic components, coupled using communication links. Additionally, automation and information technology plays an important role in order to operate and optimize such cyber-physical energy systems with a high(er) penetration of fluctuating renewable generation and controllable loads. As a result of these developments the validation on the system level becomes much more important during the whole engineering and deployment process, today. In earlier development stages and for larger system configurations laboratory-based testing is not always an option. Due to recent developments, simulation-based approaches are now an appropriate tool to support the development, implementation, and roll-out of smart grid solutions. This paper discusses the current state of simulation-based approaches and outlines the necessary future research and development directions in the domain of power and energy systems.@en

For smart grid assessment one needs to simulate varieties of components in different software environments. However, the existing simulation tools are domain oriented and cannot fulfil this need natively. Therefore, a smart grid simulation environment has to be established with accordingly accurate models for intra and inter-domain elements as well as interfaces and framework for coordination of those models in a holistic scenario. This paper presents part of the development of this smart grid simulation environment by implementing co-simulation interface for PSCAD using the mosaik framework based on functional mock-up interface (FMI). This co-simulation interface is tested using a modified dynamic model of IEEE 9 bus test system simulated in PSCAD while the wind turbine controller is simulated in MATLAB/Simulink. The results show a significant advantage over alternative methods in terms of a reduction in simulation runtime and compatibility with different simulation environments.@en

Work package JRA2 focuses on the development of advanced simulation-based methods to checkand validate smart grid scenarios, configurations and corresponding applications. The main aim isto employ offline simulation of scenarios where a combination of parallel processing, advanced optimization techniques, and design-of-experiments is used to master the system complexity. Secondary targets include the development of methods for HIL application as well as for the assessment of cyber-security concepts. This assessment will cover the following smart grid properties:system stability, system scalability, component interoperability, and information security. Eventuallyit is the goal to explore the operational limits and the sensitivity of these system properties towardssystem parameters.@en

This chapter provides a brief overview of modelling and simulation approaches for smart grid systems. A special focus is put onto the coupling of simulation environments; i.e., the co-simulation of power systems and its components. Furthermore, selected implementations of standardized interfaces for domain simulators covering the domains of power systems and ICT are presented.@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

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

An important prerequisite for the simulation-based assessment of energy systems at urban scale is the availability of high-quality, well-formatted and semantically structured data. Unfortunately, best practices and state-of-the-art approaches for urban data modelling are hardly applied in the context of energy-related simulations, such that data management and data access often become tedious and cumbersome tasks. This paper presents the so-called Simulation Package, i.e., a data model extending the 3D City Database for CityGML, and its derived data access layer, both aiming to bridge this gap between semantic 3D city modelling and simulation in the context of urban energy systems. The feasibility of this approach is demonstrated with the help of a concrete example, where the proposed extension has been implemented and integrated into a simulation toolchain. The aim is that the availability of a common, shared data model and the proof-of-concept implementation will contribute and foster adoption and further improvement in the future.@en

The following topics are dealt with: power system simulation; smart power grids; power system security; cyber-physical systems; power engineering computing; distributed power generation; power grids; digital simulation; security of data; and formal specification.@en

The gradual deployment of intelligent and coordinated devices in the electrical power system needs careful investigation of the interactions between the various domains involved. Especially due to the coupling between ICT and power systems a holistic approach for testing and validating is required. Taking existing (quasi-) standardised smart grid system and test specification methods as a starting point, we are developing a holistic testing and validation approach that allows a very flexible way of assessing the system level aspects by various types of experiments (including virtual, real, and mixed lab settings). This paper describes the formal holistic test case specification method and applies it to a particular co-simulation experimental setup. The various building blocks of such a simulation (i.e., FMI, mosaik, domain-specific simulation federates) are covered in more detail. The presented method addresses most modeling and specification challenges in cyber-physical energy systems and is extensible for future additions such as uncertainty quantification.@en

The gradual deployment of intelligent and coordinated devices in the electrical power system needs careful investigation of the interactions between the various domains involved. Especially due to the coupling between ICT and power systems a holistic approach for testing and validating is required. Taking existing (quasi-) standardised smart grid system and test specification methods as a starting point, we are developing a holistic testing and validation approach that allows a very flexible way of assessing the system level aspects by various types of experiments (including virtual, real, and mixed lab settings). This paper describes the formal holistic test case specification method and applies it to a particular co-simulation experimental setup. The various building blocks of such a simulation (i.e., FMI, mosaik, domain-specific simulation federates) are covered in more detail. The presented method addresses most modeling and specification challenges in cyber-physical energy systems and is extensible for future additions such as uncertainty quantification.@en