Cornelius Steinbrink

Integrated Smart Grid simulations for generic automation architectures with RT-LAB and mosaik

Although, a variety of established tools for analysis of power systems already exists, it is in the medium term very unlikely that one of these tools alone will provide all functionalities and models that are required to simulate future Smart Grids in all its facets. This is mainly due to the high number of Smart Grid use cases, actors, and technologies to be integrated that is not known from other industries so far. Accordingly, a mixture of various different and established tools will be required. These, again, have to be composed in use cases specific to complex and system-wide scenarios. Therefore, tools such as simulation platforms and suites are required that are additionally capable of integrating software and hardware models and components. Therefore, the proposed approach is an integrated concept allowing for analyzing large-scale scenarios taking into consideration both, stationary and dynamic simulations in real-time.

Towards a classification scheme for co-simulation approaches in energy systems

Simulations become more and more crucial in the field of future energy systems. This is caused by the increasing complexity of energy systems that consist of a variety of subsystems such as supply infrastructures, production, consumption, markets, communication, meteorology etc. Co-simulation tools provide the possibility to combine models of these subsystems and run them in a coordinated simulation. However, such simulations become more and more complex, making it improbable that the user of a simulation is the same person that develops the simulation system. To facilitate the communication between users and developers of co-simulation tools and to help the user to find the suitable software for his purpose, the authors suggest a typification of co-simulation tools. This is done by identifying the most relevant attributes each specified by a set of possible configurations. The utilization of the developed schemed is demonstrated by applying it to the mosaik co-simulation framework.

Challenges and necessity of systematic uncertainty quantification in smart grid co-simulation

The increasing installation of renewable energy generation requires the integration of new automation and communication components into a (smart) power grid. This, in turn, requires rigorous testing of these components and their interaction in order to guarantee safe, reliable energy supply. Co-simulation will become more and more important as means of testing since smart grids are multi-domain systems and as such too complex for one expert to model and analyze. However, simulation always carries uncertainty, which might defeat the purpose of testing safety-critical systems if not considered properly. The quantification of this uncertainty is of paramount importance for the design of reliable testing frameworks. Since this issue has not yet gained much attention in the smart grid simulation community, this paper presents an exemplary uncertainty quantification of a grid simulation to underline the acuteness of the issue. The groundwork of an uncertainty analysis framework for co-simulation is presented and further requirements of such a framework are discussed.

Simulation-based validation of smart grids - status quo and future research trends

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.

Ensemble-Based Uncertainty Quantification for Smart Grid Co-simulation

Coupling of independent models in the form of a co-simulation is a rather new approach for design and analysis of Smart Grids. However, uncertainty of model parameters and outputs decreases the significance of simulation results. Therefore, this paper presents an ensemble-based uncertainty quantification system as an extension to the already existing co-simulation framework mosaik.

Smart grid co-simulation with MOSAIK and HLA: a comparison study

Evaluating new technological developments for energy systems is becoming more and more complex. The overall application environment is a continuously growing and interconnected cyber-physical system so that analytical assessment is practically impossible to realize. Consequently, new solutions must be evaluated in simulation studies. Due to the interdisciplinarity of the simulation scenarios, various heterogeneous tools must be connected. This approach is known as co-simulation. During the last years, different approaches have been developed or adapted for applications in energy systems. In this paper, two co-simulation approaches are compared that follow generic, versatile concepts. The tool mosaik, which has been explicitly developed for the purpose of co-simulation in complex energy systems, is compared to the High Level Architecture (HLA), which possesses a domain-independent scope but is often employed in the energy domain. The comparison is twofold, considering the tools’ conceptual architectures as well as results from the simulation of representative test cases. It suggests that mosaik may be the better choice for entry-level, prototypical co-simulation while HLA is more suited for complex and extensive studies.

Design of experiments aided holistic testing of cyber-physical energy systems

The complex and often safety-critical nature of cyber-physical energy systems makes validation a key challenge in facilitating the energy transition, especially when it comes to the testing on system level. Reliable and reproducible validation experiments can be guided by the concept of design of experiments, which is, however, so far not fully adopted by researchers. This paper suggests a structured guideline for design of experiments application within the holistic testing procedure suggested by the European ERIGrid project. In this paper, a general workflow as well as a practical example are provided with the aim to give domain experts a basic understanding of design of experiments compliant testing.

Quantifying probabilistic uncertainty in smart grid co-simulation

Co-simulation is a promising approach for the development of cyber-physical systems like smart grids, but the inherent uncertainty of simulation models is a crucial problem. Worst-case estimations of uncertain simulation scenarios may be obtained rather easily. However, the common demand for optimization usually requires probabilistic information about the analyzed system. The paper at hand presents an approach for the quantification of probabilistic uncertainty in arbitrary smart grid co-simulation scenarios. A software prototype has been implemented as an extension to the co-simulation framework MOSAIK.

Towards Smart Grid system validation: Integrating the SmartEST and the SESA laboratories

The evolution of the European electrical energy system has been in progress for several years now. During this process the complexity of the overall power system has been continuously increasing. Installing new components and concepts into the interrelated infrastructure is getting more complicated as their impacts are hard to predict. Moreover, the energy system is a critical infrastructure that cannot be jeopardized by components with unclear behavior. Thus, new approaches have to be tested and validated in complex, large-scale co-simulations. In this paper an integration of two different laboratory infrastructures is introduced that enables such co-simulation analysis. On the one hand, the SmartEST laboratory in Austria is focusing on distributed energy resources, power electronic components as well as their integration issues. The SESA laboratory in Germany, on the other hand, addresses mainly hard- and software simulation integration.

Validating Intelligent Power and Energy Systems { A Discussion of Educational Needs

Traditional power systems education and training is flanked by the demand for coping with the rising complexity of energy systems, like the integration of renewable and distributed generation, communication, control and information technology. A broad understanding of these topics by the current/future researchers and engineers is becoming more and more necessary. This paper identifies educational and training needs addressing the higher complexity of intelligent energy systems. Education needs and requirements are discussed, such as the development of systems-oriented skills and cross-disciplinary learning. Education and training possibilities and necessary tools are described focusing on classroom but also on laboratory-based learning methods. In this context, experiences of using notebooks, co-simulation approaches, hardware-in-the-loop methods and remote labs experiments are discussed.