Kai Heussen

Cornelius Steinbrink, Sebastian Lehnhoff, Sebastian Rohjans et al.

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.

Arjen A. van der Meer, Peter Palensky, Kai Heussen et al.

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.

Thomas I. Strasser, Cyndi Moyo, Roland Bründlinger et al.

Renewables are key enablers in the plight to reduce greenhouse gas emissions and cope with anthropogenic global warming. The intermittent nature and limited storage capabilities of renewables culminate in new challenges that power system operators have to deal with in order to regulate power quality and ensure security of supply. At the same time, the increased availability of advanced automation and communication technologies provides new opportunities for the derivation of intelligent solutions to tackle the challenges. Previous work has shown various new methods of operating highly interconnected power grids, and their corresponding components, in a more effective way. As a consequence of these developments, the traditional power system is being transformed into a cyber-physical energy system, a smart grid. Previous and ongoing research have tended to mainly focus on how specific aspects of smart grids can be validated, but until there exists no integrated approach for the analysis and evaluation of complex cyber-physical systems configurations. This paper introduces integrated research infrastructure that provides methods and tools for validating smart grid systems in a holistic, cyber-physical manner. The corresponding concepts are currently being developed further in the European project ERIGrid.

Panos Kotsampopoulos, Nikos Hatziargyriou, Thomas I. Strasser et al.

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.

Van Hoa Nguyen, Yvon Besanger, Quoc Tuan Tran et al.

The integration of distributed renewable energy sources and the multi-domain behaviours inside the cyber-physical energy system (smart grids) draws up major challenges. Their validation and roll out requires careful assessment, in term of modelling, simulation and testing. The traditional approach focusing on a particular object, actual hardware or a detailed model, while drastically simplifying the remainder of the system under test, is no longer sufficient. Real-time simulation and Hardware-in-the-Loop (HIL) techniques emerge as indispensable tools for validating the behaviour of renewable sources as well as their impact/interaction to with the cyber-physical energy system. This paper aims to provide an overview of the present status-quo of real-time and HIL approaches used for smart grids and their readiness for cyber-physical experiments. We investigate the current limitations of HIL techniques and point out necessary future developments. Subsequently, the paper highlights challenges that need specific attention as well as ongoing actions and further research directions.

Xue Han, Kai Heussen, Oliver Gehrke et al.

Distributed control strategies applied to power distribution control problems are meant to offer robust and scalable integration of distributed energy resources. However, the term "distributed control" is often loosely applied to a variety of very different control strategies. This leads to problems in the design phase as well as with the performance evaluation of such systems. This paper develops a framework to assist the design and evaluation of distributed control strategies, supported by a rigorous taxonomy of control strategies and formal design criteria. The proposed framework and taxonomy are evaluated against the state of the art of control strategies as found in literature.

Kai Heussen, Jawad Kazmi, Narges Mehran et al.

Reproducibility, traceability, and transparency in testing cyber-physical energy systems are crucial for scientific advancement and cross-laboratory collaboration. Current experimentation and test documentation practices lack formal semantics, making it difficult to reproduce experiments, share data, and apply, for example, the artificial intelligence-driven analysis. A dataspace that relies on structured ontologies aims to address these gaps by providing machine-actionable descriptions. In this work, we outline an ontology-driven approach for reproducibility of cyber-physical energy systems testing and illustrate its applicability through representative cross-laboratory use cases, demonstrating feasibility while identifying remaining semantic and metadata gaps that limit reproducibility. Based on these observations, we propose an open three-viewpoint ontology framework to guide future ontology extensions.

Nils Müller, Charalampos Ziras, Kai Heussen

The increasing interaction of industrial control systems (ICSs) with public networks and digital devices introduces new cyber threats to power systems and other critical infrastructure. Recent cyber-physical attacks such as Stuxnet and Irongate revealed unexpected ICS vulnerabilities and a need for improved security measures. Intrusion detection systems constitute a key security technology, which typically monitors cyber network data for detecting malicious activities. However, a central characteristic of modern ICSs is the increasing interdependency of physical and cyber network processes. Thus, the integration of network and physical process data is seen as a promising approach to improve predictability in real-time intrusion detection for ICSs by accounting for physical constraints and underlying process patterns. This work systematically assesses machine learning-based cyber-physical intrusion detection and multi-class classification through a comparison to its purely network data-based counterpart and evaluation of misclassifications and detection delay. Multiple supervised detection and classification pipelines are applied on a recent cyber-physical dataset, which describes various cyber attacks and physical faults on a generic ICS. A key finding is that the integration of physical process data improves detection and classification of all considered attack types. In addition, it enables simultaneous processing of attacks and faults, paving the way for holistic cross-domain root cause identification.

Nils Müller, Carsten Heinrich, Kai Heussen et al.

The continuous electrification of the mobility and heating sectors adds much-needed flexibility to the power system. However, flexibility utilization also introduces new challenges to distribution system operators (DSOs), who need mechanisms to supervise flexibility activations and monitor their effect on distribution network operation. Flexibility activations can be broadly categorized to those originating from electricity markets and those initiated by the DSO to avoid constraint violations. Simultaneous electricity market driven flexibility activations may cause voltage quality or temporary overloading issues, and the failure of flexibility activations initiated by the DSO might leave critical grid states unresolved. This work proposes a novel data processing pipeline for automated real-time identification of fast-ramped flexibility activation events. Its practical value is twofold: i) potentially critical flexibility activations originating from electricity markets can be detected by the DSO at an early stage, and ii) successful activation of DSO-requested flexibility can be verified by the operator. In both cases the increased awareness would allow the DSO to take counteractions to avoid potentially critical grid situations. The proposed pipeline combines techniques from unsupervised detection and open-set classification. For both building blocks feasibility is systematically evaluated and proofed on real load and flexibility activation data.

Arjen van der Meer, Cornelius Steinbrink, Kai Heussen et al.

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.