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2018-09-30
Arjen van der Meer, Peter Palensky, Kai Heussen, D. E. Morales Bondy, Oliver Gehrke, C. Steinbrinki, M Blanki, Sebastian Lehnhoff, Edmund Widl, Cyndi Moyo et al..  2017.  Cyber-physical energy systems modeling, test specification, and co-simulation based testing. Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES), 2017 Workshop on. :1–9.

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.

Panos Kotsampopoulos, Nikos Hatziargyriou, Thomas Strasser, Cyndi Moyo, Sebastian Rohjans, Cornelius Steinbrink, Sebastian Lehnhoff, Peter Palensky, Arjen van der Meer, D. E. Morales Bondy.  2017.  Validating Intelligent Power and Energy Systems–A Discussion of Educational Needs. International Conference on Industrial Applications of Holonic and Multi-Agent Systems. :200–212.

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.