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

P. Kotsampopoulos, N. Hatziargyriou, T. I. Strasser, C. Moyo, S. Rohjans, C. Steinbrink, P. Palensky, A. A. van der Meer, Daniel Esteban Morales Bondy, Kai Heussen, M. Calin, A. M. Khavari, M. Sosnina, J. E. Rodriguez, Graeme M. Burt

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

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    Abstract

    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-inthe-loop methods and remote labs experiments are discussed.
    Original languageEnglish
    Title of host publicationProceedings of 8th International Conference on. Industrial Applications of Holonic and Multi-Agent Systems
    Number of pages13
    Publication date2017
    Pages200-212
    DOIs
    Publication statusPublished - 2017
    Event8th International Conference on. Industrial Applications of Holonic and Multi-Agent Systems - Lyon, France
    Duration: 28 Aug 201730 Aug 2017
    Conference number: 8

    Conference

    Conference8th International Conference on. Industrial Applications of Holonic and Multi-Agent Systems
    Number8
    Country/TerritoryFrance
    CityLyon
    Period28/08/201730/08/2017
    SeriesLecture Notes in Computer Science
    Volume10444
    ISSN0302-9743

    Keywords

    • Cyber-Physical Energy Systems
    • Education
    • Learning
    • Smart grids
    • Training
    • Validation

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