Validating intelligent power and energy systems – A discussion of educational needs

Panos Kotsampopoulos, Nikos Hatziargyriou, T. I. Strasser*, Cyndi Moyo, Sebastian Rohjans, C Steinbrink, Sebastian Lehnhoff, P. Palensky, A. A. van der Meer, D. E. Morales Bondy, K. Heussen, Mihai Calin, A. Khavari, M. Sosnina, J. E. Rodriguez, G. M. Burt

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationIndustrial Applications of Holonic and Multi-Agent Systems - 8th International Conference, HoloMAS 2017, Proceedings
Place of PublicationCham
Number of pages13
ISBN (Electronic)978-3-319-64635-0
ISBN (Print)978-3-319-64634-3
Publication statusPublished - 2017
EventHoloMAS 2017: 8th International Conference on Industrial Applications of Holonic and Multi-Agent Systems - Lyon, France
Duration: 28 Aug 201730 Aug 2017
Conference number: 8

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10444 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceHoloMAS 2017


  • Cyber-physical energy systems
  • Education
  • Learning
  • Smart grids
  • Training
  • Validation


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