Kotsampopoulos, P.Hatziargyriou, N.Strasser, T. I.Moyo, C.Rohjans, S.Steinbrink, C.Lehnhoff, S.Palensky, P.van der Meer, A. A.Morales Bondy, D. E.Heussen, K.Calin, M.Khavari, A.Sosnina, M.Rodriguez, J. E.Burt, G. M.Strasser, ThomasWahlster, WolfgangMarik, VladimirKadera, Petr2024-07-242024-07-242017Kotsampopoulos , P , Hatziargyriou , N , Strasser , T I , Moyo , C , Rohjans , S , Steinbrink , C , Lehnhoff , S , Palensky , P , van der Meer , A A , Morales Bondy , D E , Heussen , K , Calin , M , Khavari , A , Sosnina , M , Rodriguez , J E & Burt , G M 2017 , Validating intelligent power and energy systems – A discussion of educational needs . in T Strasser , W Wahlster , V Marik & P Kadera (eds) , Industrial Applications of Holonic and Multi-Agent Systems - 8th International Conference, HoloMAS 2017, Proceedings . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 10444 LNAI , Springer Verlag , pp. 200-212 , 8th International Conference on Industrial Applications of Holonic and Multi-Agent Systems, HoloMAS 2017 , Lyon , France , 28/08/17 . https://doi.org/10.1007/978-3-319-64635-0_15conference97833196463430302-9743https://hdl.handle.net/11556/1804Publisher Copyright: © Springer International Publishing AG 2017.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.13enginfo:eu-repo/semantics/openAccessconference output10.1007/978-3-319-64635-0_15Cyber-physical energy systemsEducationLearningSmart gridsTrainingValidationTheoretical Computer ScienceGeneral Computer ScienceSDG 4 - Quality Educationhttp://www.scopus.com/inward/record.url?scp=85028463371&partnerID=8YFLogxK