Jan Jantzen

Jan Jantzen's biography. SONAR corporal in the submarines 1972 – 1974; MSc in electric power engineering, Technical University of Denmark (DTU), 1979; PhD in Systems Science, DTU, 1982; computer systems developer at LK-NES, 1979 – 1982; visiting researcher at Queen’s University, Canada, 1982 – 1983; computer systems developer at Simcorp 1984 – 1985; visiting researcher at IBM Watson research center, New York, 1986; assistant professor of automatic control at DTU 1986; associate professor at DTU 1990; part-time consultant at Swedish power company Sydkraft 1993 – 1995; resigned from DTU 2008; engineer at the Samso Energy Academy 2008 until present. Visiting Professor at Politecnico di Bari, Italy, three months in 2022. Visiting Professor at the University of the Aegean at Chios Island, Greece, 2003 until present; Adjunct Professor since 2013. Author of Foundations of Fuzzy Control, Wiley, 2007, 2nd ed. in 2013. Member of the corps of external examiners for the engineering programmes in Denmark 2006 until present.

Five recent publications

1. Jozwiak, D., Pillai, J. R., Ponnaganti, P., Bak-Jensen, B., & Jantzen, J. (2023). Optimal Charging and Discharging Strategies for Electric Cars in PV-BESS-Based Marina Energy Systems. Electronics 2023, Vol. 12, Page 1033, 12(4), 1033. https://doi.org/10.3390/ELECTRONICS12041033
2. Hosseini, S. M., Carli, R., Jantzen, J., & Dotoli, M. (2022). Multi-block ADMM Approach for Decentralized Demand Response of Energy Communities with Flexible Loads and Shared Energy Storage System. Proc. 30th Mediterranean Conference on Control and Automation (MED), 67–72.
3. Jozwiak, D., Pillai, J. R., Ponnaganti, P., Bak-Jensen, B., & Jantzen, J. (2021). Smart Island Energy Systems: Case Study of Ballen Marina on Samsø. 2021 International Conference on Smart Energy Systems and Technologies (SEST), 1–6. https://doi.org/10.1109/SEST50973.2021.9543171
4. Scarabaggio, P., Carli, R., Jantzen, J., & Dotoli, M. (2021). Stochastic Model Predictive Control of Community Energy Storage under High Renewable Penetration. Proc. 2021 29th Mediterranean Conference on Control and Automation (MED 2021), June 22-25, Bari, Puglia, Italy, 973–978. https://doi.org/ISBN: 978-0-7381-1098-1
5. Karampotsis, E., Dounias, G., & Jantzen, J. (2019). Machine Learning Approaches for Pap-Smear Diagnosis: An Overview. In G. A. Tsihrintzis, M. Virvou, E. Sakkopoulos, & L. C. Jain (Eds.), Machine Learning Paradigms: Applications of Learning and Analytics in Intelligent Systems (pp. 67–127). Springer. https://doi.org/10.1007/978-3-030-15628-2

Contact email: jj@aegean.gr