Nikolaos Paterakis is assistant professor of Power System Optimization and Electricity Markets with the research group Electrical Energy Systems at the TU/e department of Electrical Engineering. His research interests include applications of optimization and machine learning techniques in power system and electricity market problems, focusing mainly on the integration of renewables and smart grid enabling technologies. He has authored and co-authored more than 50 publications in related topics.
Nikolaos Paterakis studied at the Department of Electrical and Computer Engineering of the Aristotle University of Thessaloniki (Greece), where he received his Dipl.Eng. degree in 2013. In September 2013, he joined the Department of Electromechanical Engineering at the University of Beira Interior (Covilhã, Portugal). In 2015, he received his PhD in Industrial Engineering and Management (cum laude), working in the EU FP7 Project SiNGULAR. He then became a post-doctoral fellow at the department of Electrical Engineering at Eindhoven University of Technology (TU/e, The Netherlands). In 2015 and 2016 he also was a consultant engineer in a research project funded by the Energy Market Regulatory Authority of Turkey (EPDK) where he worked closely with the Bosporus Distribution System Operator (Istanbul, Turkey). In 2017, he was appointed assistant professor in Power System Optimization and Electricity Markets with the research group Electrical Energy Systems at TU/e.
Coordination for prosumers' electricity trading agents via distributed optimization2nd International Conference on Smart Energy Systems and Technologies, SEST 2019 (2019)
Economic viability of smart charging EVs in the Dutch ancillary service markets2nd International Conference on Smart Energy Systems and Technologies, SEST 2019 (2019)
A hybrid robust-stochastic approach for the day-ahead scheduling of an EV aggregator2019 IEEE Milan PowerTech, PowerTech 2019 (2019)
Automated negotiations under user preference uncertainty6th International Conference on Agreement Technologies, (AT2018) (2019)
Novel incentive mechanism for end-users enrolled in DLC-based demand response programs within stochastic planning contextIEEE Transactions on Industrial Electronics (2019)
Current Educational Activities
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