Speaker I
Prof. João P. S. Catalão
IEEE Fellow
University of Porto, Portugal
Research Areas: Power System Operations and Planning, Power System Economics and Electricity Markets, Distributed Renewable Generation, Demand Response and Smart Grid
Biography: João P. S. Catalão is an IEEE Fellow. He received the M.Sc. degree from the Instituto Superior Técnico (IST), Lisbon, Portugal, in 2003, and the Ph.D. degree and Habilitation for Full Professor ("Agregação") from the University of Beira Interior (UBI), Covilha, Portugal, in 2007 and 2013, respectively. Currently, he is a Professor at the Faculty of Engineering of the University of Porto (FEUP), Porto, Portugal. He was the Primary Coordinator of the EU-funded FP7 project SiNGULAR, a 5.2-million-euro project involving 11 industry partners. He has authored or coauthored more than 500 journal publications and 400 conference proceedings papers, with an h-index of 90 and more than 30,000 citations (according to Google Scholar), having supervised more than 120 post-docs, Ph.D. and M.Sc. students, and other students with project grants. He was the General Chair and General Co-Chair of SEST 2019 and SEST 2020, respectively, after being the inaugural Technical Chair and co-founder of SEST 2018. He is a Senior Editor of the IEEE Transactions on Neural Networks and Learning Systems. Furthermore, he is an Associate Editor of nine other IEEE Transactions/Journals. He was an IEEE Computational Intelligence Society (CIS) Fellows Committee Member in 2022 and 2023. He was recognized as one of the Outstanding Associate Editors 2020 of the IEEE Transactions on Smart Grid, and one of the Outstanding Associate Editors 2021 of the IEEE Transactions on Power Systems. He has multiple Highly Cited Papers in Web of Science. He has won 5 Best Paper Awards at IEEE Conferences. Furthermore, he was the recipient of the 2017-2022 (for the sixth consecutive year) FEUP Scientific Recognition Diplomas. His research interests include power system operations and planning, power system economics and electricity markets, distributed renewable generation, demand response, smart grid, and multi-energy carriers.
Breakthroughs and Novel Insights into Demand Response Programs
Abstract: The Clean Energy for all Europeans package and the European Green Deal both put the consumers at the centre of the European Union's energy system. Under the REPowerEU Plan, the European Commission reinforced the need to effectively allow consumers to become fully-fledged actors in the energy market. Digitalization could make it easier for consumers to invest in energy transition, also enabling consumers to actively participate in demand response programs. Demand response is becoming increasingly important to allow for a larger penetration of variable renewables, simultaneously ensuring more flexibility and more resilience. This keynote speech addresses breakthroughs and novel insights into demand response programs, from several theoretical breakthroughs to real-life cases, aiming to increase consumer empowerment.
Speaker II
Prof. Dr. Hulusi Bulent ERTAN
Atilim University, Turkey
Research Areas: Electrical Machines, Smart Grids, Electric Vehicles, Electrical Drive Systems, Power Electronics, Renewable Energy
Biography: H. Bulent Ertan (M’02) received B.S. and M.S. degrees in Electrical and Electronics Engineering in 1971 and 1973 respectively from the Middle East Technical University (METU) in Ankara, Turkey and a Ph.D. degree from the University of Leeds, the UK in 1977.
He directed many industry-supported projects since 1977. He led the Intelligent Energy Conversion Group at TUBITAK (Turkish Scientific and Technological Research Council) Information Technologies and Electronics Research Institute (BILTEN) in Ankara Turkey, between 1999-2006. He was an executive committee member of the Center for Wind Energy, METU and also director of the
Electromechanics laboratory between 2011-2017. Prof. Ertan was chairman of the Mustafa Parlar Education and Research Foundation in 2000 and he was a member of the executive board of this foundation until 2016.
He has published more than 150 journal and conference papers so far. He is co-editor of two books entitled “Modern Electrical Derives”, Kluwer Academic Publishers, Netherlands, 2000 (NATO ASI series) and” Transformers: Analysis Design and Measurement” (CRC Press, 2013). Prof. Ertan is the holder of 5 national and international patents. He received the IEE Overseas Premium award in 1993 and an IEEE award in 2014, for his contributions to the IEEE standard “Trial-use guide for testing permanent
magnet machines”.
Professor Ertan is the founder of the Aegean International Conference on Electrical Machines and Power Electronics (ACEMP). Prof. Ertan is a member of the Turkish Chamber of Electrical Engineers and member of IET (UK) and a senior member of IEEE. He is currently the Mechatronics Engineering Department chair at Atilim University.
Real-Time Rotor position Estimation from Induction Motor Current
Abstract: Field orientation is commonly used in modern electrical drives to obtain superior performance. Such motor drive applications often need instantaneous rotor position information. Rotor position may be detected by using a position sensor of some kind, such as incremental encoders. However, as it is well known this is costly and requires modification to apply existing installations. There are also sensorless vector control methods. Such methods measure the motor current and voltage and estimate the rotor position for field orientation. However, in this case, the drive performance is compromised especially at low speeds the accuracy of the drive is poor in producing the desired torque. Improving the performance of such drives has always been of interest.
There are two main approaches to detecting the rotor position without using a position sensor or modifying the motor. One approach is to inject a high-frequency signal and the other is to make use of existing saliencies of the motor. The focus of this paper is to use the most obvious saliency which exists in any induction motor; the slotting harmonics. Slotting harmonics are commonly used for fault detection purposes. However, the usual approach is to use spectral estimation techniques. this approach requires long sampling and computation periods, in the order of at least several milliseconds. For field orientation purposes it is desirable to detect the rotor position within a control cycle ie in several hundred microseconds.
This paper introduces a novel approach to the position detection problem by identifying the rotor slot harmonics (RHS) in an inverter-driven motor current. The RHS are treated as modulated onto the fundamental current and via demodulation, the RHS and its higher-order harmonics are obtained. The algorithm used for this purpose is fast and can be applied within a typical control cycle of a vector-controlled drive algorithm.
The proposed method is explained in this paper and implemented using higher-order RSH for position prediction. In this manner, the position estimation resolution increases and also possible effects of harmonics stemming from other sources are avoided. Implementation of this approach is described in the presentation and its position prediction performance is evaluated by comparing its predictions with the measured rotor position from an encoder via experiments on a vector-controlled drive.