Tutorial 1 | 7th October, 9 am – 12.00 noon


Speaker: Patrick O. Glauner

Patrick GLAUNER is a PhD Candidate at the University of Luxembourg working on the detection of electricity theft in emerging markets through Machine Learning. He also holds two adjunct faculty appointments at the Universities of Applied Sciences in Karlsruhe and Trier, Germany. In parallel, he is pursuing an MBA with Smartly. He was previously a Fellow at the European Organization for Nuclear Research (CERN) in Geneva, Switzerland and worked as a visiting researcher at the University of Quebec in Montreal (UQAM). He is an alumnus of the German National Academic Foundation (Studienstiftung des deutschen Volkes). His research was featured in the New Scientist article “AI could put a stop to electricity theft and meter misreadings” and cited in the McKinsey Global Institute discussion paper “Artificial intelligence: The next digital frontier?”. He graduated as valedictorian from Karlsruhe University of Applied Sciences with a BSc in Computer Science and obtained his MSc in Machine Learning from Imperial College London. His current interests include anomaly detection, augmented/virtual reality, biases in data sets, computer vision, deep learning, machine learning, natural language processing and time series analyses.


Title: – Introduction to Machine Learning for Power Engineers


The field of Machine Learning grew out of the quest for artificial intelligence. It gives computers the ability to learn statistical patterns from data without being explicitly programmed. These patterns can then be applied to new data in order to make predictions. Machine Learning also allows to automatically adapt to changes in the data without amending the underlying model. We deal every day dozens of times with Machine Learning applications such as when doing a Google search, using spam filters, face detection, speaking to voice recognition software or when sitting in a self-driving car. In recent years, machine learning methods have evolved in the smart grid community. This change towards analyzing data rather than modeling specific problems has led to adaptable, more generic methods, that require less expert knowledge and that are easier to deploy in a number of use cases. This is an introductory level course to discuss what machine learning is and how to apply it to data-driven smart grid applications. Practical case studies on real data sets, such as load forecasting, detection of irregular power usage and visualization of customer data, will be included. Therefore, attendees will not only understand, but rather experience, how to apply machine learning methods to smart grid data. Further info can be through here.


Tutorial 2| 7th October, 2 pm – 5 pm


Speaker – Prof Ir Dr Mohd Zainal Abd Kadir

Mohd Zainal Abidin Ab Kadir received his B.Eng. in Electrical and Electronic Engineering from Universiti Putra Malaysia (UPM) and Ph.D. degree in High Voltage Engineering from the University of Manchester, U.K. Currently, he is a Strategic Hire Professor at the Institute of Power Engineering (IPE), Universiti Tenaga Nasional (UNITEN) and a Professor at the Faculty of Engineering, Universiti Putra Malaysia. He is the Founding Director at the Centre for Electromagnetic and Lightning Protection Research (CELP), UPM which is regarded as the World Leader in Lightning Safety by the lightning community. He is also an IEEE Power & Energy Society (PES) Distinguished Lecturer in the field of lightning and high voltage engineering. To date he has authored and co-authored over 300 journal and conference papers. He has supervised 17 PhD and 35 MSc students and currently 26 PhD and 10 MSc are on their way. Professor Zainal is a Professional Engineer (PEng) and a Chartered Engineer (CEng), as well as a Senior Member of the Institute of Electrical & Electronics Engineers (IEEE). Currently, he is the Chairman of the National Mirror Committee of IEC TC 81 (Lightning Protection). Apart from that, he is the Local Convener of MNC-CIGRE C4 on System Technical Performance, Past Chair of IEEE Power & Energy Society Malaysia and a Member for various Working Groups. He is also an Advisory Board Member of the National Lightning Safety Institute (NLSI) USA, Research Advisor for the African Centre for Lightning and Electromagnetic (ACLE) and Advisor to many other government agencies such as Sustainable Energy Development Authority (SEDA) and the Energy Commission of Malaysia. His research interests include high voltage engineering, lightning protection, electromagnetic compatibility and power system transients.


Title: Lightning protection for a Large Scale Solar (LSS) PV systems


Over the next decades, research related to the solar photovoltaic (PV) system continues to path its way towards more technological advancement, demand-driven and cost efficient. Studies related to the effects of lightning on PV systems have only begun recently as the researchers realised the damaging consequences to their equipments and systems due to lightning strikes. Since then, a number of studies related to lightning and photovoltaic cells have been conducted due to the interest in the possibility of such systems receiving lightning strikes and the subsequent damage caused. Previous studies through the software and experimental works have shown how the lightning affected the systems and thus influenced the performance of PV systems. High magnitude of a lightning impulse current was applied to PV panels by simulation of a direct lightning strike onto the PV panels. The outcome indicated that the efficiency of the PV panel could be reduced as well as the panels may suffer physical deterioration caused by the high lightning impulse voltage/current. Furthermore, many PV systems may not be properly protected against lightning. Due to this exposure, the PV systems may be liable to suffer a crucial impact in a way that can lead towards severe damage. This kind of destruction will undoubtedly affect the economic aspects or the return on investment that could be earned from PV power generation as well as the cost of repair or replacement to recover from the damage, all of which can be mitigated by implementing a proper and total lightning protection system (LPS). This talk aims to provide fundamental aspects of lightning interaction on PV system and to summarize the lightning protection system requirement according to the standards requirements.