Probabilistic Reliability Analysis of Power Systems

Bart W. Tuinema received his B.Sc. and M.Sc. degrees from Delft University of Technology, in 2007 and 2009 respectively. In 2010, he joined the Intelligent Electrical Power Grids group of the Electrical Sustainable Energy department at the same institution as a Ph.D. researcher. In his Ph.D. research, he studied the reliability of power systems with respect to new developments like EHV underground cables and networks for large-scale offshore wind energy. He is currently working in the same group as a postdoc researcher, was involved in the MIGRATE project (Massive InteGRATion of power Electronic devices), and is currently involved in the TSO2020 project (Electric "Transmission and Storage Options" along TEN-E and TEN-T corridors for 2020).
José Luis Rueda Torres received the Electrical Engineer Diploma from Escuela Politécnica Nacional, with cum laude honors in 2004. In November 2009, he received his Ph.D. degree in electrical engineering from the National University of San Juan, where he had studied with a scholarship from DAAD. In March 2014, he started as an Assistant Professor for Intelligent Electrical Power Grids at the Department of Electrical Sustainable Energy, Technical University Delft. In April 2018, he was promoted to Associate Professor. He has taken part in various professional activities including chairing or vice-chairing various committees and working groups, being on conference boards, and working as associate editor for the 'Swarm and Evolutionary Computation Journal'. His current research interests include power system reliability, modelling for stability studies (off-line and real-time digital simulation), optimal control design, and renewable energy technologies.
Alexandru Stefanov is currently Assistant Professor of Intelligent Electrical Power Grids at the Department of Electrical Sustainable Energy, Delft University of Technology (TU Delft), the Netherlands. His research interests are resilience of cyber-physical energy systems and cyber security for power grids. He holds the registered professional title of Chartered Engineer (CEng MIEI) from the Institution of Engineers of Ireland. He is member of the IEEE and regular member of CIGRE Working Group C2.25 on Power System Operational Resilience. He worked as Senior Engineer from 2018 until 2019 at NovoGrid Ltd. in Dublin, Ireland. Previously, he worked as Professional Engineer from 2015 until 2018 in the Operations Department at ESB Networks; the distribution system operator in Ireland. He has postdoctoral research experience and graduated his PhD in Power Systems (summa cum laude 2015) from University College Dublin, Ireland. He graduated his M.Sc. and B.Sc. in Power Systems Engineering from University Politehnica of Bucharest (summa cum laude 2011 and 2009, respectively), Romania.
Francisco M. Gonzalez-Longatt is currently full professor in electrical power engineering at Institutt for elektro, IT og kybernetikk, Universitetet i Sørøst-Norge, Norway. His academic qualifications include first Class Electrical Engineering of Instituto Universitario Politécnico de la Fuerza Armada Nacional, Venezuela (1994), Master of Business Administration (Honors) of Universidad Bicentenaria de Aragua, Venezuela (1999), PhD in Electrical Power Engineering from the Universidad Central de Venezuela (2008) and Postgraduate Certificate in Higher Education Professional Practice from Coventry University (2013) and Diploma in Leadership and Management (ILM Level 3), Loughborough University (2018). He is a former a Lecturer in Electrical Power System at Loughborough University (2013-2019). He is Vice-President of Venezuelan Wind Energy Association, Fellow of the Higher Education Academy (UK), Senior Member of the IEEE, member of The Institution of Engineering and Technology - The IET (UK) and member of International Council on Large Electric Systems -CIGRE. His research interests include innovati

Introduction.- Power System Failures.- Reliability Models of Components.- Reliability Models of Small Systems.- Reliability Models of Large Systems.- Probabilistic Optimal Power Flow.- Conclusion.