Tutorial T2 (Full day)
Probabilistic methods for power system management: state of the art, challenges and perspectives
Organizers:
- Andrea Pitto, Ricerca sul Sistema Energetico – RSE S.p.A.,andrea.pitto@rse-web.it
- Emanuele Ciapessoni, Ricerca sul Sistema Energetico – RSE S.p.A.,emanuele.ciapessoni@rse-web.it
- Pierre Henneaux, Université libre de Bruxelles, Pierre.Henneaux@ulb.ac.be
- Aydogan Ozdemir, Istanbul Technical University, ozdemiraydo@itu.edu.tr
- Ricardo Jorge Bessa, INESC TEC,ricardo.j.bessa@inesctec.pt
- Louis Wehenkel,
- Efthymios Karangelos
Abstract:
The increasing uncertainties in power systems due to the growing penetration of renewables and to market mechanisms as well as the increasing frequency of extreme weather events due to climate changes are major drivers for the application of probabilistic methods in a broad spectrum of activities aiming to assure the continuous operation of power systems: from long-term system development, through mid-term asset management towards short-term operational planning and real-time operation.
The tutorial presents an overview of state-of-art probabilistic methods for the planning and the operation of both transmission and distribution systems, taking into account the uncertainties due to growing penetration of renewables (which need accurate probabilistic modeling for decision-aid problems under risk) as well as the occurrence of extreme contingencies triggered by natural threats. The drawbacks and the limits of conventional methods are discussed and the results of case studies on real world systems are described. After demonstrating the need for probabilistic methods, the tutorial highlights the current barriers for uncertainty modeling in current decision-aid problems under risk and for a practical implementation of these probabilistic risk based approaches in control center environment.
Structure:
| 08:30-09:00 |
Registration |
| 09:00-10:30 |
Introduction (Emanuele Ciapessoni)
Probabilistic reliability analysis for transmission planning (Pierre Henneaux)
Reliability evaluation of active distribution systems (Aydogan Ozdemir) |
| 10:30-10:45 |
Coffee break |
| 10:45-12:15 |
Probabilistic methods for risk-based power system operation (Andrea Pitto) |
| 12:15-12:30 |
Questions and Answers (Emanuele Ciapessoni) |
| 12:30-13:30 |
Light lunch |
| 13:30-15:00 |
Probabilistic forecasting of renewable energy in decision aid problems under risk (Ricardo Jorge Bessa) |
| 15:00-15:15 |
Coffee break |
| 15:15-16:45 |
Challenges for the practical implementation of probabilistic risk-aware reliability management (Louis Wehenkel, Efthymios Karangelos) |
| 16:45-17:00 |
Questions and Answers (Emanuele Ciapessoni) |
Short Biographies:
Emanuele Ciapessoni
Emanuele Ciapessoni, MSc in Physics and PhD. in Computer Science at University of Milan. At present he is Leading Scientist and member of Scientific committee of Ricerca sul Sistema Energetico – RSE S.p.A. in 2011. His research activities concern risk evaluation and resilience of the power systems. He serves as Chair of Italian Electrotechnical Committee CT65 and SC65A on system automation and he contributes to the National regulation authority, to IEEE and to CIGRE C4.47 working group on power system resilience.
Pierre Henneaux
Pierre Henneaux received the M.Sc. degree in engineering physics and Ph.D. degree in applied sciences from the Université Libre de Bruxelles, Brussels, Belgium, in 2009 and 2013, respectively. He is now an associate professor with the Université Libre de Bruxelles and a key expert in power system planning and power system reliability with Tractebel, Brussels, Belgium. His research interests deal mainly with power system planning, power system security and power system adequacy.
Aydogan Ozdemir
Aydogan Ozdemir has received his Ph.D. degree in Electrical Engineering from Istanbul Technical University, Istanbul-TURKEY in 1990. He is currently Professor at Istanbul Technical University. His current research interests are in the area of electric power system with emphasis on reliability analysis, intelligent system applications in power systems and high-voltage engineering. He is a senior member of IEEE.
Andrea Pitto
Andrea Pitto (IEEE SM ‘16) got his M.Sc. degree (2005) and PhD (2009) in Electrical Engineering from the University of Genoa (Italy), where he worked as a research assistant in 2009-2010. He joined Ricerca sul Sistema Energetico – RSE S.p.A. in 2011. Active member of the IEEE Working Groups on cascading failures and on common mode dependent outages, and of CIGRE Working Group C4.47 on power system resilience. His interests concern probabilistic risk-based approaches to power system resilience assessment.
Riccardo Bessa
Ricardo Bessa: 5-year degree from the Faculty of Engineering of the University of Porto (FEUP) in 2006 in Electrical and Computer Engineering. M.Sc. degree in Data Analysis and Decision Support Systems on the Faculty of Economics of the University of Porto in 2008. Ph.D. degree in Sustainable Energy Systems at FEUP in 2013. Currently, he is Assistant Coordinator at INESC TEC in its Center for Power and Energy Systems.
Louis Wehenkel
Louis Wehenkel graduated in Electrical Engineering (Electronics) in 1986 and received the Ph.D. degree in 1990, both from the University of Liège (Belgium), where he is full Professor of Electrical Engineering and Computer Science. His research interests regard stochastic methods for systems and modeling, optimization, machine learning and data mining, with applications in complex systems, in particular large scale power systems planning, operation and control, industrial process control, bioinformatics and computer vision.
Efthymios Karangelos
Efthymios Karangelos received the Diploma in Mechanical Engineering (Energy) from the National Technical University of Athens (Greece) in 2005, the MS.c degree in Power System Economics and the Ph.D degree in Electrical Engineering both from the University of Manchester (UK) in 2008 and 2012 respectively. Presently, he is a post-doctoral researcher at the Montefiore Institute, University of Liège where his research focuses on probabilistic methods for power systems planning and operations.
