Welcome to DARE'16!
Climate change, the depletion of natural resources and rising energy
costs have led to an increasing focus on renewable sources of
energy. A lot of research has been devoted to the technologies used to
extract energy from these sources; however, equally important is the
storage and distribution of this energy in a way that is efficient and
cost effective. Achieving this would generally require integration
with existing energy infrastructure.
The challenge of renewable energy integration is inherently multidisciplinary and is particularly dependant on the use of techniques from the domains of data analytics, pattern recognition and machine learning. Examples of relevant research topics include the forecasting of electricity supply and demand, the detection of faults, demand response applications and many others. This workshop will provides a forum where interested researchers from the various related domains will be able to present and discuss their findings.
Workshop ProgramDate: 23rd September 2016
10:00 - 10:05 Welcome Address
10:10 - 10:30 "Locating Faults in Photovoltaic Systems Data"
(Alexander Kogler and Patrick Traxler, Software Competence Center Hagenberg GmbH, Austria)
10:35 - 10:55 "Forecasting of Smart Meter Time Series Based on Neural Networks"
(Thierry Zufferey, Andreas Ulbig, Stephan Koch and Gabriela Hug, ETH Zurich, Switzerland)
11:00 - 11:20 "Cyber Security for Smart Cities: Trends, Opportunities, and Challenges"
(Armin Alibasic, Wei Lee Woon and Zeyar Aung, Masdar Institute of Science and Technology, UAE)
11:20 - 11:40 Coffee Break
11:40 - 12:00 "Machine Learning Prediction of Photovoltaic Energy from Satellite Sources"
(Alejandro Catalina, Alberto Torres-Barrán and José R. Dorronsoro, Universidad Autónoma de Madrid, Spain)
12:05 - 12:25 "Approximate Probabilistic Power Flow"
(Carlos D. Zuluaga and Mauricio Álvarez, Universidad Tecnológica de Pereira, Colombia)
12:30 - 12:50 "Dealing with Uncertainty: An Empirical Study on the Relevance of Renewable Energy Forecasting Methods"
(Robert Ulbricht, Anna Thoß, Hilko Donker, Gunter Gräfe and Wolfgang Lehner, Robotron; HTW Dresden; TU Dresden, Germany) [slides]
12:55 - 13:15 "Measuring Stakeholders’ Perceptions of Cybersecurity for Renewable Energy Systems"
(Stuart Madnick, Mohammad S. Jalali, Michael Siegel, Yang Lee, Diane Strong, Richard Wang, Wee Horng Ang, Vicki Deng, Dinsha Mistree, Massachusetts Institute of Technology, USA)
13:20 - 13:40 "Selection of numerical weather forecast features for PV power predictions with Random Forests"
(Björn Wolff, Oliver Kramer and Detlev Heinemann, University of Oldenburg, Germany)
|Submission Deadline||18th of July, 2016 (extended)|
|Notification to Authors||8th of August 2016 (extended)|
|Camera-ready Deadline||8th of August 2016|
|Workshop day||23rd September 2016|
- Wei Lee Woon (Masdar Institute)
- Zeyar Aung (Masdar Institute)
- Oliver Kramer (University of Oldenburg)
- Stuart Madnick (Massachusetts Institute of Technology)
dare2016 (at) dnagroup.org , wlwoon (at) deeplearn.net
- Abel Sanchez, Massachusetts Institute of Technology, USA
- Francisco Martínez Álvarez, Pablo de Olavide University, Spain
- Fabian Gieseke, Radboud University, The Netherlands
- Jimmy Peng, National University of Singapore, Singapore
- Davor Svetinovic, Masdar Institute, UAE
- David Lowe, Aston University, UK
- Depeng Li, University of Hawaii at Mona, USA
- Srinivas Sampalli, Dalhousie Univeristy, Canada
- Paul Yoo, Bournemouth University, UK
- Erik Casagrande, GE, UAE
- Randa Herzallah, Aston University, UK