Welcome to DARE'18!

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 Program

Date: 10th September 2018

09:00 - 09:10 Introduction and Welcome

09:15 - 9:35 Mathematical Optimization of Design Parameters of Photovoltaic Module
(Dávid Kubík and Jaroslav Loebl, Slovak University of Technology in Bratislava, Slovakia)

9:40 - 10:00 Fused Lasso Dimensionality Reduction of Highly Correlated NWP Features
(Alejandro Catalina Feliu, Carlos M. Alaíz and Jose R. Dorronsoro, Universidad Autónoma de Madrid, Spain)

(10:05 - 10:25 Sampling strategies for Representative Time Series in Load Flow Calculation
Janosch Henze, Stephan Kutzner and Bernhard Sick, University of Kassel, Germany)

10:30 - 11:00 Coffee Break 11:00 - 11:20 Probabilistic Graphs for Sensor Data - driven Modelling of Power Systems at Scale
(Francesco Fusco, IBM Research, Ireland)

11:25 - 11:45 Renewable Energy Integration: Bayesian Networks for Probabilistic State Estimation
(Ole Jakob Mengshoel, Priya Krishnan Sundararajan, Erik Reed, Dongzhen Piao and Briana Johnson, Carnegie Mellon University, USA)

11:50 - 12:10 Deep Learning for Wave Height Classification in Satellite Images for Offshore Wind Access
(Ryan Spick and James Walker, University of Hull, UK)

12:10 - 12:30 Video abstracts session: * Contribution Machine learning as Surrogate to Building Performance Simulation: a Building Design Optimization Application
(Sokratis Papadopoulos, Wei Lee Woon, Elie Azar, New York University, USA)

* Clustering River Basins using Time-Series Data Mining on Hydroelectric Energy Generation
(Yusuf Arslan, Dilek Küçük, Sinan Eren and Aysenur Birturk, TÜBİTAK MRC Energy Institute, Turkey)

* Short-Term Electricity Consumption Forecast using Datasets of Various Granularities
(Yusuf Arslan, Aybike Şimşek Dilbaz, Seyda Ertekin, Pinar Karagoz, Aysenur Birturk, Sinan Eren and Dilek Küçük, TÜBİTAK MRC Energy Institute, Turkey)

Important Dates

Submission Deadline16th of July, 2018 (extended)
Notification to Authors23rd of July 2018
Camera-ready Deadline6th of August 2018
Workshop day10th of September 2018

Organizers

  • Wei Lee Woon (Masdar Institute, Khalifa University)
  • Zeyar Aung (Masdar Institute, Khalifa University)
  • Stuart Madnick (Massachusetts Institute of Technology)
  • Alejandro Catalina Feliú (Universidad Autonoma de Madrid)
You can contact us at:
wlwoon (at) deeplearn.net , dare2018 (at) easychair.org

Program Committee

  • Azar, Elie, Khalifa University of Science and Technology, UAE
  • Catalão, João, University of Beira Interior, Portugal
  • Faisal, Mustafa Amir, University of Texas at Dallas, USA
  • Kayem, Anne, Hasso-Plattner Institute, Germany
  • Li, Xiaoli, Institute for Infocomm Research, Singapore
  • Mashima, Daisuke, Advanced Digital Sciences Center, Singapore
  • Neupane, Bijay, Aalborg University, Denmark
  • Ouarda, Taha, National Institute of Scientific Research, Canada
  • Peng, Jimmy, National University of Singapore, Singapore
  • Saraiva, Filipe, Federal University of Para, Brazil
  • Sayed-Mouchaweh, Moamar, Institute Mines-Telecom Lille Douai, France
  • Xiao, Weidong, University of Sydney, Australia
  • Zhong, Haiwang, Tsinghua University, China