GlobalSIP 2016:

Symposium on Signal and Information Processing for Smart Grid Infrastructures

Schedule

Keynote Speakers

SGI-K1: Georgios B. Giannakis, University of Minnesota

Online Learning and Management of Future Cyber-Physical Networks

Cyber-physical systems (CPS) are engineered systems with built-in seamless integration of computational and physical components. Fundamental advances in sensing, learning, control, and information technologies, are well motivated to endow CPS with resilience, adaptability, scalability, and sustainability. In this context, the present talk will start with online convex optimization algorithms for estimating the state of future power grids. A framework will be then introduced for joint active and reactive power control in distribution grids, which also accounts for stochastic constraints of voltages and inverters to reduce losses. Efficacy of the novel approaches will be assessed using standard IEEE power grid benchmark distribution feeders. Leveraging statistical inference and stochastic optimization tools, the final topic will deal with state-of-the-art learning-aided management for sustainable data centers. Both analytical and empirical results will demonstrate how valuable insights from big data analytics can lead to markedly improved management policies by learning from historical user and network patterns.

SGI-K2: Josh Taylor, University of Toronto

Power Systems Without Fuel

Renewable integration is a century-long project. Over the past decade we have made impressive progress in integrating renewables, energy storage, and demand response into the existing power infrastructure. In this talk, we jump forward to a hypothetical final destination: power systems without fuel. In power systems without fuel, small, modular, renewable sources supply all power. In addition to sustainability and environmental benevolence, power systems without fuel offer superior operation to current power systems due to, for example, the obsolescence of unit commitment, the decreased importance of frequency, and the increased viability of direct current. We motivate several research problems under this umbrella, including electricity markets without fuel costs, decentralized control of direct current systems, and machine learning for demand response.

The marriage of information and communication technologies with traditional energy production, delivery and distribution systems aims to create a more reliable, efficient, environmentally friendly and resilient smart grid. Energy system stakeholders expect greater consumer-centricity and more open and flexible business models. At the heart of many of the technological challenges underlying this vision for a smarter grid is the need for optimization and information processing. New problems are arising that require the use of big data analytics to process continuous streams of data coming from sources such as smart meters, smart building sensors, phasor measurement units, and weather stations at geographically dispersed locations. Classical signal and information processing problems are adapting to support changing system requirements and grid characteristics. By the same token, the increased penetration of renewable energy generation, distributed storage, and controllable loads such as plug-in electric vehicles, calls for novel optimal resource management methods that respect user privacy while yield customer-centric and system-wide benefits. Moreover, computational and physical constraints within this new technical landscape must be assessed. This symposium aims to bring together researchers and practitioners in the field of signal and information processing for the optimization of smart grid infrastructures.

Submissions are welcome on topics including:

• Optimal power flow problems and extensions
• Unit commitment and generator scheduling
• Grid component placement & transmission system planning
• Information processing for security and resilience
• Stochastic optimal control for energy systems & pricing
• Online optimization for energy management in smart grids
• Energy management for efficient and carbon-neutral data centers
• Demand-response and real-time pricing
• Robust and stochastic optimization methods for renewable energy management
• Load and renewable energy forecasting
• Power system state estimation
• Power system dynamics and transient analysis
• Load modeling and monitoring
• Measurement-based power system analysis
• Phasor Measurement Units and cyber-security
• Smart meters and energy theft detection and mitigation
• Information processing for optimizing coupled smart grid infrastructures, e.g., smart grids and water networks

[Download the PDF Call for Papers]

Paper Submission

Prospective authors are invited to submit full-length papers, with up to four pages for technical content including figures and possible references, and with one additional optional 5th page containing only references. Manuscripts should be original (not submitted/published anywhere else) and written in accordance with the standard IEEE double-column paper template. Submission is through the GlobalSIP website at http://2016.ieeeglobalsip.org/Papers.asp.

Organizing Committee

• Deepa Kundur, University of Toronto
• Nikolaos Gatsis, University of Texas at San Antonio
• Vassilis Kekatos, Virginia Tech
• Meng Wang, Rensselaer Polytechnic Institute
• Abdallah Farraj, University of Toronto

Technical Co-Chairs

• Abdallah Farraj, University of Toronto
• Vassilis Kekatos, Virginia Tech
• Meng Wang, Rensselaer Polytechnic Institute

Technical Program Committee

• Soummya Kar, Carnegie Mellon University
• Sairaj Dhople, Universiy of Minnesota
• Baosen Zhang, University of Washington
• Daniel Molzahn, Argonne National Lab
• Hao Zhu, University of Illinois
• Tsung-Hui Chang, Chinese University of Hong Kong
• Chen Chen, Argonne National Lab
• Emiliano Dall’anese, National Renewable Energy Lab
• Na Li, Harvard University
• Jinsub Kim, Oregon State University
• Ali Tajer, Rensselaer Polytechnic Institute
• Yue Zhao, Stony Brook University
• Javad Lavaei, University of California Berkeley
• Rakesh Bobba, Oregon State University
• Yu Zhang, University of California Berkeley
• Yuanzhang Xiao, Northwestern University
• Miltiadis Alamaniotis, Purdue University
• Christos Verikoukis, Centre Tecnològic Telecomunicacions Catalunya, Spain
• Marius Pesavento, Technische Universität Darmstadt
• Joshua Taylor, University of Toronto
• Usman Khan, Tufts University
• Lalitha Sankar, Arizona State University
• Deepjyoti Deka, Los Alamos National Lab
• Wei Zhang, Ohio State University
• Ali Davoudi, University of Texas at Arlington
• Walid Saad, Virginia Tech
• Aranya Chakrabotry, North Carolina State University
• Jhi-Young Joo, Missouri University of Science & Technology
• Francesco Fusco, IBM Research, Ireland
• Jarvis Haupt, University of Minnesota
• Ning Zhou, Binghamton University
• Miao He, Texas Tech University
• Xavier Fernando, Ryerson University
• Hany Farag, York University
• Saman Zonouz, Rutgers University
• Jin Kocsis, The University of Akron