Fifteen New Awards to Accelerate Energy Science

The Siebel Energy Institute, a global consortium for innovative and collaborative energy research dedicated to advancing the science of smart energy, today announced the winners of its second round of seed grant awards.

Fifteen New Awards to Accelerate Energy Science

The Siebel Energy Institute, a global consortium for innovative and collaborative energy research dedicated to advancing the science of smart energy, today announced the winners of its second round of seed grant awards.

Fifteen research teams, led by engineering and computer science experts from seven Siebel Energy Institute consortium member universities, were each awarded $50,000 to develop proposals that accelerate energy science research. Many of the proposals are cross-collaborative between universities worldwide.

With projects that examine such topics as power grid resiliency and energy distribution efficiency, research supported by the Siebel Energy Institute in this second round of funding underscores the Institute’s focus on optimizing the energy infrastructure — from generation, to transmission, to consumption.

“The Siebel Energy Institute is spurring some of the greatest minds in energy science to leverage data analytics and machine learning to solve challenging problems in the energy sector, including the increasing threat of cyber-attacks on the power grid,” said Siebel Energy Institute Chairman Thomas M. Siebel.

The 15 second round seed grant recipients are:

• Ettore Bompard from Politecnico di Torino for “Smart Grid Resilience: Automatic Real-time Detection and Prediction of Critical Conditions and Preventive Network Management Through Distributed Sensing, Smart Metering, Environmental/Social Info”
• Elie Bou-Zeid from Princeton University for “Novel Physically-driven Approaches for Multiscale Wind-Energy Forecasting”
• Anna Creti from École Polytechnique for “From Resource to Price: Machine Learning for Italian Electricity Network and Market”
• Claudia D’Ambrosio from École Polytechnique for “Learning to Solve Hydro Unit Commitment Problems in France”
• Nick Feamster from Princeton University for “Detecting Abnormal Activity on the Internet of Things with Real-time Outlier Detection”
• Emmanuel Gobet from École Polytechnique for “Data Analytics and Stochastic Control for Optimal Management of Microgrid Generation and Storage Resources”
• Xuesong (Pine) Liu from Carnegie Mellon University for “Predictive Maintenance Planning for the Power Distribution Grid Using Machine Learning on Heterogeneous Condition Records”
• Patrizia Lombardi from Politecnico di Torino for “URBE – Understanding the Relationship Between Urban Form and Energy Consumption Through Behavioral Patterns”
• Stephen Mahin from the University of California, Berkeley for “Adaptive and Intelligent System for Energy Consumption Optimization Using IoT-based Mobile Sensor Networks and Structural Health Monitoring Systems”
• Marco Marsan from Politecnico di Torino for “CCG – Cars, Communications, and the Grid”
• David Nicol from the University of Illinois at Urbana-Champaign for “Data-driven Methods to Thwart Attacks on Microgrids”
• Asuman Ozdaglar from the Massachusetts Institute of Technology for “An Industry Equilibrium Approach to Reducing Reliance on Fossil Fuels in the Power Grid”
• Antonio Vetrò from Politecnico di Torino for “Power Aware – Lights Off, Brains On”
• Venkat Viswanathan from Carnegie Mellon University for “Data-driven Discovery of Resilient Energy Storage for Grid Applications
• Hao Zhu from the University of Illinois at Urbana-Champaign for “A Data-driven Network Tomography Approach for Evaluating and Improving the Resilience of Power Grids”

Siebel Energy Institute seed grants enable researchers at consortium member universities to develop larger research proposals and grant submissions to government entities and foundations within a leveraged funding model. To maximize the impact of any findings and potential long-term benefits to society, all research supported by the Siebel Energy Institute will be freely available in the public domain.

About the Siebel Energy Institute

By supporting cooperative and innovative research in data analytics, including statistical analysis and machine learning, the Siebel Energy Institute aims to accelerate advancements in the safety, security, reliability, efficiency, and environmental integrity of energy systems.

The nine Siebel Energy Institute consortium member universities are: Carnegie Mellon University; École Polytechnique; Massachusetts Institute of Technology; Politecnico di Torino; Princeton University; Tsinghua University; University of California, Berkeley; University of Illinois at Urbana-Champaign; and The University of Tokyo.

An Advisory Board of industry partners drives active collaboration between the private sector, consortium member universities, and Siebel Energy Institute researchers. Industry partners include C3 IoT, CESI, Enel Group, Entergy, Eversource, Honeywell, Johnson Controls, PG&E, and RWE AG.

For more detailed information about research projects funded by the Siebel Energy Institute, visit http://www.siebelenergyinstitute.org/.