REDWOOD CITY, Calif.--(BUSINESS WIRE)--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 third round of seed grant awards.
Fourteen research teams, led by engineering and computer science experts from the nine 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.
Research supported by the Siebel Energy Institute in this third round of funding underscores the Institute’s expanded focus on the synergies between data analytics in energy systems and the emerging Internet-of-Things (IoT) infrastructure in smart and connected communities.
The awarded projects investigate topics such as predicting and preventing electrical outages and cyber-attacks, managing increasingly complex load factors such as electric vehicle charging and renewable energy sources, optimizing the power value chain, and developing technology enablers that improve infrastructure for next-generation communities, or “Smart Cities.”
“Design of new resilient services built on top this emerging new technology has the potential for building a next generation infrastructure in both rural and urban environments,” noted S. Shankar Sastry, Siebel Energy Institute Director and Dean of the College of Engineering at the University of California, Berkeley.
The Siebel Energy Institute has an Advisory Board of industry partners that drives active collaboration and translation of new research between academia and the private sector, “creating an outcome oriented public-private partnership that aims to generate new technologies designed to have an impact and real-world applications,” said Siebel Energy Institute Chairman Thomas M. Siebel.
The 14 third round seed grant recipients are:
- Audun Botterud from Massachusetts Institute of Technology for “Improved Analytics for Urban Energy Distribution Grids with Smart Buildings”
- Minjie Chen from Princeton University for “Developing a Smart Energy Router for Flexible and Efficient DC Power Distribution in Smart Homes and Buildings”
- Shigehiko Kaneko from The University of Tokyo for “Development of a Novel Scheme for Introducing Distributed Generation Systems Based on Business Continuity Planning Considering Disaster Risks”
- Chongqing Kang from Tsinghua University for “Data-driven Based Low-carbon Operation of Active Distribution Systems Considering Forecasting Uncertainty and Demand Response”
- Cedric Langbort from the University of Illinois at Urbana-Champaign for “Beyond Discrete Choice and Prices in Route Choices – Towards Efficient Revealed Preferences Identification and Nudging in the Multi-utility Paradigm”
- Leo Liberti from École Polytechnique for “Quantile Regression in Large Energy Datasets”
- Marco Mellia from Politecnico di Torino for “Big Data Platform for FFCS Design: From Gas to Electric”
- Jovan Pantelic from the University of California, Berkeley for “Informing Occupants and Modifying Their Behavior Through Energy and Air Quality Sensing”
- Matteo Pozzi from Carnegie Mellon University for “Resilience of the Integrated Urban Infrastructure Under Extreme Events: A Sequential Decision-making Approach”
- Alessandro Rizzo from Politecnico di Torino for “Multi-modal Crowd Sensing to Monitor Buildings in Smart Cities”
- Stefano Schiavon from the University of California, Berkeley for “Incorporating Real-time Thermal Comfort and Indoor Occupancy into Building Management Systems”
- Kenji Tanaka from The University of Tokyo for “Blockchain-based Smart Metering and Electricity Trading”
- Lav Varshney from the University of Illinois at Urbana-Champaign for “Incentives, Choices, and Analytics for Electric Vehicle Fleets in Jointly Managing Urban Traffic and the Smart Grid”
- Daniel Work from the University of Illinois at Urbana-Champaign for “Quantifying the Predictability of City-scale Urban Traffic”
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
The Siebel Energy Institute is a global consortium for collaborative energy research, dedicated to accelerating and sharing advancements in machine learning applied to power systems and Internet-of-Things (IoT) infrastructures.
By funding cooperative and innovative research grants in data analytics, including artificial intelligence and machine learning, the Siebel Energy Institute hopes to accelerate advancements in the safety, security, reliability, efficiency, and environmental integrity of energy and cyber-physical 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.
Industry partners include C3 IoT, CESI, Enel Group, Engie, Eversource, Honeywell, innogy, Johnson Controls, and PG&E.
Since the Institute launched in 2015, more than $2 million in research grants have been awarded to engineering and computer science experts from the consortium member universities. In 2016, the Institute leveraged funding model helped consortium researchers secure $49 million in large grant support for their work.
For more detailed information about research projects funded by the Siebel Energy Institute, visit http://www.siebelenergyinstitute.org/.