Smart Grid
From PgroupW
The Smart Grid group is conducting research into informatics-driven scalable software architectures to address realtime power management in the domain of Smart Power Grids. This work is funded by the US Department of Energy as part of the five-year Los Angeles Smart Grid Demonstration project, to forecast and curtail power consumption by thousands of electricity consumers on-demand through large scale information processing and consumer pattern detection. We apply existing information technology techniques to and investigate novel algorithms and frameworks for this emerging application area of critical importance to global sustainability,
This cyberphysical domain provides unique challenges to many existing computer science algorithms, approaches and frameworks due to the data complexity, dynamism, scale and need for realtime response. Some of the research topics that we are exploring as part of this project are semantic information integration, complex event and stream processing, data analytics and machine learning, data security and privacy, and cloud computing platforms.
Recent Activities
- Posters at the Third Southern California Smart Grid Research Symposium, Caltech (13-Oct-2011)
- Several recent papers get accepted on data mining (DDDM), cloud security (DataCloud) and smart grids (BuildSys) (Sep-2011)
- Presentation on Smart Grids at USC Frontiers of Energy High School Camp (27-Jun-2011)
Research
- Areas: Machine Learning | Complex Event Processing | Cloud Computing
- Recent Publications
- Semantic Information Modeling for Emerging Applications in Smart Grid, Qunzhi Zhou, Sreehar Natarajan, Yogesh Simmhan and Viktor Prasanna , 9th IEEE International Conference on Information Technology: Next Generations , 2012
- Designing a Secure Storage Repository for Sharing Scientific Datasets using Public Clouds, Alok Kumbhare, Yogesh Simmhan and Viktor Prasanna , International Workshop on Data Intensive Computing in the Clouds (DataCloud-SC11) , 2011
- Towards Data-driven Demand-Response Optimization in a Campus Microgrid, Yogesh Simmhan, Viktor Prasanna, Saima Aman, Sreedhar Natarajan, Wei Yin and Qunzhi Zhou , Workshop On Embedded Sensing Systems For Energy-Efficiency In Buildings (BuildSys) , 2011 , ACM. (Demo)
- Improving Energy Use Forecast for Campus Micro-grids using Indirect Indicators, Saima Aman, Yogesh Simmhan and Viktor K. Prasanna , International Workshop on Domain Driven Data Mining (DDDM) , 2011
Technical Documents and Software
Presentations
- Semantic Information Integration and Processing for Demand Response, poster at Third Southern California Smart Grid Research Symposium, Caltech (13-Oct-2011)
- Machine Learning for Demand Forecasting in Smart Grid, poster at Third Southern California Smart Grid Research Symposium, Caltech (13-Oct-2011)
- Detailed overview of research, presented at 2011 Fall Technical Forum (Sep-2011)
Schedules
- Group Meetings: 2012 | Spring ≡ 2011 | Fall | Summer
- Individual Meetings: 2012 | Spring ≡ 2011 | Fall | Summer
- Member Availability: 2012 | Spring ≡ 2011 | Winter | Fall | Summer
Group Members
- Yogesh Simmhan, Sr Research Associate & Project Manager
- Saima Aman, Ph.D. Student, Computer Science
- Alok Kumbhare, Ph.D. Student, Computer Science
- Qunzhi Zhou, Ph.D. Candidate, Computer Science
Research Interns
- Sreedhar Natarajan, M.S. Student, Computer Science
- Nikhil Rajguru, M.S. Student, Computer Science
- Ian Robinson, M.S. Student, Green Technologies
- Samuel Stevens, M.S. Student, Computer Science
- Wei Yin, M.S. Student, Computer Science
