Smart Grid

From PgroupW

Jump to: navigation, search

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

  • Recent paper accepted at IEEE Big Data Conference (Fall 2014)
  • DWP demo of VSoE-FMS integration (Spring 2014)
  • Paper accepted in IEEE TKDE (Spring 2014)
  • Group Presentations for DWP (Fall 2013)
  • Group Presentations for DWP and DOE (Summer 2013)
  • Recent papers got accepted for IEEE Big Data Conference and CiSE (Fall 2013)
  • Presentation on Smart Grids at USC Frontiers of Energy High School Camp (Summer 2011)


Recent Publications

  1. Estimating Reduced Consumption for Dynamic Demand Response, Charalampos Chelmis, Saima Aman, Muhammad Rizwan Saeed, Marc Frincu, Viktor K. Prasanna, AAAI Workshop on Computational Sustainability, 2015.
  2. Accurate and Efficient Selection of the Best Consumption Prediction Method in Smart Grids, Marc Frincu, Charalampos Chelmis, Muhammad Noor, Viktor Prasanna, IEEE International Conference on Big Data (BigData), 2014
  3. Holistic Measures for Evaluating Prediction Models in Smart Grids, Saima Aman, Yogesh Simmhan, Viktor Prasanna, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2014 ([IF 1.815])
  4. Integrated Platform for Automated Sustainable Demand Response in Smart Grids, Vasileios Zois, Marc Frincu, Viktor Prasanna, 2nd IEEE International Workshop on Intelligent Energy Systems (IWIES), 2014
  5. Ef´Čücient Customer Selection for Sustainable Demand Response in Smart Grids, Vasileios Zois, Marc Frincu, Charalampos Chelmis, Muhammad Rizwan Saeed, Viktor Prasanna, 5th International Green Computing Conference (IGCC), 2014
  6. A Bottom-Up Approach to Sustained Curtailment and Comfort for Controlled Demand Response, Marc Frincu, Zachary Gima, IEEE Conference on Technologies for Sustainability (SusTech), 2014
  7. Towards Hybrid Online On-Demand Querying of Realtime Data with Stateful Complex Event Processing, Qunzhi Zhou, Yogesh Simmhan and Viktor Prasanna, Towards Hybrid Online On-Demand Querying of Realtime Data with Stateful Complex Event Processing, IEEE International Conference on Big Data (BigData), 2013
  8. Scalable Prediction of Energy Consumption using Incremental Time Series Clustering, Yogesh Simmhan and Muhammad Usman Noor, Scalable Prediction of Energy Consumption using Incremental Time Series Clustering, Workshop on Big Data and Smarter Cities, 2013
  9. Cloud-Based Software Platform for Big Data Analytics in Smart Grids, Yogesh Simmhan, Saima Aman, Alok Kumbhare, Rongyang Liu, Sam Stevens, Qunzhi Zhou and Viktor Prasanna, Computing in Science and Engineering , 15(4), pp. 38-47, July-Aug. 2013, IEEE and AIP ([IF 1.422, CORE C])
  10. Energy Management Systems: State of the Art and Emerging Trends, Saima Aman, Yogesh Simmhan and Viktor K. Prasanna, IEEE Communications Magazine , 51 (1) , 2013 , pp. 114 - 119 , IEEE. ([IF 3.785])
  11. Cryptonite: A Secure and Performant Data Repository on Public Clouds, Alok Kumbhare, Yogesh Simmhan and Viktor Prasanna, International Cloud Computing Conference (CLOUD) , 2012
  12. Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids, Yogesh Simmhan, Vaibhav Agarwal, Saima Aman, Alok Kumbhare, Sreedhar Natarajan, Nikhil Rajguru, Ian Robinson, Samuel Stevens, Wei Yin, Qunzhi Zhou and Viktor Prasanna , IEEE International Scalable Computing Challenge (SCALE) , 2012 (First Prize)
  13. Scalable Regression Tree Learning on Hadoop using OpenPlanet, Wei Yin, Yogesh Simmhan and Viktor Prasanna , International Workshop on MapReduce and its Applications (MAPREDUCE) , 2012
  14. Semantic Information Modeling for Emerging Applications in Smart Grid, Qunzhi Zhou, Sreedhar Natarajan, Yogesh Simmhany and Viktor Prasanna , International Conference on Information Technology : New Generations (ITNG) , 2012
  15. SCEPter: Semantic Complex Event Processing over End-to-End Data Flows, Qunzhi Zhou, Yogesh Simmhan and Viktor Prasanna , 2012 , Computer Science Department, University of Southern California.

Technical Documents and Software


More Presentations...

Project Documents



Group Members

  • Yogesh Simmhan, Adjunct Research Asst Professor
  • Marc Frincu, Postdoctoral Research Associate & Project Manager
  • Charalampos Chelmis, Research Associate & Co-Project Manager
  • Saima Aman, Ph.D. Student, Computer Science
  • Qunzhi Zhou, Ph.D. Candidate, Computer Science
  • Vasilis Zois, Ph.D. Student, Computer Science

Research Interns

  • Ranjan Pal, Ph.D. Candidate, Computer Science
  • Prashant Nittoor, M.S. Student, Computer Science


  • Muhammad Usman Noor, M.S. Student, Electrical Engineering
  • Rizwan Saeed, M.S. Student, Electrical Engineering
  • Zachary Gima, B.S. Student, Mechanical Engineering
  • Ian Robinson, M.S. Student, Green Technologies
  • Vaibhav Agarwal, M.S. Student, Computer Science
  • Srivathsan Rajagopalan, M.S. Student, Computer Science
  • Ashwath Rajan, B.S. Student, Biomedical Engineering
  • Nikhil Rajguru, M.S. Student, Computer Science
  • Rongyang Liu, M.S. Student, Electrical Engineering
  • Samuel Stevens, M.S. Student, Computer Science
  • Ashutosh Shanker, M.S. Student, Computer Engineering
  • Kenneth Barry, B.S. Student

General Information

Personal tools