University of Pennsylvania, USA
Flexergy: Bridging Machine Learning and Controls for Volatile Energy Markets
Abstract: In December 2014, the average price of wholesale electricity in the PJM market surged from $32/MWh to $2680/MWh - an 83x increase in 5mins. Demand response (DR) is becoming increasingly important as the volatility on the grid continues to increase. Current DR approaches are predominantly manual and rule-based or involve deriving first principles based models which are extremely cost and time prohibitive to build. We consider the problem of data-driven end-user DR for large buildings which involves predicting the demand response baseline, evaluating fixed rule based DR strategies and synthesizing DR control actions. Our machine learning algorithms capture building models with 96-98% accuracy in minutes. By bridging machine learning with controls, we perform closed-loop control for DR strategy synthesis across commercial buildings in a scalable manner. Our data-driven control synthesis algorithm outperforms rule-based DR for large DoE commercial reference buildings and leads to consistent +30% electricity cost savings across the year. Our methods have been integrated into commercial SCADA systems and acts as a recommender system for the building’s facilities manager and provides interpretable control actions to meet the desired load curtailment while maintaining operations and maximizing the economic reward. An Interactive Energy Analytics engine allows the user to ask buildings questions on their predicted operations and makes Demand Response easy with procedurally generated energy dashboards for open-ended questions.
Bio: Rahul Mangharam is the CEO of
Flexergy focused on cost-efficient energy controls and analytics for volatile
energy markets. He is also an Associate Professor in the Dept. of Electrical &
Systems Engineering and Dept. of Computer & Information Science at the
University of Pennsylvania. His interests are in cyber-physical systems at the
intersection of formal methods, machine learning and controls. He is the Penn
Director for the Department of Transportation's $14MM Mobility21 University
Transportation Center. He was the Stephen J. Angelo Term Chair Assistant
Professor from 2008-2013. He received his Ph.D. in Electrical & Computer
Engineering from Carnegie Mellon University where he also received his MS and BS
in 2007, 2002 and 2000 respectively.
Rahul received the 2016 US Presidential Early Career Award (PECASE) from President Obama for his work on Cyber-Physical Systems. He also received the 2016 Department of Energy’s CleanTech Prize (Regional), the 2014 IEEE Benjamin Franklin Key Award, 2013 NSF CAREER Award, 2012 Intel Early Faculty Career Award and was selected by the National Academy of Engineering for the 2012 and 2017 Frontiers of Engineering.