Distributed Control of Loads to Provide Virtual Energy Storage for Renewable Integration

Energy storage is required to integrate large amounts of intermittent renewable energy sources, such as solar and wind, with the electric grid. Batteries for energy storage are still quite expensive. Another possibility is to exploit the inherent flexibility of power consumption in many electrical loads, such as air conditioning, to obtain "virtual energy storage". The power consumption of these loads is varied around a baseline so that they effectively behave like batteries that are charging and discharging. A critical requirement is to ensure that consumers' quality of service (QoS) is not adversely affected.

This talk describes recent work done at the University of Florida (UF) on the design, analysis, and experimental verification of control algorithms to obtain virtual energy storage from various types of loads. We argue that limiting the bandwidth of power variation (as opposed to the magnitude) is the key to ensuring QoS of consumers. This poses unique challenges in designing control algorithms, especially distributed control algorithms for a large number of loads.

Prabir Barooah is an Associate Professor of Mechanical and Aerospace Engineering at the University of Florida, where he has been since 2007. He received the Ph.D. degree in Electrical and Computer Engineering in 2007 from the University of California, Santa Barbara. From 1999 to 2002 he was a research engineer at United Technologies Research Center, East Hartford, CT. He received the M. S. degree in Mechanical Engineering from the University of Delaware in 1999 and the B. Tech. degree in Mechanical Engineering from the Indian Institute of Technology, Kanpur, in 1996. Dr. Barooah is the winner of the ASEE-SE (American Society of Engineering Education, South East Section) outstanding researcher award (2012), NSF CAREER award (2010), General Chairs' Recognition Award for Interactive papers at the 48th IEEE Conference on Decision and Control (2009), best paper award at the 2nd Int. Conf. on Intelligent Sensing and Information Processing (2005), and NASA group achievement award (2003).