Energy and Robotics (EnerBots) Lab

Smart power grid technologies for managing solar/wind volatility

and

Unmanned vehicles for environmental monitoring.

Prof. Prabir Barooah

Prabir Barooah, 2022

Professor
Electronics and Electrical Engineering
Indian Institute of Technology, Guwahati


Prabir Barooah joined the Indian Institute of Technology, Guwahati, in July 2022. Previously he was a Professor of Mechanical and Aerospace Engineering at the University of Florida, Gainesville, Florida, USA. He received his Ph.D. 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 has won the Outstanding Researcher Award (2013) from American Society of Engineering Education (SE Section), CAREER award (2010) from the National Science Foundation (USA), General Chairs' Recognition Award for Interactive papers at the 48th IEEE Conference on Decision and Control (2009), the best paper award at the 2nd Int. Conf. on Intelligent Sensing and Information Processing (2005), and a NASA group achievement award (2003).



Energy

Virtual Energy Storage (VES) to aid solar and wind energy integration:

Green sources of energy, solar and wind, have a dark side: their intermittency. To deliver electricity when you need it, unless the sun and wind cooperate, we will need giant batteries. But batteries are expensive.
We are working on an inexpensive alternative to batteries that delivers a battery-like service by using consumer loads - air conditioners, water heaters, etc. - intelligently.

The trick is in the phrase "deliver electricity when you need it".

All power consuming devices have enormous flexibility in when they need power to deliver the expected quality of service (QoS) to the consumer. This flexibility is especially large for thermal "loads" such as air conditioners and water heaters used in our buildings. Small increase and decrease in air conditioning power over the nominal does not lead to perceptible change in indoor climate. Yet, when done intentionally, it is equivalent to a small battery charging and discharging. When a large number of such loads are coordinated through intelligent decision-making software over the Internet, a giant "virtual battery" results. After all, flexible loads such as air conditioners and water heaters account for a large fraction of the total electricity use. In the USA, for instance, 75% of the nationwide electricity use is consumed by buildings. In India and large developing economies, the share of cooling in total electricity use is large and is increasing. Even a 10% flexibility is therefore huge.

The VES service is obtained with existing equipment. Only a small change in software and communication is needed. The cost is therefore low.

While demand side management has been with power grid operators for a long time, the innovation in the VES concept lies in (i) guaranteed bounds on consumers' QoS, and (ii) robust and reliable on-demand service to the power grid 24-7.

This video explains the concept of Virtual Energy Storage (Created by my former students at the University of Florida).


Robotics:

The North East of India, where the Indian Institute of Technology Guwahati is located, contains a vast network of rivers, lakes, forests, and mountainous terrain that often inaccessible. They are also important to the region's ecology and economy as well as India's national security interests. Their monitoring is currently done manually, which is expensive and unrelianle. Robotic vehicles - including aquatic, ground and aerial - can improve the safety, reliability and expense of monitoring in this challenging region.

The EnerBots Lab is developing the technology to enable such monitoring, primarily focusing on robotic aquatic boats and IoT-based solutions. Such technologies can enable safer, more frequent, and data-driven monitoring of ecologically sensitive and geographically remote areas.