West Virginia Executive Spring/Summer 2020 | Page 57

Prolonging Power Plant Life
With the world of artificial intelligence (AI) becoming more and more
prevalent, one chemical engineer is leaning into this advanced
technology to improve and prolong the lives of coal-fired and natural
gas power plant boilers.
Many coal-fired power plants can start up and shut down several
hundred times in just one year, leading to the plants’ utilities facing
increased failure of critical boiler components that cause forced
outages, increased operations and maintenance costs, loss of
revenue and an increase in environmental emissions. There is
currently no tool that can monitor the health of boiler components
online and provide insight into what component might fail and when.
technology in Plant Barry, AL, in partnership with Southern Company
and Electric Power Research Institute.
“This project builds on the quest to fill in the gaps in the existing
technologies for addressing the critical issue of health monitoring
of the critical boiler components,” says Bhattacharyya. “An online
health monitoring tool can be instrumental in understanding the
impacts of load following and can eventually help the utilities develop
advanced process control strategies for improved flexibility without
compromising safety and reliability. Overall, the improved monitoring
can not only lead to lower operations and maintenance costs but
also improved flexibility and higher reliability.”
Debangsu
Bhattacharyya.
“AI is being used to fill
this gap,” says Debangsu
Bhattacharyya, GE Plastics
Material Engineering
Professor of Chemical and
Biomedical Engineering at
West Virginia University.
“AI models are simpler
to construct and adapt
online using the real-time
operational data available
for the power plants.”
Bhattacharyya received a $2.5 million U.S. Department of Energy
grant to develop an AI-powered online monitoring tool to observe
and predict failures in power plant boilers. He plans to test the
Photo by WVU Benjamin M. Statler College of Engineering and Mineral Resources.
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