12
Advanced
Control Modules for Hybrid Fuel Cell/Gas Turbine Power Plants--Fuelcell
Energy, Inc., 3 Great Pasture Road, Danbury, CT
06813; 203-825-6039
Dr.
Michael D. Lukas, Principal Investigator, mlukas@fce.com
Mr.
Ross Levine, Business Official, rlevine@fce.com
DOE
Grant No. DE-FG02-02ER86140
Amount:
$100,000
Research
Institution
Irvine, CA
The control and dynamic operation of Fuel Cell/Turbine Hybrid power plants will require a synergy of operation between subsystems, increased reliability of operation, and reduction in maintenance and downtime. Futhermore, the control strategy of the power plant will play a significant role in system stability and in ensuring the protection of equipment to promote maximum life. This project will optimize operation by combining an innovative control algorithm for robust control with a supervisory prediction and utilization model of future load characteristics. The supervisory control system will include learning intelligence to adjust for changing plant conditions and qualitative diagnostic capabilities to guide decision-making for maintaining optimal efficiency at all conditions. In Phase I, a two-level approach will provide integrated, robust system control at the bottom level and a supervisor at the top level to coordinate the low-level controllers. The supervisor will be implemented as a neural network, trained to provide optimal setpoints and to feedforward signals to the controllers, using information about future load profiles, to determine the best current policy. Dynamic modeling will be used to create a simulation testbed for testing the algorithms.
Commercial Applications and Other Benefits as described by the awardee: The technology should generate software packages that are particular to the characteristics of Vision 21 Hybrid Fuel Cell/Gas Turbine power plants, drawing interest from both utilities, and independent power producers.