Advanced Control Modules for Hybrid Fuel Cell/Gas Turbine Power Plants

70558B02-II 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. Furthermore, 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. Phase I developed model-based components (integrated system dynamic models, operational constraints, and control objectives) that support the development of the low-level robust controller, data reconciliation system, fault accommodation system, and initial training set for the neural network supervisor. Phase II will apply state-of-the-art dynamic optimization methods and neural network architectures, and incorporate data reconciliation and fault accommodation techniques. Commercial Applications and Other Benefits as described by 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.