Multicoordination Control Strategy Performance in Hybrid Power Systems
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Ames National Laboratory is a government-owned, contractor-operated national laboratory of the U.S. Department of Energy (DOE), operated by and located on the campus of Iowa State University in Ames, Iowa.
For more than 70 years, the Ames National Laboratory has successfully partnered with Iowa State University, and is unique among the 17 DOE laboratories in that it is physically located on the campus of a major research university. Many of the scientists and administrators at the Laboratory also hold faculty positions at the University and the Laboratory has access to both undergraduate and graduate student talent.
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Abstract
This paper evaluates a state-space methodology of a multi-input multi-output (MIMO) control strategy using a two-by-two tightly coupled scenario applied to a physical gas turbine hybrid power system. A centralized MIMO controller was preferred compared to a decentralized control approach because previous simulation studies showed that the coupling effect identified during the simultaneous control of the turbine speed and cathode airflow was better minimized. The MIMO controller was developed using a state-space dynamic model of the system that was derived using first-order transfer functions empirically implemented through experimental tests. The controller performance was evaluated in terms of disturbance rejection through perturbations in the gas turbine operation, and set-point tracking maneuver through turbine speed and cathode airflow steps. The experimental results illustrate that a multi-coordination control strategy was able to mitigate the coupling of each actuator to each output during the simultaneous control of the system, and improved the overall system performance during transient conditions. On the other hand, the controller showed different performance during validation in simulation environment compared to validation in the physical facility, which will require a better dynamic modeling of the system for the implementation of future multivariable control strategies.