Multicoordination Control Strategy Performance in Hybrid Power Systems
Author(s) -
Paolo Pezzini,
Kenneth M. Bryden,
David Tucker
Publication year - 2018
Publication title -
journal of electrochemical energy conversion and storage
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.377
H-Index - 13
eISSN - 2381-6910
pISSN - 2381-6872
DOI - 10.1115/1.4039356
Subject(s) - setpoint , control theory (sociology) , controller (irrigation) , mimo , transient (computer programming) , multivariable calculus , control system , turbine , control engineering , actuator , coupling (piping) , state space , systems modeling , power (physics) , computer science , state space representation , engineering , channel (broadcasting) , control (management) , mechanical engineering , computer network , statistics , physics , electrical engineering , mathematics , software engineering , algorithm , quantum mechanics , artificial intelligence , agronomy , biology , operating system
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.
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