CUED Publications database

Application of quadratically-constrained model predictive control in power systems

Tran, T and Eddy, YSF and Ling, KV and Maciejowski, JM (2014) Application of quadratically-constrained model predictive control in power systems. In: UNSPECIFIED pp. 193-198..

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Simulations for the quadratically-constrained model predictive control (qc-MPC) with power system linear models are studied in this work. In qc-MPC, the optimization is imposed with two additional constraints to achieve the closed-loop system stability and the recursive-feasibility simultaneously. Instead of engaging the traditional terminal constraint for MPC, both constraints in qc-MPC are imposed on the first control vector of the MPC control sequence. As a result, qc-MPC has the potential for further extension to the control of network centric power systems. The algorithm of qc-MPC has been developed in a previous paper. Here, simulation studies with small-signal linear models of three typical power systems are presented to demonstrate its efficacy. We also develop a computational strategy for the decentralized static state-feedback control using the same quadratic dissipativity constraint as of the qc-MPC. Only state constraints are considered in the state feedback design. A comparison is then provided in the simulation study of qc-MPC relatively to the constrained-state feedback control.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Divisions: Div F > Control
Depositing User: Unnamed user with email
Date Deposited: 17 Jul 2017 19:41
Last Modified: 09 Sep 2021 03:08
DOI: 10.1109/ICARCV.2014.7064303