Design of stabilising signals for power system damping using generalised predictive control optimised by a new hybrid shuffled frog leaping algorithm
Design of stabilising signals for power system damping using generalised predictive control optimised by a new hybrid shuffled frog leaping algorithm
- Author(s): E. Bijami ; J. Askari ; M.M. Farsangi
- DOI: 10.1049/iet-gtd.2011.0770
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- Author(s): E. Bijami 1 ; J. Askari 1 ; M.M. Farsangi 2
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View affiliations
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Affiliations:
1: Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran
2: Electrical Department, Shahid Bahonar University of Kerman, Kerman, Iran
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Affiliations:
1: Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran
- Source:
Volume 6, Issue 10,
October 2012,
p.
1036 – 1045
DOI: 10.1049/iet-gtd.2011.0770 , Print ISSN 1751-8687, Online ISSN 1751-8695
This study presents a hybrid method based on generalised predictive control (GPC) and a proposed new hybrid shuffled frog leaping (NHSFL) algorithm to design stabilising signals to damp the multi-machine power system low-frequency oscillations. A linearised model predictive controller based on GPC is designed in which the proposed NHSFL algorithm is employed for optimising the cost function of the GPC. The numerical results are presented on a two-area four-machine and a five-area 16-machine power system. The effectiveness of the designed controllers is shown by considering various operating conditions. The proposed approach, which is called as GPC-NHSFL, is compared with a classical-based method, GPC algorithm and GPC-based standard SFL algorithm (GPC-SFL). The simulation results show the superiority and capability of the proposed approach to enhance power systems damping.
Inspec keywords: optimisation; oscillations; linear systems; damping; control system synthesis; predictive control; power system stability
Other keywords:
Subjects: a.c. transmission; Control system analysis and synthesis methods; Power system control; Control of electric power systems; Optimal control; Optimisation techniques; Stability in control theory; Optimisation techniques
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