An advanced FMRL controller for FACTS devices to enhance dynamic performance of power systems |
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Authors: | Abdellatif Naceri Habib Hamdaoui Mohamed Abid |
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Affiliation: | [1]IRECOM Laboratory, Department of Electrical Engineering, Djillali Liabes University of Sidi Bel-Abbes, B.P. 98, SBA, 22000, Algeria [2]ICEPS Laboratory, Department of Electrical Engineering, Djillali Liabes University of Sidi Bel-Abbes, B.P. 98, SBA, 22000, Algeria |
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Abstract: | The parameters of power system slowly change with time due to environmental effects or may change rapidly due to faults. It
is preferable that the control technique in this system possesses robustness for various fault conditions and disturbances.
The used flexible alternating current transmission system (FACTS) in this paper is an advanced super-conducting magnetic energy
storage (ASMES). Many control techniques that use ASMES to improve power system stability have been proposed. While fuzzy
controller has proven its value in some applications, the researches applying fuzzy controller with ASMES have been actively
reported. However, it is sometimes very difficult to specify the rule base for some plants, when the parameters change. To
solve this problem, a fuzzy model reference learning controller (FMRLC) is proposed in this paper, which investigates multi-input
multi-output FMRLC for time-variant nonlinear system. This control method provides the motivation for adaptive fuzzy control,
where the focus is on the automatic online synthesis and tuning of fuzzy controller parameters (i.e., using online data to
continually learn the fuzzy controller that will ensure that the performance objectives are met). Simulation results show
that the proposed robust controller is able to work with nonlinear and nonstationary power system (i.e., single machine-infinite
bus (SMIB) system), under various fault conditions and disturbances. |
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Keywords: | Transient power system stability and robustness single machine-infinite bus (SMIB) system flexible alternating currenttransmission system (FACTS) advanced super-conducting magnetic energy storage (ASMES) fuzzy model reference learning controller(FMRLC) adaptive control learning controller |
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