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Load–Frequency Control Using Multi-objective Genetic Algorithm and Hybrid Sliding Mode Control-Based SMES

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Abstract

This paper aims to better the dynamic response of interconnected power systems following any load change using the combination of multi-objective optimization algorithm-based PID and a hybrid adaptive fuzzy sliding mode. In the proposed method, a hybrid sliding surface including two subsystems’ information is introduced to produce a control effort to move both subsystems toward their related sliding surface. A feedback linearization control law is mimicked by an adaptive fuzzy controller. To compensate the error between the feedback linearization and adaptive fuzzy controller, a hitting controller is developed. The design of PID controller is formulated into a multi-objective optimization problem. The performance of suggested method is assessed on two interconnected power systems. These results validate that the suggested method confirms better disturbance rejection, keeps the control quality in different situations, reduces the frequency deviations preventing the overshoot and has more robustness to uncertainties and change in parameters in the power system.

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Correspondence to Mohsen Farahani.

Appendix

Appendix

SMES control loop:

$$T_{c} = 0.03,\quad I_{d0} = 20\;{\text{kA}},\quad L = 3H,\quad k_{f} = 0.001$$

The parameters used for power system shown in Fig. 1 are provided in [2]:

The parameters used for power system shown in Fig. 3 are provided in [33].

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Khosraviani, M., Jahanshahi, M., Farahani, M. et al. Load–Frequency Control Using Multi-objective Genetic Algorithm and Hybrid Sliding Mode Control-Based SMES. Int. J. Fuzzy Syst. 20, 280–294 (2018). https://doi.org/10.1007/s40815-017-0332-z

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  • DOI: https://doi.org/10.1007/s40815-017-0332-z

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