Salp swarm algorithm-based TS-FLCs for MPPT and fault ride-through capability enhancement of wind generators.

Salp swarm algorithm-based TS-FLCs for MPPT and fault ride-through capability enhancement of wind generators.

Qais, Mohammed;Hasanien, Hany M;Alghuwainem, Saad;
ISA transactions 2020
186
qais2020salpisa

Abstract

This article presents an optimum design of Takagi-Sugeno fuzzy logic controllers (TS-FLCs) to enhance capability of fault ride-through (FRT) and the maximal power point tracking (MPPT) of the grid-tied wind farms. To obtain the optimum TS-FLCs, salp-swarm-algorithm (SSA) applied to minimize the sum of integral squared-error (ISE) function, where the variables of the cost function are the factors of Gaussian membership functions and the control rules of eight TS-FLCs. After that, the optimized TS-FLCs are applied to control the grid-tied variable-speed wind generator system, which is simulated using PSCAD/EMTDC. Thus, the transient and dynamic responses revealed that the optimum TS-FLCs have better stability margins than the optimum proportional-integral (PI) controllers. Furthermore, a realistic variable wind speed measured data are implemented to test the robustness of the MPPT based on the optimal TS-FLCs to extract more power than the MPPT based on optimal PI controllers.

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ID: 94294
Ref Key: qais2020salpisa
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