Load parameter waveforms improvement of a stand‐alone wind‐based energy storage system and Takagi–Sugeno fuzzy logic algorithm | Zendy

Kassem Ahmed M. | Zendy; Zaid S.A. | Zendy

Open Access

Load parameter waveforms improvement of a stand‐alone wind‐based energy storage system and Takagi–Sugeno fuzzy logic algorithm

Author(s) -

Kassem Ahmed M.,

Zaid S.A.

Publication year - 2014

Publication title -

iet renewable power generation

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.005

H-Index - 76

ISSN - 1752-1424

DOI - 10.1049/iet-rpg.2013.0382

Subject(s) - control theory (sociology) , pid controller , permanent magnet synchronous generator , energy storage , controller (irrigation) , fuzzy logic , computer science , rectifier (neural networks) , wind power , fuzzy control system , turbine , electric power system , power (physics) , control engineering , engineering , voltage , temperature control , control (management) , electrical engineering , artificial intelligence , stochastic neural network , recurrent neural network , biology , quantum mechanics , machine learning , artificial neural network , agronomy , mechanical engineering , physics

The application of the Takagi–Sugeno (TS) fuzzy approach for voltage and frequency control of an isolated wind turbine (WT) system with variable‐speed permanent magnet synchronous generator (PMSG) and a system for storing energy during wind speed and load variations is investigated. Energy storage systems are needed for power balance and power quality in autonomous wind energy systems. Initially, the holistic model of the entire system is achieved, including the PMSG, the uncontrolled rectifier, the buck converter and the storage system. The power absorbed by the connected loads can be effectively delivered and supplied by the proposed WT and energy storage systems, subject to TS‐fuzzy control. The main purpose is to supply 230‐V/50‐Hz through a three‐phase inverter. The performance of the proposed system is compared with the system without storage system. Moreover, the proposed system performance with the TS‐fuzzy control is compared with the conventional proportional–integral–derivative (PID) controller. The simulation results show that the proposed system with the TS‐fuzzy controller has good prediction of the electrical parameter waveforms compared with the case of absence of the storage system and the conventional PID controller.

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