Title: Experimental implementation of SEIG-based wind energy system using neural network controller

Authors: Giribabu Dyanamina

Addresses: Department of Electrical Engineering, Maulana Azad National Institute of Technology, Bhopal, Madhya Pradesh, India

Abstract: The paper presents a standalone self-excited induction generator (SASEIG)-based wind energy system (WES) connected with a back to back power converter. It consists of a generator side converter (GSC) used to regulate variation of torque and flux, and load side converter (LSC) used to adjust the variation of DC voltage. The indirect vector control (IVC) technique is employed to regulate the GSC and LSC separately. When a SASEIG is operated at variable speed, the voltage variation of controller is very critical. Therefore to enhance the voltage variation, the proportional integral (PI) controller is replaced with NNC in indirect vector control of GSC. The proposed WES is simulated using MATLAB/Simulink software and is operated at variable speeds. To validate the proposed method experimentally, the prototype model is developed and it is digitally implemented using DS-1104 R&D controller.

Keywords: self-excited induction generator; indirect vector control; IVC; wind energy system; WES; neural network controller; NNC.

DOI: 10.1504/IJPELEC.2022.124700

International Journal of Power Electronics, 2022 Vol.16 No.2, pp.226 - 247

Received: 09 Mar 2020
Accepted: 29 Sep 2020
Published online: 08 Aug 2022 *

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