Modelling and simulation of self-excited induction generator driven by a wind turbine

Ammar Shamil Ghanim,Ahmed Nasser B Alsammak

doi:10.15587/1729-4061.2020.213246

Ammar Shamil Ghanim, Ahmed Nasser B Alsammak

Open Access

https://doi.org/10.15587/1729-4061.2020.213246

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Abstract

The excellent specifications of the isolated squirrel cage self-excited induction generator (SEIG) make it the first choice for use with renewable energy sources. However, poor voltage and frequency regulation (under load and speed perturbations) are the main problems with isolated SEIGs. Wide dependence on the SEIG requires prior knowledge of its behaviour with regard to variations in the input of mechanical power and output of electrical power to develop a control system that is capable of maintaining the voltage and frequency at rated values, as far as possible, with any change in the input or output power of the SEIG. In this paper, a mathematical model of a wind energy conversion system (WECS) based on a squirrel cage SEIG with a generalized impedance control (GIC) was built using the Matlab/Simulink environment in a d-q stationary reference frame. A fuzzy logic controller (FLC) was used to control the parameters of the GIC. The training of the FLC was conducted by a neural network through Matlab's Neuro-Fuzzy designer. The results of this paper showed that the trained FLC succeeded in controlling the real and reactive power flow between the SEIG and the GIC system, in which the maximum variation for both magnitude and frequency of the generated voltage with any load or wind speed perturbation will not exceed (0.2 %) for the frequency and (3 %) for the voltage magnitude in both directions. The SEIG model was validated by comparing the results obtained with those of well-known studies with the same rating and operating conditions

Highlights

IntroductionThe reduction of greenhouse gas emissions is crucial because of the rising need for clean and unconventional energy, especially when the depletion of fossil fuel supplies in the world is considered
Explanations of the results are as follows: – results with subsection (5. 1) had explained the dynamics for both voltage build-up and load insertion; – results with subsection (5. 2) had explained the influence of both load and wind speed perturbation on the magnitude and frequency of generated voltage, the results show the influence of load change on the rotor speed; – results with subsection (5. 3) had explained the effectiveness of the generalized impedance control (GIC)-fuzzy logic controller (FLC) in maintaining the magnitude and frequency of generated voltage with rated values despite load and wind speed perturbations
The proposed mathematical model succeeded in: – gathering the required information for recognizing the behavior of the SEIG under load and wind speed perturbation as shown in Fig. 9; – design a control system capable of maintaining both magnitude and frequency of the generated voltage as shown in subsection (5.3), which happened due to training of (FIS)s by the wide input-output data set gained from excessive simulations of the SEIG-wind turbine (WT)-GIC

Summary

Introduction

The reduction of greenhouse gas emissions is crucial because of the rising need for clean and unconventional energy, especially when the depletion of fossil fuel supplies in the world is considered. As one of the exceptionally famous assets of unconventional energy, wind energy is currently seeing rapid improvements worldwide [1]. This type of power generation needs machines with variable speeds, such as asynchronous machines. Artificial intelligence technology offers a wide range of choices for the enhancement of complex control systems. In addition to control systems, the adaptive neuro-fuzzy algorithm may be used for the modelling of complex systems, as in the paper [3]

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