ABSTRACT
This research work presents the modelling, analysis and control of two topologies of induction generators for wind energy conversion. The two topologies are the shorted stator induction generator (IG) and the doubly-fed induction generator (DFIG). Each of the two topologies employs a wound rotor induction machine and a set of back-to-back converters connected to the rotor of the induction machine, for the energy conversion process.
Vector variable models are conventionally deployed for representing the dynamics of these induction machine systems, which produce elegant results. However, vector variable models have their state variables as vector quantities, which imply that the state variables depend on coordinate system orientation and therefore, are sensitive and dependent on the choice of angle θ of reference frame transformation. In this work therefore, a generalized scalar variable model that can represent each of the induction generators with their respective converters is developed such that the natural variables and power quantities of the systems become the state variables. The natural variables are the electromagnetic torque (Te), reactive torque (Tr), rotor flux linkage (λr), stator flux linkage (λs), and rotor speed (ωr) of the induction machine, while the power variables are the real power (Pf) and reactive power (Qf ) of the gird side converter (GSC). Since the natural and power variables are scalar quantities, they do not change with respect to change in angle of reference frame transformation θ. In other words they are insensitive to the reference frame frequency ω. Results obtained from the dynamic simulation of the natural variable model of the induction machine are presented and compared to results obtained from conventional vector variable simulation.
At low wind speed, a method of reducing magnetization losses in DFIG involves shorting the stator terminals. The DFIG with its stator terminals shorted to one another is referred to as the shorted stator IG. Since the stator terminals are shorted the stator loses
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synchronism with utility grid network. Hence, there exists the challenge of obtaining the stator angular velocity or frequency that corresponds to the regime of minimal electrical losses. Therefore, an optimization procedure that uniquely determines the optimal stator angular frequency is proposed in this thesis. Steady state results that reveal the generator‟s operating limits and the optimal operating regime are also presented.
The conventional DFIG system is analysed using the proposed scalar variable model. The generator‟s operating boundaries for leading, lagging and unity stator power factor operations are established and the steady state results are presented. Furthermore, an optimization procedure that uniquely determines the optimal stator power factor operation is proposed.
Finally, an experimental test rig is set up to emulate a wind turbine-generator system. The operating regimes obtained in the steady state analyses are imposed on the practical machine through dynamic control schemes. The experimental results obtained compare favourably with the dynamic simulation and steady state predictions.
BALOGUN, A (2021). Modelling, Analysis and Control of Induction Generators for Wind Energy Conversion. Afribary. Retrieved from https://afribary.com/works/modelling-analysis-and-control-of-induction-generators-for-wind-energy-conversion
BALOGUN, ADEOLA "Modelling, Analysis and Control of Induction Generators for Wind Energy Conversion" Afribary. Afribary, 01 May. 2021, https://afribary.com/works/modelling-analysis-and-control-of-induction-generators-for-wind-energy-conversion. Accessed 11 Dec. 2024.
BALOGUN, ADEOLA . "Modelling, Analysis and Control of Induction Generators for Wind Energy Conversion". Afribary, Afribary, 01 May. 2021. Web. 11 Dec. 2024. < https://afribary.com/works/modelling-analysis-and-control-of-induction-generators-for-wind-energy-conversion >.
BALOGUN, ADEOLA . "Modelling, Analysis and Control of Induction Generators for Wind Energy Conversion" Afribary (2021). Accessed December 11, 2024. https://afribary.com/works/modelling-analysis-and-control-of-induction-generators-for-wind-energy-conversion