Abstract
The doubly-fed induction generator (DFIG) wind turbine system, which is composed of the wind turbine, generator, rotor-side converter, grid-side converter, and so on, is a typical multi-time scale system. The dynamic processes at different time scales do not exist in isolation. Furthermore, neglecting the coupling of parameters of different time scales to reduce the order of the model will lead to deviation between the simulation results and the actual results, which may not be suitable for power system transient analysis. This paper proposes an electromechanical transient model and an electromagnetic transient model of the DFIG wind turbine system that consider the interaction of multiple time-scale dynamic processes. Firstly, the paper applies the modal analysis method to explain the multi-time scale characteristics of the DFIG wind turbine system. Secondly, the variation in the eigenvalues of the DFIG wind turbine system before and after the order reduction and the coupling between variables and the system, as well as the coupling between variables of different time scales, are analyzed to obtain the preliminary 21-order simplified model. Thirdly, considering the weak coupling characteristics between the mechanical part and the electromagnetic part of the DFIG wind turbine system, the 21-order simplified model is decomposed into a 15-order electromagnetic transient model and a six-order electromechanical transient model on the basis of their time scales. Then, according to the balance between simulation time and simulation accuracy, the 14-order electromagnetic transient model and the 10 or 12-order electromechanical transient model are finally obtained. Finally, the rationality of the simplified models is verified by simulations under two large disturbance conditions, namely wind speed abrupt change and voltage sag. The obtained simplified models have reference significance for improving the simulation speed of a wind power grid-connected system and analyzing the internal mechanism of the DFIG wind turbine system’s stability.
Highlights
With the continuous decline in fossil fuel reserves and the increasing demand for energy, the development and application of renewable energy is receiving more attention across the world [1].As one of the renewable energy sources with the advantages of mature technology and low cost, wind power is becoming more and more widely used in the world
While in [13], it is indicated that the transient process of rotor current can be ignored when the large step length is adopted in the simulation for the rapid variation of rotor current. This type of model reduction method selectively analyzed the influence of each module on the system, but the order reduction of the whole doubly-fed induction generator (DFIG) wind turbine system was little mentioned
The small disturbance model of the DFIG wind turbine system with the equilibrium model reduction, which is aligned with the analysis of the coupling between variables and the system, point at the maximum power tracking (MPPT) stage is constructed for exploring the multi-time scale as well as the coupling between variables of different time scales
Summary
With the continuous decline in fossil fuel reserves and the increasing demand for energy, the development and application of renewable energy is receiving more attention across the world [1]. While in [13], it is indicated that the transient process of rotor current can be ignored when the large step length is adopted in the simulation for the rapid variation of rotor current This type of model reduction method selectively analyzed the influence of each module on the system, but the order reduction of the whole DFIG wind turbine system was little mentioned. In [17], on the basis of a small disturbance model, the dynamics of the state variables, i.e., the dynamics of direct current (DC) voltage, the controller of the grid-side converter, generator stator, generator rotor, and the inner loop of the rotor-side converter current control were gradually ignored, and four simplified models of different orders were obtained In these processes of model reduction, the variables of different time scales are totally isolated, and the interaction between variables in different time scales or the same time scale are not taken into account.
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