The doubly-fed induction generator (DFIG) with virtual inertia control and reactive damping control gives a renewable energy generation system inertia and damping characteristics similar to those of a thermal power plant, and the parameters of the control strategy have a direct impact on the small-signal stability of the system. This paper firstly introduces the operating characteristics and control strategies of DFIG-based damping control and virtual inertia control, establishes a small-signal model of the control-based DFIG integrated interconnected system, and investigates the effects of virtual inertia and reactive damping values on the small-signal stability of the system; then, the maximum damping ratio of the interval oscillation mode in small disturbance analysis is taken as the optimization objective, and the control parameters are the optimization variables. An optimization method of inertia and damping parameters is established for improving the small disturbance stability of the system. The results show that the optimization procedure could improve the damping ratio of the interval oscillation mode while ensuring the system frequency. The effects of virtual inertia and reactive damping values on the small signal stability of the system are investigated, and an optimal allocation model and method for virtual inertia used to improve the small disturbance stability of the system is proposed.
This paper takes advantage of the high control flexibility and fast response time of the interfacing power electronic converter for doubly fed wind turbine grid-connected systems to address inter-area oscillations caused by inadequate system damping in power systems. A reactive-power-coordinated damping controller for a doubly fed induction generator (DFIG) is proposed, and it makes use of second-order sliding-mode technology. The suggested controller improves damping performance by controlling the reactive power. It provides benefits such as a quicker damping rate and resilience to modeling errors and parameter changes. The simulation results indicate the system’s improved performance in inter-area oscillation damping and the robustness of the suggested control technique over a broad range of functional areas.
The occurrence mechanisms of extreme events under random disturbances are relatively complex and not yet clear. In this paper, we take a class of generalized Duffing-type systems as an example to reveal three mechanisms for the occurrence of extreme events. First, it is intuitive that a very large excitation can generate extreme events, such as the Lévy noise. In such a case, extreme excitation works, while it does not require much about the systems. Second, when a system has a bifurcation structure, if the difference of the branches at the bifurcation point is large, a randomly varying bifurcation parameter can lead to extreme events. Finally, when a system has rare attractors, a random impulse excitation, such as Poisson white noise, is able to cause the system to escape from one general attractor into rare attractors. Such a kind of special regime switching behavior can lead to extreme events. These results reveal the possible mechanisms of extreme events in a class of nonlinear Duffing-type systems and provide guidance for further prediction and avoidance of extreme events.
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