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The uncertainty of power system is intensified by the integration of large-scale renewable energy resources such as wind farm (WF). Considering the impact of system uncertainties, the probabilistic stability analysis methods have been used in the stability assessments of power system with the WF integration. However, in traditional probabilistic analysis methods, WF is normally considered as PQ bus or aggregated as one single-machine equivalent model regardless of wake effect, which might reduce the accuracy of probabilistic stability studies. In this article, a dynamic equivalent modeling method of WF for probabilistic stability assessments is proposed. The wake effect is considered in the modeling process and a practical four-machine clustering method is used in wind turbines clustering. Besides, the fisher discriminant analysis (FDA) is adopt to combine the similar WTs clustering results reasonably. Then, the WF is aggregated to a multi-machine equivalent model by capacity weighted method. Also, the established WF probabilistic model can be directly used in time-domain simulation based on Monte Carlo simulation and FDA. Finally, the efficiency of the proposed method is verified in an actual WF in China. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) generators have continuously increased in recent years, whose power is usually controlled through the perturbation and observation (P&O) method. In essence, the P&O method is nonlinear and discontinuous. Hence, the conventional small-signal stability analysis is not suitable anymore when the influence of the P&O-based power control is considered. Focusing on this problem, this paper adopts the nonlinear describing function (DF) method to conduct the accurate stability analysis of PV generators with consideration of P&O-based power control. The detailed procedures about the DF method are introduced, and then the related influence factors like perturbation size, filters, and so on are analyzed quantitatively. Furthermore, the comparison with the conventional stability analysis methods is made, which suggests that the DF method can effectively enhance the accuracy of the stability analysis. All the conclusions are verified by the real-time hardware-in-loop tests. [ABSTRACT FROM AUTHOR]

Nowadays, with the highly penetrated wind generations, the accurate wind farm (WF) model is required for power system stability analysis. Due to the complexity on detailed WF model, the aggregated model, with a reasonable reduction of the detailed model meanwhile retaining the required level of accuracy is essential to be developed. In this paper, an improved WF aggregated modeling method for large-scale power system stability studies is proposed. To overcome the limitations of the traditional methods, a geometric template matching based time series wind turbines clustering method is developed. Moreover, a multiobjective optimization algorithm, which fully considered the wind speed disturbance and system fault together, is designed to identify both the generator and control parameters. Additionally, to shrink the size of the identified parameters and increase the modeling accuracy, a sensitivity and correlation analysis based key parameters selection scheme is also adopted. To verify the effectiveness of the proposed method, dynamic responses of the proposed aggregated model are compared against the responses of the traditional equivalent model for various wind scenarios through an actual case. [ABSTRACT FROM AUTHOR]

Based on the decentralized sliding mode control, a load frequency controller is designed in this paper for multi-area interconnected power systems with matching and unmatched uncertainties. The proportional and integral switching surface is constructed for each area to improve system dynamic performance in reaching intervals. The robust controller is proposed by the reaching law method to assure that frequency fluctuation converges to zero after a load and operation point variation. A three-area interconnected power system is studied to illustrate the effectiveness of the proposed decentralized sliding mode control scheme. [ABSTRACT FROM PUBLISHER]