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The operational security of power systems for wind farm (WF) integration becomes more important as the penetration of wind generation increases. A WF may contain hundreds of wind turbines (WT) and thus the power system simulations based on the complex model of a WT consume much time. This article proposes an equivalent WF model with the frequency-regulation function. The main research works include the establishment of the generic model of a WT, the development of single- and multimachine equivalent models for a large WF, the clustering of WTs based on the developed nonlinear wake model and the fuzzy C-means (FCM) clustering algorithm, the integration of the frequency-regulation function into the equivalent WF model, and the validation of the developed equivalent WF model by various operating scenarios. The results demonstrate that the proposed multimachine equivalent method based on the FCM clustering provides a more accurate model than a single-WT equivalent model. Consequently, the research results provide a solution for simulating a large-scale wind power integration, providing efficient, accurate, and fast steady-state and dynamic analyses. [ABSTRACT FROM AUTHOR]

With the increasing size of wind farms, the impact of the wake effect on wind farm energy yields become more and more evident. The arrangement of locations of the wind turbines (WTs) will influence the capital investment and contribute to the wake losses, which incur the reduction of energy production. As a consequence, the optimized placement of the WTs may be done by considering the wake effect as well as the components cost within the wind farm. In this paper, a mathematical model which includes the variation of both wind direction and wake deficit is proposed. The problem is formulated by using levelized production cost (LPC) as the objective function. The optimization procedure is performed by a particle swarm optimization (PSO) algorithm with the purpose of maximizing the energy yields while minimizing the total investment. The simulation results indicate that the proposed method is effective to find the optimized layout, which minimizes the LPC. The optimization procedure is applicable for optimized placement of WTs within wind farms and extendible for different wind conditions and capacity of wind farms. [ABSTRACT FROM PUBLISHER]