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As wind power generation increases, there is an increasing need for frequency support from wind turbines. There are many advantages to connect offshore wind farms with the electricity grid via a high-voltage direct current (HVdc) system. HVdc transmission systems allow wind farms to provide frequency regulation and voltage control, making them more flexible compared with HVac transmission systems. Several frequency-support control methods have been developed previously. However, few works have compared various control methods for HVdc-connected offshore wind farms. This work presents a detailed comparison of the main frequency-support control methods that can be used for HVdc-connected offshore wind farms. These control approaches are mainly based on the communication-based schemes or coordination-based methods. The communication-based scheme uses communication devices to directly transfer the grid frequency information to an offshore wind farm. The coordination-based method transfers the dynamic dc voltage information from the HVdc via generator emulation control and then enables the voltage-source converter on the wind-farm side to supply frequency regulation. In this work, we considered the synthetic inertial control of wind turbines for our analysis, including inertia and droop controllers. Furthermore, the capacitors in the HVdc system can release the stored energy to help wind farms regulate frequency during operation. [ABSTRACT FROM AUTHOR]

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]