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With the increasing penetration of wind power into the grid, its intermittent and fluctuating characteristics pose a challenge to the frequency stability of grids. Energy storage systems (ESSs) are beginning to be used to assist wind farms (WFs) in providing frequency support due to their reliability and fast response performance. However, the current schemes mostly focused on the sole operation of either WT or ESSs for frequency support, lacking in economy and reliability. To address these issues, this work proposes a sliding mode consensus control (SMCC) method for ESSs to assist the frequency response of WTs. First, a coordination strategy for the WTs and ESS is proposed to reinforce the frequency support capability of a WT–ESS by determining the optimal capacity of ESSs. Meanwhile, a novel SMCC is proposed to achieve proportional power sharing among ESSs and increase the total power output of the entire WFs during wind energy shortages. Moreover, an event triggered communication mechanism is utilized to reduce the information exchanges among ESSs. Subsequently, a Lyapunov stability analysis is conducted to prove the stability and finite time consensus of the proposed method. Simulation case studies are conducted in IEEE 39-bus system to validate the effectiveness of the proposed framework. [ABSTRACT FROM AUTHOR]

Energy storage systems (ESSs) are being utilized to improve wind farms’ (WF) frequency support capability due to their high reliability, fast response and the dual role of energy users and suppliers. Nevertheless, the problem of how much capacity should each ESS possesses in order to better serve the WFs has never been investigated. With this perspective, this paper proposes an optimal ESS allocation (OEA) scheme for doubly fed induction generator (DFIG) based WFs to mitigate the impact of wake effect in frequency support. Firstly, the synchronous stability of wind turbines under frequency dips is analyzed with the concept of frequency support margin (FSM), and the detrimental impact of the wake effect is also investigated. Subsequently, the role of ESSs to improve wind turbines’ synchronous stability is demonstrated. To make the OEA scheme practical, the wind turbines in a WF are segmented into different clusters based on the received wind speed. Afterwards, the OEA problem is formulated, where the objective is to optimize the coherency of the wind turbine clusters’ FSM level. The simulation results show that ESS can provide secondary frequency support under major grid frequency drops, and the proposed OEA scheme can reduce the risk of loss of synchronous stability. [ABSTRACT FROM AUTHOR]