Cascading failure is a potential threat in power systems with the scale development of wind power, especially for the large-scale grid-connected and long distance transmission wind power base in China. This introduces a complex network theory (CNT) for cascading failure analysis considering wind farm integration. A cascading failure power flow analysis model for complex power networks is established with improved network topology principles and methods. The network load and boundary conditions are determined to reflect the operational states of power systems. Three typical network evaluation indicators are used to evaluate the topology characteristics of power network before and after malfunction including connectivity level, global effective performance and percentage of load loss (PLL). The impacts of node removal, grid current tolerance capability, wind power instantaneous penetrations, and wind farm coupling points on the power grid are analyzed based on the IEEE 30 bus system. Through the simulation analysis, the occurrence mechanism and main influence factors of cascading failure are determined. Finally, corresponding defense strategies are proposed to reduce the hazards of cascading failure in power systems.

The rapid development of renewable energy sources such as wind power has brought great challenges to the power grid. Wind power penetration can be improved by using hybrid energy storage (ES) to mitigate wind power fluctuation. We studied the strategy of smoothing wind power fluctuation and the strategy of hybrid ES power distribution. Firstly, an effective control strategy can be extracted by comparing constant-time low-pass filtering (CLF), variable-time low-pass filtering (VLF), wavelet packet decomposition (WPD), empirical mode decomposition (EMD) and model predictive control algorithms with fluctuation rate constraints of the identical grid-connected wind power. Moreover, the mean frequency of ES as the cutoff frequency can be acquired by the Hilbert Huang transform (HHT), and the time constant of filtering algorithm can be obtained. Then, an improved low-pass filtering algorithm (ILFA) is proposed to achieve the power allocation between lithium battery (LB) and supercapacitor (SC), which can overcome the overcharge and over-discharge of ES in the traditional low-pass filtering algorithm (TLFA). In addition, the optimized LB and SC power are further obtained based on the SC priority control strategy combined with the fuzzy control (FC) method. Finally, simulation results show that wind power fluctuation can be effectively suppressed by LB and SC based on the proposed control strategies, which is beneficial to the development of wind and storage system.

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