A variable droop control strategy for wind farms (WFs) that considers optimal rotor kinetic energy (RKE) is presented in this paper. The process for the control strategy is as follows. First, an optimized scheduling reserve mode (OSRM) is executed by the WF control center (WFCC) according to the deloaded rate orders issued by the dispatching center. Through coordinated optimization control for overspeed control and pitch angle control, more available RKE can be stored in each wind turbine (WT) under the OSRM than can be stored in conventional overspeed reserve mode (CORM). Second, the optimization results will be sent to a variable droop coefficient set module for each WT by the WFCC. Then the sum of the available RKE capacity and the mechanical load shedding capacity (the wind power curtailment) of each WT can be computed in real-time and used as a practical spinning reserve capacity to adjust the droop coefficient. In this way, the optimized available RKE stored in the WT under the OSRM can be fully released to participate in the droop frequency control. Finally, simulations are performed in PSCAD/EMTDC to verify the proposed variable droop frequency control strategy for WFs. The simulation results indicate that the capability of the primary frequency regulation would be further improved, especially for low or medium wind speeds.

With the increasing scale of wind farms, the fault characteristics tend to be complex, which poses a technical challenge to establish the dynamic equivalent model of wind farms. In this paper, a dynamic equivalent method of DFIG-based wind farm based on the density peak clustering algorithm (DPCA) is presented. First, under an analysis of short-circuit current (SCC) in single doubly fed induction generator (DFIG), the clustering indexes are selected. Second, with the selected clustering indexes and DPCA, a more refined two-stage clustering of DFIGs in wind farm is carried out. Third, the units in the same cluster are equivalent to one unit, and then the dynamic equivalent model of the DFIG-based wind farm is established. Finally, the proposed method is validated through the MATLAB/SIMULINK-based simulation results, and the comparison results also show that the dynamic equivalent model proposed in this paper has a better performance than two other equivalent models. Moreover, another comparison between DPCA and K-means clustering algorithm is analyzed, and the result shows that DPCA has a better performance which provides a better choice for dynamic equivalence of wind farms.

The main merit of grid-connected adjustable-speed pumped storage unit (ASPSU) is the capability to control the pumping power flexibly, which contributes to active power balance in power system operation. Physics-based dynamic modeling of ASPSU in pumping mode under power regulation is the foundation of the quantitative analysis on its transient performance, which has been studied inadequately. This study aims to derive a dynamic model of ASPSU in pumping mode which embodies reversible pump-turbine characteristics, and to conduct eigen analysis on ASPSU in pumping mode which facilitates a better understanding of its intrinsic dynamics. Firstly, the dynamic model of reversible pump-turbine is revealed to depict its regulation properties that the pumping power is adjusted by rotational speed rather than guide vane opening. Then, the state-space representation of ASPSU in pumping mode is established to be utilized with small disturbances (including indicial and ramp tests) and validated by comparing simulated results with actual records of a commissioned ASPSU in Japan. It is also effective for compensating the wind power fluctuations based on a timescale of seconds in simulation. Finally, the eigenvalues, damping ratios, and participation factors of the state variables are investigated based on the small-signal-stability model of ASPSU in pumping mode under power regulation. The results of eigen analysis indicate that the small-signal behavior of the system is characterized by electromechanical mode and electromagnetic mode, and the latter is dominant. Moreover, the damping ratio of electromagnetic mode which is sensitive to system stability needs to be increased.

Crowbar protection and chopper protection (CCP) are commonly used hardware protection measures in the process of low voltage ride through (LVRT) of doubly-fed induction generator (DFIG). The protections operating states during fault have an important influence on the electromagnetic transient (EMT) process of DFIG. Therefore, different from only considering the influence of single protection, the coordinated control of crowbar protection and chopper protection are further considered in this paper, and a novel analysis method of CCP operation criterion is proposed by analyzing the relationship between rotor current, DC-link voltage and post-fault terminal voltage (PFTV) of DFIG. On this basis, the states of CCP under different voltage drop depths are analyzed. And an EMT analysis model of DFIG considering CCP is studied. The proposed method and EMT analysis model for DFIG are later validated through PSCAD/EMTDC-based simulation results. The results show that the method and model proposed in this paper have good accuracy and practicability, which provides more references for further study of the transient characteristics of DFIG.

Having great performance on active power regulation, grid-connected adjustable-speed pumped storage unit (ASPSU) has attracted world-wide concern. This superior transient response is achieved by both its excitation system and speed governing system, but dynamic characteristics study of ASPSU taking into account the optimal control of speed governor has seldom been explored. This paper first presents small-signal-stability model of on-grid ASPSU. Furthermore, instead of the dynamic-performance-indexes rule, a stability-degree criteria is proposed to optimize parameters for the speed regulator of ASPSU, which aims at improving the dynamic behavior of rotational speed and guide vane opening. Firstly, a mathematical model of on-grid ASPSU with power priority control is derived and it is validated by comparing simulated performance with on-site measurements of a Japanese commissioned ASPSU. Secondly, the small-signal-stability model is showcased, and the influence of control parameters on the stability degree which builds the bridge between eigenvalues and transient performance is investigated in details. Thirdly, instead of improved integral of time-weighted-absolute-error criteria, a novel stability-degree criteria is utilised in particle swarm optimization algorithm to optimise the regulator’s parameters of ASPSU. Finally, with the optimised parameters, the indicial response of a 400MW on-grid ASPSU built with PSCAD/EMTDC is significantly enhanced.

This paper presents a calculation method of short-circuit current (SCC) for DFIG-based wind farm considering the voltage distribution characteristics. When a short-circuit fault occur in a wind farm, a large SCC will be contributed by the dozens or even hundreds of doubly-fed induction generators (DFIGs) in the wind farm. And the security and stability of the wind farm will be affected by the SCC. The SCC characteristics of the DFIG are closely related to its post-fault terminal voltage (PFTV). Therefore, a practical calculation model of SCC in single DFIG is proposed in this paper, based on electromagnetic transient (EMT) analysis. And according to a correction method of topological matrix for post-fault wind farm proposed in this paper, the relationship model between voltages and currents under short-circuit faults is established. Then the PFTVs and SCCs of the DFIGs in the wind farm can be obtained by solving the model equation. Finally, the proposed method is validated through MATLAB/Simulink-based simulation results, and a comparison with the national standard calculation method is analyzed. The results show that this method has better accuracy, which provides a more accurate basis for the electrical safety design of wind farms.