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 over-speed 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 over-speed 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.INDEX TERMS Cost of wind power curtailment, droop coefficient, optimized scheduling model, rotor kinetic energy.
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. INDEX TERMS DFIG-based wind farm, short-circuit current (SCC), dynamic equivalent, density peak clustering algorithm (DPCA).
Having great performance on active power regulation, grid-connected adjustable-speed pumped storage unit (ASPSU) has attracted worldwide 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 dynamicperformance-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 doubly fed induction generator (DFIG)-based wind farm considering the voltage distribution characteristics. When a short-circuit fault occurs in a wind farm, a large SCC will be contributed by the dozens or even hundreds of 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 the electromagnetic transient analysis. And according to a correction method of the topological matrix for a 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. INDEX TERMS Wind farm, doubly-fed induction generator (DFIG), short-circuit current, voltage distribution, MATLAB/Simulink.
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