To address the problems of wind power abandonment and the stoppage of electricity transmission caused by a short circuit in a power line of a doubly-fed induction generator(DFIG) based wind farm, this paper proposes a...To address the problems of wind power abandonment and the stoppage of electricity transmission caused by a short circuit in a power line of a doubly-fed induction generator(DFIG) based wind farm, this paper proposes an intelligent location method for a single-phase grounding fault based on a multiple random forests(multi-RF) algorithm. First, the simulation model is built, and the fundamental amplitudes of the zerosequence currents are extracted by a fast Fourier transform(FFT) to construct the feature set. Then, the random forest classification algorithm is applied to establish the fault section locator. The model is resampled on the basis of the bootstrap method to generate multiple sample subsets, which are used to establish multiple classification and regression tree(CART) classifiers. The CART classifiers use the mean decrease in the node impurity as the feature importance,which is used to mine the relationship between features and fault sections. Subsequently, a fault section is identified by voting on the test results for each classifier. Finally, a multi-RF regression fault locator is built to output the predicted fault distance. Experimental results with PSCAD/EMTDC software show that the proposed method can overcome the shortcomings of a single RF and has the advantage of locating a short hybrid overhead/cable line with multiple branches. Compared with support vector machines(SVMs)and previously reported methods, the proposed method can meet the location accuracy and efficiency requirements of a DFIG-based wind farm better.展开更多
With the increasing share of wind power,it is expected that wind turbines would provide frequency regulation ancillary service.However,the complex wake effect intensifies the difficulty in controlling wind turbines an...With the increasing share of wind power,it is expected that wind turbines would provide frequency regulation ancillary service.However,the complex wake effect intensifies the difficulty in controlling wind turbines and evaluating the frequency regulation potential from the wind farm.We propose a novel frequency control scheme for doubly-fed induction generator(DFIG)-based wind turbines,in which the wake effect is considered.The proposed control scheme is developed by incorporating the virtual inertia control and primary frequency control in a holistic way.To facilitate frequency regulation in timevarying operation status,the control gains are adaptively adjusted according to wind turbine operation status in the proposed controller.Besides,different kinds of power reserve control approaches are explicitly investigated.Finally,extensive case studies are conducted and simulation results verify that the frequency behavior is significantly improved via the proposed control scheme.展开更多
基金supported in part by the National Natural Science Foundation of China (No. 51677072)。
文摘To address the problems of wind power abandonment and the stoppage of electricity transmission caused by a short circuit in a power line of a doubly-fed induction generator(DFIG) based wind farm, this paper proposes an intelligent location method for a single-phase grounding fault based on a multiple random forests(multi-RF) algorithm. First, the simulation model is built, and the fundamental amplitudes of the zerosequence currents are extracted by a fast Fourier transform(FFT) to construct the feature set. Then, the random forest classification algorithm is applied to establish the fault section locator. The model is resampled on the basis of the bootstrap method to generate multiple sample subsets, which are used to establish multiple classification and regression tree(CART) classifiers. The CART classifiers use the mean decrease in the node impurity as the feature importance,which is used to mine the relationship between features and fault sections. Subsequently, a fault section is identified by voting on the test results for each classifier. Finally, a multi-RF regression fault locator is built to output the predicted fault distance. Experimental results with PSCAD/EMTDC software show that the proposed method can overcome the shortcomings of a single RF and has the advantage of locating a short hybrid overhead/cable line with multiple branches. Compared with support vector machines(SVMs)and previously reported methods, the proposed method can meet the location accuracy and efficiency requirements of a DFIG-based wind farm better.
基金This work was partially supported by Natural Science Foundation of China(No.72071100)Guangdong Basic and Applied Basic Research Fund(No.2019A1515111173)Department of Education of Guangdong Province,and Young Talent Program(No.2018KQNCX223).
文摘With the increasing share of wind power,it is expected that wind turbines would provide frequency regulation ancillary service.However,the complex wake effect intensifies the difficulty in controlling wind turbines and evaluating the frequency regulation potential from the wind farm.We propose a novel frequency control scheme for doubly-fed induction generator(DFIG)-based wind turbines,in which the wake effect is considered.The proposed control scheme is developed by incorporating the virtual inertia control and primary frequency control in a holistic way.To facilitate frequency regulation in timevarying operation status,the control gains are adaptively adjusted according to wind turbine operation status in the proposed controller.Besides,different kinds of power reserve control approaches are explicitly investigated.Finally,extensive case studies are conducted and simulation results verify that the frequency behavior is significantly improved via the proposed control scheme.
