The arc-suppression coil(ASC)in parallel low resistance(LR)multi-mode grounding is adopted in the mountain wind farm to cope with the phenomenon that is misoperation or refusal of zero-sequence protection in LR ground...The arc-suppression coil(ASC)in parallel low resistance(LR)multi-mode grounding is adopted in the mountain wind farm to cope with the phenomenon that is misoperation or refusal of zero-sequence protection in LR grounding wind farm.If the fault disappears before LR is put into the system,it is judged as an instantaneous fault;while the fault does not disappear after LR is put into the system,it is judged as a permanent fault;the single-phase grounding fault(SLG)protection criterion based on zerosequence power variation is proposed to identify the instantaneous-permanent fault.Firstly,the distribution characteristic of zero-sequence voltage(ZSV)and zero-sequence current(ZSC)are analyzed after SLGfault occurs in multi-mode grounding.Then,according to the characteristics that zero-sequence power variation of non-fault collector line is small,while the zero-sequence power variation of fault collector line can reflect the active power component of fault resistance,the protection criterion based on zero-sequence power variation is constructed.The theoretical analysis and simulation results show that the protection criterion can distinguish the property of fault only by using the single terminal information,which has high reliability.展开更多
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
基金This paper is supported in part by the National Natural Science Foundations of China,and the Major Science and Technology Projects in Yunnan Province under Grant Nos.51667010,51807085,and 202002AF080001.
文摘The arc-suppression coil(ASC)in parallel low resistance(LR)multi-mode grounding is adopted in the mountain wind farm to cope with the phenomenon that is misoperation or refusal of zero-sequence protection in LR grounding wind farm.If the fault disappears before LR is put into the system,it is judged as an instantaneous fault;while the fault does not disappear after LR is put into the system,it is judged as a permanent fault;the single-phase grounding fault(SLG)protection criterion based on zerosequence power variation is proposed to identify the instantaneous-permanent fault.Firstly,the distribution characteristic of zero-sequence voltage(ZSV)and zero-sequence current(ZSC)are analyzed after SLGfault occurs in multi-mode grounding.Then,according to the characteristics that zero-sequence power variation of non-fault collector line is small,while the zero-sequence power variation of fault collector line can reflect the active power component of fault resistance,the protection criterion based on zero-sequence power variation is constructed.The theoretical analysis and simulation results show that the protection criterion can distinguish the property of fault only by using the single terminal information,which has high reliability.
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.
