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Reflected wave identification is the core of single‐ended travelling wave fault location, in which the obvious superimposed oscillation is the main obstacle for precise reflected wave identification with field data. This study proposes a reflected wave identification method based on speeded‐up robust features, which can gradually approximate from the possibly largest fault distance to the near‐end fault distance so as to exclude the reflected wave from time window containing initial wave. In particular, the time window segmentation divides initial wave and reflected wave into two inconsistent time windows, hence the reflected wave from the superimposed oscillation that usually follows the travelling wave can be effectively separated, such that the identification of reflected wave can be significantly simplified. Lastly, the superimposed oscillation is thoroughly analysed while both the field data with and without obvious superimposed oscillation are presented to evaluate the effectiveness of the proposed approach. Field data obtained from 21 substations scattered among Yunnan power grid of China validate the implementation feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

The phenomenon of wind abandoned caused by fault of transmission lines has occurred frequently. Since fault current output by wind turbine after fault may induce the frequency variation of the fundamental frequency, fault location based on the fundamental resistance is easily invalid. In order to locate fault accurately and rapidly after wind farm transmission line faults, a time‐domain‐based novel fault location method for transmission line of wind farm is introduced in this paper. The main idea of the proposed scheme is to discretise the distributed‐parameter model of transmission line that is given in the form of partial differential equations by using the finite‐difference time‐domain. In addition, the phase current and voltage at both ends of lines are regarded as boundary conditions. Then, the variational iteration method is utilised to calculate transmission line equations to obtain line length function. At last, fault location function is constructed by a minimised objective function. This paper builds wind power transmission line system simulation model and carries out simulation experiments on PSCAD/EMTDC. To verify the performance of the algorithm, several factors are taken into account for simulation including different fault distances, different fault types, different fault resistances, and different fault inception angles. Simulation results reveal the performance of the proposed method to locate fault for transmission lines connected to wind farm with high accuracy. [ABSTRACT FROM AUTHOR]

The high‐resistance faults at the far end are the most important factor that causes protection failure of HVDC transmission lines. In the initial stage of the transmission lines fault, the transient information of power grid is abundant, and the sequential overlapping derivative (SOD) transform can emphasise the characteristics of the high‐frequency transient signal and its sudden change direction, amplify fault characteristics, and eliminate noise as far as possible, which is of great benefit to identify the high‐resistance faults at the far end. A fault identification method based on the SOD transform of voltage transient is proposed. In this method, the initial fault voltage travelling wave is processed by the SOD transform, and the initial fault voltage is a travelling wave is quickly detected. The set value of SOD transform is obtained according to the traversal simulation fault location, thus the identification criteria of internal and external faults are obtained. The simulation results show that the method can accurately identify the high‐resistance faults at the far end, and it is hardly affected by transition resistance and fault distance. [ABSTRACT FROM AUTHOR]

This study develops a perturbation compensation based sliding‐mode control (PCSMC) strategy of a permanent magnetic synchronous generator (PMSG) for optimal extraction of wind energy. Firstly, PMSG non‐linearities, uncertain parameters, unmodelled dynamics, and stochastic wind speed variations are aggregated into a perturbation. Then, it is estimated by a sliding‐mode state and perturbation observer in the real time. Further, the perturbation estimate is fully cancelled by sliding‐mode controller (SMC) for global control consistency, together with considerable robustness thanks to the sliding‐mode mechanism. In addition, the upper bound of perturbation is replaced by its real‐time estimate; thus more proper control costs could be achieved without over‐conservativeness. Moreover, PCSMC does not require an accurate PMSG model while only the measurement of d‐axis current and mechanical rotation speed is required. Four case studies are carried out, e.g. step change of wind speed, low‐turbulence stochastic wind speed, high‐turbulence stochastic wind speed, and PMSG parameter uncertainties. Simulation results demonstrate that PCSMC can rapidly extract higher power under different wind speed profiles against vector control and SMC. Lastly, a dSpace‐based hardware‐in‐the‐loop experiment is undertaken which validates its implementation feasibility. [ABSTRACT FROM AUTHOR]