Traditional high‐voltage DC (HVDC) current differential protection has problems on identifying fault current and has long delay. In this study, a novel current differential protection principle for HVDC transmission lines is proposed. By the adoption of distributed parameter model, differential current criterion is formed at a selected point on the transmission line. When fault occurs on DC line, setting point differential current reaches a high value. When no fault occurs or fault occurs outside the DC line, setting point differential current reaches a small value. Comparing with the traditional current differential protection, the proposed principle eliminates the impact of distributed capacitive current and has no requirement of delay. Comparing with travelling wave protection, fault identification can be performed during both transient and steady states, and the proposed method has reasonable sampling frequency requirements and has high reliability. Simulation analysis shows that the proposed principle identifies faults reliably and rapidly. The proposed principle is theoretically novel and practically applicable.

For high‐voltage direct current (HVDC) transmission systems, the transient fault current characteristics are that: if the fault point is over the line, the fault component current measured at both converter stations would be increased and they have the same changing direction. If the fault point is beyond the line, the fault component current measured at one converter station is increasing and the fault component current measured at the other converter station is decreasing, so they have the opposite changing direction. According to this characteristic, a novel pilot protection principle for HVDC transmission line based on fault component current is proposed here. The principle proposed has no limitation to the sampling frequency. A fault, whether it occurs in the line or beyond the line, can be effectively identified only using the fault component current at both converter stations. At the same time, the setting criterion of the fault component current is also given. The simulation results show that the new method can identify the faults reliably and rapidly. The study is promising to have significant theoretical and practical value.

The large-scale access of distributed generations (DGs) increases the difficulty of islanding detection of DC microgrids. The DC islanding detection methods are still in their infancy and have low detection accuracy rate in the disturbed environments. This paper applied the concept of deep learning based on Multi scale refined composite standard deviation fuzzy entropy (MRC-SDFE) into islanding detection of DC microgrid. The method combining the Variational Mode Decomposition (VMD) and the MRC-SDFE is used to extract the characteristics of voltage and current signals at PCC, which can effectively filter out interference. On this basis, a Deep Belief Network (DBN) detection model based on the Sea-horses optimizer algorithm (SHO) is proposed for the first time. The SHO is used to automatically optimize and adjust network parameters during the training process without manual adjustments. Finally, islanding and non-islanding disturbance events are tested. Through simulation verification, it is proved that the proposed method can availably guarantee the accuracy and rapidity of islanding and non-islanding disturbance detection in an interference environment.

In view of the difficulties in coordination between reliability and sensitivity of conventional generator differential protection, this paper presents a novel generator differential protection scheme based on a new braking method. On the basis of the mathematical model of the field-circuit coupling method and the electrical network cascade characteristics, the stator windings were combined and decoupled by the improved six-sequence component method to eliminate electromagnetic coupling between winding coils. In accordance with the basic characteristics of longitudinal impedance, the function of sub-item discrimination was realized. Numerous simulations and the up-to-date dynamic experiments showed that the proposed method has good state discrimination ability and can effectively resist the influence of current transformer saturation. Thus, it has an excellent prospect for engineering promotion.

Low-frequency transformer is the key equipment in the low-frequency transmission system of offshore wind power, and its fault characteristics are significantly different from those of conventional transformers, so the traditional transformer protection scheme is not applicable to this system. In order to solve this problem, this paper proposes a fast protection method for low-frequency transformers based on instantaneous phase difference. The method firstly utilizes the amplitude of differential current as the criterion for protection initiation, and then combines the characteristics of the instantaneous phase difference of low-frequency transformers under different operating conditions to construct the corresponding protection criterion. Finally, a simulation model of the low-frequency transmission system is constructed using PSCAD, and the proposed protection scheme is verified based on this model. The simulation results show that the method can act reliably during low-frequency transformer faults and has good protection performance.

At present, the MVDC distribution grid is developing rapidly and relay protection is the key technology to ensure stable operation. Therefore, this paper focuses on the fault line selection method. Firstly, the fault characteristics are analysed when a fault occurs in the line, and a novel single‐pole fault line selection method is proposed based on 0‐mode power. The polarity of current fault component measured at the terminal of each line is used to identify the internal and external faults. And the 0‐mode power is used to select the faulty line. Finally, to verify the correctness of the proposed method, a radial MVDC distribution grid is built in PSCAD to output fault data in different fault conditions, and the fault line selection algorithm is implemented in MATLAB. The simulation results show that the proposed method is fast, effective, reliable and it has a certain degree of tolerance to transition resistance with a strong anti‐data delay and anti‐interference ability. Moreover, the fault line selection method proposed in this paper can still correctly select the fault line in the case of serious faults such as multiple line faults, sudden removal of lines, and sudden changes in photovoltaic output power.