ANN-based robust DC fault protection algorithm for MMC high-voltage direct current grids

Fast and reliable protection is a significant technical challenge in modular multilevel converter (MMC) based DC grids. The existing fault detection methods suffer from the difficulty in setting protective thresholds, incomplete function, insensitivity to high resistance faults and vulnerable to noise. This paper proposes an artificial neural network (ANN) based method to enable DC bus protection and DC line protection for DC grids. The transient characteristics of DC voltages are analysed during DC faults. Based on the analysis, the discrete wavelet transform (DWT) is used as an extractor of distinctive features at the input of the ANN. Both frequency-domain and time-domain components are selected as input vectors. A large number of offline data considering the impact of noise is employed to train the ANN. The outputs of the ANN are used to trigger the DC line and DC bus protections and select the faulted poles. The proposed method is tested in a four-terminal MMC based DC grid under PSCAD/EMTDC. The simulation results verify the effectiveness of the proposed method in fault identification and the selection of the faulty pole. The intelligent algorithm based protection scheme has good performance concerning selectivity, reliability, robustness to noise and fast action

An improved DC fault protection scheme independent of boundary components for MMC based HVDC grids

For Modular Multilevel Converter (MMC) based DC grids, current-limiting reactors (CLRs) are mainly employed to suppress the fault current and provide boundary effects to detect internal faults. Thus, most existing protection schemes are highly dependent on the larger CLRs to guarantee high selectivity. However, in existing MMC based HVDC projects, the size of CLRs is restrained by the cost, weight and system stability under normal state. Thus, boundary protections may fail to detect high-resistance faults and pole-to-ground faults. To overcome these shortcomings, this paper proposes a fast and selective DC fault detection algorithm independent of boundary components. The propagation characteristics of line-mode backward traveling-waves (TW) are analyzed to identify external and internal faults. The polarities of zero-mode backward TWs are employed to select faulted poles. To detect remote faults, a pilot protection scheme based on the directional overcurrent is adopted as the complementary criterion. The detection speed of the proposed protection is fast, with a delay less than 1.1ms. Besides, it is robust to fault resistance and immune to noise. Various simulation results in PSCAD/EMTDC demonstrate that the proposed method is not affected by AC faults, fault distances and fault type

A single-end protection scheme for hybrid MMC HVDC grids considering the impacts of the active fault current-limiting control

In the hybrid modular multilevel converter (MMC) based high voltage direct current (HVDC) systems, the fault current can be actively suppressed by the converter itself, which endows a smaller requirement for current-limiting reactors (CLR) and a larger time margin for fault detection algorithms, comparing with the half-bridge MMC. But the robustness to fault resistance and noise disturbance of existing boundary protection schemes will be deteriorated with small CLRs. Moreover, the fast response of the fault current-limiting control will change the output DC voltage of hybrid MMC, which affects the fault characteristics and may cause mal-operation of existing protection algorithms. Thus, a single-end protection scheme considering the impacts of the active current-limiting control is proposed for the hybrid MMC based DC grids. The traveling-wave characteristics under different fault stages are analyzed to evaluate the impacts of the fault current-limiting control. In addition, a coordination protection strategy versus different fault conditions is adopted to improve reliability. Various cases in PSCAD/EMTDC are simulated to verify that the proposed method is robust to fault resistance, fault distance, power reversal, AC faults, and immune to noise

An adaptive reclosing strategy for MMC-HVDC systems with hybrid DC circuit breakers

Modular multilevel converter (MMC) based high voltage direct current transmission (HVDC) is an effective solution for large-scale renewable power integration over long-distance. In the overhead MMC-HVDC systems, the high voltage DC circuit breakers (DCCB) are implemented to interrupt the DC fault current. Subsequent to fault isolation, the DCCBs are required to automatically re-close to restore power transmission quickly. However, when the DCCBs are re-closed to permanent faults, they will be tripped again, resulting in a high requirement of interruption capacity for DCCBs and second overcurrent strikes on the HVDC systems. To overcome the drawbacks of the conventional auto-reclosing scheme, this paper proposes an adaptive reclosing scheme based on the active pulse injection from the converter associated with the coordination control of hybrid DCCBs. The single-end adaptive reclosing scheme as well as two ends adaptive reclosing scheme dedicated to two-terminal HVDC systems and meshed DC grids are presented respectively. By applying this method, the location of faults can also be achieved in the case of permanent faults. In order to verify the effectiveness of the proposed adaptive reclosing schemes, extensive simulations have been conducted under PSCAD/EMTDC

An improved DC fault protection algorithm for MMC HVDC grids based on modal domain analysis

To detect the DC faults for MMC based DC grids using overhead line transmission, many protection methods in phase-domain have been proposed. These existing protection methods suffer from incomplete function, weak theoretical basis and sensitivity to fault resistance and noise disturbance. To overcome these shortcomings, this paper proposes an improved DC fault protection algorithm using the modal-domain approach for the MMC based overhead DC grids, which decouples interaction between positive and negative poles and mitigates the strong frequency-dependency of the characteristic impedance in phase-domain. The DC fault equivalent circuits are established in modal-domain and the fault characteristics during the initial stage are analysed. Based on the modal-domain analysis, the line-mode reactor voltage which combines fault characteristics of negative and positive reactor voltages, is employed to identify the internal faults. The zero-mode reactor voltage which enlarges the differences between faulty and healthy poles, is employed to select the faulted pole. This method is robust to fault resistance and noise with high detection speed. In addition, it is not affected by power reversal, AC faults and DCCB operation, which are validated and evaluated by simulations in PSCAD/EMTDC

A transient voltage based DC fault line protection scheme for MMC based DC grid embedding DC breakers

Fast and reliable DC fault detection is one of the main challenges for modular multilevel converter (MMC) based DC grid with DC circuit breakers (DCCBs). This paper extracts the high frequency components of transient voltages by wavelet transform and proposes a fault identification method based on the difference of transient voltages to identify the faulted lines for DC grids using overhead lines. Meanwhile, a faulted pole discrimination method based on the difference between the change of positive and negative pole voltages is presented. A line protection scheme including detection activation, fault identification, faulted pole discrimination and post-fault re-closing is designed. Using only the local measurements, the scheme can realize the protection of the whole line without communication and has the capability of fault resistance endurance and anti-disturbance. The proposed method is tested with a four-terminal MMC based DC grid in PSCAD/EMTDC. The selection methods of threshold values are presented and the impact of DCCB operation on the reliability of DC fault protection is analysed. Simulation results verify the fast detection and reliability of the designed DC line protection scheme

A fault detection and location algorithm for the LVDC interconnection network in rural area

Low voltage DC (LVDC) microgrids (MGs) can be linked together through an interconnection network to enhance the utilization of their energy resources in remote locations, particularly in rural low-income areas. However, the identification of the fault is challenging due to the fast fault transients and equipment limitations, where there are no sensors and DC circuit breakers (DCCBs) in the lines. To solve this problem, this article proposes a fault detection and location algorithm without requiring extra sensors and DCCBs in lines. The proposed algorithm uses the sensors of the interface converters to detect the fault. Following this, a coordinated current injection method is used to identify the faulty element by coordinating converters with disconnectors. This process employs two strategies “weight check” and “scope check” to minimize the time and the number of actions. The algorithm is robust to various fault impedance, fault types and network topology modifications. The effectiveness of the algorithm is validated through a series of simulation case studies

An improved DC line fault detection scheme using zone partition for MTDC wind power integration systems

The MMC based DC grids are an effective solution to integrate bulk wind power. Under DC faults, the wind power is continuously fed into DC grids, resulting in large fault currents. To guarantee the uninterrupted and safe operation of healthy parts, DC faults should be detected and isolated selectively. Most existing DC fault detection schemes rely on large current-limiting reactors (CLR) to guarantee high selectivity. The reliability of them will be deteriorated under weak boundary conditions. Besides, some schemes fail to identify close-in faults. Though fault detection schemes independent of CLRs are proposed, they cannot work well for remote faults. Hence, to protect the entire transmission line with smaller CLRs, an improved DC fault detection scheme using zone partition is proposed. Firstly, according to different fault distances, internal faults are partitioned into four zones along the transmission line. The fault characteristics in different zones are analyzed. Then, the polarities and arrival times of traveling-waves are used to design the criteria dedicated to different zones. The proposed method is endurable to fault resistance and noise disturbance. Simulation results show that the MTDC wind power integration systems can operate safely during DC fault isolation

A differential pilot protection scheme for MMC based DC grid resilient to communication failure

Primary single-end line protection strategies of MMC HVDC systems are difficult to make a tradeoff between fast detection speed and high reliability. To improve reliability, the pilot protection schemes based on communication and data exchange can be adopted. However, the communication-based schemes suffer from potential communication failure problems, such as data error, data loss and time synchronization error. To avoid blocking of protection devices during communication failures, a resilience-oriented differential pilot protection method is proposed in this paper. To address the problem of synchronization error, a startup element based on the multi-resolution morphological gradient (MMG) of traveling wave is proposed. For the problems of data error and data loss in communication, the sampled data are preprocessed by the morphological filtering (MF). And the correlation of traveling waves is used to identify the internal and external faults; the ratio of the morphological gradient of pole voltages is adopted to discriminate the faulty poles. A four-terminal MMC based DC grid model is built in PSCAD/EMTDC interfaced with the optical fiber-based communication system built in MATLAB/Simulink. The simulation results show that the protection scheme can effectively identify the faults against serious communication problems of 1% bit error rate and 5% data loss