This paper develops a novel graph convolutional network (GCN) framework for fault location in power distribution networks. The proposed approach integrates multiple measurements at different buses while taking system topology into account. The effectiveness of the GCN model is corroborated by the IEEE 123 bus benchmark system. Simulation results show that the GCN model significantly outperforms other widely-used machine learning schemes with very high fault location accuracy. In addition, the proposed approach is robust to measurement noise and data loss errors. Data visualization results of two competing neural networks are presented to explore the mechanism of GCNs superior performance. A data augmentation procedure is proposed to increase the robustness of the model under various levels of noise and data loss errors. Further experiments show that the model can adapt to topology changes of distribution networks and perform well with a limited number of measured buses.

High-voltage dc (HVdc) circuit breakers (CBs) are a key technology of multiterminal dc (MTdc) systems and grids. In this article, a state-of-the-art 500-kV hybrid CB (HCB) topology is proposed and compared with other existing HCB solutions. Implementing the topology includes three important components: a modular designed high-current bidirectional solid-state switch (SS), an ultrafast mechanical switch (MS) based on a Thomson (CCDC) equipment with no conduction loss, whose corresponding functional verification test results have been presented in detail. On this basis, the overall 500-kV HCB and a comprehensive experimental platform are developed. Detailed experiments, including 25-kA turn-off and reclosing experiments, are conducted. The HCB was found to be capable of breaking a 25-kA current in 2.7 ms with 800-kV overvoltage, which is on par with the level of leading CBs worldwide.

Different from the continuous-switching behavior of series power electronic devices in converters, the single-switching attribute of DC breakers (DCBs) provide opportunities to integrate metal oxide varistors (MOVs), balancing circuits and series power power devices. This paper proposes a modular design methodology based on discrete MOVs of DC breaker (DCB) with series power electronic devices. The modular DCB (MDCB) topology and voltage balance issues, the steep front effect and solution, and the design method are proposed and analyzed in this study. Compared with the traditional DCB, the MDCB has self-balancing ability, thereby removing the voltage-balancing circuit and reducing the series module amount. The standard designed cell can be operated as an independent DCB or compose a high-voltage DCB in series flexibly, which decreases the difficulty of design and commission. Finally, a series experimental platform based on IGCT, IGBT, and IEGT is built to verify the correctness and effectiveness of the proposed design methodology.

The measurement of intense E-fields is a fundamental need in various research areas. Integrated optical E-field sensors (IOESs) have important advantages and are potentially suitable for intense E-field detection. This paper comprehensively reviews the development and applications of several types of IOESs over the last 30 years, including the Mach-Zehnder interferometer (MZI), coupler interferometer (CI) and common path interferometer (CPI). The features of the different types of IOESs are compared, showing that the MZI has higher sensitivity, the CI has a controllable optical bias, and the CPI has better temperature stability. More specifically, the improvement work of applying IOESs to intense E-field measurement is illustrated. Finally, typical uses of IOESs in the measurement of intense E-fields are demonstrated, including application areas such as E-fields with different frequency ranges in high-voltage engineering, simulated nuclear electromagnetic pulse in high-power electromagnetic pulses, and ion-accelerating field in high-energy physics.

DC grids, including highvoltage dc (HVdc) transmissions, midvoltage dc (MVdc) distributions, and low-voltage dc (LVdc) supply systems, have elicited widespread concern and rapidly developed in recent years [1]-[6]. Voltage and power can be flexibly controlled because power electronic equipment is widely used in dc grids. Moreover, the conversion stage for energy storage and renewable energy systems in dc grids can be simplified. Such simplification can reduce cost, enhance power conversion efficiency, and improve power quality.

With the rapid development of rene wable energy (e.g., wind and photovoltaic energy) and energy storage, the dc collector has become an effective conversion link of distributed energy access to medium-voltage power distribution grids. However, considering the inconsistency of dc voltage and the duty cycle of each submodule, the traditional carrier phase-shifting modulation is difficult to achieve the excellent harmonic characteristic in the dc collector, thereby introducing difficulties in the design of passive filters. To solve this problem, this article proposes a selective virtual synthetic vector embedding algorithm to realize full-range current harmonic suppression in the dc collector system. In this scheme, the switching voltage vectors outputted by each submodule are sorted, and the voltage vectors are selectively extracted and synthesized to calculate the embedded virtual voltage vector. Afterward, the voltage vector of each submodule is rotated and calculated online from the perspective of space geometry, and the optimal carrier phase combination in variable-angle carrier phase-shift modulation is obtained. Finally, the experimental results show that the proposed control algorithm can not only be used in the dc collector with any number of modules but also achieve fast and effective harmonic suppression in the whole operating range.