SiC MOSFET has low on-state resistance and can work on high switching frequency, high voltage, and some other tough conditions with less temperature drift, which could provide the significant improvement of power density in power converters. However, for the bridge circuit in an actual converter, high dv/dt during fast switching transient of one mosfet will amplify the negative influence of parasitic components and produce the significant negative voltage spikes on the complementary MOSFET, which will threaten its safe operation. This paper proposes a new gate driver circuit for SiC MOSFET to attenuate the negative voltage spikes in a bridge circuit. The proposed gate driver adopts a simple voltage dividing circuit to generate a negative gate-source voltage as traditional and a passive triggered transistor with a series-connected capacitor to suppress the negative voltage spikes, which could satisfy the stringent requirements of fast switching SiC MOSFETs under the high dc voltage condition with low cost and less complexity. An analysis is presented in this paper based on the simulation and experimental results with the performance comparison evaluated.

Battery storage has an important role to play in integrating large-scale renewable power generations and in transport decarbonization. Real-time monitoring of battery temperature profiles is indispensable for battery safety management. Due to the advantages of small size, resistance to corrosion, immunity to electromagnetic interference, and multiplexing, fiber Bragg-grating (FBG) sensing has received substantial interest in recent years for battery temperature measurement. However, traditional temperature calibration for FBG sensors often requires a high-standard reference and causes the sensors to fail to be consistent during the calibration or recalibration processes. To tackle the challenges, an ensemble data-driven calibration method is developed in this article for FBG sensors. The calibration model consists of a linear part and a nonlinear part. First, the fuzzy ${C}$ -means (FCM) algorithm is used to extract the linear relationship between the measured FBG wavelength shift and temperature variation. Then, the empirical mode decomposition (EMD) technique is used to classify the intrinsic mode functions (IMFs) and the remainder of the unmodeled nonlinear information. The unmodeled nonlinear information is further compensated using battery state of charge (SOC) and cycle number information. The experimental results confirm that the proposed temperature calibration method achieves desirable accuracy and reliability, with both the mean absolute error (MAE) and root mean square error (RMSE) being around 0.2 °C, respectively. Compared with the traditional temperature calibration method, the proposed approach can be used online in real-life applications.

To fully leverage the application potential of distributed energy storage systems (DESS) and network reconfiguration, a coordinated optimization method is proposed to enhance the economic efficiency of distribution networks under normal conditions and the reliability of a power supply during fault conditions. First, a scenario-generation method is developed based on Latin hypercube sampling and Kantorovich distance synchronous back-substitution reduction is used to obtain the typical scenario of wind and solar output. Next, a planning operation coordinated optimization framework and model are established, considering both normal and fault states of the distribution network. In the planning layer, the objective is to minimize the annual comprehensive capital expenditures for the distribution network to improve the economic efficiency of the distribution network. The operation layer includes both normal operation and fault operation states, with the optimization goal of minimizing the sum of normal operation costs and the fault costs associated with load shedding. Subsequently, a hybrid optimization algorithm combining an improved Aquila Optimizer-Second-Order Cone Programming (IAO-SOCP) is proposed to solve the coordinated optimization model. Finally, the proposed coordinated optimization method is validated using an enhanced IEEE 33-bus distribution network case study. The results demonstrate that the method effectively reduces network losses and minimizes load shedding costs during fault conditions, thereby ensuring a balance between the economic efficiency and reliability of the distribution network.

The integration of distributed power generation mainly consisting of photovoltaic and wind power into active distribution networks can lead to safety accidents in grid operation. At the same time, climate change can also cause voltage fluctuations, direct current injection, harmonic pollution, frequency fluctuations, and other issues. To achieve economic and safe operation of the distribution network, an active distribution network-network planning model considering the dynamic configuration of energy storage system energy storage is constructed. This model focuses on energy storage batteries with high ease of use, high modularity, and strong mobility. The route location planning involving different load operating scenarios in spring, summer, autumn, and winter is constructed. The objective function includes the revenue from selling electricity in the distribution network, the expenditure on purchasing electricity in the distribution network, and the cost during the planned construction period. The constraints include three major constraints: distribution network operation, network topology, and energy storage system operation. Three numerical examples are set up to analyze the impact of energy storage system dynamic configuration on grid planning. The results confirmed the active distribution network-grid planning model for dynamic configuration of energy storage systems. Both Example 2 and Example 3 had 3 ESS configurations. Case 3 showed different access methods for ESS in different seasons. The access nodes for ESS in spring and winter were 4, 5, and 6, while the access nodes for summer and autumn were 3, 5, and 6. After applying the proposed method, the daily energy storage investment of commercial, residential, and industrial users gradually stabilized. The reliability of electricity consumption was improved, with an improvement rate of about 40%. The research has brought considerable economic benefits to distribution network operators. It has forward-looking academic value in the joint planning of grid structures and energy storage.

Multi-layer spiral compact cable based on high-temperature superconducting tapes is a potential candidate for large-scale superconducting applications. During magnet processing and operation, superconducting tapes and cables are subject to complex mechanical and electromagnetic forces. Plentiful studies are conducted on the cable's mechanical performance during the preparation process and the operating electromagnetic characteristics separately, but still lack sufficient focus on the electromagnetic-mechanical coupling. In this paper, an electromagnetic-mechanical field co-simulation is carried out. The effect of residual strain from the winding process is included. The electromagnetic force characteristics in spiral cables as well as mechanical response are studied. This study is fundamental for further analysis on large-scale magnets made of spiral cables that are subject to large Lorentz forces in operation with preparation-induced residual strain.

Aiming at the problems of OLT for the LCC-VSC hybrid HVDC system, this paper proposes an improved OLT control strategy. First, the OLT method of rectifier and inverter station is analyzed. The analysis results show that we must be tested the LCC and VSC converters of the inverter station separately in the OLT. Then, the problems of the original OLT control strategy of the VSC converter are proved, and an improved OLT control strategy based on optimization of the number of Sub-modules is proposed. Finally, the simulation shows that the OLT process adopting the improved control strategy has superior transient performance.