Xiaolong Chen

The widespread integration of inverter-based distributed generators (IIDGs) severely limits the adaptability of conventional three-step overcurrent protection in distribution networks (DNs). To address weak rural infrastructure and incomplete post-fault data, this paper proposes a dynamic adaptive current protection strategy for active distribution networks (ADNs) against two-phase short-circuit faults (TPSCFs), using local sequence components. First, we derive analytical expressions for positive/negative-sequence current/voltage at feeder outlet protection devices during TPSCFs, analyzing how the IIDG fault output affects these components. Based on this, an adaptive scheme is developed using only local measurements, with feeder head voltage/current sequence components as criteria. Leveraging line impedance and topology, the scheme ensures selective, accurate fault section identification under incomplete measurements, requiring only feeder head sequence data. A high-IIDG-penetration DN model is built in PSCAD/EMTDC, and TPSCFs under various conditions are simulated. Results show the scheme provides rapid, reliable full-line protection for TPSCFs in IIDG-penetrated ADNs, enhancing protection effectiveness.

Accurate fault location is crucial for enabling maintenance personnel to quickly reach the fault site for inspection and repair, thereby minimizing power outage duration. To address the low fault location accuracy caused by phase unsynchronization of double-ended recording data and the dependence of traditional algorithms on accurate line parameters, this paper introduces a novel fault location algorithm for hybrid transmission lines. The method integrates a data synchronization approach with a physics-informed neural network (PINN) implemented using a backpropagation (BP) neural network architecture. First, the proposed synchronization algorithm corrects the phase misalignment between double-ended recordings. Second, a distributed-parameter fault location model is developed to derive a location function, which is then used to construct physics-informed input features. This approach reduces the need for large fault datasets, addressing the challenge of the low occurrence of faults in practice. Finally, a BP neural network employing these physics-informed features is utilized to learn the nonlinear mapping to the fault location, allowing for accurate fault location, enabling accurate positioning without requiring precise line parameters. Validation using actual line data confirms the high precision of the synchronization algorithm. Furthermore, simulations show that the proposed fault location algorithm achieves high accuracy and remains robust against variations in fault position, type, transition resistance, inception angle, and load current, making it highly practical for real engineering applications.

The traditional centralized optimization method encounters challenges in representing the interaction among multi-agents and cannot consider the interests of each agent. In traditional low-carbon scheduling, the fixed carbon quota trading price can easily cause arbitrage behavior of the trading subject, and the carbon reduction effect is poor. This paper proposes a two-layer dynamic community integrated energy system (CIES) low-carbon collaborative optimization operation method. Firstly, a multi-agent stage feedback carbon trading model is proposed, which calculates carbon trading costs in stages and introduces feedback factors to reduce carbon emissions indirectly. Secondly, a two-layer CIES low-carbon optimal scheduling model is constructed. The upper energy seller (ES) sets energy prices. The lower layer is the combined cooling, heating, and power (CCHP) system and load aggregator (LA), which is responsible for energy output and consumption. The energy supply and consumption are determined according to the ES energy price strategy, which reversely affects the energy quotation. Then, the non-dominated sorting genetic algorithm embedded with quadratic programming is utilized to solve the established scheduling model, which reduces the difficulty and improves the solving efficiency. Finally, the simulation results under the actual CIES example show that compared with the traditional centralized scheduling method, the total carbon emission of the proposed method is reduced by 16.34%, which can improve the income of each subject and make the energy supply lower carbon economy.

In view of the fact that the influence of positive and negative sequence decomposition, which is widely used in positive and negative sequence decoupling control in control system, on the fault current calculation process is not deeply considered in the existing transient analysis methods of permanent magnet direct-drive wind farm short circuit current, this paper proposes a transient short circuit current calculation model that takes into account positive and negative sequence decomposition. The influence of the transient characteristics of positive and negative sequence decomposition on the control system is studied, and the mechanism of its action on the transient change of short circuit current is revealed. The positive and negative sequence decoupling processes of the circuit equation are modified, and the characteristics of the coupling equation are analyzed. The difference in the converter output voltage between the circuit equation and the control equation and the depth of its influence on the calculation process is revealed. On the basis of quantifying the difference at the converter output voltage, the circuit equation and the control equation are combined to form a short-circuit current calculation model with positive and negative sequence decomposition, which accurately characterizes the transient characteristics of fault current under different voltage drops and effectively improves the accuracy of the calculation results.

Faulty phase selection (FPS) methods are used to solve the problem of single phase to ground fault (SPGF) in the distribution network. When a false FPS (FFPS) issue occurs, the short-circuit current in the faulty line suddenly increases. It is crucial to diminish damages caused by the FFPS issue and rapidly re-select the faulty phase. Therefore, this paper proposes a fault-tolerant method based on an active-intervention-type arc suppression device with a soft switch mode (AASD-SSM) and a fast FPS method based on wavelet packet transform (WPT). To strengthen the fault-tolerant performance of FPS, the AASD-SSM is first developed with an intermediate resistance and a soft switch. Then the value of intermediate resistance is determined by the short-circuit current in AASD-SSM. To realize the accuracy and rapidity of FPS, a modified WPT (MWPT) method based on frequency band energy is presented. In different fault scenarios, the number of wavelet decomposition layer is updated by MWPT and the SPGF issues in the faulty lines can be monitored in real-time. Simulation results demonstrate that AASD-SSM improves the fault-tolerant performance of FPS. The phase selection accuracy of MWPT is better than that of WPT in all fault scenarios and the computational complexity of MWPT is reduced for more than 10%.

To meet the application requirements of high-precision and fast-response thrust vector control from a solid rocket motor, a digital and integrated servo controller for four brushless direct current motors was designed and implemented. The controller hardware system proposed in this paper includes control circuit module and drive circuit module. The former mainly includes power conversion circuit, DSP system circuit, A/D circuit, SPI communication interface circuit, and SCI communication interface circuit. The later mainly includes three-phase full-bridge six-arm drive circuit and optocoupler isolation circuit. The three closed-loop control strategies of position, speed and current based on PID control algorithm are adopted, and the mathematical model of the motor is established in Matlab/Simulink for verification. The structure composition and working principle of the servo controller are briefly introduced, and the hardware design scheme, software workflow and control strategy are described in detail. Experimental results show that the response speed and control accuracy of the proposed controller meet the technical requirements.

Aiming at the defect that the current-limiting strategy based on MMC-HVDC system only focuses on the unilateral AC-side or DC-side, this paper proposes a current -limiting strategy that is suitable for both AC-side ground fault and DC-side short-circuit fault. Firstly, for the ground fault on the AC-side, the outer-loop controller with power state equation and the inner-loop controller with passivity -based control (PBC) strategy are used to control it, and the genetic algorithm, which takes the absolute value of the difference between the reference current and the actual current as the fitness function, is used to fit the optimal injection damping parameters for the PBC method. Then, for the short-circuit fault on the DC-side, the capacitor discharge duty ratio is introduced on the basis of the equivalent capacitance without considering the voltage drop, and its segmented control is combined with the current-limiting reactors to achieve current-limiting at different fault points. Finally, a two-port +500KV HVDC transmission system was built on Matlab /Simlink software, and the effectiveness of the current-limiting method proposed in this paper was verified.

With the occurrence of the major blackouts in “Australia 9·28” and the “U.K. 8·9,” the technical bottlenecks in the power generation system with a high proportion of renewable energy have attracted more and more attention. Based on this background, this article studies a control method that is suitable for AC microgrid with strong current-limiting ability. First, the outer loop controller adopts the method of power-state equation based on PI control to achieve accurate tracking of the reference power. Furthermore, in order to make the fault current having a lower asymmetry degree and smaller amplitude, the outer loop controller only considers the positive-sequence components of the voltage and adds twice rated current limiter. Second, the inner loop controller adopts an improved Lyapunov-function method with antiparametric disturbance ability to track the reference inductance current. By selecting the optimal controller gains, the current harmonics and amplitudes can meet the desired requirements. Finally, the simulation builds a microgrid with four distributed generators (DGs) in MATLAB/Simulink and tests the effectiveness of the proposed current-limiting method.