Abstract:The increase in the number of sensitive loads in power systems has made power quality, particularly voltage sag, a prominent problem due to its effects on consumers from both the utility and customer perspectives. Thus, to evaluate the effects of voltage sag caused by short circuits, it is necessary to determine the areas of vulnerability (AOVs). In this paper, a new method is proposed for the AOV determination that is applicable to large-scale networks. The false position method (FPM) is proposed for the precise calculation of the critical points of the system lines. Furthermore, a new method is proposed for the voltage sag monitor (VSM) placement to detect the fault locations. A systematic placement scheme is used to provide the highest fault location detection (FLD) index at buses and lines for various short-circuit fault types. To assess the efficiency of the proposed methods for AOV determination and VSM placement, simulations are conducted in IEEE standard systems. The results demonstrate the accuracy of the proposed method for AOV determination. In addition, through VSM placement, the fault locations at buses and lines are detected.

Abstract:The distinctive fault characteristics of battery energy storage stations (BESSs) significantly affect the reliability of conventional protection methods for transmission lines. In this paper, the three-dimensional (3D) data scattergrams are constructed using current data from both sides of the transmission line and their sum. Following a comprehensive analysis of the varying characteristics of 3D data scattergrams under different conditions, a 3D data scattergram image classification based protection method is developed. The depth-wise separable convolution is used to ensure a lightweight convolutional neural network (CNN) structure without compromising performance. In addition, a Bayesian hyperparameter optimization algorithm is used to achieve a hyperparametric search to simplify the training process. Compared with artificial neural networks and CNNs, the depth-wise separable convolution based CNN (DPCNN) achieves a higher recognition accuracy. The 3D data scattergram image classification based protection method using DPCNN can accurately separate internal faults from other disturbances and identify fault phases under different operating states and fault conditions. The proposed protection method also shows first-class tolerability against current transformer (CT) saturation and CT measurement errors.

Abstract:This paper constructs a synthetic framework for the operational reliability evaluation and risk mitigation of asynchronous grids coupled through flexible high-voltage DC (HVDC) systems (AGs-FDCSs). First of all, an analytical model for the unavailability of DC units is reformulated to refine and facilitate the reliability modeling of such flexible HVDC systems considering their time-dependent features as well as the impacts of converter station configurations. Subsequently, the operational risk associated with the redispatch procedure is extended to the reliability evaluation of composite power system, and the risk is mitigated through an optimal power flow (OPF) based short-term state assessment model. In addition, some new reliability indices like expected DC transmission power (EDCTP) and DC terminal outage probability (DCTOP) are defined to quantify the impact of the reliability of flexible HVDC systems on the entire grid. The effectiveness of the proposed framework on a modified IEEE RTS-79 system is validated with the elaborate discussions on the time-dependent reliability of AGs-FDCSs as well as the impacts of the converter station configurations.

Abstract:This study introduces a distributed specified-time control mechanism (DSTCM) for secondary control in islanded microgrids (MGs) operating under directed switching communication topologies. The proposed mechanism ensures convergence properties that are independent of initial conditions, enabling the design of an exact offline settling time to reduce power losses and limit the upper bound of convergence time. By employing a piecewise function-based communication approach and directed switching graphs, the proposed mechanism effectively reduces computational and communication demands on the system. Moreover, the proposed mechanism significantly enhances power system performance while minimizing adjustment costs, delivering precise control actions under various operating conditions. The accuracy and effectiveness of the proposed mechanism are validated through extensive MATLAB simulations, demonstrating its ability to regulate MG voltages and frequencies, achieve accurate proportional active power sharing, and maintain state-of-charge (SoC) balancing. Its superiority over previously established mechanisms is also confirmed by a comparative analysis.

Abstract:The setting work of backup protection using steady-state current is tedious, and mismatches occasionally occur due to the increased proportion of distributed generations (DGs) connected to the power grid. Thus, there is a practical need to study a backup protection technology that does not require step-by-step setting and can be adaptively coordinated. This paper proposes an action sequence adaptive to fault positions that uses only positive sequence fault component (PSFC) voltage. Considering the influence of DGs, the unified time dial setting can be obtained by selecting specific points. The protection performance is improved by using the adjacent upstream and downstream protections to meet the coordination time interval in the case of metallic faults at the near- and far-ends of the line. Finally, the expression and implementation scheme for inverse-time backup protection (ITBP) based on the unified characteristic equation is given. Simulation results show that this scheme can adapt to DG penetration scenarios and can realize the adaptive coordination of multi-level relays.

Abstract:Medium-voltage distribution systems (MVDSs) mainly consist of a feeder head, lines, distribution transformers, and the equivalent load or power supply interfaced with the distribution transformers. The information of such load or power supply can be measured via the three-wattmeter method (THM) and the two-wattmeter method (TWM). The measurements can be used to perform the control of the power supply and simulate the characteristics of the load, so the models of the load and the power supply need to consider the measurement characteristics. Existing research works on three-phase power flow (PF) just consider the measurement characteristics of THM. Hence, the PF equation of the bus measured via TWM is firstly built. Based on conventional measurements, an accurate and general model of the grounded and ungrounded slack bus is proposed. Furthermore, the influence arising from the connection type and angle shift of distribution transformers on the admittance matrix is considered, and thus a general three-phase transformer model is summarized, which is applicable for all the transformers mentioned herein. Finally, Newton ’ s method is adopted to solve the PF calculation, and the performance of the proposed PF model is demonstrated through designed tests.

Abstract:The partial differential equation (PDE) solution of the telegrapher is a promising fault location method among time-domain and model-based techniques. Recent research works have shown that the leap-frog process is superior to other explicit methods for the PDE solution. However, its implementation is challenged by determining the initial conditions in time and the boundary conditions in space. This letter proposes two implicit solution methods for determining the initial conditions and an analytical way to obtain the boundary conditions founded on the signal decomposition. The results show that the proposal gives fault location accuracy superior to the existing leap-frog scheme, particularly in the presence of harmonics.

Abstract:This paper proposes an adaptive method based on fuzzy logic that utilizes data from phasor measurement units (PMUs) to assess and classify generating-side voltage trajectories. The voltage variable and its associated derivatives are used as the input variables of a fuzzy-logic block. In addition, the voltage trajectory is compared with the pre-selected pilot-bus voltage to make a reliable decision about the voltage operational state. Different types of short-term voltage dynamics are considered in the proposed method. The fuzzy membership functions are determined using a systematic method that considers the current situation of the voltage trajectory. Finally, the voltage status is categorized into four classes to determine appropriate remedial actions. The proposed method is validated on a IEEE 73-bus power system in a MATLAB environment.

Abstract:Battery energy storage stations (BESSs) pose several challenges for both phasor-based differential protection and the newly-proposed time-domain differential protection. These challenges include low sensitivity and even rejection. Besides, the negative impact of various nonideal conditions, including current transformer (CT) saturation, errors, and outliers, on the security of differential protection remains an important problem. Motivated by the aforementioned issues, this study accounts for the trajectory distribution discrepancy on Cartesian plane under various conditions and proposes a time-domain differential protection method. In this paper, the trajectory formed by operating and restraining current samples is developed. Subsequently, after considering different operating states, the fault severity levels, and nonideal conditions, the variances in trajectory distribution between internal and external faults are extensively analyzed. On this basis, the Cartesian plane is divided into operating, uncertainty, and restraining zones. Further, the operating and restraining trajectory indices are meticulously designed and a protection criterion based on these indices is formed to accurately separate internal faults from other events, unaffected by CT saturation, errors, and outliers. The exceptional performance of the proposed protection method is extensively validated through PSCAD simulations and a hardware-in-the-loop testing platform. Regarding the dependability, sensitivity, and security, the proposed protection method outperforms three state-of-the-art differential protection methods.

Abstract:An nonlinear model predictive controller (NMPC) is proposed in this paper for compensations of single line-to-ground (SLG) faults in resonant grounded power distribution networks (RGPDNs), which reduces the likelihood of power line bushfire due to electric faults. Residual current compensation (RCC) inverters with arc suppression coils (ASCs) in RGPDNs are controlled using the proposed NMPC to provide appropriate compensations during SLG faults. The proposed NMPC is incorporated with the estimation of ASC inductance, where the estimation is carried out based on voltage and current measurements from the neutral point of the distribution network. The compensation scheme is developed in the discrete time using the equivalent circuit of RGPDNs. The proposed NMPC for RCC inverters ensures that the desired current is injected into the neutral point during SLG faults, which is verified through both simulations and control hardware-in-the-loop (CHIL) validations. Comparative results are also presented against an integral sliding mode controller (ISMC) by demonstrating the capability of power line bushfire mitigation.

Abstract:This paper proposes a novel fault location method for overhead feeders, which is based on the direct load flow approach. The method is developed in the phase domain to effectively deal with unbalanced network conditions, while it can also handle distributed generation (DG) units of any type without requiring equivalent models. By utilizing the line series parameters and synchronized or unsynchronized voltage and current phasor measurements taken from the sources, the method reliably identifies the most probable faulty sections. With the aid of an index, the exact faulty section among the multiple candidates is determined. Extensive simulation studies for the IEEE 123-bus test feeder demonstrate that the proposed method accurately estimates the fault position under numerous short-circuit conditions with varying pre-fault system loading conditions, fault resistances, and measurement errors. The proposed method is promising for practical applications due to the limited number of required measurement devices as well as the short computation time.

Abstract:The accurate identification of smart meter (SM) fault types is crucial for enhancing the efficiency of operation and maintenance (O&M) and the reliability of power collection systems. However, the intelligent classification of SM fault types faces significant challenges owing to the complexity of features and the imbalance between fault categories. To address these issues, this study presents a fault diagnosis method for SM incorporating three distinct modules. The first module employs a combination of standardization, data imputation, and feature extraction to enhance the data quality, thereby facilitating improved training and learning by the classifiers. To enhance the classification performance, the data imputation method considers feature correlation measurement and sequential imputation, and the feature extractor utilizes the discriminative enhanced sparse autoencoder. To tackle the interclass imbalance of data with discrete and continuous features, the second module introduces an assisted classifier generative adversarial network, which includes a discrete feature generation module. Finally, a novel Stacking ensemble classifier for SM fault diagnosis is developed. In contrast to previous studies, we construct a two-layer heuristic optimization framework to address the synchronous dynamic optimization problem of the combinations and hyperparameters of the Stacking ensemble classifier, enabling better handling of complex classification tasks using SM data. The proposed fault diagnosis method for SM via two-layer stacking ensemble optimization and data augmentation is trained and validated using SM fault data collected from 2010 to 2018 in Zhejiang Province, China. Experimental results demonstrate the effectiveness of the proposed method in improving the accuracy of SM fault diagnosis, particularly for minority classes.

Abstract:Fault currents emanating from inverter-based resources (IBRs) are controlled to follow specific references to support the power grid during faults. However, these fault currents differ from the typical fault currents fed by synchronous generators, resulting in an improper operation of conventional phase selection methods (PSMs). In this paper, the relative angles between sequence voltages measured at the relay location are determined analytically in two stages ① a short-circuit analysis is performed at the fault location to determine the relative angles between sequence voltages; and ② an analysis of the impact of transmission line on the phase difference between the sequence voltages of relay and fault is conducted for different IBR controllers. Consequently, new PSM zones based on relative angles between sequence voltages are devised to facilitate accurate PSM regardless of the fault currents, resistances, or locations of IBR. Comprehensive time-domain simulations confirm the accuracy of the proposed PSM with different fault locations, resistances, types, and currents.

Abstract:When high-impedance faults (HIFs) occur in resonant grounded distribution networks, the current that flows is extremely weak, and the noise interference caused by the distribution network operation and the sampling error of the measurement devices further masks the fault characteristics. Consequently, locating a fault section with high sensitivity is difficult. Unlike existing technologies, this study presents a novel fault feature identification framework that addresses this issue. The framework includes three key steps ①utilizing the variable mode decomposition (VMD) method to denoise the fault transient zero-sequence current (TZSC); ② employing a manifold learning algorithm based on t-distributed stochastic neighbor embedding (t-SNE) to further reduce the redundant information of the TZSC after denoising and to visualize fault information in high-dimensional 2D space; and ③ classifying the signal of each measurement point based on the fuzzy clustering method and combining the network topology structure to determine the fault section location. Numerical simulations and field testing confirm that the proposed method accurately detects the fault location, even under the influence of strong noise interference.

Abstract:Carbon capture and storage (CCS) systems can provide sufficient carbon raw materials for power-to-gas (P2G) systems to reduce the carbon emission of traditional coal-fired units, which helps to achieve low-carbon dispatch of integrated energy systems (IESs). In this study, an extended carbon-emission flow model that integrates CCS-P2G coordinated operation and low-carbon characteristics of an energy storage system (ESS) is proposed. On the energy supply side, the coupling relationship between CCS and P2G systems is established to realize the low-carbon economic operation of P2G systems. On the energy storage side, the concept of “ state of carbon” is introduced to describe the carbon emission characteristics of the ESS to exploit the potential of coordinated low-carbon dispatch in terms of both energy production and storage. In addition, a low-carbon economic dispatch model that considers multiple uncertainties, including wind power output, electricity price, and load demands, is established. To solve the model efficiently, a parallel multidimensional approximate dynamic programming algorithm is adopted, while the solution efficiency is significantly improved over that of stochastic optimization without losing solution accuracy under a multilayer parallel loop nesting framework. The low-carbon economic dispatch method of IESs is composed of the extended carbon emission flow model, low-carbon economic dispatch model, and the parallel multidimensional approximate dynamic programming algorithm. The effectiveness of the proposed method is verified on E14-H6-G6 and E57-H12-G12 systems.