Search

A power line carrier (PLC) communication characteristics-based method is proposed for single-phase-to-ground fault location in neutral isolated medium voltage (MV) meshed distribution networks in this paper. The carrier signals with a time-varying frequency and constant amplitude are processed by a set of PLC transmitters and receivers, whose placement is optimized by regarding the power network as an undirected graph. Two signal encoding and decoding algorithms for the PLC terminals are proposed to avoid using expensive timing systems between the terminals. The fault location technique is implemented by comparing the cosine similarity of amplitude attenuation (AA) and phase offset (PO) between the fault and a library. The node corresponding to the maximum cosine similarity of the characteristics between the present fault and the library is selected as the location of the current fault. Only one set of low-cost PLC communication terminals and the widely available power lines are needed in the fault location system, making this approach highly practical. Numerical simulations using MATLAB/Simulink have been performed to verify the technique’s feasibility. The results show that the method can accurately locate faults in neutral isolated MV meshed distribution networks. Besides, the presented approach achieves high accuracy in estimating transition resistance values.

With a large number of distributed generators (DG) and sensitive power loads connected to the distribution network, power quality issues have increasingly become the focus of users’ attention. Accurate and quick estimation of the amount of bulk capacitor removal that causes voltage sag is helpful to maintain power quality management equipment in time. This paper presents a novel size estimation of bulk capacitor removal using a limited power quality monitor (PQM) in the distribution network, including PQM deployment optimization, feeder localization, and capacitor removal amount calculation. The PQM placement is optimized by taking the estimated capacitance removal sizes of all buses as a constraint. The change of reactive power consumption before and after removing the capacitor at each power line is adopted to determine the feeder where the disturbance is located. Based on the impedance characteristics of the power grid components, the steady estimation method (SEM) is deduced using the fundamental voltage and current. Applying the sampling points of instantaneous voltage and current waveform, the transient estimation method (TEM) is constructed by data fitting. Case studies and index analysis for the IEEE 13 bus test work are presented to verify the reasonableness and accuracy of the proposed method for disturbed bus, capacitor size, load symmetry, disturbance duration, and DGs. SEM shows more stability and accuracy, while TEM performs faster and is more robust. The new methods provide a reliable and acceptable disturbance size estimation with several limited PQMs.

The increasing household loads make series arc faults more complex, which are difficult to be detected by traditional circuit breakers and lead to the frequent occurrence of residential fire accidents. In this paper, a comprehensive approach of complex load recognition and series arc detection is proposed on the basis of principal component analysis and support vector machine (PCA-SVM) combination model. Several typical loads were selected and analyzed, especially nonlinear and complex loads like power electronics load and multi-state load. Three time-domain parameters, maximum slip difference (MSD), zero current period (ZCP) and maximum Euclidean distance (MED), and nine frequency-domain harmonics information are collected to complex waveforms. To decrease the computation cost and further to enhance the response velocity, all the time-domain and frequency-domain information were blended and dimensionally reduced to three parameters by principal component analysis (PCA). Prior to the series arc detection, load recognition is trained and completed with the artificial intelligence (AI) algorithm. At last, the comprehensive model of load recognition and series arc detection is achieved based on a support vector machine (SVM). The accuracy of load recognition and series arc detection reaches 99.1% and 99.3%, respectively, demonstrating the excellent performances of the intelligent approach to diagnose the series arcing activities in modern household applications.

Grounding fault and injecting AC into DC control system in substation may lead to many protector problems, such as maloperation and miss trip, Based on the traditional unbalanced bridge and blocking condenser principle, the IUB(Improved Unbalanced Bridge) is put forward to detect ground resistance and alternating voltage occurred in substation DC system. The circuit of IUB models in MATLAB/Simulink is presented, and a DC system fault detection circuit board is constructed to achieve the detection function of grounding fault and AC intrusion. The results showed that the proposed method is correct and effective.