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The fault location problem is one of the most important issues in power system operation and control. To obtain an experimental system for teaching and training electrical engineering students, this paper performed a study to design and implement a real-time fault location laboratory-scale model from practical hardware components. The impedance-based fault location method is embedded in the system to determine the distance to fault in the transmission line. Furthermore, the monitoring and controlling program is designed by the Matlab App Designer – A new professional app to create the graphical user interface and use the integrated editor quickly. Several fault types including three-phase fault, phase-to-phase fault, phase-to-ground fault are created to evaluate the performance of the fault location experimental system. The real-time measurement results which are acquired and observed on the user guide interface of the program confirm the effectiveness of the experimental system; therefore, the system can be considered a powerful tool for electrical engineering students.

This paper presents an architecture of the Doubly-Fed Induction Generator based on Wind Energy Conversion System (DFIG-WECS) to study with the Low Voltage Ride Through (LVRT) capability. The proposed architecture consists of three main parts namely the wind turbine, electric generator, control systems. The wind turbine and gearbox are modeled by a servo motor driven by using an inverter system. The electric generator uses the Wound Rotor Induction Generator (WRIG). The control system composes of the rotor-side converter (RSC) and the grid-side converter (GSC). The integration of the digital signal processor (DSP) with the Simulink/Matlab software of the vector control scheme is implemented to control both RSC and GSC. Besides, to protect the overcurrent of the generator’s rotor and overvoltage of the DC-link, the crowbar and chopper circuits and the logical scheme between the crowbar and the RSC are also proposed. To approve the control algorithms implemented in DSP as hardware in the loops, the proposed 0.8kW DFIG-WESC system has been performed under the experimental environment considering LVRT requirement in German grid code.

Nowadays, more distributed generations (DGs) are connected to a radial distribution network, so conventional overcurrent relays cannot operate correctly when a fault occurs in the network. This study proposes a method to determine the fault direction in a three-phase distribution network integrated with DGs. The obtained pre-fault and fault currents are utilized to extract their phasors by the fast Fourier transform, and the phase angle difference between the positive-sequence components of the pre-fault and fault currents is used. Moreover, the method only uses the local current measurement to calculate and identify the phase angle change of the fault current without using the voltage measurement. Matlab/Simulink software is used to simulate the three-phase distribution network integrated with DGs. The faults with different resistances are assumed to occur at backward and forward fault locations. The simulation results show that the proposed method correctly determines the fault direction.

Trong những năm gần đây, Internet of Things (IoT) đã trở thành một chủ đề về xã hội, kỹ thuật và kinh tế đang được quan tâm đặc biệt. Bài báo này nhằm mục đích nghiên cứu, thiết kế, kiểm tra và triển khai một hệ thống điều khiển và giám sát điện năng dựa trên công nghệ IoT. Hệ thống này có thể được điều khiển và giám sát từ xa bằng cách sử dụng các thiết bị IoT thông qua máy tính cá nhân (PC) hoặc điện thoại thông minh mà nó được kết nối với mạng Internet. Để đạt được mục tiêu này, một hệ thống hoàn chỉnh bao gồm thiết bị thông minh, cơ sở dữ liệu đám mây, tương tác lập trình và hệ phần cứng được đề xuất để nghiên cứu. Các đại lượng điện bao gồm điện áp, dòng điện, công suất tác dụng và điện năng tiêu thụ được đo lường, hiển thị và giám sát trong suốt thời gian thực. Bên cạnh đó, một kỹ thuật quản lý nhu cầu phụ tải (DSM) cũng được tích hợp vào trong hệ thống này để quản lý hiệu quả sự tiêu thụ năng lượng ở phía phụ tải với mục đích nhằm cắt giảm chi phí phát sinh đối với phía nguồn cấp. Cuối cùng, hệ thống này cho phép toàn bộ dữ liệu giám sát tích trữ trong cơ sở dữ liệu đám mây có thể được phân tích và báo cáo cho các mục đích xa hơn.

In this paper, an experimental system based on Arduino Uno microcontroller board was developed for measuring electrical quantities and protecting overvoltage and undervoltage conditions in a single-phase power supply. The main components are described in detail, including the hardware and software to build the system in which an Arduino Uno platform is implemented as a vital microcontroller to read voltage and current measurement from a voltage sensor (ZMPT101B) and a current sensor (ACS712) respectively. In addition, the Arduino is also used to send all measurement to a PC through a serial port for monitoring the measured data graphically. The proposed method for designing the software uses the root mean square (RMS) method for measuring electrical quantities and then the RMS voltage measurement is compared with the minimum voltage and the maximum voltage to switch on or switch off the load. The monitoring GUI is designed with the use of the free and open-source Telemetry Viewer v0.5 software to monitor RMS voltage, RMS current, active power, and trip signal of the experimental system. The experimental results in this paper demonstrate that the system operated correctly.

The impact of thyristor controlled series capacitor (TCSC) on distance protection relays in transmission lines is analyzed in this paper. Voltage and current data are measured and collected at the relay locations to calculate the apparent impedance seen by distance protection relays in the different operating modes of the TCSC connected to the line. Short-circuit faults which occur at different locations on the power transmission line are considered in order to locate the fault for the purpose of evaluating the impact of TCSC on the distance protection relay. Matlab/Simulink simulation software is used to model the power transmission line with two sources at the two ends. Voltage source, transmission line, TCSC, voltage and current measurement, and discrete Fourier transform (DFT) blocks are integrated into the model. Simulation results show the impact of TCSC on the distance protection relay and determine the apparent impedance and fault location in the line.

Voltage sag event is one of the most important power quality disturbances in power systems. It can have affect on voltage quality and sensitive equipment in power systems. Detecting voltage sag events in power systems is a vital role in operating systems, therefore, this paper proposes an algorithm based on extended Kalman filter (EKF) for characterizing and detecting the parameters of voltage sag events accurately. A status-space modeling of voltage sag signals is defined to model voltage sag signal according to status-space modeling of EKF. The parameters of voltage sag events are estimated using the proposed method including voltage magnitude, estimation error, starting and ending times, duration time of the event. Matlab software is used to generate database of voltage sag waveforms modeled by a mathematical equation and then the waveforms are used to evaluate the proposed method. The simulation results of the proposed method are also compared with the simulation results of the root mean square (RMS) method to confirm the effectiveness of the proposed method in this paper.

The detection, mitigation, and classification of power quality (PQ) disturbances have been issues of interest in the power system field. This paper proposes an approach to detect and classify various types of PQ disturbances based on the Stockwell transform (ST) and decision tree (DT) methods. At first, the ST is developed based on the moving, localizing, and scalable Gaussian window to detect five statistical features of PQ disturbances such as the high frequency of oscillatory transient, distinction between stationary and non-stationary, the voltage amplitude oscillation around an average value, the existence of harmonics in a disturbance signal, and the root mean square voltage at the internal period of sag, swell or interruption. Then, these features are classified into nine types, such as normal, sag, swell, interruption, harmonic, flicker, oscillatory transient, harmonic voltage sag, and harmonic voltage swell by using the DT algorithm that is based on a set of rules with the structure &ldquo, if&hellip, then&rsquo, &rsquo, This proposed study is simulated using MATLAB simulation. The IEEE 13-bus system, the recorded real data based on PQube, and the experiment based on the laboratory environment are applied to verify the effectiveness.

Today, the development of the demand is very fast, so the management of demand and the planning of purchasing power is a challenge for Electricity companies. Moreover, the continuous data collection is very difficult especially for Vietnam since the types of measuring equipment are too old or not enough budget to mass equip. Therefore, the paper analyses data processing methods to develop a tool to build typical load graphs for distribution grids corresponding to different load components in order to optimize the distribution grid. The calculation tool is integrated with the proposed algorithm and built-in Matlab and applied to the actual power grid in Thua Thien Hue province for various load components.

The flexible alternating current transmission systems (FACTS) have been widely used in modern power systems. Because of the presence of the FACTS devices, distance relays in transmission lines may inaccurately locate fault locations. Therefore, it is significant to find a mechanism for locating fault in transmission lines connected to FACTS in which a static var compensator (SVC) is investigated in this work. Based on the development of a phasor measurement unit (PMU) with global positioning system (GPS), this paper proposes a new method for calculating apparent impedance seen by the distance relay location while a short-circuit fault occurs in a transmission line connected the SVC to the midpoint of the line. According to the method, sampled voltage and current measurement at the relay and SVC locations are synchronized using PMUs and the synchronized measurements are then used to calculate a new apparent impedance and to locate the fault location in the line. The method in this paper has the capability for fast calculation and it also has the robustness for identifying different fault types in power systems. Matlab/Simulink software is applied to simulate the study results and to evaluate the correctness of the modeling and effectiveness of the proposed method for locating fault in this paper.

This paper focuses on analyzing and evaluating impact of a Static Var Compensator (SVC) on the measured impedance at distance protection relay location on power transmission lines. The measured impedance at the relay location when a fault occurs on the line is determined by using voltage and current signals from voltage and current transformers at the relay and the type of fault occurred on the line. The MHO characteristic is applied to analyze impact of SVC on the distance protection relay. Based on the theory, the authors in this paper develop a simulation program on Matlab/Simulink software to analyze impact of SVC on the distance protection relay. In the power system model, it is supposed that the SVC is located at mid-point of the transmission line to study impact of SVC on the distance relay. The simulation results show that SVC will impact on the measured impedance at the relay when the fault occurs after the location of the SVC on the power transmission line.

This paper presents a configuration and a control strategy for dynamic voltage restorer (DVR). In order to compensate the voltage of each phase separately, a closed-loop PI control law in the d-q reference frame is proposed. The proposed method provides a fast response and effective sag compensation capabilities. In addition, in order to detect voltage sag, a linear Kalman filter is employed to estimate three-phase voltages. By using Kalman filter, the voltage sag can be detected faster than other conventional methods. Therefore DVR can compensate voltage sag quickly and accurately. The obtained results that are simulated in Matlab/ Simulink indicate that the proposed method can mitigate the balanced and unbalanced voltage sag types efficiently in the distribution networks.

This paper proposes a new method to classify power quality disturbances using wavelet transform and K-nearest neighbor classifier. New features of power quality disturbances are extracted from discrete wavelet transform then using K-nearest neighbor classifier to classify these disturbances according to the features. Block diagram of the proposed method has been shown in this paper. Performance of the proposed method is trained and verified with power quality disturbances generated by Matlab software. The classification accuracy for these disturbances has been presented and shows that the proposed method is doing well in classifying these types of power quality disturbances.

This paper proposes a method to monitor, detect and classify voltage disturbances including voltage sag, voltage swell, voltage interruption, and long duration voltage variations. The detail coefficient in discrete wavelet transform is used to extract the start and end times of the voltage disturbance. The decomposed level of multi-resolution analysis in discrete wavelet transform is calculated according to the sampling frequency of the voltage signal for determining the approximation coefficient that only contains the fundamental frequency band. Then an adaptive linear neural network is used to estimate the voltage magnitude from the approximation coefficient. Finally, the disturbance will be classified into groups of voltage disturbances based on the characteristics according to the rules in IEEE Std. 1159-2009. The voltage waveforms based on theoretical signal models and actual voltage waveforms which recorded by power quality monitoring equipment are applied to evaluate the proposed method. The simulation results show that the proposed method can detect and classify voltage disturbances better than traditional methods based on root mean square and conventional adaptive linear neural network techniques.