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 proposes an advanced Internet of Things (IoT) system for measuring, monitoring, and recording some power quality (PQ) parameters. The proposed system is designed and developed for both hardware and software. For the hardware unit, three PZEM-004T modules with non-invasive current transformer (CT) sensors are used to measure the PQ parameters and an Arduino WeMos D1 R1 ESP8266 microcontroller is used to receive data from the sensors and send this data to the server via the internet. For the software unit, an algorithm using Matlab software is developed to send measurement data to the ThingSpeak cloud. The proposed system can monitor and analyse the PQ parameters including frequency, root mean square (RMS) voltage, RMS current, active power, and the power factor of a low-voltage load in real-time. These PQ parameters can be stored on the ThingSpeak cloud during the monitoring period; hence the standard deviation in statistics of the voltage and frequency is applied to analyse and evaluate PQ at the monitoring point. The experimental tests are carried out on low-voltage networks 380/220 V. The obtained results show that the proposed system can be usefully applied for monitoring and analysing chosen PQ parameters in micro-grid solutions.

This paper presents the design and implementation of an adaptive extended Kalman filter (EKF) for the sensorless Permanent Magnet Synchronous Motor (PMSM) on a Field Programmable Gate Array (FPGA) chip. The rotor position and speed of the motor are estimated by the adaptive EKF and their estimates are then used in vector control of the PMSM. Most EKF techniques for state estimation rely on fixed values of the state and measurement noise covariance matrices. In many practical applications, an a priori assumption of these matrices is often inadequate and it is desirable to tune online the process noise covariance to improve the filtering performance. For this, improved EKF versions can be obtained by incorporating an adjustment mechanism of the noise covariances into the filter. The adaptive EKF is, therefore, a promising estimator for sensorless PMSM drives with more accurate estimation features, provided it is feasible in implementation. Here, for realization of the PMSM sensorless control using the system-on-programmable-chip technology, high speed arithmetic functions and pipelining are employed in the FPGA implementation. The finite state machine (FSM) method is also used to facilitate the execution timing and chip design. The co-simulation of Modelsim/Simulink shows the effectiveness of the adaptive EKF-based PMSM speed estimation.

The subsynchronous resonance (SSR) is an important problem in the power system, and especially the series compensated transmission lines may cause SSR in the turbine generators, such that it leads to the electrical instability at subsynchronous frequencies and potential turbine-generator shaft failures. Taking the Vietnamese Vungang thermal plants as an example, a shaft failure of Vungang I thermal power unit has occurred on November 24, 2015, due to SSR. The main cause for this failure is a resonance caused by the series capacitors on the 500 kV grid. This paper analyzes the SSR based on the location of shaft cracks and turbine generator mode shape for Vungang I and II thermal power plants. On the basis of that, it develops a novel control strategy for each Flexible AC Transmission system (FACTS) device as the thyristor controlled series compensator (TCSC), static VAR compensator (SVC), and static synchronous compensator (STATCOM). Then they are comparable to one another in order to choose a feasible solution for mitigating the SSR. The effectiveness of the proposed control strategy is verified via time domain simulation of the Vietnamese 500/220 kV transmission system using EMTP-RV and PSS/E programs. The obtained results show that the proposed strategy for SVC can be applied to immediately solve the difficulties encountering in the Vietnamese power system.

The Vietnamese power system has experienced instabilities due to the effect of increase in peak load demand or contingency grid faults; hence, using flexible alternating-current transmission systems (FACTS) devices is a best choice for improving the stability margins. Among the FACTS devices, the thyristor-controlled series capacitor (TCSC) is a series connected FACTS device widely used in power systems. However, in practice, its influence and ability depend on setting. For solving the problem, this paper proposes a relevant method for optimal setting of a single TCSC for the purpose of damping the power system oscillations. This proposed method is developed from the combination between the energy method and Hankel-norm approximation approach based on the controllability Gramian matrix considering the Lyapunov equation to search for a number of feasible locations on the small-signal stability analysis. The transient stability analysis is used to compare and determine appropriate settings through various simulation cases. The effectiveness of the proposed method is confirmed by the simulation results based on the power system simulation engineering (PSS/E) and MATLAB programs. The obtained results show that the proposed method can apply to immediately solve the difficulties encountering in the Vietnamese power system.

A number of techniques have been proposed to dampen the power system oscillations in the electric power systems. Flexible alternating current transmission system (FACTS) devices are becoming one of them. Among the FACTS family, the static synchronous compensator (STATCOM), a shunt connected FACTS device, has been widely used to provide smooth and rapid steady state, limit transient voltage, and improve the power system stability and performance by absorbing or injecting reactive power. However, the influence ability depends on its placement, control signal, and place of receiving-signal in the network. In order to satisfy these issues, this paper proposes a method for optimal setting and signal position of the STATCOM into the multi-machine power systems with the aim for damping the electromechanical oscillations. This method is developed from the energy approach based on Gramian matrices considering multiple tasks on the Lyapunov equation, in which the observability Gramian matrix is used to seek an optimal location for STATCOM placement. The another is the controllability one used to determine the best local input signal placement that is chosen as a feedback signal for the power oscillation damping (POD) of STATCOM. In addition, the Krylov-based model reduction method is introduced to shorten the calculation time. The proposed method has been verified on the IEEE 24-bus system by analyzing the small-signal stability to search several feasible placements, and then the transient stability is analyzed to compare and determine an optimal placement through testing various cases. The obtained result is also compared with other optimal method.