Search

Large penetration of distributed generations into a distribution network can make a reverse power flow that causes overvoltage on the network. This paper studied a hybrid volt/var control algorithm between the on-load tap changer (OLTC) and the distributed generation (DG) to prevent overvoltage on the network. This algorithm is integrated in the central control program at the control center where all the measurement, control and monitoring data of the network are carried out. This algorithm is verified and evaluated through the simulation using the Matlab/Simulink software. The simulation results show the effectiveness of mitigating overvoltage of the hybrid volt/var control algorithm between the OLTC and the DG.

This paper presents a novel method of voltage estimation in distribution networks integrated with distributed generations (DGs). The proposed method is based on applying the weighted least squares (WLS) method to minimize the object function of error measurement which is formulated from the network configuration, the real-time and pseudo measurements at the main substation and DG buses. The method has been evaluated through various simulation case studies of the 17-bus radial distribution network integrated with one solar power plant and two wind power plants. The simulation results have shown the performance of the proposed method.

Integrating wind power and solar power plants into a power system has significantly grown over the past decade and is expected to grow to unprecedented levels in the coming years. In Vietnam, much large-scale wind power and solar power plants have been built and connected to the power system in recent years. To investigate and evaluate the impact of these power plants on system power operation, the 110kV power transmission network of Binh Dinh province in Vietnam is used in this paper. In the system, the Phuong Mai 3 wind power plant with a capacity of 21MW, the Fujiwara solar power plant with a peak capacity of 50MWp, and the Cat Hiep solar power plant with a peak capacity of 49.5MWp are modeled by using the PSS/E software to simulate and analyze their impacts on power system stability of the 110kV transmission network in Binh Dinh province, Vietnam. Besides, the control strategies of these power plants are also established to investigate their impacts on the network. In addition, this paper proposes three typical scenarios for the wind power and solar power plants in the system. For each scenario, the grid's operating parameters such as voltage variations and frequency variations are acquired for analyzing and evaluating their impacts on the frequency and voltage variations of the network. The simulation results show that the 110kV power transmission network remains in a stable operation mode after the fault scenarios for the wind and solar power plants. Furthermore, these simulation results provide some guidance for the actual operation

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.

For voltage-source-converter based high-voltage-direct-current (VSC-HVDC) transmission systems, fault ride-through (FRT) capability is a very important grid requirement in order to enhance its operational availability under an alternating current (AC) grid fault condition. Voltage sags during a short-circuit fault in power transmission lines can lead to fluctuations in the direct current (DC) link voltage of converter systems, and may induce reversed power flow and even trip a VSC-HVDC transmission system. A practical method is developed in this paper for investigating FRT capability of VSC-HVDC transmission system characteristics during a voltage sag event using experimental results from Smart Grid Laboratory. Symmetrical and asymmetrical voltage sag events with different remaining voltages are applied to an AC grid that lasts with a variable duration. The experimental waveforms of the two converter systems are recorded and analyzed in order to evaluate the FRT capability of VSC-HVDC transmission systems.

With the penetration of distributed generation (DG) units, the power systems will face insecurity problems and voltage stability issues. This paper proposes an innovatory method by modifying the conventional continuation power flow (CCPF) method. The proposed method is realized on two prediction and correction steps to find successive load flow solutions according to a specific load scenario. Firstly, the tangent predictor is proposed to estimate the next predicted solution from two previous corrected solutions. And then, the corrector step is proposed to determine the next corrected solution on the exact solution. This corrected solution is constrained to lie in the hyperplane running through the predicted solution orthogonal to the line from the two previous corrected solutions. Besides, once the convergence criterion is reached, the procedure for cutting the step length control down to a smaller one is proposed to be implemented. The effectiveness of the proposed method is verified via numerical simulations on three standard test systems, namely, IEEE 14-bus, 57-bus, and 118-bus, and compared to the CCPF method.

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 “if…then’’. 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.

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.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]