Journal of Operation and Automation in Power Engineering
Volume:11 Issue: 1, Spring 2023

Current sensors are required in Field-Oriented Control (FOC) strategies of Three-Phase Induction Motor (TPIM) drives. Nevertheless, the current sensors are subject to different electrical/mechanical faults which reduce the safety and dependability of the drive system. Single phase current sensor Fault-Tolerant Control (FTC) for sensorless TPIM drives using flux observer and Extended Kalman Filter (EKF) is proposed in this research. In the suggested FTC scheme, current sensor fault detection is based on axes transformation, a logic circuit is served as the fault isolation and reconstruction of faulted currents are achieved through flux observer and EKF. The presented FTC system is capable of detecting and localizing the current sensor fault and switching the drive system to tolerant FOC mode without the rotor speed measurement. The effectiveness of the suggested FTC system is confirmed by experiments on a 0.75kW TPIM drive platform.

The Frequency Response Analysis (FRA) technique has advantages in identifying faults related to power transformers, but it suffers from the interpretation of frequency responses. This paper presents an approach based on statistical indices and Artificial Neural Network (ANN) methods to interpret frequency responses. The proposed procedure divides frequency responses into four frequency regions based on frequency resonances and anti-resonances. Then, Lin’s Concordance Coefficient (LCC) index is used as one of the most appropriate numerical indices to extract features of the four frequency regions. Finally, the Multilayer Perceptron (MLP) neural network is trained by the extracted features to identify and differentiate the types of winding faults. Besides, other intelligent algorithms such as Support Vector Machine (SVM), Extreme Learning Machine (ELM), Probabilistic Neural Network (PNN), and Radial Basis Function (RBF) neural network have been employed to compare the classification results. The proposed techniques have been practically implemented. The Axial Displacement (AD) and Disk Space Variation (DSV) faults are applied as two common mechanical faults in different locations and intensities on the 20kV windings of a 1.6MVA distribution power transformer and their corresponding frequency responses are calculated. Frequency responses calculated from the AD and DSV faults constitute the MLP input data set. The network is trained with part of the input data, and the rest of the data is allocated to validate and test the network. The results show that the suggested method has more proper performance than others using the phase component of the frequency responses in interpreting frequency responses and separation and identifying various mechanical fault types of transformer windings.

Voltage drop during the fault can be effected on the performance of generation units such as wind turbines. The ability to ride through the fault is important for these generation units. Superconducting fault current limiter and superconducting magnetic energy storage can improve the fault ride through due to fault current limiting and voltage restoring ability during the fault, respectively. This paper presents a method for optimal allocation and control of superconducting magnetic energy storage and superconducting fault current limiters in meshed microgrids. For this purpose, the doubly-fed induction generator voltage deviation, the point of common coupling power deviation, the fault current of transmission lines, and superconducting fault current limiter and superconducting magnetic energy storage characteristics were considered as objective functions. In this paper, the optimization is performed in single-step and two-step by particle swarm optimization algorithm, and the system with the optimal superconducting magnetic energy storage and superconducting fault current limiters are analyzed and compared. The results of simulations show superconducting fault current limiter and superconducting magnetic energy storage reduce 85% of voltage drop, decreases 63% of doubly fed induction generator power deviation, and limits the maximum fault current of transmission lines by 9.8 pu. Finally, the status of the studied system variables has been investigated, in two scenarios related to the different fault locations with equipment that the optimal allocated.

In recent years, as a result of remarkable increase in energy industry, discrimination between lower and higher loads as well as economic crisis which pestered a majority of countries; hence the usage of power plants became a significant issue. In addition, growing consumption of power and inexistence of valid source in satisfying the requirements has brought different problems such as diminish of fossil fuel resources, adversarial environmental influences, universal growth of Greenhouse Gases (GHGs). The associated issues have created technologies compatible with situations including Electric Vehicles (EVs). Regarding the efficiency of two-side exchange of energy within these vehicles, if there was a connection among the number of them and net under management and intelligent monitor of organization stability, so they can treat like a virtual tiny energy plant with start- up speed and free of cost. This paper presented the modeling and optimizing of the charge of electric vehicles with genetic algorithm in the presence of renewable energy sources. According to the results of this study, the cost of the HEV charge connected to the net is 75.88% less than the EV compared to the payment costs of the car (dis)charge in optimal patterns.

The power system in upcoming years will face issues of power frequency instability due to an increase in the share of Renewable Energy Sources (RES). The RESs are integrated into the power system through the power electronic converters. The operation and control of RES are drastically different than the conventional energy sources. This paper is focused on the effect of a rise in the share of RES on power system frequency stability and its possible solutions. The RESs are not taking part in the frequency regulation process in case of disturbance. Despite this, they generate disturbances in the power system caused by the intermittent nature of input energy. The RES doesn’t have extra active power for the frequency regulation as they already operate at their maximum power point. These power electronic-based generators don’t contain inertia like conventional generators. The inertia-less systems adversely affect the Rate of Change of Frequency (RoCoF) and frequency nadir. This is demonstrated on IEEE 9-bus system with different scenarios. According to that analysis, the RES should provide an inertial response during disturbances. In this paper, the proposed Modified Virtual Inertia Control (M-VIC) technique emulates inertia like conventional generators by using external Energy Storage Systems (ESS). In M-VIC the inertial response is replicated by controlling the rate and duration of power provided by ESS. The proposed technique is more effective to reduce the frequency nadir and RoCoF with better utilization of ESS. To demonstrate this, the PV integrated single-area power system model is simulated in MATLAB R2019a.

The space vector pulse-width modulation (SVPWM) is a simple and suitable method for voltage control of three-phase two-level voltage source inverters (VSI)s. However, there are plenty of methods to improve the two-level VSIs performance by adding virtual vectors or sub-sectors to the SVPWM diagram which cause complexity in implementation of SVPWM for VSIs similar to multilevel inverters. Operation in overmodulation mode is the other reason for complexity in conventional SVPWM. This paper proposes a novel modulation method, named as level vector pulse-width modulation (LVPWM), for voltage control of VSIs. The concept of the proposed method is similar to SVPWM but with different vector diagram and dwell times calculations. Unlike the SVPWM, the α and β axes and also their variables are considered separately without gathering in complex variables. The vector diagram has two separated α and β axes each of which contains individual switching vectors and reference vectors. The selection of the vectors to synthesize the reference vectors depends on only the amplitudes of the reference vectors. With lower computational overhead and easy and continuous extension to overmodulation region, the proposed method is a simple solution to the mentioned problems. Simulation and experimental results and harmonics analysis verify the effectiveness of the proposed algorithm.

This paper presents the mitigation of subsynchronous resonance (SSR) based on wide-area wide-area fuzzy controller in power systems including a double-fed induction generator (DFIG)-based wind farms linked to series capacitive compensated transmission networks. SSR damping is achieved by adding the fuzzy controller as a supplementary signal at the stator voltage loop of the grid-side converter (GSC) of doubly-fed induction generator (DFIG)-based wind farms. In addition, delays due to communication signals are important in using WAMS. If these delays are ignored, it causes system instability. In this paper, the delays are modeled with a separate fuzzy input to the controller. The effectiveness and efficiency of the WAMS-based fuzzy controller has been demonstrated by comparison with the particle swarm optimization (PSO), and imperialist competitive algorithm (ICA) optimization methods. The effectiveness and validity of the proposed Auxiliary damping control are verified on a modified version of the IEEE second benchmark model including DFIG-based wind farms via time simulation analysis by using MATLAB/Simulink.

The Internet of Things (IoT) is a multidisciplinary concept that includes a wide range of application domains and device capabilities. The IoT technology provides a platform that allows apparatus to be monitored by sensors, connected using a communication channel, and controlled remotely across a network infrastructure. This paper represents the IoT-based remote monitoring, control, and protection of irrigation water pumping systems. The sensors measure parameters; namely supply voltage and motor current to estimate operating conditions and provide protection. The measured parameters are sent to the user through the SIM900 GSM module for remote monitoring and control purposes. The android application has been developed to provide a better user interface, timer-based operation, status of pump and feedback notifications, etc. Protection to the pump (3-Փ Induction Motor) is provided through an ATmega 328P microcontroller embedded in the Arduino Uno board. Appropriate relay characteristics are programmed in the microcontroller for protection against various types of faults like thermal overload, single phasing, under/over voltage, voltage imbalance, reverse rotation. The system is tested in the lab and it is observed that all the protections are working satisfactorily. Single phasing is detected and the supply is tripped within 0.15 sec, undervoltage protection operated in 0.3 sec, and 5% unbalance in supply voltage is detected successfully and protection is operated within time.