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In present day, SFCLs are found increasing demand in power systems due to their advancements in recent years. SFCLs are implemented to limit the fault current during faults within the grid in power system. SFCL has manifested to be the most effective protection scheme in power system. Here we propose the implementation of SFCL for protection against any faults. An analysis is made for three phase Unsymmetrical faults (Namely L-G fault). To observe the influence of the SFCL in the system, analysis with and without SFCL, is implemented in MATLAB/SIMULINK. With this analysis effectiveness of SFCL is identified during a fault. Resistive type SFCL is proposed here. Outcomes obtained reinforce the implementation of SFCL for protection during faults.

The increasing demand of future power requirements Photovoltaic (pv) systems to be a better alternatives. At present situation sunlight has huge priority. It is freely available resource for power production. The output of this system is subjected to change in the sunlight and temperature. To grasp more energy from the solar array the MPPT can play the crucial function in photovoltaic systems. MPPT is mainly raise the productivity of Photovoltaic system. This paper presents the design of pv array using step-up chopper by MPPT technique.

Summary Impulse voltage testing is generally carried out for assessing the insulation strength of power equipment using standard impulse voltage waveforms in high‐voltage laboratory. However, in actual field, the power equipment experiences standard and non‐standard lightning impulse voltages. The main objective of this work is to analyse the voltage stress on surge arresters under standard and non‐standard lightning impulse waveforms. Surge arrester models are developed in matlab (The MathWorks, Inc., Natick, Massachusetts, United States), and residual voltage test results are compared with manufacturer data for validation. Impulse voltage test is performed on the Institute of Electrical and Electronics Engineers surge arrester model using standard and non‐standard lightning impulse voltage waveforms. The obtained test results showed that non‐standard impulses have the potential to develop higher voltage stress and hence pose a high risk to surge arresters. However, results of this study provide the basis for further laboratory‐based investigation considering a wide variety of impulse voltage waveforms representing the real lightning overvoltages. The test results will contribute to identify the need for modifying existing test standards or introducing new standards for impulse testing of surge arrester. Copyright © 2015 John Wiley & Sons, Ltd.

In this study, the authors investigate the secondary control of microgrids (MGs) in the presence of cyber imperfections such as delay and/or noise, and system disturbances. The existence of cyber imperfections and disturbance could bring in system uncertainty that will seriously degrade the effectiveness of most existing secondary control such as proportional–integral–derivative (PID), etc. To tackle these issues, a biologically-inspired reinforcement learning technique has been proposed which adjusts its parameters to the perturbed system setpoints generated by the cyber imperfections and system disturbances. The learning capability and low computational complexity of the proposed controller make it a promising approach to take cyber imperfections and system disturbances into account, where traditional control methodologies are not suitable due to their vulnerability to the cyber imperfections. First, an emotional learning-based secondary control structure is proposed, where the impacts of cyber imperfection and disturbance have been captured efficiently. Then, the real-time update laws are developed for generating the proper emotional signals (ESs) to stabilize the frequency and voltage. Ultimately, using the generated ESs, the secondary control of MGs is achieved. The Lyapunov analysis has been provided to prove the stability of the proposed design. Moreover, MATLAB/Simulink-based simulations demonstrate the effectiveness of the proposed algorithm.

Microgrids are small-scale power networks that include renewable energy sources, load, energy storage systems, and energy management systems (EMS). Lithium-ion batteries are the most used battery for energy storage in microgrids due to their advantages over other types of batteries. However, to protect the battery from the explosion and to manage to charge and discharge based on state-of-charge (SoC) value, this type of battery requires the use of an energy management system. The main objective of this paper is to propose an intelligent control strategy for energy management in the microgrid to control the charge and discharge of Li-ion batteries to stabilize the system and reduce the cost of electricity due to the high cost of grid electricity. The proposed technique is based on a fuzzy logic controller (FLC) for voltage control. The FLC is based on the measured voltage of the direct current (DC) bus and the fixed reference voltage to generate buck/boost converter signal control. The proposed technique has been simulated and tested using MATLAB/Simulink software which illustrates the tracking of desired power and DC bus voltage regulation. The simulation results confirm that the proposed systems can diminish the deviations of the system's voltage.

Low power brushless direct current (BLDC) motors are used in many consumer appliances. These motors have a relatively high winding resistance and therefore current control loop can be avoided in some cases, but fast and accurate speed regulation can be still needed. To minimize harmonics and generated sound noise, improved sinusoidal pulse width modulation (PWM) has been tested in the paper. As the most suitable commutation type, the sine wave with the third harmonic component has been selected. This type of communication reduced the torque ripple of the motor. This paper analyses the possibility to improve traditional proportional-integral-derivative (PID) speed regulator with Fuzzy logic block. A simulation model of BLDC motor, inverter, speed detection circuit and controller have been created. Simulation results showed that by applying the Fuzzy-based PID controller, the transient time can be reduced from 0.2 s to 0.05 s and overshoot can be avoided in comparison with traditional PID controller. Experimental results show a significant improvement in the motor dynamics—the overshoot and transient time were reduced twice. The difference with simulation results and experimental ones can be explained by delays introduced by the microcontroller.

This study focuses on reduced-order dynamical modelling of droop controlled converter-based DC sub-microgrid (MG) in a hybrid AC/DC MG. In hybrid MGs, electrical power is exchanged between the AC and DC sub-MGs by a bidirectional AC/DC converter. The authors aim to develop a comprehensive reduced-order dynamical model for the DC side in this part, incorporating standard classes of electrical loads including constant current, constant power, and constant resistance loads. Furthermore, dynamical behaviour of the power exchange between the AC and DC sub-MGs is modelled, considering that the bidirectional power converter controller aims to equalise the load ratios of AC and DC sub-MGs in order to facilitate overall decentralised control over the hybrid MG. Analytical derivations of steady-state values of main variables are given and the overall dynamical and algebraic equations are determined. In order to validate the developed model, a hybrid MG is implemented in PSCAD. Then, the proposed model for the case study is implemented in Matlab/Simulink and the results are compared with the PSCAD outputs. The comparative results show the validity of the developed reduced-order comprehensive model. The reduced-order models are preferred in designing observers such as model-based fault detection and diagnosis observers.

Enhancing the performance of photovoltaic (PV) systems has recently become a key concern because of the market demand for green energy. To obtain the most possible power from the solar module, it is imperative to allow the PV system to operate at its maximum power point (MPP) regardless of the climatic conditions. In this study, a comparison of distinctive Maximum Power-Point Tracking (MPPT) techniques is provided, which are Perturb and Observe (P&O) and Modified Variable Step-Size P&O, as well as Incremental Conductance (INC) and Modified Variable Step-Size INC, using a boost converter for two types of solar panels. Using MATLAB software, simulations have been performed to assess the efficiency of the solar module under several environmental conditions, standard test conditions (STCs), and sudden and ramp variations in both solar irradiance and temperature. The output power efficiency, time response, and steady-state power oscillations have all been taken into account in this study. The simulation results of the improved algorithms demonstrate an enhancement in the PV module performance over conventional algorithms in many factors including steady-state conditions, tracking time, and converter efficiency. Furthermore, a boost in the dynamic response in monitoring the MPP is observed in a variety of climatical circumstances. Moreover, the proposed P&O MPPT algorithm is implemented in a hardware system and the experimental results verified the effectiveness, regarding both fast-tracking speed and lower oscillations, of the proposed Variable Step-Size P&O algorithm and its superiority over the conventional P&O technique.

The microgrid (MG) faces significant security issues due to the two-way power and information flow. Integrating an Energy Management System (EMS) to balance energy supply and demand in Malaysian microgrids, this study designs a Fuzzy Logic Controller (FLC) that considers intermittent renewable sources and fluctuating demand patterns. FLC offers a flexible solution to energy scheduling effectively assessed by MATLAB/Simulink simulations. The microgrid consists of PV, battery, grid, and load. A Maximum Power Point Tracking (MPPT) controller helps to extract the maximum PV output and manages the power storage by providing or absorbing excess power. System analysis is performed by observing the State of Charge (SoC)of the battery and output power for each source. The grid supplies additional power if the battery and PV fail to meet the load demand. Total Harmonic Distortion (THD) analysis compares the performance of the Proportional-Integral Controller (PIC) and FLC. The results show that the PI controller design reduces the THD in the current signal, while FLC does not reduce the THD of the grid current when used in the EMS. However, FLC offers better control over the battery’s SOC, effectively preventing overcharging and over-discharging. While PI reduces THD, FLC provides superior SOC control in a system comprising PV, battery, grid, and load. The findings demonstrate that the output current is zero when the SOC is higher than 80% or lower than 20%, signifying that no charging or discharging takes place to avoid overcharging and over-discharging. The third goal was accomplished by comparing and confirming that the grid current’s THD for the EMS designed with both the PI Controller and the FLC is maintained below 5%, following the IEEE 519 harmonic standard, using the THD block in MATLAB Simulink. This analysis highlights FLC’s potential to address demand-supply mismatches and renewable energy variability, which is crucial for optimizing microgrid performance.

This study presents a dynamic modeling and performance analysis of three electric vehicles (Renault ZOE, Volkswagen ID.3, and Peugeot e-208) developed and simulated using MATLAB/Simulink. Three driving scenarios are investigated: constant-speed operation on flat and inclined roads, tracking of the FTP-75 driving cycle, and a multi-segment trajectory involving successive road slope and direction variations. The resulting analysis provides a rigorous comparative assessment of vehicle speed-tracking accuracy, dynamic behavior, and energy consumption, offering valuable insights into the influence of driving conditions on overall vehicle performance and energy efficiency.