Abstract
Economic and environmental constraints are causing power systems to operate near their critical restrictions because of the growing demand for energy. Flexible alternating current transmission systems (FACTS) devices can be used to control power flow and regulate bus voltage in networks in order to improve ...
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Economic and environmental constraints are causing power systems to operate near their critical restrictions because of the growing demand for energy. Flexible alternating current transmission systems (FACTS) devices can be used to control power flow and regulate bus voltage in networks in order to improve transfer capability and reduce system losses. The purpose of this research is to determine the best location and capacity for a FACTS device, in particular a static synchronous compensator (STATCOM) within power systems. Grey wolf optimization (GWO) is utilized to address this issue and enhance system performance. The outcomes indicate the superiority of the GWO algorithm in terms of convergence speed and solution quality when compared to conventional optimization techniques. In this paper, the Newton-Raphson approach is utilized due to its quick convergence. The design was applied to IEEE 14 and 30 bus networks, with STATCOM and without STATCOM, in order to validate the efficacy of the proposed method. Thefindings demonstrate that the active and reactive power losses of IEEE-14 bus system were reduced by 11.8% and 10.4%, respectively, after installation of STATCOM. Additionally, the STATCOM reduced both active and reactive power losses of the IEEE-30 bus system by 21.2% and 19.2%, respectively. All simulations are performed using MATLAB/Simulink.
Abstract
Providing reliable and sufficient power to the client is essential. Power quality is determined by the consistency of frequency and tie-line power between control regions. Thus, the importance of Load Frequency Control in an electrical network cannot be overstated. In this work, a PID controller using ...
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Providing reliable and sufficient power to the client is essential. Power quality is determined by the consistency of frequency and tie-line power between control regions. Thus, the importance of Load Frequency Control in an electrical network cannot be overstated. In this work, a PID controller using the Grey Wolf Optimization algorithm is employed to help with frequency management in a multi-area power network. A reheated turbine power system with five area is controlled by the PID controller. The experimental data showed a comparison between GWO-PID, Genetic Algorithm-based PID, Particle Swarm Optimization-based PID, and Firefly Algorithm-based PID. With a 1% step load variation, the findings confirmed the efficiency of using the integral time absolute error (ITAE) performance index. GA, PSO, and FA can’t keep up with the GWO-based PID controller when it comes to optimising an integrated power system. Simulation results reveal that GWO has the shortest settling time for frequency variations, as well as the lowest undershoot, overshoot, and ITAE values. To evaluate the robustness of GWO-PID, sensitivity analysis is done by modifying the system parameters like turbine and governor time constant in the range of ±10% from their nominal values.
Abstract
The concept of the Internet of Things (IoT) and its countless applications are considered as an inseparable part of the modern technology era. The placement of IoT- based devices and their limitations make the environment more vulnerable due to its openness. Security plays a critical role in IoT applications ...
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The concept of the Internet of Things (IoT) and its countless applications are considered as an inseparable part of the modern technology era. The placement of IoT- based devices and their limitations make the environment more vulnerable due to its openness. Security plays a critical role in IoT applications due to the pervasiveness of the IoT in all of the aspects in daily life. On the other hand, final devices such as their limited computing power, large number of devices connected to each other, and communication between devices and users do not allow for using traditional methods to solve security issues. Intrusion detection systems (IDSs) which can separate malicious traffic from normal mode are among the effective solutions in this field. the installed IDS should be highly accurate and lightweight to affect accuracy. In order to bring services closer to electronic devices, a concept called “fog” has emerged. A large number of studies have been conducted to make the light IDS for IoT networks utilizing various methods. The present study aims to proposea two-layer hierarchical IDS based on machine learning, which detects attacks by considering the limitations of IoT resources. In order to create an efficient and accurate IDS, the combination of two improved K-nearest neighbor (KNN) algorithms and a multi-layer perceptron (MLP) neural network was applied in the fog and cloud to separate the attacks from normal traffic, respectively. we evaluated our proposed method using IOT23 dataset. The results prove the improvement in accuracy, compared to the previous methods.
Abstract
The integration of advanced metering technology in power systems has enabled real-time data access for every node in a smart grid. As a result, the power system can now access large volumes of data. This vast amount of data requires an alternative method of analysis. Machine learning-based load forecasting ...
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The integration of advanced metering technology in power systems has enabled real-time data access for every node in a smart grid. As a result, the power system can now access large volumes of data. This vast amount of data requires an alternative method of analysis. Machine learning-based load forecasting technologies are being applied in this scenario. However, this massive data collection needs to be processed through the appropriate data pre-processing method, such as the removal of noise, outliers, and erroneous data, the detection of missing data, the normalization of widely divergent datasets, etc., to improve the effectiveness of the load forecaster. Thus, to eliminate the various kinds of errors and outliers present in the data that was directly obtained from smart meters, this study analyses and compares the efficacy of eight distinct smoothing and filtering techniques as a novel contribution of this work. Using the processed data acquired, a neural network-based load forecasting model was developed to compare the efficacy of the variouspreprocessing approaches. This study makes use of real-time data obtained from the smart meter placed at a node within the NIT Patna campus. The proposed moving average filter surpasses the other methods for filtering and smoothing the raw data by an average MAPE of 2.66, according to the load forecasting results that were obtained.
Abstract
This research presents a new three-phase switched capacitor multilevel inverter (SCMLI) with a power enhancement capability. The structural design comprises six switches, two diodes and two capacitors to achieve a voltage gain of three times. Inherent self-balancing of capacitor voltage reduced active/passive ...
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This research presents a new three-phase switched capacitor multilevel inverter (SCMLI) with a power enhancement capability. The structural design comprises six switches, two diodes and two capacitors to achieve a voltage gain of three times. Inherent self-balancing of capacitor voltage reduced active/passive part count, and the ability to generate bipolar output voltage without an H-bridge at the back end are the important aspects of the suggested topology. A concise description of the structural design, basic operation, determination of capacitance, and power loss analysis has been presented, along with comparisons with recent previous topologies. To regulate the switching process, a basic level-shift PWM modulation strategy has been designed. The simulation and hardware studies demonstrate the feasibility and efficacy of the proposed topology (PT).
Abstract
With the incorporation of the various DG sources in the power system, numerous changes appear and have serious effects on the protective scheme. Knowledge of the impact of these energy sources on the dynamics of the power system is utmost necessary. Also, the performance of the protection system under ...
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With the incorporation of the various DG sources in the power system, numerous changes appear and have serious effects on the protective scheme. Knowledge of the impact of these energy sources on the dynamics of the power system is utmost necessary. Also, the performance of the protection system under these circumferences needs to be analyzed. Under the penetration of Renewable Energy Sources, it is desired to develop a new technique that can identify the Power Swing conditions and Fault conditions. It is also required to discriminate between stable or balanced power swing and unstable or unbalanced power swing conditions as an unstable swing may result in cascading of the system. Sometimes, the impedance trajectory falls into the tripping zone of the Mho relay used for line protection during stable swing conditions. This situation is unnecessary because the system has a chance to return to its normal state. Hence, it is necessary to identify the proper system conditions and prevent the maloperation of protective devices in such a situation.The technique suggested here can also able to differentiate between Stable Power Swings and Unstable Power Swing, the latter sometimes leads to maloperation of the system. The Suggested method uses Kalman Filtering due to its adaptability to deal with noisy data, which makes it a valuable and robust tool in the Power System. Considering the rate of change of impedance in real-time, the scheme can correctly identify the stable, unstable power swing and fault situations.
Abstract
The current research introduces an enhanced buck converter. The introduced converter improves the performance of similar converters thanks to causing lower switch voltage stress, higher efficiency and fewer number of elements. To make use of low voltage MOSFETs with a smaller ON resistance, using multiple ...
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The current research introduces an enhanced buck converter. The introduced converter improves the performance of similar converters thanks to causing lower switch voltage stress, higher efficiency and fewer number of elements. To make use of low voltage MOSFETs with a smaller ON resistance, using multiple switching strategies would reduce the voltage stress across the switch and thus allow them to be used. This study compares the performance of the proposed converterwith the similar converters. The gate pulses are similar in the proposed converter, so the control is very simple. Input voltage is divided between the blocking capacitors at the input and as a result, the voltage stress on the switches is lower than the input voltage. So, the converter can be designed with MOSFETs with low drain-source resistance. Also, the voltage gain is reduced in comparison with the conventional buck converter. Furthermore, output power is shared between two switches which results in better heat dissipation. Also, it is possible to implement the proposed converterusing a single magnetic element. Therefore, the total number of components in comparison with similar converters is reduced. The results show that the introduced converter technically performs with lower switching losses and increased overall efficiency discussion of operating modes, as well as converter design and test results shall be provided. Step-down DC to DC converter
Abstract
generation generates power for local loads as well as sharing it to the main grid. The system may get islanded after the occurrence of fault. It is necessary to detect islanding earlier. It is necessary to detect islanding and provide trip signal earlier. Also, the oscillations should be damped out as ...
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generation generates power for local loads as well as sharing it to the main grid. The system may get islanded after the occurrence of fault. It is necessary to detect islanding earlier. It is necessary to detect islanding and provide trip signal earlier. Also, the oscillations should be damped out as early as possible to prevent instability. Harmonics are injected due to the introduction of a disturbance signal hence; total harmonic distortion should be as minimum as possible. Hereadaptive network-based fuzzy inference system is used for the CEGRE LV system for the purpose of islanding detection and anti-islanding protection. An active oscillatory disturbance signal is injected in controller. Generally, proportional integral controller and fuzzy logic controller are used for anti-islanding protection. But an adaptive network-based fuzzy inference system can be used for earlier detection of islanding and also it gives better performance than a proportionalintegral controller and fuzzy logic controller. System analysis is discussed by comparing Adaptive network-based fuzzy interference system performance with proportional gain controller and fuzzy logic controller by considering zero power mismatch condition. The simulation results of this proposed method is evaluated by using MATLAB Software.
Abstract
The efficient and economical operation of a distribution power network (DPN) has been essential in recent times, considering the energy crisis and shortage of fossil fuels. A DPN is known to be efficient and economical if power losses are minimal, the voltage drop along the lines is less, and stability ...
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The efficient and economical operation of a distribution power network (DPN) has been essential in recent times, considering the energy crisis and shortage of fossil fuels. A DPN is known to be efficient and economical if power losses are minimal, the voltage drop along the lines is less, and stability is maintained during different operating conditions. However, due to the crisis for primary fuel, all DPNs including radial power distribution networks (RPDN) are operated at threshold level. This has led to higher power losses, more voltage drops, and stability issues in RDPN. Hence, to reduce the power losses and voltage deviation and improve the stability of the power system network, distributed generation (DG) units are optimally allocated into radial DPN. In this study, an optimization technique using Jellyfish search optimizer (JSO) algorithm is proposed to optimize multiple DGs into RDPN to minimize a multi-objective function corresponds to real power loss (RPL) minimization, voltage stability (VS) enhancement, and total operating cost (TOC) minimization. The performance of the proposed technique is evaluated for multiple type I and type III DGs placement on an IEEE standard 33-bus RDPN. Besides, the effectiveness of the proposed technique is investigated considering a nominal and peak power demand. The efficacy of the research outcome of the suggested JSO approach has been compared with the outcome ofother optimization algorithms presented in the literature. The comparison exemplifies that JSO gives more promising outcomes than other algorithms by delivering the least real power losses and better voltage profile enhancement at minimum operating cost.
Abstract
Conventional direct torque control (DTC) improves the dynamic performance of the five-phase induction machine (FPIM). Nevertheless, it suffers from significant drawbacks of high stator flux and electromagnetic torque ripples. Moreover, the DTC technique relies on an open-loop estimator for accurate stator ...
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Conventional direct torque control (DTC) improves the dynamic performance of the five-phase induction machine (FPIM). Nevertheless, it suffers from significant drawbacks of high stator flux and electromagnetic torque ripples. Moreover, the DTC technique relies on an open-loop estimator for accurate stator flux module and position knowledge. However, this method is subjected to substandard performance, mainly during the low-speed operation range. Therefore, a sliding mode sensorless stator flux and rotor speed DTC based on an artificial neural network (DTC-ANN) for two parallel-connected FPIMs is discussed to tackle the problems above. This approach optimizes the DTC performance by replacing the two hysteresis controllers (HC) and the look-up table. As for the poor estimation drawback, the sliding mode observer (SMO) offers a robust estimation and reconstruction of the FPIM variables and eliminates the need for additional sensors, increasing the system’s reliability. The present results verify and compare the performance of the control scheme.
Abstract
A tandem solar cell consisting of three cells is designed and simulated by the Solar Cell Capacitor Simulator (SCAPS) program. The bandgap of the top cell absorber (Cs2AgBi0.75Sb0.25Br6) is 1.8 eV, the middle cell absorber (CH3NH3PbI3) has a bandgap of 1.55 eV), and a single-crystal silicon cell (with ...
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A tandem solar cell consisting of three cells is designed and simulated by the Solar Cell Capacitor Simulator (SCAPS) program. The bandgap of the top cell absorber (Cs2AgBi0.75Sb0.25Br6) is 1.8 eV, the middle cell absorber (CH3NH3PbI3) has a bandgap of 1.55 eV), and a single-crystal silicon cell (with 1.12 eV bandgap) is selected as the bottom cell. Each of these cells were simulated and optimized separately. To improve current density in the middle cell, CuSCN is chosen as the holetransport layer (HTL). Power conversion efficiencies (PCE) of individual Cs2AgBi0.75Sb0.25Br6, MAPbI3, and Si cells are 14.32%, 25.09%, and 25.22%, respectively. which are quite close to the results published in the literature. Consequently, the tandem structure of these cells is simulated and the optimal thicknesses for the absorber layers (as required by the current-matching condition) in a two-terminal (2T) monolithic structure is calculated. The optimized thicknesses of Cs2AgBi0.75Sb0.25Br6 and MAPbI3 absorber layers in the tandem configuration are 300 and 550 nm, respectively. The transmitted spectra of the top and middle cells are obtained using the Matlab software. Subsequently, the SCAPS numerical simulation for the 2T tandem structure gave an enhanced power conversion efficiency (PCEs) of 38.9%.
