Yashar Zehforoosh; Mahdi Jalali
Abstract
This study presents a four-element compact Multi-Input Multi-Output antenna with enhanced isolation for applications with three bands. The four port antenna elements have hook-shape multiband monopole elements with 50 Ω microstrip feed line and placed so that they are perpendicular to one another to ...
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This study presents a four-element compact Multi-Input Multi-Output antenna with enhanced isolation for applications with three bands. The four port antenna elements have hook-shape multiband monopole elements with 50 Ω microstrip feed line and placed so that they are perpendicular to one another to enhance the act of the MIMO system. Simulation and measurement consequences demonstrate that the antenna operates a consistent gain and radiation patterns at the major frequency bands of 2.11-2.47 GHz, 3.14-3.54 GHz and 5.15-5.85 GHz with S11<-10 dB. To verify the claimed MIMO antenna performance, data in format of radiation patterns, peak gain (4.9,5.2,5.8 dB), diversity gain (DG) (9.95,9.92,9.92 dB), Envelope Correlation Coefficient (ECC) (0.005,0.003,0.002), TRAC, channel capacity and MEG ratio are retrieved. These specifications of the suggested antenna cause it a suitable candidate for WiMAX, Bluetooth and WLAN uses. Additionally, the suggested antenna outperformed current work by providing a superior balance of size, bandwidth, and several performance characteristics.
Sana Sadeghi; Alireza Jahangiri; Ahmad Ghaderi Shamim
Abstract
Distribution systems pose a significant challenge within the power grid, primarily due to their high current, low voltage, and comparatively high ohmic resistance compared to transmission and sub-transmission systems.This results in substantial power losses, necessitating the need for effective mitigation ...
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Distribution systems pose a significant challenge within the power grid, primarily due to their high current, low voltage, and comparatively high ohmic resistance compared to transmission and sub-transmission systems.This results in substantial power losses, necessitating the need for effective mitigation strategies.To address this issue, a wide range of methods and algorithms have been proposed and continuously developed. Over the past half-century, reconfiguring the distribution network has emerged as a cost-effective and straightforward approach to reducing distribution losses. Distribution system reconfiguration has been extensively studied, with each study aiming to achieve distinct objectives. Additionally, numerous studies have explored the dynamics of distribution system reconfiguration, evaluating and comparing various approaches. This study comprehensively assesses both static and dynamic methods of reconfiguring distribution systems and introduces a novel dynamic reconfiguration technique. Unlike traditional methods that rely on real-time or hourly load models, this approach utilizes a load model to address the dynamic reconfiguration problem. Simulations were conducted on the well-established IEEE 33-bus test system, employing MATLAB software in conjunction with a genetic algorithm to minimize losses and optimize voltage profiles. Based on the simulation results, this novel dynamic reconfiguration method demonstrated superior performance compared to previously employed methods. It effectively reduced power losses and enhanced the voltage profile, demonstrating its potential for improving the overall efficiency of distribution systems.
Ailin Asadpour; Amir Sabbagh Molahosseini; Azadeh Alsadat Emrani Zarandi
Abstract
As an emerging technology, reversible computing enables the development of high-performance computing systems with low energy consumption. A residue number system (RNS) that performs arithmetic operations in parallel with error tolerance and no carry propagation requires forward and reverse converters ...
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As an emerging technology, reversible computing enables the development of high-performance computing systems with low energy consumption. A residue number system (RNS) that performs arithmetic operations in parallel with error tolerance and no carry propagation requires forward and reverse converters to communicate with other digital circuits. Designing reversible forward and reverse converters using new technologies is very important due to their wide applications in implementing the RNS. These converters, which are the overhead of the system, increase energy consumption. This study proposes a hybrid converter conforming to reversible logic for the RNS. This hybrid converter unifies forward and reverse converters by sharing hardware and reversible gates. By using the mixed-radix conversion (MRC), the reverse conversion arithmetic relations adopt a similar format to that of the forward conversion arithmetic relations, and by the addition of a number of Fredkin gates and modifying the inputs, the reverse converter hardware is used to perform forward conversion. Based on the findings, the hybrid converter, which conformed to reversible logic for the moduli set {2^2n,2^n-1,2^(n+1)-1} and {2^n-1,2^n+1,2^2n+1}, decreased the quantum cost to 19.56% and 19.52%, respectively.
Khanh Huu Doan; Tuan Anh Dinh
Abstract
This paper presents the construction of a method to find the optimal route for ships with two criteria: fuel consumption and sailing time. Unlike most previous studies, the data used in this research was generated from a simulation model using the HIL (Hardward-In-The-Loop) technology instead of real ...
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This paper presents the construction of a method to find the optimal route for ships with two criteria: fuel consumption and sailing time. Unlike most previous studies, the data used in this research was generated from a simulation model using the HIL (Hardward-In-The-Loop) technology instead of real operational data. The HIL simulator is built from equations of the ship's 6 degrees of freedom (6-DOF), models of environmental disturbances, propulsion systems, and technical records of the real ship. In fact, operating data of the real ship is collected from noon reports, which are often incomplete in terms of environmental disturbances acting on the ship, not to mention the large sampling time (usually updated once a day). Meanwhile, the dataset generated from the HIL simulator will fully include the three main environmental components acting on ships, including waves, wind, and currents, with various scenarios. Based on that dataset, an algorithm to find optimal routes with two criteria is proposed using neural networks and the A-star algorithm. Test results show that the proposed algorithm operates reliably and has low errors. This research can be applied to find the optimal routes for small and medium-sized ships in Vietnam before each voyage at a low cost instead of using high-cost weather routing services.
SWETA KUMARI; Rajib Kumar Mandal
Abstract
For transformer-less operation, a wind energy generating system (WEGS) with an 8.5 kW wind turbine and a 6.6 kW Z-source inverter (ZSI) is modelled. A closed-loop control technique is employed at the load side of the WEGS to obtain a constant voltage with a fluctuating load at the output side of the ...
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For transformer-less operation, a wind energy generating system (WEGS) with an 8.5 kW wind turbine and a 6.6 kW Z-source inverter (ZSI) is modelled. A closed-loop control technique is employed at the load side of the WEGS to obtain a constant voltage with a fluctuating load at the output side of the system. The ZSI is used with a proportional-integral (PI) controller for closed-loop control since it is the least complicated controller to operate and tune. As an effect of ZSI's nonlinear nature, PI controllers cannot be used directly with this system. The primary focus of this study is the optimization of stabilized PI coefficients (Kp, Ki). PI tuning for closed-loop ZSI is taken care of with the use of particle swarm optimization (PSO), the sine-cosine algorithm (SCA), and the opposition-based sine-cosine algorithm (OB-SCA). The OB-SCA provides superior closed-loop ZSI stability when used with WEGS. MATLAB is used for both the design and simulation of the system. The results demonstrate that the proposed controller can precisely regulate the AC output voltage of ZSI with WEGS.
CHARAN SEKHAR MAKULA; Ratna Dahiya
Abstract
Due to the growing popularity of microgrids in buildings, the foreseeable electricity demand for a building draws the attention of many researchers. The precise short-term demand forecast efficiently directs building managers and operators for interactions with electrical distribution systems, daily ...
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Due to the growing popularity of microgrids in buildings, the foreseeable electricity demand for a building draws the attention of many researchers. The precise short-term demand forecast efficiently directs building managers and operators for interactions with electrical distribution systems, daily operational decisions, and energy conservation. This research proposes a hybrid optimization-based deep learning (DL) approach to increase the accuracy of short-term forecasts. The present work employs the Bilateral Long Short-Term Memory (BiLSTM) network-based DL technique because the BiLSTM technique has an exceptional ability to manage nonlinear interactions in data and learn the temporal dependencies. The performance of the BiLSTM technique is improved by using the optimally determined hyperparameters via a hybrid optimization algorithm that combines particle swarm optimization (PSO) and grey wolf optimization (GWO). The exploration ability of GWO and exploitation ability of PSO are effectively combined in the hybrid optimization GWO-PSO. The performance of the recommended approach is assessed using a case study of an educational building. The performance of the proposed model is compared to existing nonoptimal BiLSTM and single optimization-based BiLSTM for short-term load forecast.
Himanshu N Chaudhari; PRANAV B DARJI
Abstract
This research paper introduces a modified single DC-sourced multilevel inverter (MLI) consisting of several cells made from a controlled switch, a diode, and a capacitor to generate voltage levels in series connection with the H-bridge. By increasing the number of cells more output voltage levels can ...
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This research paper introduces a modified single DC-sourced multilevel inverter (MLI) consisting of several cells made from a controlled switch, a diode, and a capacitor to generate voltage levels in series connection with the H-bridge. By increasing the number of cells more output voltage levels can be generated in proposition to 2n+3 for symmetrical multilevel inverter (S-MLI) and maximum 2(N+1) +1 for asymmetrical multilevel inverter (A-MLI), where N is the number of connected cells. In this article, the proposed inverter utilizes seven control switches, three power diodes, a
DC voltage source, and three floating capacitors to generate nine-level (S-MLI), fifteen-level, and seventeen-level (AMLI) output. By employing a modified single DC source configuration, we achieve a substantial reduction in the number of isolated DC sources and switches required for operation. The reduction in control switches minimizes the requirement of gate driver and protection circuit. This enhancement not only simplifies the circuitry but also enhances the inverter's cost-effectiveness and efficiency. A comparison of proposed and other recently developed single-sourced topologies has been done to show the benefits of the proposed topology. The performance of the proposed modified inverter topology is analyzed through MATLAB/Simulink and validated by a laboratory prototype. Through extensive simulation and analysis, we demonstrate the improved performance, reduced component count, and complexity of the proposed MLI design.
Morteza Asadi; Seyyed Mostafa Abedi; Hassan Siahkali
Abstract
In today's society, the importance of creating highly reliable distribution networks cannot be overstated. Utilities face challenges in planning and developing these systems effectively, aiming to decrease costs and meet consumer demands. This research proposes a coordinated architecture that focuses ...
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In today's society, the importance of creating highly reliable distribution networks cannot be overstated. Utilities face challenges in planning and developing these systems effectively, aiming to decrease costs and meet consumer demands. This research proposes a coordinated architecture that focuses on the integration of a Demand Response Program (DRP) to improve the reliability of power distribution networks. Specifically, in this paper the reliability improvement is presented through finding optimal price, location, and amount of participated load in demand response program considering automatic switches and ESUs in service restoration process in electrical distribution systems. Also, uncertainty of repair time for faulted equipment is considered in this paper. suggested objective is to minimize the Total Cost of the system (TC) by optimizing the placement of the price, location, and amount of participation loads. The TC includes the cost of customer interruption, energy not supplied, ESU participation, and DRP. To illustrate the applicability and efficiency of the suggested approach, it is applied to three cases on a test case. Additionally, a sensitivity study is conducted. The results demonstrate that optimizing the incentive and penalty costs leads to significantly reduced SAIDI index and total costs. Moreover, the value of the incentive and penalty costs is lower than the fixed ones in this study, resulting in increased participation of sensitive load points in DRP.
Ahmadreza Abdollahi Chirani
Abstract
Due to economic and environmental constraints, power systems are operating near critical limits as load demand keeps growing rapidly. To improve the transfer capability, system losses, stability, and maximum loading parameters of electrical power systems, Flexible Alternating Current Transmission Systems ...
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Due to economic and environmental constraints, power systems are operating near critical limits as load demand keeps growing rapidly. To improve the transfer capability, system losses, stability, and maximum loading parameters of electrical power systems, Flexible Alternating Current Transmission Systems (FACTS) devices can be used to control power flow and regulate bus voltage. This research article focuses on the problem of identifying the optimal location for a FACTS device, specifically a Static Synchronous Compensator (STATCOM), within power systems. This design is based on the loss reduction using Newton-Raphson load flow method, to increase stability and maximum load ability of a network by considering the optimal location and capacity of STATCOM devices in a network. To address this challenge, the Grey Wolf Optimization (GWO) is employed as a metaheuristic optimization technique to reduce power losses. The outcomes indicate the superiority of the GWO algorithm in terms of convergence speed and solution quality when compared to conventional optimization techniques. To verify the performance, the design is applied to IEEE 14 and 30 bus networks considering STATCOM and base case without STATCOM. All simulations are performed using MATLAB/Simulink.
Somasundaram VASUDEVAN; Kandasamy Jothinathan
Abstract
Short-term electrical load forecasting plays a pivotal role in modern energy systems, addressing the need for accurate predictions of electricity demand within a time frame ranging from a few hours to a few days. The implications of inaccurate predictions extend beyond operational challenges to potential ...
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Short-term electrical load forecasting plays a pivotal role in modern energy systems, addressing the need for accurate predictions of electricity demand within a time frame ranging from a few hours to a few days. The implications of inaccurate predictions extend beyond operational challenges to potential economic and environmental consequences, emphasizing the critical role that short-term electrical load forecasting plays in the modern energy landscape. The purpose of this research is to address the aforementioned consequences by developing an optimally configured Long Short-Term Memory (LSTM) model for predicting short-term electrical load forecasting in Tamil Nadu, specifically focusing on India's Villupuram region. While LSTM models are recognized for their overall effectiveness, their performance in short-term electrical load forecasting necessitates a tailored approach. Hyperparameter optimization is the appropriate choice for configuring the LSTM model for short-term electrical load forecasting. The manual or trial-and-error process in hyperparameter tuning is time-consuming and complex to compute. To address this, the research integrates the Cauchy-distributed Harris Hawks Optimization (Cd-HHO) approach for the optimal configuration of the LSTM model. The optimally configured LSTM through Cd-HHO consistently achieves lower Mean Squared Error (MSE) compared to other state-of-the-art methods, which is 0.7225 in the 2017 database, 0.974 in the 2018 database, and 0.116 in the 2019 database.
Narender Saini; Jyoti Ohri
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.
KALAGOTLA CHENCHIREDDY; Mulla Gous basha; VISLAVATH KUMAR; Shabbier Ahmed Sydu
Abstract
This article describes the use of a sliding mode controller (SMC) in conjunction with an integral (PI) controller for a MLI based DSTATCOM to balance dc side voltage, control a cascaded H-bridge inverter, and compensate for power quality issues related to current harmonics. Several benefits come with ...
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This article describes the use of a sliding mode controller (SMC) in conjunction with an integral (PI) controller for a MLI based DSTATCOM to balance dc side voltage, control a cascaded H-bridge inverter, and compensate for power quality issues related to current harmonics. Several benefits come with using SMC for DSTATCOMDC link voltage regulation, including a decrease in switching ripple in the DC side voltage and a steady DC side capacitor voltage under dynamic conditions. A DSTATCOM based CHBMLI supplying three phase loads is used to implement the SMC algorithm. When using the suggested dc link voltage balancing method, the DSTATCOM characteristics perform satisfactorily in terms of voltage balancing and the removal of power quality issues such current harmonics. Additionally, the DSTATCOM's improved voltage balancing (IVB) scheme is used to compare the performance of the PI controller with the SMC's improved voltage balancing method. The real-time investigation validates the performance characteristics, and the enhanced voltage balancing scheme of SMC results in better transient and steady state response.
Ali Kaffash; Seyed Reza Kamel; Maryam Kheirabadi
Abstract
The concept of Internet of Things (IoT) and its countless applications are considered as an inseparable part of modern technology era. Security plays a critical role in IoT applications due to pervasiveness of the IoT in all of the aspects in daily life. from the other hand final devices such as their ...
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The concept of Internet of Things (IoT) and its countless applications are considered as an inseparable part of modern technology era. Security plays a critical role in IoT applications due to pervasiveness of the IoT in all of the aspects in daily life. from the other hand final devices such as their limited computing power, communication constraints, 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 light weight 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 network utilizing various methods. The present study aims to propose 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 algorithms (KNN) applied in the fog to separate malicious traffic from normal mode and Multi-Layer Perceptron neural network (MLP) applied in the cloud to determine type of the attacks, respectively. we evaluated our proposed method using IOT23 dataset. The results prove the improvement in accuracy about 99.9%, and in time complexity compared to the previous methods.
Vikash Kumar; Rajib Kumar Mandal
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 various pre-processing 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.
Kasinath Jena; Dhananjay Kumar
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).
Shaeekul Ameen; Md. Sayed Farhan; Md. Farhun Monsur; Md. Faysal Nayan
Abstract
This study examines the behavior of carbon nanotube field effect transistors under ballistic conditions by analyzing the effect of gate (α_G) and drain (α_D) control coefficient modifications on the device's diameter. The effect of α_G and α_D on the outcome of CNTFETs has ...
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This study examines the behavior of carbon nanotube field effect transistors under ballistic conditions by analyzing the effect of gate (α_G) and drain (α_D) control coefficient modifications on the device's diameter. The effect of α_G and α_D on the outcome of CNTFETs has been thoroughly investigated, and the performance of the device has been evaluated using a variety of parameters for different diameters. In this CNTFET design, the lowest sub-threshold swing recorded is 60.7 mV/decade when using a lower CNT diameter which is 1 nm. The smaller value of sub-threshold swing is contributed by the highest value of gate control coefficient i.e. 0.98, which is desirable for a better ratio between the on- and off-currents and faster-switching device. Again, the maximum quantum capacitance obtained was 1.97×10-10 F/cm2 while utilizing a smaller CNT diameter of 1 nm. The maximum value of quantum capacitance is supplied by the value of the gate control coefficient, which is 0.83. Also, the highest transconductance measured, with a greater CNT diameter of 5 nm, is 14.50 uS. With a gate control coefficient of 0.98, the quantum capacitance reaches its maximum value. Overall, the sub-threshold swing decreases as the gate control coefficient increases, while it increases as the drain control coefficient increases. Again, as the gate control coefficient increases, the value of quantum capacitance decreases with a smaller diameter, whereas the quantum capacitance of the device does not fluctuate significantly with a larger diameter. When the diameter changes, the drain control coefficient undergoes an analogous transformation. Furthermore, an increase in the gate control coefficient causes the transconductance to increase. However, when the drain control coefficient is increased along with a change in diameter, the transconductance value remains almost unchanged. Thus, the ideal values for both control coefficients can be determined in this manner to ensure optimal performance.
Pankaj H. Vasava; Dharmesh D. Patel; Nilesh Chothani; Sanjay Joshi
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 effect 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 effect 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, 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 in terms of the system having a chance to return to its normal state. Hence, in such a situation, it is necessary to identify the proper system conditions and prevent the mal operations of protective devices. 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.
Sharareh Bashirazami; Mohammad Reza Amini; Ehsan Adib; Majid Delshad
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 converter with 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 converter using 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.
Dhanashri Changan; Pranav Darji
Abstract
In this era, distributed energy resources are sustainable solution on energy crisis. Distributed generation are generating power for local loads as well as sharing it to main grid. System may get islanded after occurrence of fault. It is necessary to detect islanding earlier. Here adaptive network based ...
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In this era, distributed energy resources are sustainable solution on energy crisis. Distributed generation are generating power for local loads as well as sharing it to main grid. System may get islanded after occurrence of fault. It is necessary to detect islanding earlier. Here adaptive network based fuzzy inference system is used for 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 adaptive network based fuzzy inference system can be used for earlier detection of islanding and also it gives better performance than proportional integral 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.
Sundar Ramesh; Vijayakumar Govindaraj; Soumya Santhosh; Ilakkia Tholkappian; Sachin Sumathi Rajaram; Rajakumar Palanisamy
Abstract
Efficient and economic operation of distribution power network (DPN) is essential in recent times considering the energy crisis and shortage of fossil fuel. 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 ...
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Efficient and economic operation of distribution power network (DPN) is essential in recent times considering the energy crisis and shortage of fossil fuel. 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 of other optimization algorithms presented in the literature. The comparison exemplifies that JSO gives promising outcomes than other algorithms by delivering the least real power losses and better voltage profile enhancement at minimum operating cost.
Gopal M. Dandime; Manish D sawale
Abstract
The research focuses on the foundational elements of the Internet of Things (IoT) infrastructure and its applications in smart buildings, smart parking, and smart cities. Wireless Sensor Networks (WSNs) play a critical role in enabling these applications. However, due to their low battery energy, WSN ...
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The research focuses on the foundational elements of the Internet of Things (IoT) infrastructure and its applications in smart buildings, smart parking, and smart cities. Wireless Sensor Networks (WSNs) play a critical role in enabling these applications. However, due to their low battery energy, WSN nodes are severely constrained, limiting their operation to a few days. To address this issue, solar energy harvesting is proposed as a promising solution to provide long-term power autonomy for WSNs. This research aims to develop an efficient Solar Energy Harvesting System (SEHS) using the Enhanced Water Strider Algorithm (EWSA) and a Fractional Order Proportional-Integral-Derivative (FOPID) controller to harvest the maximum energy from photovoltaic panels for the WSN. The proposed approach demonstrates a solar energy harvesting efficiency of 98.3%, which is superior to comparative techniques. Additionally, integrating the Cauchy distribution function with the traditional WSA updating strategy helps identify the optimal FOPID tuning parameters, thus improving the solar energy harvesting efficiency. This research provides valuable insights into the development of efficient SEHS for WSNs, enabling their widespread adoption in several applications.
FARADJI Boubakar; ameur aissa
Abstract
The main objectify of this article subject is the study and feasibility of micro wind turbine used for small farms , the electrical power generated from an axial flux permanent magnet generator , when the power scale is in direct correlation with wind velocity. The proposed design shows more economic ...
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The main objectify of this article subject is the study and feasibility of micro wind turbine used for small farms , the electrical power generated from an axial flux permanent magnet generator , when the power scale is in direct correlation with wind velocity. The proposed design shows more economic costs with accepted recovered power , the originality of this proposed generator is due to the flexibility and malleability of stator windings various positions connection which aloud to pass from signal phase to multiphase generator . The mechanical coupling between the generator and wind turbine is direct drive system without mechanical gear, when the rotor is designed to be exciting the stator from hollow disc permanent magnets. However, the generator electromagnetic model study with finite element analyses is carried out in three dimensions thanks to Flux3D accuracy software. The curing out simulation results assenting to forefront a decision to proceed for primary experimental testes on the designed prototype.
Khaled Mohammed Said Benzaoui; Elakhdar Benyoussef; Ahmed Zouhir Kouache
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.
Nor Farisha Diana Binti Rosli; Wahyu Mulyo Utomo; Afarulrazi Abubakar; Suriana Salimin; Tharnisha Sithananthan
Abstract
This paper aims to investigate the performance of a bidirectional DC-DC converter utilizing an ANFIS-PID controller in closed-loop mode. This is because operating a bidirectional DC-DC converter in open-loop mode can result in several problems, including poor regulation, limited flexibility, and limited ...
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This paper aims to investigate the performance of a bidirectional DC-DC converter utilizing an ANFIS-PID controller in closed-loop mode. This is because operating a bidirectional DC-DC converter in open-loop mode can result in several problems, including poor regulation, limited flexibility, and limited performance, especially in transient response and efficiency. Additionally, there is a risk of overloading the converter or damaging connected devices due to uncontrolled operation. Therefore, the main objective of this study is to address the critical requirement for enhanced response and load efficiency within the context of a three-phase interleaved bidirectional DC-DC converter designed for Hybrid Electric Vehicle (HEV) applications with 1kW rated power of converter and 10kHz switching frequency which exhibits 14.29% reduce overshoot in the system. This research aims to utilize the capabilities of an ANFIS-PID controller to optimize the dynamic responsiveness and load efficiency of the converter. The findings of the study reveal that the implementation of an ANFIS-PID controller leads to improved transient response and load efficiency, highlighting its potential to enhance bidirectional DC-DC converters. To design and simulate the behavior of the converter, MATLAB/Simulink software has been employed.
Shohreh Ajoudanian; Maryam Nooraei Abadeh
Abstract
Large scale requirement engineering needs automated precise and efficient capability modeling and analyzing methods formally to interoperate with the evolving and goal driven requirements. The proposed capability driven requirement engineering framework presents a two-layer framework for the automation ...
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Large scale requirement engineering needs automated precise and efficient capability modeling and analyzing methods formally to interoperate with the evolving and goal driven requirements. The proposed capability driven requirement engineering framework presents a two-layer framework for the automation of requirements engineering. In the first layer, a meta-model is proposed to define a fault-free model instantiating of the requirements model, and thereby ensuring consistency in the process of requirement execution and in the second layer the analysis algorithms are provided for discovering and querying the boundaries and capabilities of the system at the abstract level. The proposed capability driven requirement framework provides the ability to specify, decomposition, and identification of the requirement traces to execute the activities in terms of available capacities and resources. We also provide the applicability of the approach from various points of view including quality and stability of bounded contexts, average precision and query assessment. As a running example, we highlight the essential role of electrical features in achieving seamless integration and operation, encompassing power distribution, automation systems, energy efficiency and safety measures. The proposed capability-driven requirement framework is crucial for effective smart home engineering in this context. The proposed structured, formal description of software requirement capabilities may increase the precision and recall of module discovery mechanisms for large-scale software engineering.
Bogaraj Thirumalaisamy; Sweety Jose Paul; Natarajan Angappan; Karthikeyan Subramanian
Abstract
An innovative Synchronous Buck Converter (SBC) with a wide input voltage range is presented in this article for use in Electric Vehicle (EV) applications. The disadvantages of higher losses in an Asynchronous Buck Converter (ABC) are intended to be addressed by the Synchronous Buck Converter. Fewer losses ...
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An innovative Synchronous Buck Converter (SBC) with a wide input voltage range is presented in this article for use in Electric Vehicle (EV) applications. The disadvantages of higher losses in an Asynchronous Buck Converter (ABC) are intended to be addressed by the Synchronous Buck Converter. Fewer losses occur in the circuit when MOSFET (or any controlled switch) is used in place of diode. To enhance system performance, the control approach known as Emulated Peak Current Mode (EPCM) is employed. The design of a broad range input SBC and the investigation of power loss calculations using different control techniques, which are implemented using PSIM, are the primary contributions made in this paper. The buck converter employed in this paper has an output voltage of 12 V and a wider input voltage range of 40–75 V. It is utilized by electric vehicles' light and horn systems. Using PSIM software, the SBC using the EPCM, Current Mode Control (CMC), and Voltage Mode Control (VMC) techniques is simulated. Hardware results coincide with the simulation results and thus the results are validated.
Norsuhada Zainal Abidin; Muhammad Saufi Kamarudin; Erwan Sulaiman
Abstract
Sulfur hexafluoride (SF6) is extensively utilised as an essential insulating material in high-voltage industries owing to its outstanding electrical characteristics. However, the use of SF6 gas faces two significant challenges: its substantial impact on global warming and the high toxicity of its breakdown ...
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Sulfur hexafluoride (SF6) is extensively utilised as an essential insulating material in high-voltage industries owing to its outstanding electrical characteristics. However, the use of SF6 gas faces two significant challenges: its substantial impact on global warming and the high toxicity of its breakdown byproducts. This study aims to analyse the breakdown properties of various gas and gas mixtures, including, pure Nitrogen (N2), pure Oxygen(O2), O2+N2 gas mixture, and SF6+N2 gas mixture as alternative insulation media under positive standard lightning impulses. The experiments involve sphere and plate electrodes with varying gap distances. Following the BS EN 60060-1 standard, the breakdown voltage is measured using the Up and Down method, with a voltage interval between levels set between 1.5% and 3%. Based on the findings, N2 gas has been determined to be a highly efficient insulator, outperforming other options. The reason for this is its superior breakdown voltage, which reaches 37.415 kV, surpassing the values of other gas and gas mixtures.
Hadi Mohebalizadeh; Ebrahim Babaei; Mehran Sabahi; Leila Mohammadian
Abstract
A double-coupled isolated inductor-based high step-down DC-DC converter is proposed in this work. This converter employs two windings on the secondary section of every coupled coil within a single core which enhances the utilization factor of the core. As the primary section voltage of the second coil ...
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A double-coupled isolated inductor-based high step-down DC-DC converter is proposed in this work. This converter employs two windings on the secondary section of every coupled coil within a single core which enhances the utilization factor of the core. As the primary section voltage of the second coil is reduced, the leakage inductance and turn ratio are minimized. A simple gate pulse control is employed to generate 180o phase shift between two switches. The active clamped method is adopted to reduce voltage spikes and return the energy of leakage impedance. This topology is applicable in low-voltage applications. Using a coupled coil with a midpoint doubles the output current ripple frequency, which minimizes the output filter volume and size. The paper includes information of the operating modes of the converter and the topology's designing parameters. Additionally, simulation results are provided to verify the performance of the proposed topology in 250 W.
Adel Akbarimajd; Amir Mohammadhoseini Heiran
Abstract
Jet engines consume a lot of power at start time which makes necessary to use a ground power supply unit (GPU). The GPU must provide the aircraft's demanded power at the start point only. One of the most important factors in supplying the required power for jet engines is to provide the necessary ...
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Jet engines consume a lot of power at start time which makes necessary to use a ground power supply unit (GPU). The GPU must provide the aircraft's demanded power at the start point only. One of the most important factors in supplying the required power for jet engines is to provide the necessary quality for the transmission of electricity to the aircraft. There are a lot of standards to check the quality of the starter among them MIL-STD-704 military standard is one of the most frequently used ones. This standard governs two principles of the power quality and transmitted power to flying vehicle. A GPU system is designed and implemented in this paper to meet the requirements of MIL-STD-704.
This paper proposes a new approach to implement a starter system for turbo-shaft engines. Transformer tap changer mechanism is used to voltage control and parameters of transformer are also optimized using Maxwell software to reduce losses. The power quality value is achieved based on an adaptive smart filtering system implemented at the output terminal of the starter system. This smart filter is designed to be controlled based on SVM machine learning scheme. Experimental results are provided to illustrate the successful and high-quality supply of power needed to start a helicopter.
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