Background: This article presents a novel strategy that utilizes the nature-inspired Spotted Hyena Optimizer Algorithm (SHOA) to optimize the placement of solar and wind-based renewable distributed generation (RDG) and distribution static compensators (DSTATCOMs) in radial distribution systems (RDS). Methods: The proposed technique aims to determine the optimal locations of DSTATCOM and RDGs based on the loss sensitivity factor (LSF), while the appropriate sizes are determined using the newly developed SHOA. To facilitate efficient load flow calculations, a fast and effective backward/forward sweep algorithm (BFSA) is employed. Results: The primary objective of this method is to minimize overall power losses within the system. The effectiveness of the optimization approach based on SHOA is demonstrated through extensive simulations conducted on a standard IEEE 33-bus test system with diverse load models. Conclusion: The results of the simulations and comparisons of multiple case studies clearly indicate that the allocation of DSTATCOMs leads to significant reductions in power losses and improvements in voltage profiles.
{"title":"Solar and Wind-based Renewable DGs and DSTATCOM Allotment in Distribution System with Consideration of Various Load Models Using Spotted Hyena Optimizer Algorithm","authors":"Yuvaraj T., Suresh T.D., Joly M., Balamurugan P., N.V. Phanendra Babu","doi":"10.2174/0123520965267223231030194325","DOIUrl":"https://doi.org/10.2174/0123520965267223231030194325","url":null,"abstract":"Background: This article presents a novel strategy that utilizes the nature-inspired Spotted Hyena Optimizer Algorithm (SHOA) to optimize the placement of solar and wind-based renewable distributed generation (RDG) and distribution static compensators (DSTATCOMs) in radial distribution systems (RDS). Methods: The proposed technique aims to determine the optimal locations of DSTATCOM and RDGs based on the loss sensitivity factor (LSF), while the appropriate sizes are determined using the newly developed SHOA. To facilitate efficient load flow calculations, a fast and effective backward/forward sweep algorithm (BFSA) is employed. Results: The primary objective of this method is to minimize overall power losses within the system. The effectiveness of the optimization approach based on SHOA is demonstrated through extensive simulations conducted on a standard IEEE 33-bus test system with diverse load models. Conclusion: The results of the simulations and comparisons of multiple case studies clearly indicate that the allocation of DSTATCOMs leads to significant reductions in power losses and improvements in voltage profiles.","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":" 36","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135187934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-08DOI: 10.2174/0123520965263412231031060225
Srinivasan P., Heeravathi S., Jay Prasanna M., Sreedharsh R. Pillai, Dhanush M.
Abstract:: MPPT refers to the process of continuously tracking and adjusting the operating point of a photovoltaic (PV) system to maximize the power output from the solar panels. The operating point at which a PV system produces the most power under a specific set of environmental circumstances is known as the maximum power point (MPP). The Maximum power point tracking (MPPT) technique is used to overcome the challenges of PV arrays with variable irradiance levels, which collects the greatest power from the PV array. Standalone PV systems, as well as gridconnected systems, can benefit from a DC-DC converter with MPPT. This study compares the standard perturbation and observation (P&O) technique with the soft-switching method used in the SEPIC converter utilizing the cuckoo search (CS) algorithm using MATLAB/Simulink. Reviewing the simulation results and assessing the SEPIC converter's performance. Background:: SEPIC soft-switching converter, the soft-switching technique is applied to the SEPIC converter topology. It typically uses additional components, such as inductor and capacitors, to enable soft-switching operation. These additional components help to control the voltage and current waveforms across the main switching devices, reducing switching losses. Methods:: The proposed method uses a soft switching technique to reduce switching losses and to improve efficiency. Soft switching is used in SEPIC (Single Ended Primary Inductor Converter) converters, a type of DC-DC converter, to enhance their performance. The projected solution further addresses the maximum power point tracking (MPPT) issue in PV systems using the Cuckoo Search (CS) method. Results:: Soft switching technique is implemented in SEPIC converters to reduce these switching losses. In this system, Zero Voltage Switching (ZVS) involves turning on the switch when the voltage across it is zero. This allows the current to flow through the switch without creating any significant switching losses. CS algorithm can track the MPP quickly and accurately, it exhibits less prone to oscillations, easily monitor the MPP under a variety of weather circumstances. However, it exhibits negligible oscillation in a steady state, which results in significant power savings. Conclusion:: The modified SEPIC converter with a soft-switching MPPT cuckoo algorithm is used with a solar-powered system. A prototype comprising a solar panel, a SEPIC converter, a driver, and a controller circuit was created. A soft-switching SEPIC converter with an MPPT cuckoo algorithm for the PV system is implemented, as are the converter operation, converter analysis, and theoretical analysis, and a controller circuit is analysed. The PV system, MPPT controller with tracking algorithm, and PMSM load were used in the system simulation. A 60-watt SEPIC converter prototype is built, and the outcomes are also tested experimentally.
摘要:MPPT是指对光伏发电系统的工作点进行连续跟踪和调整，使太阳能电池板输出功率最大化的过程。在特定的环境条件下，光伏系统产生最大功率的工作点称为最大功率点(MPP)。最大功率点跟踪(MPPT)技术用于克服可变辐照度光伏阵列的挑战，该技术从光伏阵列收集最大的功率。独立光伏系统以及并网系统都可以从带有MPPT的DC-DC转换器中受益。本研究使用MATLAB/Simulink将标准扰动和观测(P&O)技术与SEPIC变换器中使用的基于布谷鸟搜索(CS)算法的软开关方法进行了比较。回顾仿真结果，评估SEPIC变换器的性能。背景:SEPIC软开关变换器，将软开关技术应用到SEPIC变换器的拓扑结构中。它通常使用额外的组件，如电感和电容器，以实现软开关操作。这些附加元件有助于控制主开关器件的电压和电流波形，减少开关损耗。方法:采用软开关技术，降低开关损耗，提高效率。SEPIC (Single end Primary Inductor Converter，单端初级电感转换器)变换器是一种DC-DC变换器，采用软开关技术可以提高变换器的性能。该方案使用布谷鸟搜索(CS)方法进一步解决了光伏系统中的最大功率点跟踪(MPPT)问题。结果:在SEPIC变换器中实现了软开关技术，减少了这些开关损耗。在这个系统中，零电压开关(ZVS)涉及到当开关上的电压为零时打开开关。这允许电流流过开关而不产生任何显著的开关损耗。CS算法可以快速准确地跟踪MPP，振荡较小，便于在各种天气情况下监测MPP。然而，它在稳定状态下表现出可忽略不计的振荡，从而显著节省功率。结论:采用软开关MPPT布谷鸟算法的改进SEPIC变换器可用于太阳能供电系统。一个原型包括太阳能电池板、SEPIC转换器、驱动器和控制器电路。实现了一种基于MPPT布谷鸟算法的光伏系统软开关SEPIC变换器，对变换器进行了工作、分析和理论分析，并对控制电路进行了分析。系统仿真采用了光伏系统、带跟踪算法的MPPT控制器和永磁同步电机负载。建立了60瓦SEPIC变换器样机，并对结果进行了实验验证。
{"title":"Soft Switching Technique in a Modified SEPIC Converter with MPPT using Cuckoo Search Algorithm","authors":"Srinivasan P., Heeravathi S., Jay Prasanna M., Sreedharsh R. Pillai, Dhanush M.","doi":"10.2174/0123520965263412231031060225","DOIUrl":"https://doi.org/10.2174/0123520965263412231031060225","url":null,"abstract":"Abstract:: MPPT refers to the process of continuously tracking and adjusting the operating point of a photovoltaic (PV) system to maximize the power output from the solar panels. The operating point at which a PV system produces the most power under a specific set of environmental circumstances is known as the maximum power point (MPP). The Maximum power point tracking (MPPT) technique is used to overcome the challenges of PV arrays with variable irradiance levels, which collects the greatest power from the PV array. Standalone PV systems, as well as gridconnected systems, can benefit from a DC-DC converter with MPPT. This study compares the standard perturbation and observation (P&O) technique with the soft-switching method used in the SEPIC converter utilizing the cuckoo search (CS) algorithm using MATLAB/Simulink. Reviewing the simulation results and assessing the SEPIC converter's performance. Background:: SEPIC soft-switching converter, the soft-switching technique is applied to the SEPIC converter topology. It typically uses additional components, such as inductor and capacitors, to enable soft-switching operation. These additional components help to control the voltage and current waveforms across the main switching devices, reducing switching losses. Methods:: The proposed method uses a soft switching technique to reduce switching losses and to improve efficiency. Soft switching is used in SEPIC (Single Ended Primary Inductor Converter) converters, a type of DC-DC converter, to enhance their performance. The projected solution further addresses the maximum power point tracking (MPPT) issue in PV systems using the Cuckoo Search (CS) method. Results:: Soft switching technique is implemented in SEPIC converters to reduce these switching losses. In this system, Zero Voltage Switching (ZVS) involves turning on the switch when the voltage across it is zero. This allows the current to flow through the switch without creating any significant switching losses. CS algorithm can track the MPP quickly and accurately, it exhibits less prone to oscillations, easily monitor the MPP under a variety of weather circumstances. However, it exhibits negligible oscillation in a steady state, which results in significant power savings. Conclusion:: The modified SEPIC converter with a soft-switching MPPT cuckoo algorithm is used with a solar-powered system. A prototype comprising a solar panel, a SEPIC converter, a driver, and a controller circuit was created. A soft-switching SEPIC converter with an MPPT cuckoo algorithm for the PV system is implemented, as are the converter operation, converter analysis, and theoretical analysis, and a controller circuit is analysed. The PV system, MPPT controller with tracking algorithm, and PMSM load were used in the system simulation. A 60-watt SEPIC converter prototype is built, and the outcomes are also tested experimentally.","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"18 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135430320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-08DOI: 10.2174/0123520965266074231005053838
Asif S, Kartheeban Kamatchi
Aim and background:: Congestion on China's roads has worsened in recent years due to the country's rapid economic development, rising urban population, rising private car ownership, inequitable traffic flow distribution, and growing local congestion. As cities expand, traffic congestion has become an unavoidable nuisance that endangers the safety and progress of its residents. Improving the utilization rate of municipal transportation facilities and relieving traffic congestion depend on a thorough and accurate identification of the current state of road traffic and necessitate anticipating road congestion in the city. Methodology:: In this research, we suggest using a deep spatial and temporal graph convolutional network (DSGCN) to forecast the current state of traffic congestion. To begin, we grid out the transportation system to create individual regions for analysis. In this work, we abstract the grid region centers as nodes, and we use an adjacency matrix to signify the dynamic correlations between the nodes. Results and Discussion:: The spatial correlation between regions is then captured utilizing a Graph Convolutional-Neural-Network (GCNN), while the temporal correlation is captured using a two-layer long and short-term feature model (DSTM). Conclusion:: Finally, testing on real PeMS datasets shows that the DSGCN has superior performance than other baseline models and provides more accurate traffic congestion prediction.
{"title":"An Adaptive Framework for Traffic Congestion Prediction Using Deep Learning","authors":"Asif S, Kartheeban Kamatchi","doi":"10.2174/0123520965266074231005053838","DOIUrl":"https://doi.org/10.2174/0123520965266074231005053838","url":null,"abstract":"Aim and background:: Congestion on China's roads has worsened in recent years due to the country's rapid economic development, rising urban population, rising private car ownership, inequitable traffic flow distribution, and growing local congestion. As cities expand, traffic congestion has become an unavoidable nuisance that endangers the safety and progress of its residents. Improving the utilization rate of municipal transportation facilities and relieving traffic congestion depend on a thorough and accurate identification of the current state of road traffic and necessitate anticipating road congestion in the city. Methodology:: In this research, we suggest using a deep spatial and temporal graph convolutional network (DSGCN) to forecast the current state of traffic congestion. To begin, we grid out the transportation system to create individual regions for analysis. In this work, we abstract the grid region centers as nodes, and we use an adjacency matrix to signify the dynamic correlations between the nodes. Results and Discussion:: The spatial correlation between regions is then captured utilizing a Graph Convolutional-Neural-Network (GCNN), while the temporal correlation is captured using a two-layer long and short-term feature model (DSTM). Conclusion:: Finally, testing on real PeMS datasets shows that the DSGCN has superior performance than other baseline models and provides more accurate traffic congestion prediction.","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"22 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135430742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-06DOI: 10.2174/0123520965263887231026071657
Prabaakaran K., Thilagar K.V., Venkatesh M., Sudharsan S., Sethuraman A., Barath Chander B.
Introduction: The roots of virtual reality (VR) go back to the work of Ivan Sutherland in the 1960s. At the time, virtual reality showed promise in universities and labs, peaking in the early 1990s at a stable level. The latest form of IoT is merging with the Internet of Everything (IOE). Using this technology, users can access any device, device, and machine in the environment through any middleware application or system. In recent years, smart speakers have become a common commercial method for controlling household appliances, solving some of the problems of remote control. For example, speech recognition is difficult in noisy environments and is minimized using noise cancellation. It also takes a long time to determine the current state of the device as the user need to request or issue a command to the smart speaker and need to wait for a response. The evaluation of prototype system found, using a device with gestures and interacting with a virtual 3D device instead of a real device was acceptable in terms of usability. In this article, the Unity and Vuforia are used to create an AR-based IoT virtual switch that can control any device connected to a LAN controller via HTTP requests. Methods: The system is made experimental with the Augmented Reality (AR), the virtual communication system is designed instead of physical mode. It provide the real time based image for active control of Energy management. It consist of virtual switches, it supports the AR based power control system. Results: The proposed system are made evaluated and tested under various load conditions. The virtual image consist of virtual switches to make real time control of power equipment. The proposed system achieve the latency of about 0.06 sec. Conclusion: The advancement in day today activities required with AR based energy management system with proper control measures. The designed system is supportive for such mechanism. The further system is proposed to make more energy saving concept for enhancement in proposed work.
{"title":"Augmented Reality Control Based Energy Management System for Residence","authors":"Prabaakaran K., Thilagar K.V., Venkatesh M., Sudharsan S., Sethuraman A., Barath Chander B.","doi":"10.2174/0123520965263887231026071657","DOIUrl":"https://doi.org/10.2174/0123520965263887231026071657","url":null,"abstract":"Introduction: The roots of virtual reality (VR) go back to the work of Ivan Sutherland in the 1960s. At the time, virtual reality showed promise in universities and labs, peaking in the early 1990s at a stable level. The latest form of IoT is merging with the Internet of Everything (IOE). Using this technology, users can access any device, device, and machine in the environment through any middleware application or system. In recent years, smart speakers have become a common commercial method for controlling household appliances, solving some of the problems of remote control. For example, speech recognition is difficult in noisy environments and is minimized using noise cancellation. It also takes a long time to determine the current state of the device as the user need to request or issue a command to the smart speaker and need to wait for a response. The evaluation of prototype system found, using a device with gestures and interacting with a virtual 3D device instead of a real device was acceptable in terms of usability. In this article, the Unity and Vuforia are used to create an AR-based IoT virtual switch that can control any device connected to a LAN controller via HTTP requests. Methods: The system is made experimental with the Augmented Reality (AR), the virtual communication system is designed instead of physical mode. It provide the real time based image for active control of Energy management. It consist of virtual switches, it supports the AR based power control system. Results: The proposed system are made evaluated and tested under various load conditions. The virtual image consist of virtual switches to make real time control of power equipment. The proposed system achieve the latency of about 0.06 sec. Conclusion: The advancement in day today activities required with AR based energy management system with proper control measures. The designed system is supportive for such mechanism. The further system is proposed to make more energy saving concept for enhancement in proposed work.","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135724138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-01DOI: 10.2174/0123520965267477231018114250
Yuvaraj T, Suresh T D, Selvi S, Balamurugan P
Background:: The utilization of electric vehicles (EVs) is on the rise, which has led to significant challenges for the radial distribution system (RDS). This research aimed to investigate the impact of electric vehicle charging stations (EVCS) on power loss, voltage stability, and reliability within the RDS. Solar-based renewable distributed generation (SRDG) offers a range of benefits in mitigating the impact of EVCS on the distribution system. To simulate the integration of EV charging loads and assess their effects on the RDS, the study has employed the widely used IEEE 69-bus system as a test platform. Methods:: A novel approach utilizing the cuckoo search algorithm (CSA) is presented in this article to determine the optimal locations for EVCS and SRDG. Results:: The study has examined the potential power losses resulting from additional EV loads and explored strategies to optimize charging rates and minimize resistive losses. Voltage stability has been assessed by analyzing the voltage drop caused by high charging loads, and the efficiency of voltage regulation devices and control strategies has been evaluated. Moreover, the paper has discussed the reliability implications of EV charging, including localized overloads and the possibility of outages. Conclusion:: Overall, this research has enhanced our understanding of the challenges associated with integrating EVCS into the RDS and offered potential solutions to address these challenges.
{"title":"Mitigation of the Impact of Incorporating Charging Stations for Electric Vehicles Using Solar-based Renewable DG on the Electrical Distribution System","authors":"Yuvaraj T, Suresh T D, Selvi S, Balamurugan P","doi":"10.2174/0123520965267477231018114250","DOIUrl":"https://doi.org/10.2174/0123520965267477231018114250","url":null,"abstract":"Background:: The utilization of electric vehicles (EVs) is on the rise, which has led to significant challenges for the radial distribution system (RDS). This research aimed to investigate the impact of electric vehicle charging stations (EVCS) on power loss, voltage stability, and reliability within the RDS. Solar-based renewable distributed generation (SRDG) offers a range of benefits in mitigating the impact of EVCS on the distribution system. To simulate the integration of EV charging loads and assess their effects on the RDS, the study has employed the widely used IEEE 69-bus system as a test platform. Methods:: A novel approach utilizing the cuckoo search algorithm (CSA) is presented in this article to determine the optimal locations for EVCS and SRDG. Results:: The study has examined the potential power losses resulting from additional EV loads and explored strategies to optimize charging rates and minimize resistive losses. Voltage stability has been assessed by analyzing the voltage drop caused by high charging loads, and the efficiency of voltage regulation devices and control strategies has been evaluated. Moreover, the paper has discussed the reliability implications of EV charging, including localized overloads and the possibility of outages. Conclusion:: Overall, this research has enhanced our understanding of the challenges associated with integrating EVCS into the RDS and offered potential solutions to address these challenges.","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"154 3-4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135614476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract: The need for low power in portable and smart devices is the demand to be fulfilled for sustaining the semiconductor industry. Static Random Access Memory (SRAM) is the main part of the core design in chips. It is important to reduce the leakage power consumption during the steady mode of the device for the long run of the battery. This article is about the study of different modules using pre-existing low power. Application of different methods other than lowering the supply voltage leads to an increment in the number of transistors in conventional 6T (six transistor) SRAM cells like 7T to 14T. Power gating and the Multi-threshold complementary metal oxide semiconductor (MTCMOS) technique is the most relevant method. Hybrid low power techniques are in high demand because it shows better results than using individual techniques. However, the biggest challenge is to maintain the area and delay as well. FinFET came into the scenario to overcome the leakage power and short channel effect due to scaling in CMOS. Comparative study analysis shows that FinFET decreases the overall power and delay even when the number of transistors increases. A comparison was done between 6T, 8T, and 10T using FinFET and CMOS in a paper, and concluded that FinFET shows 77.792% improved write power.
{"title":"Comprehensive Study of Low-Power SRAM Design Topologies","authors":"Anandita Srivastava, Shailendra Kumar Tripathi, Usha Tiwari, Sushanta Kumar Mandal","doi":"10.2174/0123520965275861231027060817","DOIUrl":"https://doi.org/10.2174/0123520965275861231027060817","url":null,"abstract":"Abstract: The need for low power in portable and smart devices is the demand to be fulfilled for sustaining the semiconductor industry. Static Random Access Memory (SRAM) is the main part of the core design in chips. It is important to reduce the leakage power consumption during the steady mode of the device for the long run of the battery. This article is about the study of different modules using pre-existing low power. Application of different methods other than lowering the supply voltage leads to an increment in the number of transistors in conventional 6T (six transistor) SRAM cells like 7T to 14T. Power gating and the Multi-threshold complementary metal oxide semiconductor (MTCMOS) technique is the most relevant method. Hybrid low power techniques are in high demand because it shows better results than using individual techniques. However, the biggest challenge is to maintain the area and delay as well. FinFET came into the scenario to overcome the leakage power and short channel effect due to scaling in CMOS. Comparative study analysis shows that FinFET decreases the overall power and delay even when the number of transistors increases. A comparison was done between 6T, 8T, and 10T using FinFET and CMOS in a paper, and concluded that FinFET shows 77.792% improved write power.","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"251 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135977597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-30DOI: 10.2174/0123520965265547231019111330
xiaodong zheng, Bao guo Yu, Feng Yang, Junwei Lv
Background:: It gives out the design and verification of single-layer dual-band antenna unit and multi-layer dual-band broadband antenna unit of phased array antenna, and verifies that the multi-layer dualband broadband antenna unit can meet the design requirements of the receiving frequency band. Objective:: It gives out the the design and implementation of a wide-band circularly polarized conformal antenna, and presents the characteristics analysis of the antenna. Method:: Through related simulation methods, the proposed methods are verified and they can effectively solve the array phase compensation and beam shaping and control in the wide-band circularly polarized conformal antenna. Results:: Based on the basic design of the antenna, the active superposition algorithm, phase compensation technology and particle swarm optimization antenna beam shaping technology are both studied. Conclusion:: The proposed wide-band circularly polarized conformal antenna can be used in the actual application.
{"title":"The Design and Implementation of a Wide-band Circularly Polarized Conformal Antenna","authors":"xiaodong zheng, Bao guo Yu, Feng Yang, Junwei Lv","doi":"10.2174/0123520965265547231019111330","DOIUrl":"https://doi.org/10.2174/0123520965265547231019111330","url":null,"abstract":"Background:: It gives out the design and verification of single-layer dual-band antenna unit and multi-layer dual-band broadband antenna unit of phased array antenna, and verifies that the multi-layer dualband broadband antenna unit can meet the design requirements of the receiving frequency band. Objective:: It gives out the the design and implementation of a wide-band circularly polarized conformal antenna, and presents the characteristics analysis of the antenna. Method:: Through related simulation methods, the proposed methods are verified and they can effectively solve the array phase compensation and beam shaping and control in the wide-band circularly polarized conformal antenna. Results:: Based on the basic design of the antenna, the active superposition algorithm, phase compensation technology and particle swarm optimization antenna beam shaping technology are both studied. Conclusion:: The proposed wide-band circularly polarized conformal antenna can be used in the actual application.","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"30 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136132363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-20DOI: 10.2174/0123520965255860231012020315
Santosh Shakya, Priyanka Tripathi
Abstract: The goal of the distributed computing paradigm known as "cloud computing," which necessitates a large number of resources and demands, is to share the resources as services delivered over the internet. Task scheduling is a very significant stage in today's cloud computing. While lowering the makespan and cost, the task scheduling method must schedule the tasks to the virtual machines. Various academics have proposed many scheduling methods for organizing work in cloud computing environments. Scheduling has been considered the most important for cloud computing since it might directly impact a system's performance, including the efficiency of resource utilization and running costs. This paper has compared all the already used algorithms that work on different parameters. We have tried to give better solutions for resource allocation and resource scheduling. In this study, various swarm optimization, evolutionary, physical, evolving, and fusion meta-heuristic scheduling methods are categorized according to the environment of the scheduling problem, the main scheduling goal, the task-resource mapping pattern, and the scheduling constraint. More specifically, the fundamental concepts of cloud task scheduling are addressed without difficulty.
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Pub Date : 2023-10-19DOI: 10.2174/0123520965261228231008183353
Mohamed M. Abdelaziz, Soliman M. Sharaf, Helmy M. El Zoghby
Background: Due to the partial shading effects on different photovoltaic (PV) modules in a PV array, PV module operating conditions are inconsistent, and PV array output power is significantly reduced. Although the maximum power point (MPP) of a non-uniform irradiance PV array can be observed through global maximum power point tracking (GMPPT), no evaluation of the array's energy potential has been done. Objective: One of the most effective solutions to overcome the negative effects of partial shading in PV systems is the PV array reconfiguration process. To optimize the electrical structure of the PV array as the PV modules are partially shaded in a non-uniform manner, this study proposes a promising technique for dynamic reconfiguring a PV array in order to improve the extracted maximum power from a PV array under partial shading conditions (PSC). Method: PV modules are rearranged by iteratively sorting them to allow the PV array with nonuniform irradiance to produce as much power as possible. This is conducted by applying a switching matrix to implement a PV-switched system approach. The proposed system with different PV array dimensions (e.g., 3×4, 4×6, and 5×8) is assessed in order to validate the proposed algorithm. A MATLAB/Simulink PV array developed model is used to find the global maximum power point for the different PV array dimensions in both pre-reconfiguration and post-reconfiguration states. Results: A detailed numerical comparison of the extracted power from the proposed system has been provided. Conclusion: The results show that the proposed system has the potential to extract the exact global maximum power for a PV-switched system under PSC, irrespective of array dimensions, according to simulation results.
{"title":"PV Array Reconfiguration for Global Maximum Power Optimizing Under Partial Shading Conditions Based on PV Switched System","authors":"Mohamed M. Abdelaziz, Soliman M. Sharaf, Helmy M. El Zoghby","doi":"10.2174/0123520965261228231008183353","DOIUrl":"https://doi.org/10.2174/0123520965261228231008183353","url":null,"abstract":"Background: Due to the partial shading effects on different photovoltaic (PV) modules in a PV array, PV module operating conditions are inconsistent, and PV array output power is significantly reduced. Although the maximum power point (MPP) of a non-uniform irradiance PV array can be observed through global maximum power point tracking (GMPPT), no evaluation of the array's energy potential has been done. Objective: One of the most effective solutions to overcome the negative effects of partial shading in PV systems is the PV array reconfiguration process. To optimize the electrical structure of the PV array as the PV modules are partially shaded in a non-uniform manner, this study proposes a promising technique for dynamic reconfiguring a PV array in order to improve the extracted maximum power from a PV array under partial shading conditions (PSC). Method: PV modules are rearranged by iteratively sorting them to allow the PV array with nonuniform irradiance to produce as much power as possible. This is conducted by applying a switching matrix to implement a PV-switched system approach. The proposed system with different PV array dimensions (e.g., 3×4, 4×6, and 5×8) is assessed in order to validate the proposed algorithm. A MATLAB/Simulink PV array developed model is used to find the global maximum power point for the different PV array dimensions in both pre-reconfiguration and post-reconfiguration states. Results: A detailed numerical comparison of the extracted power from the proposed system has been provided. Conclusion: The results show that the proposed system has the potential to extract the exact global maximum power for a PV-switched system under PSC, irrespective of array dimensions, according to simulation results.","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135778331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-18DOI: 10.2174/0123520965258879231011182850
Muthu Eshwaran Ramachandran, None Ramya R, Gurukarthik Babu Balachandran, None Devie P M, Prince Winston D, None Meenakshi A, None Nirmala G
Background: Consumption of electricity always varies based on demand. The load cluster pattern aims at categorizing periodical changes over a specific time. Predicting the electric load was the initial goal of this study. Additionally, the outcomes of the load prediction were utilized as data for categorizing electrical loads using a descriptive-analytical method. Objective: The study has dealt with a matching of load-side electric demand with the electric supply. To ensure dependable power-generating stability, it is vital to anticipate and categorize loads. Thus, the research presented here has focused on electrical load forecasting and classification. Methods: Alternative algorithms, including Naive Bayes, decision tree, and support vector machine classifier, were employed to address the cluster pattern. The data used for this research presentation was collected from the D Block of the Kamaraj College of Engineering and Technology, K. Vellakulam, India, every 15 minutes. Multiple unsuitable loaded circumstances were ignored during the pre-processing of the dataset. Additionally, other algorithms, like Naive Bayes, decision tree, and support vector machine, were used to categorize the raw data. The processing of data was done by a feature selection approach. Results: The performance was predicted by comparing the entire machine learning algorithms. Out of the machine learning techniques, an accuracy of 4.2% for Academic Block 4, a precision of 33% for Boys Hostel, a recall score of 4.7% for Academic Block 4, and an F1 score of 5.3% for Academic Block 4, were obtained. Conclusion: In the study, the decision tree algorithm has shown promising performance than the other machine learning techniques used.
{"title":"Energy Monitoring for Renewable Energy System Using Machine Learning Algorithms","authors":"Muthu Eshwaran Ramachandran, None Ramya R, Gurukarthik Babu Balachandran, None Devie P M, Prince Winston D, None Meenakshi A, None Nirmala G","doi":"10.2174/0123520965258879231011182850","DOIUrl":"https://doi.org/10.2174/0123520965258879231011182850","url":null,"abstract":"Background: Consumption of electricity always varies based on demand. The load cluster pattern aims at categorizing periodical changes over a specific time. Predicting the electric load was the initial goal of this study. Additionally, the outcomes of the load prediction were utilized as data for categorizing electrical loads using a descriptive-analytical method. Objective: The study has dealt with a matching of load-side electric demand with the electric supply. To ensure dependable power-generating stability, it is vital to anticipate and categorize loads. Thus, the research presented here has focused on electrical load forecasting and classification. Methods: Alternative algorithms, including Naive Bayes, decision tree, and support vector machine classifier, were employed to address the cluster pattern. The data used for this research presentation was collected from the D Block of the Kamaraj College of Engineering and Technology, K. Vellakulam, India, every 15 minutes. Multiple unsuitable loaded circumstances were ignored during the pre-processing of the dataset. Additionally, other algorithms, like Naive Bayes, decision tree, and support vector machine, were used to categorize the raw data. The processing of data was done by a feature selection approach. Results: The performance was predicted by comparing the entire machine learning algorithms. Out of the machine learning techniques, an accuracy of 4.2% for Academic Block 4, a precision of 33% for Boys Hostel, a recall score of 4.7% for Academic Block 4, and an F1 score of 5.3% for Academic Block 4, were obtained. Conclusion: In the study, the decision tree algorithm has shown promising performance than the other machine learning techniques used.","PeriodicalId":43275,"journal":{"name":"Recent Advances in Electrical & Electronic Engineering","volume":"875 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135889735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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