2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)最新文献

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An Autonomous Internet of Things (IoT) pipeline network for Image acquisition in Agricultural Applications 农业应用中图像采集的自主物联网(IoT)管道网络
Amarjeet Singh, N. Jeebaratnam, U. Sesadri, K. S. Rao, Nellore Manoj Kumar
{"title":"An Autonomous Internet of Things (IoT) pipeline network for Image acquisition in Agricultural Applications","authors":"Amarjeet Singh, N. Jeebaratnam, U. Sesadri, K. S. Rao, Nellore Manoj Kumar","doi":"10.1109/ICAECT54875.2022.9807923","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807923","url":null,"abstract":"Agriculture is considered to be a self-sufficient component of the country's economy. In terms of agricultural output, India is second only to the United States in terms of production. Irrigation, fertiliser, and crop rotation are three of the most significant elements in agricultural production. The usage of the Internet of Things can make crop production predictions and other components that contribute to high yielding crops more accurate and efficient (IoT). In the past, a pipeline for making predictions was created. A solution based on the Internet of Things (IoT) is being developed and designed to address this problem (IoT). When operating in a Wireless Sensor Network (WSN), sensor nodes are required to perform tasks such as observation, data collection, and transaction processing in order to exhaust their energy. Farmers saving time and money by collecting this information on their own is a win-win situation. To make advantage of this network, you must have a wireless sensor network (WSN), which must be capable of transmitting large amounts of data at a low rate while also consuming little power and communicating over short distances.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128228439","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}
引用次数: 0
Optimum Gain Selection of Sliding Mode Control using Grey Wolf Optimization Technique 基于灰狼优化技术的滑模控制最优增益选择
D. C, Ramesh Kumar P, Saghil Abhayadev
{"title":"Optimum Gain Selection of Sliding Mode Control using Grey Wolf Optimization Technique","authors":"D. C, Ramesh Kumar P, Saghil Abhayadev","doi":"10.1109/ICAECT54875.2022.9807875","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807875","url":null,"abstract":"This paper presents a new methodology for the selection of controller gains in sliding mode control. The goal is to create an adaptive gain sliding mode control mechanism that is robust to uncertainty and perturbations without knowing the bounds of the uncertainties (only the boundedness feature is known). In addition, the approach should work with higher-order sliding mode controllers. The proposed method uses Grey Wolf Optimization (GWO), a new evolutionary algorithm that has been proved to outperform existing swarm intelligent optimization algorithms. Optimization characteristics assures that the gain is not overestimated. The effectiveness of the proposed approach is proven in an example using a robotic manipulator.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128078531","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}
引用次数: 0
Comparative analysis of SRF based Shunt Active Filter using Grey Wolf and Eagle Perching Optimization 基于SRF的灰狼和鹰栖优化并联有源滤波器的比较分析
B. Rao, Pushpa Sahu, Rajkumar Jhapte
{"title":"Comparative analysis of SRF based Shunt Active Filter using Grey Wolf and Eagle Perching Optimization","authors":"B. Rao, Pushpa Sahu, Rajkumar Jhapte","doi":"10.1109/ICAECT54875.2022.9807876","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807876","url":null,"abstract":"Power electronic devices play a vital role in manufacturing process, research and development because it provides high efficiency, low cost, rapid operation, and optimal size of the system. In recent years, power electronic devices have become widely employed in a variety of fields. Application of power electronic devices leads to harmonic generations which have a substantial impact on power systems. The main sources of harmonics are nonlinear loads and energy conversion devices such as static converters, choppers, cyclo-converters, battery charging systems and heating elements etc. To reduce harmonics, different kind of filters are introduced, shunt active power filter is one of the most significant and effective filter. In this research the performance of a shunt active power filter based on synchronous reference frame theory is described and it is tuned for significant performance employing Grey Wolf Optimization and Eagle Perching Optimization techniques.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129686372","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}
引用次数: 0
LSTM Based Approach for Timely Detection of Gradual Development of Electrical Fault in Power System 基于LSTM的电力系统逐步发展的电气故障及时检测方法
A. R., T. Rajeev
{"title":"LSTM Based Approach for Timely Detection of Gradual Development of Electrical Fault in Power System","authors":"A. R., T. Rajeev","doi":"10.1109/ICAECT54875.2022.9807893","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807893","url":null,"abstract":"Power system reliability and efficiency are becoming a primary concern with the increase in load and expansion of power grids. Electrical faults in the power system should be detected and cleared immediately due to their critical impact on the reliability and stability of the system. This paper proposes an approach to predict the faults in the power system using machine learning techniques like Long Short-Term Memory (LSTM). The LSTM model is used to predict gradual faults in the system before their actual occurrence. Three-phase measurements of voltages, currents, and active power during faults and normal operating conditions are taken as data inputs to train the models. The robustness of the method is verified by simulating the fault with different parameters. The proposed method can be expanded to the distribution network of the power system. A modified IEEE 9 bus system is modelled in MATLAB/Simulink and is used to get the data for the experiment. The results from the experiment prove the feasibility of using LSTM networks for predicting the faults in the power system.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129841132","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}
引用次数: 1
Automatic Spectrum Sensing Techniques Using Support Vector Machine In Cognitive Radio Network 认知无线电网络中基于支持向量机的自动频谱感知技术
Mustafa Arkwazee, M. Ilyas, Ammar Dawood Jasim
{"title":"Automatic Spectrum Sensing Techniques Using Support Vector Machine In Cognitive Radio Network","authors":"Mustafa Arkwazee, M. Ilyas, Ammar Dawood Jasim","doi":"10.1109/ICAECT54875.2022.9807922","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807922","url":null,"abstract":"Cognitive Radio (CR) network is established for spectrum utilization. This technology allows unlicensed users to share the spectrum with licensed users. In order to perform such a process, the spectrum needs to be periodically scanned in order to find the voids in the white (licensed) spectrum. Automatic spectrum sensing approaches are proposed in this paper. Deep learning classifier namely Neural Network a Multilayer Perceptron (MLP) and machine learning approaches such as Gradient Boosting (GB), Support Vector Machine (SVM), Logistic Regression (L_R), K-nearest Neighbor (KNN) and Bagging algorithm. SVM-based spectrum sensing is outperformed with 94.01 % spectrum sensing accuracy was achieved using this technique.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128751492","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}
引用次数: 1
Single Server Queueing Model with Multiple Working Vacation and with Breakdown 具有多个工作假期和故障的单服务器排队模型
M. Seenivasan, S. Chandiraleka
{"title":"Single Server Queueing Model with Multiple Working Vacation and with Breakdown","authors":"M. Seenivasan, S. Chandiraleka","doi":"10.1109/ICAECT54875.2022.9807852","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807852","url":null,"abstract":"In our model, we discussed about the queueing model where the server takes Multiple Working Vacation and also get breakdown during service. Customer get in to the organization with parameter λ comes off Poisson process. Service time during multiple working vacation epoch, normal service epoch and vacation epoch are all exponentially distribution with parameters μ1, μ2 and γ respectively. If queue length increases during a working vacation epoch, the server goes to normal busy epoch. If there is no arrival the server takes another vacation is called Multiple Working Vacation. When a server can breakdown while providing service with rate α0 and α1 and become unavailable to the customers. After breakdown, it should be repaired with rate ß0 and ß1. This type of model is analyzed by using Matrix Geometric Approach to device probability vectors. From that, we also obtain some performance measurements.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114065033","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}
引用次数: 0
Performance and Comparative Analysis of PI and PID Controller-based Single Phase PWM Inverter Using MATLAB Simulink for Variable Voltage 基于PI控制器和PID控制器的变电压单相PWM逆变器的性能及对比分析
Md. Tahmid Wara Ucchas, Mehrab Mustafiz Nuhas, Md. Toufiquzzaman, Al Jaber Mahmud, Md. Fokhrul Islam
{"title":"Performance and Comparative Analysis of PI and PID Controller-based Single Phase PWM Inverter Using MATLAB Simulink for Variable Voltage","authors":"Md. Tahmid Wara Ucchas, Mehrab Mustafiz Nuhas, Md. Toufiquzzaman, Al Jaber Mahmud, Md. Fokhrul Islam","doi":"10.1109/ICAECT54875.2022.9807857","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807857","url":null,"abstract":"This article examines the performance of a single-phase PWM inverter equipped with a PI and PID controller. The research aims to decrease Total Harmonic Distortion (THD) in case of fixed and variable output voltages. To reduce THD, PI and PID controllers are used, which are tuned using PID tuner and Trial and Error methods, and the THD is measured using the Simulink powergui’s FFT analysis tool. MATLAB Simulink is used for inverter modelling and simulation. For PI controller-based Inverter, the THD is 0.45% for fixed 400V output voltage and it is increased to 50.85% for rapidly changed output voltage. Furthermore, for PID controller-based Inverter, the THD is 0.01% for fixed 400V output voltage and it is increased to 52.41% for rapidly changed output voltage. So, PI controller-based inverter works better for rapidly changing output voltage, but the PID controller-based inverter performs better for fixed output voltage, according to the comparison analysis.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122203918","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}
引用次数: 0
Performance Analysis of PV-Fuel cell hybrid system in small scale DC system 小型直流系统中pv -燃料电池混合系统的性能分析
Snehashis Ghoshal, Sumit Banerjee, Chandan K. Mahato, C. K. Chanda
{"title":"Performance Analysis of PV-Fuel cell hybrid system in small scale DC system","authors":"Snehashis Ghoshal, Sumit Banerjee, Chandan K. Mahato, C. K. Chanda","doi":"10.1109/ICAECT54875.2022.9807960","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807960","url":null,"abstract":"Reduction of greenhouse gases without hampering economic growth has become a matter of great concern in present scenario. Most of the energy extraction techniques extensively depend on fossil fuels and so the researchers are engaged in finding an alternate eco-friendly economic path since last few decades. Although renewable sources are environment-friendly but major challenge with these is lower energy density and costly extraction process. Among several renewable resources, solar PV and fuel cell are two promising way for meeting up energy demand. Photovoltaic system operating under variable weather condition provide a reasonable output if operated at maximum power point. This operating point is the global maxima of the P-V curve operating under dynamic weather conditions. On the other hand, fuel cell also plays a vital role particularly for small scale DC applications. Fuel cell converts chemical energy to electricity unlike IC engine which utilizes combustion causing emission of greenhouse gases. In present study, a hybrid PV-fuel system is developed in MATLAB/Simulink environment and the results are analyzed.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122222476","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}
引用次数: 2
Research on wind power Prediction based on BP neural Network 基于BP神经网络的风电功率预测研究
D. Hu, Zhaoyun Zhang, Hao Zhou
{"title":"Research on wind power Prediction based on BP neural Network","authors":"D. Hu, Zhaoyun Zhang, Hao Zhou","doi":"10.1109/ICAECT54875.2022.9807962","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807962","url":null,"abstract":"Accurate prediction of wind power is beneficial to relieve the peak load of power grid and improve the capacity of power grid to accept wind power. Aiming at the problem of low precision of wind power prediction, this paper proposes an improved BP neural network prediction method, namely, an iterative genetic optimization BP neural network power prediction model with the power one hour in advance and other influencing factors as input. In this paper, wind speed, wind direction, temperature, humidity and air pressure are selected as the input data of the model, as well as the wind power of the previous period which is highly correlated with wind power. Since it is very unlikely that the values of adjacent moments will change before, the power of the first 15 minutes, the last hour and the previous day are selected in this paper. Finally, this paper analyzes and compares the above three situations, and the experiment shows that the model can effectively meet the relevant prediction demand of the power system for the actual short-term power of the wind farm.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123594147","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}
引用次数: 2
Modelling Investigations on Efficiency of Miniaturized Piezoelectric Energy Harvester 小型压电能量采集器效率的建模研究
Satyanarayana Talam, S. L. S. Iswarya Vinjamuri, Siva Keerthi Rayuru Akkala, Padmaja Nirmala Gudipati, Gokul Phala Chandra Lankireddy
{"title":"Modelling Investigations on Efficiency of Miniaturized Piezoelectric Energy Harvester","authors":"Satyanarayana Talam, S. L. S. Iswarya Vinjamuri, Siva Keerthi Rayuru Akkala, Padmaja Nirmala Gudipati, Gokul Phala Chandra Lankireddy","doi":"10.1109/ICAECT54875.2022.9808035","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9808035","url":null,"abstract":"Currently, energy harvesting is an interesting area of research, and the world is looking for green energy as an alternative source. Energy harvesters take advantage of ambient sources including light, heat, and motion. The present investigation focuses on modelling a piezoelectric unimorph cantilever to evaluate the static analysis of the electric potential by optimizing the dimensions, materials (PZT-4, ZnO, and PVDF), and shapes to realize optimized efficiency. The unimorph cantilever was modelled with L-and H-shapes by exploring its electric potential through boundary loads ranging from 10 to 100N and the simulation was performed with and without the steps included. Among all three materials, PVDF material has shown the maximum electric potential than that of other materials under 100N boundary load when steps are inserted compared to without insertion of steps. The maximum electric potential observed for L and H shapes are 14.6mV and 69.4mV respectively. From the analysis of these results, the H-shaped piezoelectric energy harvester with PVDF under a 100N boundary load exhibited the highest conversion efficiency. COMSOL Multiphysics software version 5.2 is used.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126826722","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}
引用次数: 0
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