Pub Date : 2023-02-10DOI: 10.1109/PIECON56912.2023.10085808
Prabhash Kumar Sonwani, Manini Swarnkar, Gurpinder Singh, Amit Soni, A. Swarnkar, K. R. Niazi
Non-Intrusive load monitoring (NILM) is an emerging technology for extracting potent information from a consumer’s electric load profile. The NILM techniques are gaining popularity among researchers as they reduce the requirement for external hardware for load monitoring. These techniques require only the smart meter’s data, thus reducing the need for other measuring and sensing devices. In this paper, the research status of non-intrusive load monitoring has been reviewed. The utilisation of NILM techniques for event detection, load monitoring and energy disaggregation has been discussed in this paper. Furthermore, the research gap and future aspects are discussed. This paper has a great utility factor for upcoming researchers interested in NILM techniques.
{"title":"A Review on Non-Intrusive Load Monitoring","authors":"Prabhash Kumar Sonwani, Manini Swarnkar, Gurpinder Singh, Amit Soni, A. Swarnkar, K. R. Niazi","doi":"10.1109/PIECON56912.2023.10085808","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085808","url":null,"abstract":"Non-Intrusive load monitoring (NILM) is an emerging technology for extracting potent information from a consumer’s electric load profile. The NILM techniques are gaining popularity among researchers as they reduce the requirement for external hardware for load monitoring. These techniques require only the smart meter’s data, thus reducing the need for other measuring and sensing devices. In this paper, the research status of non-intrusive load monitoring has been reviewed. The utilisation of NILM techniques for event detection, load monitoring and energy disaggregation has been discussed in this paper. Furthermore, the research gap and future aspects are discussed. This paper has a great utility factor for upcoming researchers interested in NILM techniques.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130122284","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 : 2023-02-10DOI: 10.1109/PIECON56912.2023.10085863
B. Sakthisudhursun, S. Muralidharan
Traditional carrier-based Sinusoidal Pulse Width Modulation (SPWM) solutions for multilevel inverters, such as phase shifted and level shifted modulation, cannot be implemented on standard digital controllers as it requires many carrier waves. Single carrier based sinusoidal pulse width modulation is an alternative approach to realize SPWM for multilevel inverters and can be implemented on standard digital controllers. The implementation of single carrier sinusoidal pulse width modulation using a low-cost Arduino microcontroller along with multiplexer is discussed in this work. The experimental setup proposed in this paper is capable to examine the performance of sinusoidal pulse width modulation for any multilevel inverter. The proposed method can be easily extended for any multilevel inverter topology and any level. The hardware results obtained from two different multilevel inverter topologies validates its effectiveness.
{"title":"Low Cost Microcontroller based Experimental Setup to Study Sinusoidal Pulse Width Modulation for Multilevel Inverter","authors":"B. Sakthisudhursun, S. Muralidharan","doi":"10.1109/PIECON56912.2023.10085863","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085863","url":null,"abstract":"Traditional carrier-based Sinusoidal Pulse Width Modulation (SPWM) solutions for multilevel inverters, such as phase shifted and level shifted modulation, cannot be implemented on standard digital controllers as it requires many carrier waves. Single carrier based sinusoidal pulse width modulation is an alternative approach to realize SPWM for multilevel inverters and can be implemented on standard digital controllers. The implementation of single carrier sinusoidal pulse width modulation using a low-cost Arduino microcontroller along with multiplexer is discussed in this work. The experimental setup proposed in this paper is capable to examine the performance of sinusoidal pulse width modulation for any multilevel inverter. The proposed method can be easily extended for any multilevel inverter topology and any level. The hardware results obtained from two different multilevel inverter topologies validates its effectiveness.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115935175","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 : 2023-02-10DOI: 10.1109/PIECON56912.2023.10085723
Munna Khan, Shoaa Akbari, Kashif I. K. Sherwani
Currently, Multi-Input and Multi-Output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) are widely used in most emerging transmission systems. Using MIMO-OFDM technology boosts capacity of a system and improves reliability of transmission. In MIMO-OFDM systems due to time-varying channels, orthogonality between subcarriers is lost, and introduces ICI. There are many attempts in OFDM systems made to mitigate ICI, using different channel and frame structure, but the methods are usually very complex. The MIMO-OFDM technique was originally used in Inter-carrier Interference (ICI) mitigation, however, this technology has proved to be very promising for high-speed wireless data transmissions in the future. Proposed ICI mitigation algorithm is naturally compatible with Time-domain synchronous OFDM this is because of its receiver’s ability to estimate time-varying linear channels lightly. In the simulation with 16QAM and QPSK modulation, the BER and MSE are reduced, especially for Time-Varying Channels in MIMOOFDM, while simultaneously using SUI and ETU channels. In the presented work, BER and MSE are effectively suppressed in the LTI channel.
{"title":"Reduction of Bit Error Rate (BER) and Mean Square Error (MSE) in MIMO-OFDM System Using SUI and ETU Channels","authors":"Munna Khan, Shoaa Akbari, Kashif I. K. Sherwani","doi":"10.1109/PIECON56912.2023.10085723","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085723","url":null,"abstract":"Currently, Multi-Input and Multi-Output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) are widely used in most emerging transmission systems. Using MIMO-OFDM technology boosts capacity of a system and improves reliability of transmission. In MIMO-OFDM systems due to time-varying channels, orthogonality between subcarriers is lost, and introduces ICI. There are many attempts in OFDM systems made to mitigate ICI, using different channel and frame structure, but the methods are usually very complex. The MIMO-OFDM technique was originally used in Inter-carrier Interference (ICI) mitigation, however, this technology has proved to be very promising for high-speed wireless data transmissions in the future. Proposed ICI mitigation algorithm is naturally compatible with Time-domain synchronous OFDM this is because of its receiver’s ability to estimate time-varying linear channels lightly. In the simulation with 16QAM and QPSK modulation, the BER and MSE are reduced, especially for Time-Varying Channels in MIMOOFDM, while simultaneously using SUI and ETU channels. In the presented work, BER and MSE are effectively suppressed in the LTI channel.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131967947","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 : 2023-02-10DOI: 10.1109/PIECON56912.2023.10085781
G. Ahmad, H. Fatima, Shafiullah, M. Haris
Timely prediction of heart disease and its cause is the most challenging issue in medical science. This paper uses various machine learning algorithms such as Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, Naive Bayes, K-Nearest Neighbourhood, and K-fold cross-validation are used to predict heart diseases. The system uses a K-fold cross-validation technique to enhance the accuracies of algorithms. The UCI Kaggle Cleveland heart disease datasets is used to analyse the performance of the models. It is found in the experiment that the training accuracy of K-Nearest Neighbour is 88.52%, and Recall is 93.30%. The Random Forest produced the highest and most comparable Receiver Operating Characteristics Curve accuracy. Moreover, the experimental results of the recommended techniques are compared with previous heart disease prediction studies, and it is found that among the suggested technique, the performance of K-Nearest Neighbour is best. The fundamental goal of this study is to design a novel and distinctive model-creation approach for resolving practical issues.
{"title":"Hybrid Machine Learning Algorithms for Optimal Diagnosis of Heart Disease with Feature Analysis","authors":"G. Ahmad, H. Fatima, Shafiullah, M. Haris","doi":"10.1109/PIECON56912.2023.10085781","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085781","url":null,"abstract":"Timely prediction of heart disease and its cause is the most challenging issue in medical science. This paper uses various machine learning algorithms such as Logistic Regression, Support Vector Machine, Decision Tree, Random Forest, Naive Bayes, K-Nearest Neighbourhood, and K-fold cross-validation are used to predict heart diseases. The system uses a K-fold cross-validation technique to enhance the accuracies of algorithms. The UCI Kaggle Cleveland heart disease datasets is used to analyse the performance of the models. It is found in the experiment that the training accuracy of K-Nearest Neighbour is 88.52%, and Recall is 93.30%. The Random Forest produced the highest and most comparable Receiver Operating Characteristics Curve accuracy. Moreover, the experimental results of the recommended techniques are compared with previous heart disease prediction studies, and it is found that among the suggested technique, the performance of K-Nearest Neighbour is best. The fundamental goal of this study is to design a novel and distinctive model-creation approach for resolving practical issues.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116363233","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 : 2023-02-10DOI: 10.1109/PIECON56912.2023.10085881
Pragati Tripathi, M. A. Ansari, T. Gandhi, Rajat Mehrotra, Chandresh Singh, Apoorva Singh, Sejal Chauhan
Electrocardiogram signal is the utmost crucial parameter for recognition and analysis of cardiovascular disorders. The feature of the ECG signal is removed by the changeable parameter with time by applying some signal processing approach because the graph obtained from analysis is not clear in the case of graphical ECG signal. For analysis purpose a type of WT that is Daubechies wavelet transform is a robust device. In this paper an algorithm for automatic detection of ECG signals the features are extracted and calculated. The data has been occupied from the physio-net.org arrythmia database. For wavelet transform Daubechies wavelet has been used as the scaling functions of this kind of wavelet filter are same to the shape of the ECG. In the primary section, the ECG signal was denoised by excluding the associated higher scale wavelet coefficients. Then in the next section, R wave peaks were diagnosed that have higher dominated amplitude. These diagnosed R peaks were afterwards applied to diagnose the other peaks as P, Q, R.S, T and also the zero-crossing stage. From the distinct peaks, the features of the ECG signal have been extracted. Relying on different features the distinct kinds of disorders are classified.
{"title":"A Robust R Peak Recognition Procedure of a cardiac Signal using Modified Db 20 Wavelet Transform","authors":"Pragati Tripathi, M. A. Ansari, T. Gandhi, Rajat Mehrotra, Chandresh Singh, Apoorva Singh, Sejal Chauhan","doi":"10.1109/PIECON56912.2023.10085881","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085881","url":null,"abstract":"Electrocardiogram signal is the utmost crucial parameter for recognition and analysis of cardiovascular disorders. The feature of the ECG signal is removed by the changeable parameter with time by applying some signal processing approach because the graph obtained from analysis is not clear in the case of graphical ECG signal. For analysis purpose a type of WT that is Daubechies wavelet transform is a robust device. In this paper an algorithm for automatic detection of ECG signals the features are extracted and calculated. The data has been occupied from the physio-net.org arrythmia database. For wavelet transform Daubechies wavelet has been used as the scaling functions of this kind of wavelet filter are same to the shape of the ECG. In the primary section, the ECG signal was denoised by excluding the associated higher scale wavelet coefficients. Then in the next section, R wave peaks were diagnosed that have higher dominated amplitude. These diagnosed R peaks were afterwards applied to diagnose the other peaks as P, Q, R.S, T and also the zero-crossing stage. From the distinct peaks, the features of the ECG signal have been extracted. Relying on different features the distinct kinds of disorders are classified.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123549829","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 : 2023-02-10DOI: 10.1109/PIECON56912.2023.10085799
Kaleeswari Chinnakkaruppan, K. Krishnamoorthy, Senthilrajan Agniraj
The detection of anomalous data from sensor data is the intractable problem in today’s hydrological data monitoring. Hardware malfunctions, power issues, battery life, and efficiency are challenges encountered while employing sensor devices to collect data. In such situations, data that is inconsistent may be recorded. By applying these types of dataset, inaccurate results may be produced when performing classification or other data analytic methods. In order to discover anomalous data from a huge dataset, this paper suggests a hybrid mechanism. Three unsupervised machine learning techniques are used to construct this mechanism. First, this study reduces superfluous data by using Principal Component Analysis (PCA). Isolation Forest (IF) is then used to find outlier scores. Finally, K-means clustering is used to distinguish between abnormal (anomalies) and regular data using a visual representation of cluster assignments. The cluster assessment indices’ criteria were used to evaluate this hybrid approach. According to the findings, this hybrid technique would be suitable for identifying anomalous data inside each data index of the dataset, depending on the target value.
{"title":"A Hybrid Approach for Forecasting the Technical Anomalies in Sensor-based Water Quality Distribution Data","authors":"Kaleeswari Chinnakkaruppan, K. Krishnamoorthy, Senthilrajan Agniraj","doi":"10.1109/PIECON56912.2023.10085799","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085799","url":null,"abstract":"The detection of anomalous data from sensor data is the intractable problem in today’s hydrological data monitoring. Hardware malfunctions, power issues, battery life, and efficiency are challenges encountered while employing sensor devices to collect data. In such situations, data that is inconsistent may be recorded. By applying these types of dataset, inaccurate results may be produced when performing classification or other data analytic methods. In order to discover anomalous data from a huge dataset, this paper suggests a hybrid mechanism. Three unsupervised machine learning techniques are used to construct this mechanism. First, this study reduces superfluous data by using Principal Component Analysis (PCA). Isolation Forest (IF) is then used to find outlier scores. Finally, K-means clustering is used to distinguish between abnormal (anomalies) and regular data using a visual representation of cluster assignments. The cluster assessment indices’ criteria were used to evaluate this hybrid approach. According to the findings, this hybrid technique would be suitable for identifying anomalous data inside each data index of the dataset, depending on the target value.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"21 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123243357","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 : 2023-02-10DOI: 10.1109/PIECON56912.2023.10085827
Babita Faujdar, R. K. Pandey
Electric Vehicle Charging Infrastructure is an essential component in deployment of Electric Vehicles at large scale in the world. The Smart Control Architecture is the backbone for facilitating the EV charging/Battery swapping in real time environment. The massive usage of EV in transportation is only feasible once the charging infrastructure is structured/facilitated intelligently to provide seamless charging in the respective region with upcoming EV penetration. The massive integration of EVs charging point/bay in Distribution System may also result in an unacceptable performance at given point of time in case the power infeed to the charging infrastructure is not properly regulated depending on the vehicle penetration. The paper firstly reviews the concept for Smart Control Architecture for upcoming EV Charging points/bay in each distribution/sub-transmission system and also highlights the requirements of intelligent power control to the respective charging infrastructure for quality and quick charging in order to ensure regulated power control for distribution system sustainability and reliability.
{"title":"Overview of EV Charging Smart Control Architecture-Recent Developments","authors":"Babita Faujdar, R. K. Pandey","doi":"10.1109/PIECON56912.2023.10085827","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085827","url":null,"abstract":"Electric Vehicle Charging Infrastructure is an essential component in deployment of Electric Vehicles at large scale in the world. The Smart Control Architecture is the backbone for facilitating the EV charging/Battery swapping in real time environment. The massive usage of EV in transportation is only feasible once the charging infrastructure is structured/facilitated intelligently to provide seamless charging in the respective region with upcoming EV penetration. The massive integration of EVs charging point/bay in Distribution System may also result in an unacceptable performance at given point of time in case the power infeed to the charging infrastructure is not properly regulated depending on the vehicle penetration. The paper firstly reviews the concept for Smart Control Architecture for upcoming EV Charging points/bay in each distribution/sub-transmission system and also highlights the requirements of intelligent power control to the respective charging infrastructure for quality and quick charging in order to ensure regulated power control for distribution system sustainability and reliability.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128042454","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 : 2023-02-10DOI: 10.1109/PIECON56912.2023.10085756
Tanviruzzama, S. Mehfuz
Lane line detection is given great attention in the study on autonomous driving and driver support systems, which, in the last few years, has become a crucial area in the field of intelligent transportation. Without any human involvement, autonomous vehicles can genuinely assess their surroundings, navigate, and provide transportation for people. The transportation system of the entire world will soon be replaced by autonomous vehicles. In order to accomplish this goal, the automobile industries are now researching in this area to maximize the benefits and address the issues [1]. Image processing is a major aspect of the electronic industry’s automation, protection, and surveillance-related applications. This study examined a detailed literature on autonomous vehicle systems, including various types of image preprocessing techniques, lane detection and tracking techniques, and these techniques are utilized to improve lane edge detection. Along with the Canny edge detection methodology, a cutting-edge method known as the Spiking Neural Network for lane boundary detection is also described in this paper. In order to speed up processing, an on-board camera of a vehicle initially sets the region of interest (ROI) on the original picture. The ROI is next subjected to picture preprocessing, which includes converting RGB to grayscale, stretching the grayscale, and using a median filter to remove noise. Hough transform is employed to identify the lane in this study work. Research findings demonstrate that such a strategy is much more reliable and accurate than alternative approaches.
{"title":"Review: Lane Detection for Autonomous Vehicles Using Image Processing Techniques","authors":"Tanviruzzama, S. Mehfuz","doi":"10.1109/PIECON56912.2023.10085756","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085756","url":null,"abstract":"Lane line detection is given great attention in the study on autonomous driving and driver support systems, which, in the last few years, has become a crucial area in the field of intelligent transportation. Without any human involvement, autonomous vehicles can genuinely assess their surroundings, navigate, and provide transportation for people. The transportation system of the entire world will soon be replaced by autonomous vehicles. In order to accomplish this goal, the automobile industries are now researching in this area to maximize the benefits and address the issues [1]. Image processing is a major aspect of the electronic industry’s automation, protection, and surveillance-related applications. This study examined a detailed literature on autonomous vehicle systems, including various types of image preprocessing techniques, lane detection and tracking techniques, and these techniques are utilized to improve lane edge detection. Along with the Canny edge detection methodology, a cutting-edge method known as the Spiking Neural Network for lane boundary detection is also described in this paper. In order to speed up processing, an on-board camera of a vehicle initially sets the region of interest (ROI) on the original picture. The ROI is next subjected to picture preprocessing, which includes converting RGB to grayscale, stretching the grayscale, and using a median filter to remove noise. Hough transform is employed to identify the lane in this study work. Research findings demonstrate that such a strategy is much more reliable and accurate than alternative approaches.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129272673","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 : 2023-02-10DOI: 10.1109/PIECON56912.2023.10085818
M. Khan, Imdadullah, M. Bilal
Power grids are interconnected for economical operation, reliable power supply, and maintaining power supply under contingencies. The grid interconnection can be realized using AC tie lines and HVDC systems. Like the HVDC link, a variable frequency transformer (VFT) is another option available for grid interconnection. The VFT is considered a better option due to its natural damping capability, considerable overloading limit, and lesser requirement of reactive power compensation. This paper analyzes the VFT system connecting two asynchronous power systems under different unbalanced voltage sag conditions. The system performance under symmetrical voltage sag is analyzed for light voltage sag (10% dip), medium voltage sag (30% dip), and severe voltage sag (80% dip). Moreover, it is also analyzed for asymmetrical voltage sag of Type-C, Type-D, and Type-F. The effect of symmetrical and asymmetrical sags on the sending end current, receiving end current, and real power are discussed in detail. The VFT system under various sag conditions is simulated in PSCAD/EMTDC environment.
{"title":"Effect of Unbalanced Grid Voltage Conditions on The Performance of a Variable Frequency Transformer","authors":"M. Khan, Imdadullah, M. Bilal","doi":"10.1109/PIECON56912.2023.10085818","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085818","url":null,"abstract":"Power grids are interconnected for economical operation, reliable power supply, and maintaining power supply under contingencies. The grid interconnection can be realized using AC tie lines and HVDC systems. Like the HVDC link, a variable frequency transformer (VFT) is another option available for grid interconnection. The VFT is considered a better option due to its natural damping capability, considerable overloading limit, and lesser requirement of reactive power compensation. This paper analyzes the VFT system connecting two asynchronous power systems under different unbalanced voltage sag conditions. The system performance under symmetrical voltage sag is analyzed for light voltage sag (10% dip), medium voltage sag (30% dip), and severe voltage sag (80% dip). Moreover, it is also analyzed for asymmetrical voltage sag of Type-C, Type-D, and Type-F. The effect of symmetrical and asymmetrical sags on the sending end current, receiving end current, and real power are discussed in detail. The VFT system under various sag conditions is simulated in PSCAD/EMTDC environment.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130963587","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 : 2023-02-10DOI: 10.1109/PIECON56912.2023.10085747
S. Prabhu, V. Arun, M. Balaji, V. Kalaimagal, A. Manikandan, V. Chandrasekar
A Internal Permanent Magnet Misc Machine (IPMMM) possesses a cylindrical rotor reduces the torque ripple, enables the performance of a machine. This article evidences in the process of estimation and reduction of heat generation in machine. A 290V, 10 A and 3000 RPM IPMMM is utilized in finite element investigation in the view of instantons and cogging torque. The novelty of this machine is that laminating core based rotor poles arranged with permanent magnet poles on either side. In addition, the outer perimeter of the rotor enclosed by ring like structure. The simulation environment create for estimation of maximum temperature rise in the machine and its distribution. The numerical outcomes are tabulate and analyze with virtualized findings.
{"title":"Analysis on Misc Type Permanent Magnet Synchronous Reluctance Machine for Transportation Systems","authors":"S. Prabhu, V. Arun, M. Balaji, V. Kalaimagal, A. Manikandan, V. Chandrasekar","doi":"10.1109/PIECON56912.2023.10085747","DOIUrl":"https://doi.org/10.1109/PIECON56912.2023.10085747","url":null,"abstract":"A Internal Permanent Magnet Misc Machine (IPMMM) possesses a cylindrical rotor reduces the torque ripple, enables the performance of a machine. This article evidences in the process of estimation and reduction of heat generation in machine. A 290V, 10 A and 3000 RPM IPMMM is utilized in finite element investigation in the view of instantons and cogging torque. The novelty of this machine is that laminating core based rotor poles arranged with permanent magnet poles on either side. In addition, the outer perimeter of the rotor enclosed by ring like structure. The simulation environment create for estimation of maximum temperature rise in the machine and its distribution. The numerical outcomes are tabulate and analyze with virtualized findings.","PeriodicalId":182428,"journal":{"name":"2023 International Conference on Power, Instrumentation, Energy and Control (PIECON)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125533602","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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