Pub Date : 2024-01-18DOI: 10.1109/icpc2t60072.2024.10474839
Sameer Kumar Behera, A. Panda, N. Naik, S. Pattnaik, Prerana Mohapatra, Markala Karthik
This article proposes an resilient heterogeneous voltage and current control scheme (RHVCS) for a three-phase grid-tied virtual synchronous generator (GTVSG) system to provide harmonic compensation and consequently improve the system's power quality. The GTVSG system, as mentioned above, incorporates renewable energy-based distributed generation units (REDG) profoundly photovoltaic generators (PVGs) on the source terminal, having dynamic input characteristics. Considering the control aspects for GTVSG, it adopts various current and voltage control methods discussed in the literature. However, the proposed RHVCS implemented in the GTVSG digital controller helps reduce the number of lowpass/band-pass filter involved. Furthermore, the proposed controller uses a phase lock loop (PLL) less strategy which automatically necessitates the identification of the deviation in the GTVSG system frequency from the power control loop. The proposed RHVCS incorporates three different harmonic compensation objectives illustrated in different sections. Additionally, the proposed control strategy minimizes the digital controller's complexity without infringing on the harmonic compensation's performance, which is commendable. Finally, the above controller is implemented in MATLAB/Simulink platform
{"title":"Flexible GTVSG Power Quality Enhancement Using Resilient Heterogeneous Voltage and Current Control","authors":"Sameer Kumar Behera, A. Panda, N. Naik, S. Pattnaik, Prerana Mohapatra, Markala Karthik","doi":"10.1109/icpc2t60072.2024.10474839","DOIUrl":"https://doi.org/10.1109/icpc2t60072.2024.10474839","url":null,"abstract":"This article proposes an resilient heterogeneous voltage and current control scheme (RHVCS) for a three-phase grid-tied virtual synchronous generator (GTVSG) system to provide harmonic compensation and consequently improve the system's power quality. The GTVSG system, as mentioned above, incorporates renewable energy-based distributed generation units (REDG) profoundly photovoltaic generators (PVGs) on the source terminal, having dynamic input characteristics. Considering the control aspects for GTVSG, it adopts various current and voltage control methods discussed in the literature. However, the proposed RHVCS implemented in the GTVSG digital controller helps reduce the number of lowpass/band-pass filter involved. Furthermore, the proposed controller uses a phase lock loop (PLL) less strategy which automatically necessitates the identification of the deviation in the GTVSG system frequency from the power control loop. The proposed RHVCS incorporates three different harmonic compensation objectives illustrated in different sections. Additionally, the proposed control strategy minimizes the digital controller's complexity without infringing on the harmonic compensation's performance, which is commendable. Finally, the above controller is implemented in MATLAB/Simulink platform","PeriodicalId":518382,"journal":{"name":"2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T)","volume":"8 2","pages":"439-444"},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531364","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 : 2024-01-18DOI: 10.1109/ICPC2T60072.2024.10475038
Himanshu Sekhar Sahu, Shashank Kumar, Papul Changmai, S. K. Nayak
This paper describes the MPP determination of a photovoltaic (PV) panel using the explicit equation of current, which is only a function of voltage. Using an approximation of a straight line expression, the explicit equation of current is derived from implicit V-I characteristics. The V-I curves obtained from an implicit expression of current for various panel ratings are used to implement the proposed PV system expression of current. Under various environmental conditions (DEC), the proposed explicit V-I expression is used to directly estimate the MPP of a PV system. Using the MATLAB program, the MPP of the panel at DEC obtained by applying the proposed algorithm is contrasted with various existing techniques. The estimated MPP of a panel using the developed method closely matches the actual MPP values, according to the results. Additionally, there is little (%) error between estimated peak power using the developed method and measured peak power. As a result, a panel's estimated MPP calculated using the developed method is more precise.
{"title":"Peak Power Extraction from a PV System for Various DC and AC Loads","authors":"Himanshu Sekhar Sahu, Shashank Kumar, Papul Changmai, S. K. Nayak","doi":"10.1109/ICPC2T60072.2024.10475038","DOIUrl":"https://doi.org/10.1109/ICPC2T60072.2024.10475038","url":null,"abstract":"This paper describes the MPP determination of a photovoltaic (PV) panel using the explicit equation of current, which is only a function of voltage. Using an approximation of a straight line expression, the explicit equation of current is derived from implicit V-I characteristics. The V-I curves obtained from an implicit expression of current for various panel ratings are used to implement the proposed PV system expression of current. Under various environmental conditions (DEC), the proposed explicit V-I expression is used to directly estimate the MPP of a PV system. Using the MATLAB program, the MPP of the panel at DEC obtained by applying the proposed algorithm is contrasted with various existing techniques. The estimated MPP of a panel using the developed method closely matches the actual MPP values, according to the results. Additionally, there is little (%) error between estimated peak power using the developed method and measured peak power. As a result, a panel's estimated MPP calculated using the developed method is more precise.","PeriodicalId":518382,"journal":{"name":"2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T)","volume":"24 30","pages":"259-264"},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531375","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}
This paper presents a new configuration and analysis to share energy between electric vehicle to vehicle (V2V). The proposed converter uses on-board equipment of the electric vehicle (EV) and an externally connected capacitor. This configuration is capable of transferring energy between EVs with either identical or non-identical battery ratings. Further, it uses only the DC-DC converter components of the on-board equipment. Thus, reduces the number of devices conduction during the V2V power transfer. The operation of the proposed arrangement is validated by using simulation studies and the results are presented for different battery charging conditions.
{"title":"Electric Vehicle to Vehicle (V2V) Power Transfer with On-Board Network and Capacitor-Link","authors":"Mounika Reddimalla, Srinivasan Pradabane, Keshav Dahal","doi":"10.1109/ICPC2T60072.2024.10474760","DOIUrl":"https://doi.org/10.1109/ICPC2T60072.2024.10474760","url":null,"abstract":"This paper presents a new configuration and analysis to share energy between electric vehicle to vehicle (V2V). The proposed converter uses on-board equipment of the electric vehicle (EV) and an externally connected capacitor. This configuration is capable of transferring energy between EVs with either identical or non-identical battery ratings. Further, it uses only the DC-DC converter components of the on-board equipment. Thus, reduces the number of devices conduction during the V2V power transfer. The operation of the proposed arrangement is validated by using simulation studies and the results are presented for different battery charging conditions.","PeriodicalId":518382,"journal":{"name":"2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T)","volume":"22 21","pages":"565-568"},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531383","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 : 2024-01-18DOI: 10.1109/icpc2t60072.2024.10474764
A.Subramaniya Siva, S.G. Rameshkumar, K. Dhayalini
Supraharmonic analysis, as applied to power systems through Welch's Power Spectral Density Estimation, emerges as a crucial technique for assessing the stability and reliability of electrical grids. This paper offers a novel approach to investigate the non-standard frequency components and disturbances that can affect power distribution networks. By breaking down the electrical signals into supraharmonic components, this method enables a deep understanding of complex power system behaviors and the sources of instability. Welch's Power Spectral Density Estimation plays a pivotal role in this process, allowing for a detailed examination of the spectral content of power system signals. The extraction of supraharmonic information facilitates the identification of irregularities and anomalies, which are often elusive when analyzing traditional harmonic frequencies. The use of various window functions enhances the precision of Supraharmonic Analysis, allowing for a finely tuned investigation of power system behaviors and disturbances. Different window functions offer flexibility in capturing specific characteristics within the signals, making it easier to identify and isolate irregularities and anomalies. Among triangular,hanning, and hamming windows, reduced spectral leakage and smoother power spectral density are achieved from the hamming window. Also, the comparative analysis of harmonics and supraharmonics by Welch's Power Spectral Density estimation has been performed.
{"title":"Supraharmonic Analysis by Welch's-Power Spectral Density Estimation","authors":"A.Subramaniya Siva, S.G. Rameshkumar, K. Dhayalini","doi":"10.1109/icpc2t60072.2024.10474764","DOIUrl":"https://doi.org/10.1109/icpc2t60072.2024.10474764","url":null,"abstract":"Supraharmonic analysis, as applied to power systems through Welch's Power Spectral Density Estimation, emerges as a crucial technique for assessing the stability and reliability of electrical grids. This paper offers a novel approach to investigate the non-standard frequency components and disturbances that can affect power distribution networks. By breaking down the electrical signals into supraharmonic components, this method enables a deep understanding of complex power system behaviors and the sources of instability. Welch's Power Spectral Density Estimation plays a pivotal role in this process, allowing for a detailed examination of the spectral content of power system signals. The extraction of supraharmonic information facilitates the identification of irregularities and anomalies, which are often elusive when analyzing traditional harmonic frequencies. The use of various window functions enhances the precision of Supraharmonic Analysis, allowing for a finely tuned investigation of power system behaviors and disturbances. Different window functions offer flexibility in capturing specific characteristics within the signals, making it easier to identify and isolate irregularities and anomalies. Among triangular,hanning, and hamming windows, reduced spectral leakage and smoother power spectral density are achieved from the hamming window. Also, the comparative analysis of harmonics and supraharmonics by Welch's Power Spectral Density estimation has been performed.","PeriodicalId":518382,"journal":{"name":"2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T)","volume":"22 6","pages":"357-362"},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531385","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 : 2024-01-18DOI: 10.1109/ICPC2T60072.2024.10475008
Rahila Parveen, P. Dewangan, S. Sinha, V. P. Singh
The presented research article is providing the approximation of mathematically modelled higher order wind turbine generator (HOWTG) system. The modelling of eighth order WTG system is formulated by utilizing system parameters value, primarily. Then, the eighth order HOWTG is approximated to comparatively lower order (LO) WTG model. The approximation of HOWTG is done with the help of direct truncation (DT) approximation approach. The truncated second, third, fourth, fifth, sixth, and seventh order LOWTG models are proposed for HOWTG system. To determine the best suited LOWTG model for HOWTG system, the obtained results are supported by findings and discussion in the terms of plots and tabulated data. The step response, error plot, and Bode plot are provided to highlight the compatibility of approximated LOWTG model with respect to HOWTG system. The approximated models are also compared with respect to HOWTG by considering time domain specifications and error index values in this contribution.
{"title":"Approximation of Grid Connected Higher Order Wind Turbine Generator System Employing Direct Truncation","authors":"Rahila Parveen, P. Dewangan, S. Sinha, V. P. Singh","doi":"10.1109/ICPC2T60072.2024.10475008","DOIUrl":"https://doi.org/10.1109/ICPC2T60072.2024.10475008","url":null,"abstract":"The presented research article is providing the approximation of mathematically modelled higher order wind turbine generator (HOWTG) system. The modelling of eighth order WTG system is formulated by utilizing system parameters value, primarily. Then, the eighth order HOWTG is approximated to comparatively lower order (LO) WTG model. The approximation of HOWTG is done with the help of direct truncation (DT) approximation approach. The truncated second, third, fourth, fifth, sixth, and seventh order LOWTG models are proposed for HOWTG system. To determine the best suited LOWTG model for HOWTG system, the obtained results are supported by findings and discussion in the terms of plots and tabulated data. The step response, error plot, and Bode plot are provided to highlight the compatibility of approximated LOWTG model with respect to HOWTG system. The approximated models are also compared with respect to HOWTG by considering time domain specifications and error index values in this contribution.","PeriodicalId":518382,"journal":{"name":"2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T)","volume":"46 6","pages":"474-479"},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531260","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 : 2024-01-18DOI: 10.1109/ICPC2T60072.2024.10474943
Pranjali Yadav, Sanskriti Chandrakar, Zeesha Mishra, B. Acharya
The development of the Internet of Things has led to a notable increase in the adoption of low-power, multipurpose sensors. Ensuring data security during transmission is crucial for these Internet of Things nodes. A compromised node can severely damage the network. However, due to their limited resources, it is difficult to implement suitable cryptographic functionality on constrained devices. In such circumstances, lightweight cryptography acts as a benefactor. A lightweight cryptographic method is a protocol that is intended to be used in situations with limitations, such as RFID tags, contactless smart cards, sensors, etc. Because of the peculiarities of rotation, XOR (ARX), and addition or AND operations, the round function must be based on the Feistel structure in order for decryption to be accurately performed. The issue with ARX-based block ciphers is that they only modify half of the plaintext block at a time, requiring additional rounds of iteration. In this project, a new logical approach that combines generalized Feistel structure and ARX operations is implemented. The challenge faced by conventional ARX ciphers is that they can only spread half of a plaintext block in a single round. Shadow solves this issue by considering the complete plaintext block. In order to guarantee the effectiveness of the encryption hardware circuit while preserving the security of the physical-layer signal, the suggested study examined the round-based hardware design of the Shadow cipher. The use of VLSI technology in the form of Xilinx software is also done in the paper. Shadow has shown almost 3 times better efficiency as compared to other block cipher.
{"title":"Hardware Implementation of Shadow Lightweight Block Cipher for Resource-Constrained IoT Devices","authors":"Pranjali Yadav, Sanskriti Chandrakar, Zeesha Mishra, B. Acharya","doi":"10.1109/ICPC2T60072.2024.10474943","DOIUrl":"https://doi.org/10.1109/ICPC2T60072.2024.10474943","url":null,"abstract":"The development of the Internet of Things has led to a notable increase in the adoption of low-power, multipurpose sensors. Ensuring data security during transmission is crucial for these Internet of Things nodes. A compromised node can severely damage the network. However, due to their limited resources, it is difficult to implement suitable cryptographic functionality on constrained devices. In such circumstances, lightweight cryptography acts as a benefactor. A lightweight cryptographic method is a protocol that is intended to be used in situations with limitations, such as RFID tags, contactless smart cards, sensors, etc. Because of the peculiarities of rotation, XOR (ARX), and addition or AND operations, the round function must be based on the Feistel structure in order for decryption to be accurately performed. The issue with ARX-based block ciphers is that they only modify half of the plaintext block at a time, requiring additional rounds of iteration. In this project, a new logical approach that combines generalized Feistel structure and ARX operations is implemented. The challenge faced by conventional ARX ciphers is that they can only spread half of a plaintext block in a single round. Shadow solves this issue by considering the complete plaintext block. In order to guarantee the effectiveness of the encryption hardware circuit while preserving the security of the physical-layer signal, the suggested study examined the round-based hardware design of the Shadow cipher. The use of VLSI technology in the form of Xilinx software is also done in the paper. Shadow has shown almost 3 times better efficiency as compared to other block cipher.","PeriodicalId":518382,"journal":{"name":"2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T)","volume":"79 1","pages":"680-685"},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531314","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}
The increasing global demand for electricity underscores the need to transition from fossil fuels to sustainable alternatives like solar energy. Despite solar power's advantages of abundance, sustainability, and quiet operation, environmental factors such as temperature and irradiance affect the efficiency of photovoltaic (PV) systems. This study utilizes the Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) approach to optimize a PV panel, validated through a cost-effective Arduino-based hardware model. The approach integrates simulation and practical testing, offering insights into energy production variations under diverse conditions, with parameters continuously monitored and updated on a web server.
{"title":"Real-time Solar Power Optimization and Energy Monitoring System with Maximum Power Point Tracking","authors":"Cherukumpalem Mohiddin Khan, S.V.R Lakshmi Kumari, Chundi Vinay Kumar, Mekala Hema, Rayipudi Angel","doi":"10.1109/icpc2t60072.2024.10474843","DOIUrl":"https://doi.org/10.1109/icpc2t60072.2024.10474843","url":null,"abstract":"The increasing global demand for electricity underscores the need to transition from fossil fuels to sustainable alternatives like solar energy. Despite solar power's advantages of abundance, sustainability, and quiet operation, environmental factors such as temperature and irradiance affect the efficiency of photovoltaic (PV) systems. This study utilizes the Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) approach to optimize a PV panel, validated through a cost-effective Arduino-based hardware model. The approach integrates simulation and practical testing, offering insights into energy production variations under diverse conditions, with parameters continuously monitored and updated on a web server.","PeriodicalId":518382,"journal":{"name":"2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T)","volume":"25 6","pages":"781-786"},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531117","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 : 2024-01-18DOI: 10.1109/ICPC2T60072.2024.10475088
Osamah N. Neamah, R. Bayir
This scientific paper presents groundbreaking advancements in Predictive Maintenance (PdM) within Industry 4.0, employing cutting-edge machine learning classification algorithms for fault prediction and diagnosis in Air Production Unit (APU) systems like MetroPT and MetroPT -3. This research uses data-driven methodologies to optimize feature extraction techniques to enhance fault prediction and improve diagnostic accuracy. A robust and versatile model emerges through comprehensive testing, displaying exceptional potential in fault prediction and diagnosis for complex systems. The paper highlights the significance of enhanced analytical techniques, such as cross-validation, ensuring the reliability and robustness of the model, contributing to refined and accurate fault prediction and diagnosis, all without succumbing to overfitting. This work significantly advances the application of machine learning in predicting malignancy within Industry 4.0, showcasing the promise of these methodologies in fault prediction and diagnosis for intricate systems.
{"title":"Revolutionizing Fault Prediction in MetroPT Datasets: Enhanced Diagnosis and Efficient Failure Prediction through Innovative Data Refinement","authors":"Osamah N. Neamah, R. Bayir","doi":"10.1109/ICPC2T60072.2024.10475088","DOIUrl":"https://doi.org/10.1109/ICPC2T60072.2024.10475088","url":null,"abstract":"This scientific paper presents groundbreaking advancements in Predictive Maintenance (PdM) within Industry 4.0, employing cutting-edge machine learning classification algorithms for fault prediction and diagnosis in Air Production Unit (APU) systems like MetroPT and MetroPT -3. This research uses data-driven methodologies to optimize feature extraction techniques to enhance fault prediction and improve diagnostic accuracy. A robust and versatile model emerges through comprehensive testing, displaying exceptional potential in fault prediction and diagnosis for complex systems. The paper highlights the significance of enhanced analytical techniques, such as cross-validation, ensuring the reliability and robustness of the model, contributing to refined and accurate fault prediction and diagnosis, all without succumbing to overfitting. This work significantly advances the application of machine learning in predicting malignancy within Industry 4.0, showcasing the promise of these methodologies in fault prediction and diagnosis for intricate systems.","PeriodicalId":518382,"journal":{"name":"2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T)","volume":"192 1","pages":"310-315"},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531127","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 : 2024-01-18DOI: 10.1109/ICPC2T60072.2024.10474615
K. Halder, M. F. Orlando, R. S. Anand
The aim of this research work is to implement a trajectory tracking controller for a flexible needle within a tissue region, using a neural network-based approach. Initially, a kinematic model for steerable needle inside the tissue domain is considered based on a unicycle model while considering nonholonomic constraints. Subsequently, a neural network (NN) architecture based closed loop control strategy is implemented to track a desired trajectory on a specified plane. The efficacy of the developed controller is confirmed through simulation studies. Furthermore, a comparative study is conducted, involving a standard Proportional-Integral-Derivative (PID) controller, to demonstrate the efficacy of the proposed controller. The simulation outcomes demonstrate that the proposed control scheme outperforms the conventional PID approach.
{"title":"Trajectory Tracking Controller Design for Percutaneous Interventional Procedures","authors":"K. Halder, M. F. Orlando, R. S. Anand","doi":"10.1109/ICPC2T60072.2024.10474615","DOIUrl":"https://doi.org/10.1109/ICPC2T60072.2024.10474615","url":null,"abstract":"The aim of this research work is to implement a trajectory tracking controller for a flexible needle within a tissue region, using a neural network-based approach. Initially, a kinematic model for steerable needle inside the tissue domain is considered based on a unicycle model while considering nonholonomic constraints. Subsequently, a neural network (NN) architecture based closed loop control strategy is implemented to track a desired trajectory on a specified plane. The efficacy of the developed controller is confirmed through simulation studies. Furthermore, a comparative study is conducted, involving a standard Proportional-Integral-Derivative (PID) controller, to demonstrate the efficacy of the proposed controller. The simulation outcomes demonstrate that the proposed control scheme outperforms the conventional PID approach.","PeriodicalId":518382,"journal":{"name":"2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T)","volume":"23 16","pages":"775-780"},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531381","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 : 2024-01-18DOI: 10.1109/ICPC2T60072.2024.10474728
Gayatri S. Patil, Uma S. Patil, Priyanka P. Shinde
The global energy sector operates within a highly competitive market, necessitating uninterrupted power supply to industrial, commercial, and domestic sectors. Transformers serve a critical role in electricity transmission, emphasizing the importance of maintaining their performance to minimize losses. Dissolved Gas Analysis (DGA) emerges as a pivotal tool for monitoring transformer performance and identifying fault types in oil-immersed transformers. Despite the existence of several conventional DGA interpretation techniques, their accuracy has been subpar. This research paper presents a novel machine learning(ML) approach for predicting power transformer faults using DGA data. The proposed method leverages DGA samples sourced from the IEEE data port to train and test various machine learning models within the WEKA platform.
{"title":"Enhancing Power Transformer Reliability through Machine Learning-Based Fault Prediction Using Dissolved Gas Analysis","authors":"Gayatri S. Patil, Uma S. Patil, Priyanka P. Shinde","doi":"10.1109/ICPC2T60072.2024.10474728","DOIUrl":"https://doi.org/10.1109/ICPC2T60072.2024.10474728","url":null,"abstract":"The global energy sector operates within a highly competitive market, necessitating uninterrupted power supply to industrial, commercial, and domestic sectors. Transformers serve a critical role in electricity transmission, emphasizing the importance of maintaining their performance to minimize losses. Dissolved Gas Analysis (DGA) emerges as a pivotal tool for monitoring transformer performance and identifying fault types in oil-immersed transformers. Despite the existence of several conventional DGA interpretation techniques, their accuracy has been subpar. This research paper presents a novel machine learning(ML) approach for predicting power transformer faults using DGA data. The proposed method leverages DGA samples sourced from the IEEE data port to train and test various machine learning models within the WEKA platform.","PeriodicalId":518382,"journal":{"name":"2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T)","volume":"2 4","pages":"72-76"},"PeriodicalIF":0.0,"publicationDate":"2024-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140531284","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：