Pub Date : 2021-12-10DOI: 10.1109/CAPS52117.2021.9730634
M. Rajvaidya, Deepak Batham
Efficient routing with 100% survivability level is one of the challenging task for wavelength division multiplexing (WDM) optical networks. In this paper, we have proposed an efficient cluster based protection (CBP) strategy to improve the survivability in WDM optical networks. CBP strategy provides protection against a single link failure. In CBP, the connection requests are classified into different clusters. The requests having link-disjoint primary paths are considered in the same cluster. Each cluster is processed one by one as per the decreasing order of cluster size or the number of requests in a cluster. Simulation results of the proposed CBP strategy shows improved performance on the evaluating parameter of blocking probability (BP), resource overbuild (RO) and link load (LL) in comparison to the traditional shared path protection (SPP) strategy. CBP strategy shows 16.51 % and 12.57 % reduction in BP and RO, respectively. Also, the CBP distributes traffic load uniformly along each link of the network which is demonstrated by LL metric.
{"title":"Efficient cluster based protection strategy to improve survivability in optical networks","authors":"M. Rajvaidya, Deepak Batham","doi":"10.1109/CAPS52117.2021.9730634","DOIUrl":"https://doi.org/10.1109/CAPS52117.2021.9730634","url":null,"abstract":"Efficient routing with 100% survivability level is one of the challenging task for wavelength division multiplexing (WDM) optical networks. In this paper, we have proposed an efficient cluster based protection (CBP) strategy to improve the survivability in WDM optical networks. CBP strategy provides protection against a single link failure. In CBP, the connection requests are classified into different clusters. The requests having link-disjoint primary paths are considered in the same cluster. Each cluster is processed one by one as per the decreasing order of cluster size or the number of requests in a cluster. Simulation results of the proposed CBP strategy shows improved performance on the evaluating parameter of blocking probability (BP), resource overbuild (RO) and link load (LL) in comparison to the traditional shared path protection (SPP) strategy. CBP strategy shows 16.51 % and 12.57 % reduction in BP and RO, respectively. Also, the CBP distributes traffic load uniformly along each link of the network which is demonstrated by LL metric.","PeriodicalId":445427,"journal":{"name":"2021 International Conference on Control, Automation, Power and Signal Processing (CAPS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124631827","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 : 2021-12-10DOI: 10.1109/CAPS52117.2021.9730595
G. Deo, C. Mahamuni, Ayushi Mishra
Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which has spread worldwide, creating an unprecedented pandemic situation. Due to rapid spreading, the pandemic forced several nations to impose lockdown for isolating the population and new policies of quarantine were adopted. After the government eased the restrictions, the most prominent challenges faced by daily commuters (employees or students) include maintaining a safe distance from others, regular sanitization, and washing hands, wearing masks and face shields, contact tracing, etc. It is quite difficult to practice social distancing and always use hand sanitizer when using public transport or at the workplace and people do not have a track of their temperature, heart rate, and oxygen saturation level. Though it is ideal to avoid traveling, when necessary some factors need to be considered such as personal hygiene, contactless interaction, disinfection, and monitoring important health parameters. Given this, we aim to develop an IoT-enabled compact wearable system including all essential features like an electronic face mask, an automatic sanitizer dispenser, and a Temperature-SpO2 monitoring wearable to avoid any physical touch and discomfort and alert the nearby doctors about irregularity in any parameter through the GSM module. The results of the software simulation of the system and the web-scraping using Python software to extract coordinates of containment zones are discussed in the paper.
{"title":"COVID-19 Lifeguard: A Compact Wearable-IoT (W-IoT) System for Health Safety and Protection of Outgoers in the Post- Lockdown World","authors":"G. Deo, C. Mahamuni, Ayushi Mishra","doi":"10.1109/CAPS52117.2021.9730595","DOIUrl":"https://doi.org/10.1109/CAPS52117.2021.9730595","url":null,"abstract":"Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which has spread worldwide, creating an unprecedented pandemic situation. Due to rapid spreading, the pandemic forced several nations to impose lockdown for isolating the population and new policies of quarantine were adopted. After the government eased the restrictions, the most prominent challenges faced by daily commuters (employees or students) include maintaining a safe distance from others, regular sanitization, and washing hands, wearing masks and face shields, contact tracing, etc. It is quite difficult to practice social distancing and always use hand sanitizer when using public transport or at the workplace and people do not have a track of their temperature, heart rate, and oxygen saturation level. Though it is ideal to avoid traveling, when necessary some factors need to be considered such as personal hygiene, contactless interaction, disinfection, and monitoring important health parameters. Given this, we aim to develop an IoT-enabled compact wearable system including all essential features like an electronic face mask, an automatic sanitizer dispenser, and a Temperature-SpO2 monitoring wearable to avoid any physical touch and discomfort and alert the nearby doctors about irregularity in any parameter through the GSM module. The results of the software simulation of the system and the web-scraping using Python software to extract coordinates of containment zones are discussed in the paper.","PeriodicalId":445427,"journal":{"name":"2021 International Conference on Control, Automation, Power and Signal Processing (CAPS)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122617015","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 : 2021-12-10DOI: 10.1109/CAPS52117.2021.9730603
H. Pal, Adarsh Kumar, A. Vishwakarma
In the biomedical field, electrocardiogram (ECG) recording produces a large amount of data, which are stored in a digitized format for monitoring and diagnosis purposes. In this regard, it is essential to reduce data size due to memory constraints in ambulatory and tel-e-medicine systems. This paper proposes an algorithm using optimized tunable-Q wavelet transform (TQWT) to reduce the memory requirement. It has the flexibility to tune its parameters to obtain the desired compression. For optimizing the parameters of TQWT, nature-inspired algorithm ant colony optimization (ACO) is used. The compression is achieved by using a dead-zone quantizer (DZQ) and run-length encoding (RLE). Results illustrate that significant compression has been achieved at the cost of acceptable distortion in the signal quality. The performance of the proposed technique is evaluated using percentage-root-mean square difference (PRD), compression ratio (CR), and quality score (QS). The average value obtained of CR, PRD, and QS are given as 22.42, 4.52%, and 6.05, respectively.
{"title":"Electrocardiogram Compression using Optimized TQWT and Dead-Zone Quantizer","authors":"H. Pal, Adarsh Kumar, A. Vishwakarma","doi":"10.1109/CAPS52117.2021.9730603","DOIUrl":"https://doi.org/10.1109/CAPS52117.2021.9730603","url":null,"abstract":"In the biomedical field, electrocardiogram (ECG) recording produces a large amount of data, which are stored in a digitized format for monitoring and diagnosis purposes. In this regard, it is essential to reduce data size due to memory constraints in ambulatory and tel-e-medicine systems. This paper proposes an algorithm using optimized tunable-Q wavelet transform (TQWT) to reduce the memory requirement. It has the flexibility to tune its parameters to obtain the desired compression. For optimizing the parameters of TQWT, nature-inspired algorithm ant colony optimization (ACO) is used. The compression is achieved by using a dead-zone quantizer (DZQ) and run-length encoding (RLE). Results illustrate that significant compression has been achieved at the cost of acceptable distortion in the signal quality. The performance of the proposed technique is evaluated using percentage-root-mean square difference (PRD), compression ratio (CR), and quality score (QS). The average value obtained of CR, PRD, and QS are given as 22.42, 4.52%, and 6.05, respectively.","PeriodicalId":445427,"journal":{"name":"2021 International Conference on Control, Automation, Power and Signal Processing (CAPS)","volume":"210 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131502627","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 : 2021-12-10DOI: 10.1109/CAPS52117.2021.9730719
K. Das, Sagnik Ghosh, Himandri Sekhar Dutta
The COVID-19 pandemic has hit the world at large claiming large number of lives till date leaving us with no solution except maintaining social distancing or washing hands regularly, wearing masks and staying at homes. Social distancing is one of the key aspects to prevent spreading of this virus. It means more of maintaining suitable distance between each other. Artificial intelligence has been used widely for a large number of purposes and as such is one of the key tools used here for implementing this project. The proposed system identifies people who are not suitable distance apart by using object detection and calculating the Euclidian distance between two people. This system would be beneficial to the authorities for alerting people if the situation is serious.
{"title":"A Deep learning based approach for Social Distance Monitoring","authors":"K. Das, Sagnik Ghosh, Himandri Sekhar Dutta","doi":"10.1109/CAPS52117.2021.9730719","DOIUrl":"https://doi.org/10.1109/CAPS52117.2021.9730719","url":null,"abstract":"The COVID-19 pandemic has hit the world at large claiming large number of lives till date leaving us with no solution except maintaining social distancing or washing hands regularly, wearing masks and staying at homes. Social distancing is one of the key aspects to prevent spreading of this virus. It means more of maintaining suitable distance between each other. Artificial intelligence has been used widely for a large number of purposes and as such is one of the key tools used here for implementing this project. The proposed system identifies people who are not suitable distance apart by using object detection and calculating the Euclidian distance between two people. This system would be beneficial to the authorities for alerting people if the situation is serious.","PeriodicalId":445427,"journal":{"name":"2021 International Conference on Control, Automation, Power and Signal Processing (CAPS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122928226","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 : 2021-12-10DOI: 10.1109/CAPS52117.2021.9730656
Neha Smitha Lakra, Baidyanath Bag
Conservation Voltage Reduction (CVR) is the most adopted energy efficient technology. It is adopted in the distribution system due to its effectiveness in achieving a reduction in power consumption and peak reduction. In this article the concept of CVR is integrated with VAr optimization to enhance the voltage levels of the network within bounds, to reduce line losses and to decrease the power consumption of the network. All simulations have been performed in the IEEE-33 node system assuming different levels of loads such as RE, CO and IN is to be connected at different buses of the system. A comparative analysis of power demand and other performance parameters have been presented for three different cases. The impact of CVR effects has been tested for two different voltage conditions.
{"title":"An Energy Efficient Method to Reduce Power Loss and Power Consumption in Distribution System","authors":"Neha Smitha Lakra, Baidyanath Bag","doi":"10.1109/CAPS52117.2021.9730656","DOIUrl":"https://doi.org/10.1109/CAPS52117.2021.9730656","url":null,"abstract":"Conservation Voltage Reduction (CVR) is the most adopted energy efficient technology. It is adopted in the distribution system due to its effectiveness in achieving a reduction in power consumption and peak reduction. In this article the concept of CVR is integrated with VAr optimization to enhance the voltage levels of the network within bounds, to reduce line losses and to decrease the power consumption of the network. All simulations have been performed in the IEEE-33 node system assuming different levels of loads such as RE, CO and IN is to be connected at different buses of the system. A comparative analysis of power demand and other performance parameters have been presented for three different cases. The impact of CVR effects has been tested for two different voltage conditions.","PeriodicalId":445427,"journal":{"name":"2021 International Conference on Control, Automation, Power and Signal Processing (CAPS)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115766495","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 : 2021-12-10DOI: 10.1109/CAPS52117.2021.9730607
Lakshay, S. K. Jain
Accurate inertia estimation and forecasting of inertia is very crucial because inertia is the most important parameter in stability studies to keep the frequency at nominal levels with help of energy stored in synchronous generator rotating masses. As the integration of renewable sources increases, power system inertia decreases results in overloading of generation units which may reduce the stability of the power system and system becomes dynamic and causes concern for many grid operators. As a result, inertia assessment is required so that transmission system operators can take appropriate steps to guarantee stability. This paper reviews the inertia estimation techniques used and their evolution in the last decades. An overview and classification of different methods are also carried out and shortcomings of existing techniques have been identified.
{"title":"A Review on Power System Inertia Estimation Techniques","authors":"Lakshay, S. K. Jain","doi":"10.1109/CAPS52117.2021.9730607","DOIUrl":"https://doi.org/10.1109/CAPS52117.2021.9730607","url":null,"abstract":"Accurate inertia estimation and forecasting of inertia is very crucial because inertia is the most important parameter in stability studies to keep the frequency at nominal levels with help of energy stored in synchronous generator rotating masses. As the integration of renewable sources increases, power system inertia decreases results in overloading of generation units which may reduce the stability of the power system and system becomes dynamic and causes concern for many grid operators. As a result, inertia assessment is required so that transmission system operators can take appropriate steps to guarantee stability. This paper reviews the inertia estimation techniques used and their evolution in the last decades. An overview and classification of different methods are also carried out and shortcomings of existing techniques have been identified.","PeriodicalId":445427,"journal":{"name":"2021 International Conference on Control, Automation, Power and Signal Processing (CAPS)","volume":"238 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116108962","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 : 2021-12-10DOI: 10.1109/CAPS52117.2021.9730732
Milinda Sagar Behera, S. K. Jain
Demand-side management (DSM) enables customers and utilities to make intelligent decisions regarding energy usage, allowing them to alter the load profile and reduce peak demand in the smart distribution system. In recent years, DSM has been used as a technique to balance electricity usage and the rising electricity demand in line. Demand-side management and demand response (DR) methods are both examined in this research. In this paper, we have discussed different types of DSM programs and especially we have focused on the DR program, its types, and benefits. Different technologies used to establish demand response program has been discussed in this paper. Additionally, it highlights the impact of electric vehicles on this DR program and DR strategy for the electric vehicle sector, along with the future research trends has addressed.
{"title":"A Review on Different Techniques of Demand Response Management and its Future Scopes","authors":"Milinda Sagar Behera, S. K. Jain","doi":"10.1109/CAPS52117.2021.9730732","DOIUrl":"https://doi.org/10.1109/CAPS52117.2021.9730732","url":null,"abstract":"Demand-side management (DSM) enables customers and utilities to make intelligent decisions regarding energy usage, allowing them to alter the load profile and reduce peak demand in the smart distribution system. In recent years, DSM has been used as a technique to balance electricity usage and the rising electricity demand in line. Demand-side management and demand response (DR) methods are both examined in this research. In this paper, we have discussed different types of DSM programs and especially we have focused on the DR program, its types, and benefits. Different technologies used to establish demand response program has been discussed in this paper. Additionally, it highlights the impact of electric vehicles on this DR program and DR strategy for the electric vehicle sector, along with the future research trends has addressed.","PeriodicalId":445427,"journal":{"name":"2021 International Conference on Control, Automation, Power and Signal Processing (CAPS)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114792523","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 : 2021-12-10DOI: 10.1109/CAPS52117.2021.9730709
Barukula Snehitha, Raavi Sai Sreeya, V. Manikandan
Human activity detection is an active research topic now, the difficult problem of fine-grained activity detection is often ignored. This paper proposes a method to detect human activity from still images. Iterative detection of human activity in a scene is another tough and exciting area of computer vision research. In our day to day life, we have seen implementations of automated cars, speech recognition, and various machine learning models. Unlike action detection in videos that have spatio-temporal features, still images can't be considered similarly, making the problem more complex. The current work solely comprises activities that involve objects to reach a simple answer. Based on semantics, a complicated human activity is broken down into smaller components. The significance of each of these elements in action recognition is investigated in depth. This system is based on detecting an individual's action or behaviour with the help of a single frame (image). Activity detection consists of various tasks like object recognition, pose estimation, video action recognition, and image recognition. Since the current paper is focused only on actions that involve objects, a dataset with specified classes is created. Images for this dataset will be chosen from different sources. This study aims at the development of computational algorithms for activity detection in still images.
{"title":"Human Activity Detection from Still Images using Deep Learning Techniques","authors":"Barukula Snehitha, Raavi Sai Sreeya, V. Manikandan","doi":"10.1109/CAPS52117.2021.9730709","DOIUrl":"https://doi.org/10.1109/CAPS52117.2021.9730709","url":null,"abstract":"Human activity detection is an active research topic now, the difficult problem of fine-grained activity detection is often ignored. This paper proposes a method to detect human activity from still images. Iterative detection of human activity in a scene is another tough and exciting area of computer vision research. In our day to day life, we have seen implementations of automated cars, speech recognition, and various machine learning models. Unlike action detection in videos that have spatio-temporal features, still images can't be considered similarly, making the problem more complex. The current work solely comprises activities that involve objects to reach a simple answer. Based on semantics, a complicated human activity is broken down into smaller components. The significance of each of these elements in action recognition is investigated in depth. This system is based on detecting an individual's action or behaviour with the help of a single frame (image). Activity detection consists of various tasks like object recognition, pose estimation, video action recognition, and image recognition. Since the current paper is focused only on actions that involve objects, a dataset with specified classes is created. Images for this dataset will be chosen from different sources. This study aims at the development of computational algorithms for activity detection in still images.","PeriodicalId":445427,"journal":{"name":"2021 International Conference on Control, Automation, Power and Signal Processing (CAPS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125416970","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 : 2021-12-10DOI: 10.1109/CAPS52117.2021.9730707
J. Rahul, Ashutosh Kumar, L. Sharma
Object detection is a technique to tag objects present in the frame of an image, video sequence, and real-time video. In recent years, the world has been reshaped around deep learning algorithms. This paper makes the user aware of the obstacles present in his environment. There are two fundamental parts in this paper: the software part and the hardware part. The state-of-the-art You Look Only Once (YOLO) algorithm was applied in the present work for object identification. The overall analysis shows that this algorithm produces accurate results for real-time object detection and can be considered faster object identification.
目标检测是一种标记出现在图像、视频序列和实时视频帧中的对象的技术。近年来，世界已经围绕深度学习算法进行了重塑。这篇论文让用户意识到他的环境中存在的障碍。本文主要分为软件部分和硬件部分。最先进的You Look Only Once (YOLO)算法应用于本工作的目标识别。综合分析表明，该算法可以产生准确的实时目标检测结果，可以认为是更快的目标识别。
{"title":"Artificial intelligence enabled smart glove for visually impaired","authors":"J. Rahul, Ashutosh Kumar, L. Sharma","doi":"10.1109/CAPS52117.2021.9730707","DOIUrl":"https://doi.org/10.1109/CAPS52117.2021.9730707","url":null,"abstract":"Object detection is a technique to tag objects present in the frame of an image, video sequence, and real-time video. In recent years, the world has been reshaped around deep learning algorithms. This paper makes the user aware of the obstacles present in his environment. There are two fundamental parts in this paper: the software part and the hardware part. The state-of-the-art You Look Only Once (YOLO) algorithm was applied in the present work for object identification. The overall analysis shows that this algorithm produces accurate results for real-time object detection and can be considered faster object identification.","PeriodicalId":445427,"journal":{"name":"2021 International Conference on Control, Automation, Power and Signal Processing (CAPS)","volume":"147 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125870446","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 : 2021-12-10DOI: 10.1109/CAPS52117.2021.9730589
S. R. Gaigowal, M. Renge, S. Bhongade
Flexible AC Transmission System (FACTS) provides a possibility to enable utilization of the existing transmission line to its full power flow rating. Distributed-FACTS converters proven to be the new horizon in power system operation and control. It is capable of controlling power flow with low cost and high reliability. Distributed Static Series Compensator (DSSC) is a series D-FACTS device which is distributed over the existing line. It is similar to lumped series FACTS device i.e. SSSC. This paper presents DSSC to limit fault current in the transmission system. The prime function of DSSC is to enable network to control power flow in the lines. DSSC is a single-phase inverter which is low power, light in weight and it can be directly attached on the existing transmission conductor. It is emulating inductive and capacitive reactance and alters line reactance to control active power flow in the lines. Scope of this DSSC devices to reduce fault current is presented. A fault current in DSSC compensated transmission line is investigated in this paper. MATLAB Simulink results are presented to validate DSSC operation in fault condition.
{"title":"Fault Current Limiting using DSSC on the existing Transmission Lines","authors":"S. R. Gaigowal, M. Renge, S. Bhongade","doi":"10.1109/CAPS52117.2021.9730589","DOIUrl":"https://doi.org/10.1109/CAPS52117.2021.9730589","url":null,"abstract":"Flexible AC Transmission System (FACTS) provides a possibility to enable utilization of the existing transmission line to its full power flow rating. Distributed-FACTS converters proven to be the new horizon in power system operation and control. It is capable of controlling power flow with low cost and high reliability. Distributed Static Series Compensator (DSSC) is a series D-FACTS device which is distributed over the existing line. It is similar to lumped series FACTS device i.e. SSSC. This paper presents DSSC to limit fault current in the transmission system. The prime function of DSSC is to enable network to control power flow in the lines. DSSC is a single-phase inverter which is low power, light in weight and it can be directly attached on the existing transmission conductor. It is emulating inductive and capacitive reactance and alters line reactance to control active power flow in the lines. Scope of this DSSC devices to reduce fault current is presented. A fault current in DSSC compensated transmission line is investigated in this paper. MATLAB Simulink results are presented to validate DSSC operation in fault condition.","PeriodicalId":445427,"journal":{"name":"2021 International Conference on Control, Automation, Power and Signal Processing (CAPS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126654179","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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