Pub Date : 2014-05-08DOI: 10.1109/ICACCCT.2014.7019145
Satendra Kumar, Anamika Yadav
Rapid growth in Internet and in parallel attacks, vulnerability and threats, has made intrusion detection systems very essential component in all parts of security infrastructure. Building IDS is not a new task, classical signature based IDS are used but they are unable to handle novel attacks. In this paper artificial neural network based intrusion detection is proposed for complete KDD cup 99 dataset. Performance of the proposed ANN based IDS system is evaluated and results shows high anomaly detection accuracy for the complete KDD cup 99 dataset as compared to existing techniques.
随着互联网的快速发展以及并行攻击、漏洞和威胁的日益增多，入侵检测系统已成为安全基础设施中必不可少的组成部分。建立入侵检测系统并不是一项新任务，传统的基于签名的入侵检测系统被使用，但它们无法处理新的攻击。针对KDD cup 99完整数据集，提出了基于人工神经网络的入侵检测方法。对基于人工神经网络的IDS系统的性能进行了评估，结果表明，与现有技术相比，对于完整的KDD cup 99数据集，IDS系统的异常检测精度很高。
{"title":"Increasing performance Of intrusion detection system using neural network","authors":"Satendra Kumar, Anamika Yadav","doi":"10.1109/ICACCCT.2014.7019145","DOIUrl":"https://doi.org/10.1109/ICACCCT.2014.7019145","url":null,"abstract":"Rapid growth in Internet and in parallel attacks, vulnerability and threats, has made intrusion detection systems very essential component in all parts of security infrastructure. Building IDS is not a new task, classical signature based IDS are used but they are unable to handle novel attacks. In this paper artificial neural network based intrusion detection is proposed for complete KDD cup 99 dataset. Performance of the proposed ANN based IDS system is evaluated and results shows high anomaly detection accuracy for the complete KDD cup 99 dataset as compared to existing techniques.","PeriodicalId":239918,"journal":{"name":"2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128525485","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 : 2014-05-08DOI: 10.1109/ICACCCT.2014.7019182
Sugandh Shah, B. Mehtre
With increasing world-wide connectivity of Information systems, and growth in accessibility of data resources, the threat to the Integrity and Confidentiality of Data and Services has also increased. Every now and then cases of Hacking and Exploitation are being observed. So in order to remain immune and minimize such threats, the Organizations conduct regular Vulnerability Assessment and Penetration Testing (VAPT) on their Technical Assets [1]. We at IDRBT have developed a new automated VAPT Testing Tool named Net-Nirikshak 1.0 which will help the Organizations to assess their Application/Services and analyze their Security Posture. Net-Nirikshak 1.0 detects the vulnerabilities based on the applications and Services being used on the target system. Apart from these it detects the SQL Injection vulnerabilities and reports all the Identified vulnerable links on the Target. Further the tool can also exploit the identified SQLI vulnerable links and grab confidential information from Target.The automated VAPT report generated by the tool is sent to the specified Email and all the traces of Scan along with the Report are removed from the Hard disk so as to ensure the Confidentiality of the VAPT Report. All the Technical and Operational aspects of Net-Nirikshak 1.0 are described in this paper along with the Outputs of a sample VAPT Test conducted on www.webscantest.com using Net-Nirikshak 1.0.
{"title":"An automated approach to Vulnerability Assessment and Penetration Testing using Net-Nirikshak 1.0","authors":"Sugandh Shah, B. Mehtre","doi":"10.1109/ICACCCT.2014.7019182","DOIUrl":"https://doi.org/10.1109/ICACCCT.2014.7019182","url":null,"abstract":"With increasing world-wide connectivity of Information systems, and growth in accessibility of data resources, the threat to the Integrity and Confidentiality of Data and Services has also increased. Every now and then cases of Hacking and Exploitation are being observed. So in order to remain immune and minimize such threats, the Organizations conduct regular Vulnerability Assessment and Penetration Testing (VAPT) on their Technical Assets [1]. We at IDRBT have developed a new automated VAPT Testing Tool named Net-Nirikshak 1.0 which will help the Organizations to assess their Application/Services and analyze their Security Posture. Net-Nirikshak 1.0 detects the vulnerabilities based on the applications and Services being used on the target system. Apart from these it detects the SQL Injection vulnerabilities and reports all the Identified vulnerable links on the Target. Further the tool can also exploit the identified SQLI vulnerable links and grab confidential information from Target.The automated VAPT report generated by the tool is sent to the specified Email and all the traces of Scan along with the Report are removed from the Hard disk so as to ensure the Confidentiality of the VAPT Report. All the Technical and Operational aspects of Net-Nirikshak 1.0 are described in this paper along with the Outputs of a sample VAPT Test conducted on www.webscantest.com using Net-Nirikshak 1.0.","PeriodicalId":239918,"journal":{"name":"2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124799382","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 : 2014-05-08DOI: 10.1109/ICACCCT.2014.7019253
A. Mishra, D. P. Acharya, P. K. Patra
Address Decoder is an important digital block in SRAM which takes up to half of the total chip access time and significant part of the total SRAM power in normal read/write cycle. To design address decoder need to consider two objectives, first choosing the optimal circuit technique and second sizing of their transistors. Novel address decoder circuit is presented and analysed in this paper. Address decoder using NAND-NOR alternate stages with predecoder and replica inverter chain circuit is proposed and compared with traditional and universal block architecture, using 90nm CMOS technology. Delay and power dissipation in proposed decoder is 60.49% and 52.54% of traditional and 82.35% and 73.80% of universal block architecture respectively.
{"title":"Novel design technique of address Decoder for SRAM","authors":"A. Mishra, D. P. Acharya, P. K. Patra","doi":"10.1109/ICACCCT.2014.7019253","DOIUrl":"https://doi.org/10.1109/ICACCCT.2014.7019253","url":null,"abstract":"Address Decoder is an important digital block in SRAM which takes up to half of the total chip access time and significant part of the total SRAM power in normal read/write cycle. To design address decoder need to consider two objectives, first choosing the optimal circuit technique and second sizing of their transistors. Novel address decoder circuit is presented and analysed in this paper. Address decoder using NAND-NOR alternate stages with predecoder and replica inverter chain circuit is proposed and compared with traditional and universal block architecture, using 90nm CMOS technology. Delay and power dissipation in proposed decoder is 60.49% and 52.54% of traditional and 82.35% and 73.80% of universal block architecture respectively.","PeriodicalId":239918,"journal":{"name":"2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130196639","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 : 2014-05-08DOI: 10.1109/ICACCCT.2014.7019297
Suresh Fatehpuria, A. Goyal
There are a vast number of diversified fields where a pattern may need to be searched in a given string. Processing of signals in telecommunication, finding DNA patterns, searching a word pattern in a document in Microsoft Word document or over the web are some of the examples of pattern matching. The algorithm presented in this paper i.e. Jumping Algorithm is a very new idea for finding a pattern. The algorithm preprocesses the whole string by indexing all the characters of the string and storing the indexes in a two dimensional array. This two dimensional array contains alphabet size number of columns with the index entry for every occurrence of every character of the string. In the matching process the pattern is jumped over the given string until the match is found (or a match doesn't occur). For shifting the pattern on every mismatch, the help of two dimensional array is taken that ensures only relevant shifts. The time complexity for matching processes is very much less than other proposed algorithms because of a very few number of shifts.
{"title":"A very unique, fast and efficient approach for pattern matching (the Jumping Algorithm)","authors":"Suresh Fatehpuria, A. Goyal","doi":"10.1109/ICACCCT.2014.7019297","DOIUrl":"https://doi.org/10.1109/ICACCCT.2014.7019297","url":null,"abstract":"There are a vast number of diversified fields where a pattern may need to be searched in a given string. Processing of signals in telecommunication, finding DNA patterns, searching a word pattern in a document in Microsoft Word document or over the web are some of the examples of pattern matching. The algorithm presented in this paper i.e. Jumping Algorithm is a very new idea for finding a pattern. The algorithm preprocesses the whole string by indexing all the characters of the string and storing the indexes in a two dimensional array. This two dimensional array contains alphabet size number of columns with the index entry for every occurrence of every character of the string. In the matching process the pattern is jumped over the given string until the match is found (or a match doesn't occur). For shifting the pattern on every mismatch, the help of two dimensional array is taken that ensures only relevant shifts. The time complexity for matching processes is very much less than other proposed algorithms because of a very few number of shifts.","PeriodicalId":239918,"journal":{"name":"2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130218433","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 : 2014-05-08DOI: 10.1109/ICACCCT.2014.7019325
D. Devi, K. Muthukannan
For any automated image analysis process, the segmentation is an important task because all subsequent tasks in image processing heavily rely on the quality of image segmentation. It determines the eventual success or failure of the analysis. The problem in image segmentation occurs when an image has a varying gray level background. There are several algorithms and methods are available for image segmentation, but there is a need to develop a unique method for it. In this paper, some of the image segmentation algorithms are compared to segment the diseased portion of rice leaves.
{"title":"Analysis of segmentation scheme for diseased rice leaves","authors":"D. Devi, K. Muthukannan","doi":"10.1109/ICACCCT.2014.7019325","DOIUrl":"https://doi.org/10.1109/ICACCCT.2014.7019325","url":null,"abstract":"For any automated image analysis process, the segmentation is an important task because all subsequent tasks in image processing heavily rely on the quality of image segmentation. It determines the eventual success or failure of the analysis. The problem in image segmentation occurs when an image has a varying gray level background. There are several algorithms and methods are available for image segmentation, but there is a need to develop a unique method for it. In this paper, some of the image segmentation algorithms are compared to segment the diseased portion of rice leaves.","PeriodicalId":239918,"journal":{"name":"2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125643934","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 : 2014-05-08DOI: 10.1109/ICACCCT.2014.7019318
Sharvari S S Deshpande, A. Wakankar
Polycystic Ovarian Syndrome (PCOS) is one of the most common hormonal disorder present in females in reproductive age group. Early detection and treatment of PCOS is important since it is often associated with obesity, type 2 diabetes mellitus, and high cholesterol levels. In this paper, automated detection of PCOS is done by calculating no of follicles in ovarian ultrasound image and then incorporating clinical, biochemical and imaging parameters to classify patients in two groups i.e. normal and PCOS affected. Number of follicles are detected by ovarian ultrasound image processing using preprocessing which includes contrast enhancement and filtering, feature extraction using Multiscale morphological approach and segmentation. Support Vector Machine algorithm is used for classification which takes into account all the parameters such as body mass index (BMI), hormonal levels, menstrual cycle length and no of follicles detected in ovarian ultrasound image processing. The results obtained are verified by doctors and compared with manual detection. The accuracy obtained for the proposed method is 95%.
{"title":"Automated detection of Polycystic Ovarian Syndrome using follicle recognition","authors":"Sharvari S S Deshpande, A. Wakankar","doi":"10.1109/ICACCCT.2014.7019318","DOIUrl":"https://doi.org/10.1109/ICACCCT.2014.7019318","url":null,"abstract":"Polycystic Ovarian Syndrome (PCOS) is one of the most common hormonal disorder present in females in reproductive age group. Early detection and treatment of PCOS is important since it is often associated with obesity, type 2 diabetes mellitus, and high cholesterol levels. In this paper, automated detection of PCOS is done by calculating no of follicles in ovarian ultrasound image and then incorporating clinical, biochemical and imaging parameters to classify patients in two groups i.e. normal and PCOS affected. Number of follicles are detected by ovarian ultrasound image processing using preprocessing which includes contrast enhancement and filtering, feature extraction using Multiscale morphological approach and segmentation. Support Vector Machine algorithm is used for classification which takes into account all the parameters such as body mass index (BMI), hormonal levels, menstrual cycle length and no of follicles detected in ovarian ultrasound image processing. The results obtained are verified by doctors and compared with manual detection. The accuracy obtained for the proposed method is 95%.","PeriodicalId":239918,"journal":{"name":"2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127289710","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 : 2014-05-08DOI: 10.1109/ICACCCT.2014.7019154
L. Gladence, T. Ravi, M. Karthi
A number of studies demonstrated the relationship of HRV (Heart Rate Variability) measures. Over the past years, automatic classifier, based on several clinical & instrumental parameters have been proposed to support CHF assessment. Considering only the low level features will not fulfill the classification needs. In order to avoid the gap between low level i.e general causes for CHF & high level features i.e attribute retrieved from long term HRV & make a decision correctly proposed a classifier to individuate severity of CHF. The proposed classifier separates lower risk patients from higher risk ones, using standard long-term heart rate variability (HRV) measures. The method we used to develop the Automatic Classifier is Bayesian belief network Classifier. The Bayesian Belief Network Classifier has been used in several applications especially for medical diagnosis. The Bayesian Belief Network algorithm iteratively splits the dataset, according to a criterion that maximizes the separation of the data which will produce a tree-like decision.
{"title":"An enhanced method for detecting congestive heart failure - Automatic Classifier","authors":"L. Gladence, T. Ravi, M. Karthi","doi":"10.1109/ICACCCT.2014.7019154","DOIUrl":"https://doi.org/10.1109/ICACCCT.2014.7019154","url":null,"abstract":"A number of studies demonstrated the relationship of HRV (Heart Rate Variability) measures. Over the past years, automatic classifier, based on several clinical & instrumental parameters have been proposed to support CHF assessment. Considering only the low level features will not fulfill the classification needs. In order to avoid the gap between low level i.e general causes for CHF & high level features i.e attribute retrieved from long term HRV & make a decision correctly proposed a classifier to individuate severity of CHF. The proposed classifier separates lower risk patients from higher risk ones, using standard long-term heart rate variability (HRV) measures. The method we used to develop the Automatic Classifier is Bayesian belief network Classifier. The Bayesian Belief Network Classifier has been used in several applications especially for medical diagnosis. The Bayesian Belief Network algorithm iteratively splits the dataset, according to a criterion that maximizes the separation of the data which will produce a tree-like decision.","PeriodicalId":239918,"journal":{"name":"2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116007956","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 : 2014-05-08DOI: 10.1109/ICACCCT.2014.7019320
Yashika Katyal, Suhas V. Alur, Shipra Dwivedi, R. Menaka
Depression is a common phenomenon in the present scenario. Due to the fast pace at which our lives move and immense pressure that we face adolescents, office goers and even the elders face depression. Diagnosing depression in the early curable stages is very important and may even save the life of a patient. EEG signal analysis has been used for medical research like epilepsy, sleep disorder, insomnia etc. Similarly, video signal analysis has been used for facial features detection, eye movement, emotion recognition etc. Collaborating both the methods accuracy of depression detection can be improved upon. This paper describes a novel method for combining both EEG signal analysis and facial emotion recognition through video analysis to successfully categorize depression into various levels. For this aim, power spectrum of three frequency bands (alpha, beta, and theta) and the whole bands of EEG are used as features along with standard deviation, mean and entropy.
{"title":"EEG signal and video analysis based depression indication","authors":"Yashika Katyal, Suhas V. Alur, Shipra Dwivedi, R. Menaka","doi":"10.1109/ICACCCT.2014.7019320","DOIUrl":"https://doi.org/10.1109/ICACCCT.2014.7019320","url":null,"abstract":"Depression is a common phenomenon in the present scenario. Due to the fast pace at which our lives move and immense pressure that we face adolescents, office goers and even the elders face depression. Diagnosing depression in the early curable stages is very important and may even save the life of a patient. EEG signal analysis has been used for medical research like epilepsy, sleep disorder, insomnia etc. Similarly, video signal analysis has been used for facial features detection, eye movement, emotion recognition etc. Collaborating both the methods accuracy of depression detection can be improved upon. This paper describes a novel method for combining both EEG signal analysis and facial emotion recognition through video analysis to successfully categorize depression into various levels. For this aim, power spectrum of three frequency bands (alpha, beta, and theta) and the whole bands of EEG are used as features along with standard deviation, mean and entropy.","PeriodicalId":239918,"journal":{"name":"2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121161322","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 : 2014-05-08DOI: 10.1109/ICACCCT.2014.7019405
A. S. Deepiga, Senthil Velan S, C. Babu
Service Oriented Architecture (SOA) is an architectural style used to provide services to consumers that promotes loose coupling between services. The scattered and tangled functionalities modeled in an SOA application can be redesigned using Aspect Oriented Programming (AOP). This results in two sets of services, the first set having services for the base functionalities and the other modeling cross-cutting functionalities. During compilation, cross-cutting functionalities in the second set are woven to the functionalities modeled in the first set. By introducing AOP in SOA, the quality attributes such as re-usability, extendibility and maintainability can be improved. The objective of this paper is to perform an empirical investigation by quantitatively measuring the effect of introducing Aspect Orientation (AO) in SOA by developing with multiple versions of a given application. An AO based SOA application (University Automation System) for automating the functionalities of a typical University with multiple versions has been developed as an experimental test bed. An equivalent set of versions without introducing aspectization are also developed in parallel. The values of the AOP metrics are measured for the different versions of University Automation System both aspectized and unaspectized. The measured values show that the quality attributes namely maintainability, reusability and extendibility improve whereas the complexity of the application decreases during the evolution of the case study application.
{"title":"Empirical investigation of introducing Aspect Oriented Programming across versions of an SOA application","authors":"A. S. Deepiga, Senthil Velan S, C. Babu","doi":"10.1109/ICACCCT.2014.7019405","DOIUrl":"https://doi.org/10.1109/ICACCCT.2014.7019405","url":null,"abstract":"Service Oriented Architecture (SOA) is an architectural style used to provide services to consumers that promotes loose coupling between services. The scattered and tangled functionalities modeled in an SOA application can be redesigned using Aspect Oriented Programming (AOP). This results in two sets of services, the first set having services for the base functionalities and the other modeling cross-cutting functionalities. During compilation, cross-cutting functionalities in the second set are woven to the functionalities modeled in the first set. By introducing AOP in SOA, the quality attributes such as re-usability, extendibility and maintainability can be improved. The objective of this paper is to perform an empirical investigation by quantitatively measuring the effect of introducing Aspect Orientation (AO) in SOA by developing with multiple versions of a given application. An AO based SOA application (University Automation System) for automating the functionalities of a typical University with multiple versions has been developed as an experimental test bed. An equivalent set of versions without introducing aspectization are also developed in parallel. The values of the AOP metrics are measured for the different versions of University Automation System both aspectized and unaspectized. The measured values show that the quality attributes namely maintainability, reusability and extendibility improve whereas the complexity of the application decreases during the evolution of the case study application.","PeriodicalId":239918,"journal":{"name":"2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122306530","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 : 2014-05-08DOI: 10.1109/ICACCCT.2014.7019434
A. Prasanthi, Sindhu T.K
FACTS, is an effective means to enhance capacity of existing power transmission network to their maximum limits. This paper deals with an approach for the optimal allocation of FACTS devices in a power system network to improve line loadability and provide voltage support and thus minimize total generation cost. Minimizing total generation cost implies optimal scheduling of generation by different generator units to satisfy load demand. The same objective is analysed in a normal power system and to a system with the integration of wind energy. In the wind energy integrated system the objective function is to minimize the standard deviation of voltage in the system so as to reduce the voltage flicker. As FACTS devices are costly devices and improper placement leads to voltage instability, optimal allocation of FACTS devices is important. Particle Swarm Optimization method is used for optimization and is implemented using MATLAB programming.
{"title":"Optimal placement and rating of FACTS devices for congestion management in power system without and with wind energy integration","authors":"A. Prasanthi, Sindhu T.K","doi":"10.1109/ICACCCT.2014.7019434","DOIUrl":"https://doi.org/10.1109/ICACCCT.2014.7019434","url":null,"abstract":"FACTS, is an effective means to enhance capacity of existing power transmission network to their maximum limits. This paper deals with an approach for the optimal allocation of FACTS devices in a power system network to improve line loadability and provide voltage support and thus minimize total generation cost. Minimizing total generation cost implies optimal scheduling of generation by different generator units to satisfy load demand. The same objective is analysed in a normal power system and to a system with the integration of wind energy. In the wind energy integrated system the objective function is to minimize the standard deviation of voltage in the system so as to reduce the voltage flicker. As FACTS devices are costly devices and improper placement leads to voltage instability, optimal allocation of FACTS devices is important. Particle Swarm Optimization method is used for optimization and is implemented using MATLAB programming.","PeriodicalId":239918,"journal":{"name":"2014 IEEE International Conference on Advanced Communications, Control and Computing Technologies","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127140273","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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