{"title":"基于DNN的IM-DWT三区距离继电器功率摆动闭锁方案","authors":"Cholleti Sriram, J. Somlal","doi":"10.1080/23080477.2021.2023790","DOIUrl":null,"url":null,"abstract":"ABSTRACT Zone 3 distance relay is linked in the system for protecting the transmission line that acts as a backup relay while the primary relay is in failure due to fault or any other issues; it can act as a secondary relay to clear the problems. Under power swing conditions, the magnitude of current and voltage is entirely in the relay to cause maloperation. In the mal-operative conditions, the relay was not working correctly as well to trip the transmission line. The above problem is mitigated by using the proper method of power swing blocking scheme. In the proposed approach, the supervision-based blocking scheme is introduced to avoid the maloperation of zone 3 distance relay under power swing conditions. The proposed blocking scheme is based on active power and the deviation of source and load voltage. The voltage and current signals are sensed by improved discrete wavelet transform (IM-DWT). It senses the power to generate the coefficients for analysis of the system conditions, whether the system is stressed or not. Here, the most advantageous algorithm of deep neural network (DNN) is utilized to analyze the IM-DWT coefficient for selecting the working function of distance relay. DNN operates two modes based on the coefficient values, namely RDL-1 (state assessment) and RDL-2 (power swing identification). The threshold-based blocking approach chooses the optimal function of DNN. The overall proposed system is implemented in the Western System Coordinating Council (WSCC) IEEE 9 bus system, and the design and performance are verified in MATLAB/Simulink software. The proposed approach is more advantageous and offers a rapid operation to avoid the maloperation of the zone 3 distance relay as compared to the existing methods like support vector machine, artificial neural network, and k-nearest neighbour. GRAPHICAL ABSTRACT","PeriodicalId":53436,"journal":{"name":"Smart Science","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2022-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"IM-DWT with DNN Based Blocking Scheme of Third Zone Distance Relay in Power Swing Condition\",\"authors\":\"Cholleti Sriram, J. Somlal\",\"doi\":\"10.1080/23080477.2021.2023790\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Zone 3 distance relay is linked in the system for protecting the transmission line that acts as a backup relay while the primary relay is in failure due to fault or any other issues; it can act as a secondary relay to clear the problems. Under power swing conditions, the magnitude of current and voltage is entirely in the relay to cause maloperation. In the mal-operative conditions, the relay was not working correctly as well to trip the transmission line. The above problem is mitigated by using the proper method of power swing blocking scheme. In the proposed approach, the supervision-based blocking scheme is introduced to avoid the maloperation of zone 3 distance relay under power swing conditions. The proposed blocking scheme is based on active power and the deviation of source and load voltage. The voltage and current signals are sensed by improved discrete wavelet transform (IM-DWT). It senses the power to generate the coefficients for analysis of the system conditions, whether the system is stressed or not. Here, the most advantageous algorithm of deep neural network (DNN) is utilized to analyze the IM-DWT coefficient for selecting the working function of distance relay. DNN operates two modes based on the coefficient values, namely RDL-1 (state assessment) and RDL-2 (power swing identification). The threshold-based blocking approach chooses the optimal function of DNN. The overall proposed system is implemented in the Western System Coordinating Council (WSCC) IEEE 9 bus system, and the design and performance are verified in MATLAB/Simulink software. The proposed approach is more advantageous and offers a rapid operation to avoid the maloperation of the zone 3 distance relay as compared to the existing methods like support vector machine, artificial neural network, and k-nearest neighbour. GRAPHICAL ABSTRACT\",\"PeriodicalId\":53436,\"journal\":{\"name\":\"Smart Science\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2022-01-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Smart Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/23080477.2021.2023790\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23080477.2021.2023790","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
IM-DWT with DNN Based Blocking Scheme of Third Zone Distance Relay in Power Swing Condition
ABSTRACT Zone 3 distance relay is linked in the system for protecting the transmission line that acts as a backup relay while the primary relay is in failure due to fault or any other issues; it can act as a secondary relay to clear the problems. Under power swing conditions, the magnitude of current and voltage is entirely in the relay to cause maloperation. In the mal-operative conditions, the relay was not working correctly as well to trip the transmission line. The above problem is mitigated by using the proper method of power swing blocking scheme. In the proposed approach, the supervision-based blocking scheme is introduced to avoid the maloperation of zone 3 distance relay under power swing conditions. The proposed blocking scheme is based on active power and the deviation of source and load voltage. The voltage and current signals are sensed by improved discrete wavelet transform (IM-DWT). It senses the power to generate the coefficients for analysis of the system conditions, whether the system is stressed or not. Here, the most advantageous algorithm of deep neural network (DNN) is utilized to analyze the IM-DWT coefficient for selecting the working function of distance relay. DNN operates two modes based on the coefficient values, namely RDL-1 (state assessment) and RDL-2 (power swing identification). The threshold-based blocking approach chooses the optimal function of DNN. The overall proposed system is implemented in the Western System Coordinating Council (WSCC) IEEE 9 bus system, and the design and performance are verified in MATLAB/Simulink software. The proposed approach is more advantageous and offers a rapid operation to avoid the maloperation of the zone 3 distance relay as compared to the existing methods like support vector machine, artificial neural network, and k-nearest neighbour. GRAPHICAL ABSTRACT
期刊介绍:
Smart Science (ISSN 2308-0477) is an international, peer-reviewed journal that publishes significant original scientific researches, and reviews and analyses of current research and science policy. We welcome submissions of high quality papers from all fields of science and from any source. Articles of an interdisciplinary nature are particularly welcomed. Smart Science aims to be among the top multidisciplinary journals covering a broad spectrum of smart topics in the fields of materials science, chemistry, physics, engineering, medicine, and biology. Smart Science is currently focusing on the topics of Smart Manufacturing (CPS, IoT and AI) for Industry 4.0, Smart Energy and Smart Chemistry and Materials. Other specific research areas covered by the journal include, but are not limited to: 1. Smart Science in the Future 2. Smart Manufacturing: -Cyber-Physical System (CPS) -Internet of Things (IoT) and Internet of Brain (IoB) -Artificial Intelligence -Smart Computing -Smart Design/Machine -Smart Sensing -Smart Information and Networks 3. Smart Energy and Thermal/Fluidic Science 4. Smart Chemistry and Materials