{"title":"配电系统中无需测量的母线电压稳定指数预测","authors":"Mohammad Hasan Hemmatpour","doi":"10.1049/gtd2.13211","DOIUrl":null,"url":null,"abstract":"<p>In power systems, voltage collapse during overload can be a significant threat. Accurate forecasting of critical operational conditions within power grids is crucial for preventing such situations. Precise predictions of voltage collapse enable operators to monitor the system closely and implement necessary corrective measures promptly, avoiding potential issues. However, monitoring networks can be costly due to the numerous loads and transformers in the distribution system. A comprehensive approach known as the voltage stability index (VSI) forecast without measurement buses (VFWMB) has been introduced to address this challenge. This approach involves innovative methods, including the seeking observation zone with weight least square (SOZWLS) technique for determining the number and location of measurements in the network based on its topology. Additionally, short-term load forecasting is performed using the long short-term memory (LSTM) forecasting method, followed by voltage estimation for buses without measurements. Finally, the proposed method calculates the modern voltage stability index for distribution systems (MVSIDS) for upcoming hours. All indicators and techniques in the VFWMB method have been validated. The algorithm has been thoroughly tested on various networks, including small and large, balanced and unbalanced, and both real and test networks, showing high efficiency in the electricity industry.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13211","citationCount":"0","resultStr":"{\"title\":\"Prediction of voltage stability index in buses without measurement in distribution systems\",\"authors\":\"Mohammad Hasan Hemmatpour\",\"doi\":\"10.1049/gtd2.13211\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In power systems, voltage collapse during overload can be a significant threat. Accurate forecasting of critical operational conditions within power grids is crucial for preventing such situations. Precise predictions of voltage collapse enable operators to monitor the system closely and implement necessary corrective measures promptly, avoiding potential issues. However, monitoring networks can be costly due to the numerous loads and transformers in the distribution system. A comprehensive approach known as the voltage stability index (VSI) forecast without measurement buses (VFWMB) has been introduced to address this challenge. This approach involves innovative methods, including the seeking observation zone with weight least square (SOZWLS) technique for determining the number and location of measurements in the network based on its topology. Additionally, short-term load forecasting is performed using the long short-term memory (LSTM) forecasting method, followed by voltage estimation for buses without measurements. Finally, the proposed method calculates the modern voltage stability index for distribution systems (MVSIDS) for upcoming hours. All indicators and techniques in the VFWMB method have been validated. The algorithm has been thoroughly tested on various networks, including small and large, balanced and unbalanced, and both real and test networks, showing high efficiency in the electricity industry.</p>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-06-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/gtd2.13211\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/gtd2.13211\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/gtd2.13211","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
Prediction of voltage stability index in buses without measurement in distribution systems
In power systems, voltage collapse during overload can be a significant threat. Accurate forecasting of critical operational conditions within power grids is crucial for preventing such situations. Precise predictions of voltage collapse enable operators to monitor the system closely and implement necessary corrective measures promptly, avoiding potential issues. However, monitoring networks can be costly due to the numerous loads and transformers in the distribution system. A comprehensive approach known as the voltage stability index (VSI) forecast without measurement buses (VFWMB) has been introduced to address this challenge. This approach involves innovative methods, including the seeking observation zone with weight least square (SOZWLS) technique for determining the number and location of measurements in the network based on its topology. Additionally, short-term load forecasting is performed using the long short-term memory (LSTM) forecasting method, followed by voltage estimation for buses without measurements. Finally, the proposed method calculates the modern voltage stability index for distribution systems (MVSIDS) for upcoming hours. All indicators and techniques in the VFWMB method have been validated. The algorithm has been thoroughly tested on various networks, including small and large, balanced and unbalanced, and both real and test networks, showing high efficiency in the electricity industry.