D. Truong, V. Ta, M. N. Thi, V. Ngo, H. Nguyen, Xuan-Hoa Pham Thi
{"title":"提高基于光伏电池的微电网系统暂态稳定性","authors":"D. Truong, V. Ta, M. N. Thi, V. Ngo, H. Nguyen, Xuan-Hoa Pham Thi","doi":"10.1109/ICSSE58758.2023.10227148","DOIUrl":null,"url":null,"abstract":"A microgrid system is a distributed energy system that can operate autonomously or connected to the utility grid. It typically consists of renewable energy sources such as solar photovoltaics (PV) and energy storage systems such as batteries. The transient stability of a microgrid system refers to its ability to maintain a stable voltage and frequency when subjected to sudden changes in load or generation. Transient stability can result in system failure or damage to the equipment, which can affect the reliability and resiliency of the system. To address this issue, a new controller has been developed to improve the transient stability of a PV-battery based microgrid system. The proposed Adaptive neuro fuzzy inference system (ANFIS) controller is designed to optimize the power flow between the PV array, battery storage, and load, and to ensure a stable voltage and frequency during sudden changes in the system. The application of this new controller has shown promising results in improving the transient stability of PV-battery based microgrid systems. It has been tested under various operating conditions, including sudden changes in load and solar irradiance, and has demonstrated superior performance compared to traditional control methods such as PID controller.","PeriodicalId":280745,"journal":{"name":"2023 International Conference on System Science and Engineering (ICSSE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improving Transient Stability of a PV-battery based Microgrid System\",\"authors\":\"D. Truong, V. Ta, M. N. Thi, V. Ngo, H. Nguyen, Xuan-Hoa Pham Thi\",\"doi\":\"10.1109/ICSSE58758.2023.10227148\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A microgrid system is a distributed energy system that can operate autonomously or connected to the utility grid. It typically consists of renewable energy sources such as solar photovoltaics (PV) and energy storage systems such as batteries. The transient stability of a microgrid system refers to its ability to maintain a stable voltage and frequency when subjected to sudden changes in load or generation. Transient stability can result in system failure or damage to the equipment, which can affect the reliability and resiliency of the system. To address this issue, a new controller has been developed to improve the transient stability of a PV-battery based microgrid system. The proposed Adaptive neuro fuzzy inference system (ANFIS) controller is designed to optimize the power flow between the PV array, battery storage, and load, and to ensure a stable voltage and frequency during sudden changes in the system. The application of this new controller has shown promising results in improving the transient stability of PV-battery based microgrid systems. It has been tested under various operating conditions, including sudden changes in load and solar irradiance, and has demonstrated superior performance compared to traditional control methods such as PID controller.\",\"PeriodicalId\":280745,\"journal\":{\"name\":\"2023 International Conference on System Science and Engineering (ICSSE)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on System Science and Engineering (ICSSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSSE58758.2023.10227148\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on System Science and Engineering (ICSSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSE58758.2023.10227148","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improving Transient Stability of a PV-battery based Microgrid System
A microgrid system is a distributed energy system that can operate autonomously or connected to the utility grid. It typically consists of renewable energy sources such as solar photovoltaics (PV) and energy storage systems such as batteries. The transient stability of a microgrid system refers to its ability to maintain a stable voltage and frequency when subjected to sudden changes in load or generation. Transient stability can result in system failure or damage to the equipment, which can affect the reliability and resiliency of the system. To address this issue, a new controller has been developed to improve the transient stability of a PV-battery based microgrid system. The proposed Adaptive neuro fuzzy inference system (ANFIS) controller is designed to optimize the power flow between the PV array, battery storage, and load, and to ensure a stable voltage and frequency during sudden changes in the system. The application of this new controller has shown promising results in improving the transient stability of PV-battery based microgrid systems. It has been tested under various operating conditions, including sudden changes in load and solar irradiance, and has demonstrated superior performance compared to traditional control methods such as PID controller.