{"title":"考虑系统频率约束的自适应惯性调整方法","authors":"Xibin Wu, Guan Huang, Weijie Cao, Guohua Cui, Wei-Jing Qiu, Yiwu Ge","doi":"10.1109/ICCSI55536.2022.9970604","DOIUrl":null,"url":null,"abstract":"As the modern energy system transitions towards a cleaner one, the penetration of converter-interfaced distributed resources is increased, resulting in the lack of inertia and damping. Virtual synchronous generator (VSG) control enables these resources to provide inertial support by simulating the characteristics of the synchronous generation. However, the inertia requirements evaluation of the system becomes critical yet challenging for the operator due to the uneven distribution of inertia. The inertia parameter of VSG control is difficult to be adjusted appropriately. Also, the regulation requirements of the system, including the rate of change of frequency (RoCoF) and nadir limits, tend to be ignored in the inertia adjustment process. In this paper, we propose a minimum system inertia estimation model considering the distribution characteristics of system inertia and establish the relationship between the frequency nadir and the control parameters. Also, we design an inertia adjustment method based on the RBF neural network. Significantly, the index constraints of the system are integrated into the inertia adjustment process. A case study on IEEE 9 bus system illustrates the effectiveness of the proposed method.","PeriodicalId":421514,"journal":{"name":"2022 International Conference on Cyber-Physical Social Intelligence (ICCSI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive Inertia Adjustment Method Considering System Frequency Constraints\",\"authors\":\"Xibin Wu, Guan Huang, Weijie Cao, Guohua Cui, Wei-Jing Qiu, Yiwu Ge\",\"doi\":\"10.1109/ICCSI55536.2022.9970604\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the modern energy system transitions towards a cleaner one, the penetration of converter-interfaced distributed resources is increased, resulting in the lack of inertia and damping. Virtual synchronous generator (VSG) control enables these resources to provide inertial support by simulating the characteristics of the synchronous generation. However, the inertia requirements evaluation of the system becomes critical yet challenging for the operator due to the uneven distribution of inertia. The inertia parameter of VSG control is difficult to be adjusted appropriately. Also, the regulation requirements of the system, including the rate of change of frequency (RoCoF) and nadir limits, tend to be ignored in the inertia adjustment process. In this paper, we propose a minimum system inertia estimation model considering the distribution characteristics of system inertia and establish the relationship between the frequency nadir and the control parameters. Also, we design an inertia adjustment method based on the RBF neural network. Significantly, the index constraints of the system are integrated into the inertia adjustment process. A case study on IEEE 9 bus system illustrates the effectiveness of the proposed method.\",\"PeriodicalId\":421514,\"journal\":{\"name\":\"2022 International Conference on Cyber-Physical Social Intelligence (ICCSI)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Cyber-Physical Social Intelligence (ICCSI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSI55536.2022.9970604\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Cyber-Physical Social Intelligence (ICCSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSI55536.2022.9970604","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive Inertia Adjustment Method Considering System Frequency Constraints
As the modern energy system transitions towards a cleaner one, the penetration of converter-interfaced distributed resources is increased, resulting in the lack of inertia and damping. Virtual synchronous generator (VSG) control enables these resources to provide inertial support by simulating the characteristics of the synchronous generation. However, the inertia requirements evaluation of the system becomes critical yet challenging for the operator due to the uneven distribution of inertia. The inertia parameter of VSG control is difficult to be adjusted appropriately. Also, the regulation requirements of the system, including the rate of change of frequency (RoCoF) and nadir limits, tend to be ignored in the inertia adjustment process. In this paper, we propose a minimum system inertia estimation model considering the distribution characteristics of system inertia and establish the relationship between the frequency nadir and the control parameters. Also, we design an inertia adjustment method based on the RBF neural network. Significantly, the index constraints of the system are integrated into the inertia adjustment process. A case study on IEEE 9 bus system illustrates the effectiveness of the proposed method.