{"title":"基于多模型预测控制策略的输电网电压协调控制","authors":"Jia-lin Bai, I. Erlich","doi":"10.1109/ISGTEurope.2018.8571851","DOIUrl":null,"url":null,"abstract":"This paper proposes a multi-model based predictive control (MMPC) strategy for the coordinated voltage control of the transmission grid that may operate under diverse anticipated conditions. Since both Kalman filtering and optimization process are based on mathematical model, a model database representing the critical operating conditions is required. For unrepresented conditions, MMPC is designed to be robust by setting the noise model of Kalman filter and by tuning the optimization window of MMPC. In each control cycle, MMPC searches for the optimal coordination of Automatic Voltage Regulators and Static Var Compensators. The case studies take into account two types of operation changes: load change over 24 hour and generator in/out of service. In different simulation tests, in comparison with single -model based control strategy, the superiority and robustness of MMPC following a load increase disturbance are demonstrated.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Coordinated Voltage Control for Transmission Grid Based on Multi-model Predictive Control Strategy\",\"authors\":\"Jia-lin Bai, I. Erlich\",\"doi\":\"10.1109/ISGTEurope.2018.8571851\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a multi-model based predictive control (MMPC) strategy for the coordinated voltage control of the transmission grid that may operate under diverse anticipated conditions. Since both Kalman filtering and optimization process are based on mathematical model, a model database representing the critical operating conditions is required. For unrepresented conditions, MMPC is designed to be robust by setting the noise model of Kalman filter and by tuning the optimization window of MMPC. In each control cycle, MMPC searches for the optimal coordination of Automatic Voltage Regulators and Static Var Compensators. The case studies take into account two types of operation changes: load change over 24 hour and generator in/out of service. In different simulation tests, in comparison with single -model based control strategy, the superiority and robustness of MMPC following a load increase disturbance are demonstrated.\",\"PeriodicalId\":302863,\"journal\":{\"name\":\"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISGTEurope.2018.8571851\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGTEurope.2018.8571851","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Coordinated Voltage Control for Transmission Grid Based on Multi-model Predictive Control Strategy
This paper proposes a multi-model based predictive control (MMPC) strategy for the coordinated voltage control of the transmission grid that may operate under diverse anticipated conditions. Since both Kalman filtering and optimization process are based on mathematical model, a model database representing the critical operating conditions is required. For unrepresented conditions, MMPC is designed to be robust by setting the noise model of Kalman filter and by tuning the optimization window of MMPC. In each control cycle, MMPC searches for the optimal coordination of Automatic Voltage Regulators and Static Var Compensators. The case studies take into account two types of operation changes: load change over 24 hour and generator in/out of service. In different simulation tests, in comparison with single -model based control strategy, the superiority and robustness of MMPC following a load increase disturbance are demonstrated.