{"title":"A stochastic power flow-based static security assessment under uncertain scenarios","authors":"Yuyue Zhang, Xin Tian, Lina Zhang","doi":"10.3389/fenrg.2024.1429160","DOIUrl":null,"url":null,"abstract":"With the gradual increase in the grid-connected capacity of renewable energy sources, the uncertainty in the operation of power systems has increased, posing challenges to static security assessment considering N-1 contingency scanning. To address this, this article first establishes a static security calculation model based on stochastic power flow. Then, it proposes stochastic component-level safety indexes and system-level safety indexes. Finally, using the analytic hierarchy process to analyze the obtained weighting coefficients, the article establishes a system of static security assessment indexes for power systems. A data-driven simulation method based on extreme gradient boosting (XGBoost) is proposed to tackle the high time consumption of multi-scenario static security assessment, which brings difficulties in model debugging and application. Case studies based on the IEEE 39-bus system demonstrate the effectiveness of the proposed model and the rapidity of the data-driven approach.","PeriodicalId":503838,"journal":{"name":"Frontiers in Energy Research","volume":"83 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Energy Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fenrg.2024.1429160","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the gradual increase in the grid-connected capacity of renewable energy sources, the uncertainty in the operation of power systems has increased, posing challenges to static security assessment considering N-1 contingency scanning. To address this, this article first establishes a static security calculation model based on stochastic power flow. Then, it proposes stochastic component-level safety indexes and system-level safety indexes. Finally, using the analytic hierarchy process to analyze the obtained weighting coefficients, the article establishes a system of static security assessment indexes for power systems. A data-driven simulation method based on extreme gradient boosting (XGBoost) is proposed to tackle the high time consumption of multi-scenario static security assessment, which brings difficulties in model debugging and application. Case studies based on the IEEE 39-bus system demonstrate the effectiveness of the proposed model and the rapidity of the data-driven approach.