Yuerong Yang;Shunjiang Lin;Qiong Wang;Mingbo Liu;Qifeng Li
{"title":"考虑风电不确定性的多$N-1$突发事件下静态电压稳定的预防纠偏控制","authors":"Yuerong Yang;Shunjiang Lin;Qiong Wang;Mingbo Liu;Qifeng Li","doi":"10.17775/CSEEJPES.2023.00310","DOIUrl":null,"url":null,"abstract":"An optimal preventive-corrective control model for static voltage stability under multiple <tex>$N-1$</tex> contingencies considering the wind power uncertainty is established in this paper. The objective is to minimize the control variable adjustment cost including the load shedding cost of each contingency. The chance constraints of the static voltage stability margins (SVSMs) in the normal operation state and after each <tex>$N-1$</tex> contingency are included. The approximate functions between the probability density functions (PDFs) of SVSMs and load shedding quantity with respect to preventive control variables are obtained to transform the expectation of load shedding quantity and the SVSM chance constraints into deterministic expressions. An approximate sequential convex quadratically constrained quadratic programming iteration method is proposed to solve the optimal control model. In each iteration, the approximate expressions and range are determined by the generated data samples. Moreover, a fast approximation calculation method of second-order matrices is proposed. By the naive Bayes classifier, the most severe <tex>$N-1$</tex> contingencies are selected to replace all the contingencies to be added to the optimization model to improve the computational efficiency. Case studies on the IEEE-39 bus system and an actual provincial power grid demonstrate the effectiveness and efficiency of the proposed method.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":"11 4","pages":"1466-1480"},"PeriodicalIF":5.9000,"publicationDate":"2024-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520197","citationCount":"0","resultStr":"{\"title\":\"Preventive-Corrective Control for Static Voltage Stability Under Multiple $N-1$ Contingencies Considering Wind Power Uncertainty\",\"authors\":\"Yuerong Yang;Shunjiang Lin;Qiong Wang;Mingbo Liu;Qifeng Li\",\"doi\":\"10.17775/CSEEJPES.2023.00310\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An optimal preventive-corrective control model for static voltage stability under multiple <tex>$N-1$</tex> contingencies considering the wind power uncertainty is established in this paper. The objective is to minimize the control variable adjustment cost including the load shedding cost of each contingency. The chance constraints of the static voltage stability margins (SVSMs) in the normal operation state and after each <tex>$N-1$</tex> contingency are included. The approximate functions between the probability density functions (PDFs) of SVSMs and load shedding quantity with respect to preventive control variables are obtained to transform the expectation of load shedding quantity and the SVSM chance constraints into deterministic expressions. An approximate sequential convex quadratically constrained quadratic programming iteration method is proposed to solve the optimal control model. In each iteration, the approximate expressions and range are determined by the generated data samples. Moreover, a fast approximation calculation method of second-order matrices is proposed. By the naive Bayes classifier, the most severe <tex>$N-1$</tex> contingencies are selected to replace all the contingencies to be added to the optimization model to improve the computational efficiency. Case studies on the IEEE-39 bus system and an actual provincial power grid demonstrate the effectiveness and efficiency of the proposed method.\",\"PeriodicalId\":10729,\"journal\":{\"name\":\"CSEE Journal of Power and Energy Systems\",\"volume\":\"11 4\",\"pages\":\"1466-1480\"},\"PeriodicalIF\":5.9000,\"publicationDate\":\"2024-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10520197\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CSEE Journal of Power and Energy Systems\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10520197/\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CSEE Journal of Power and Energy Systems","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10520197/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Preventive-Corrective Control for Static Voltage Stability Under Multiple $N-1$ Contingencies Considering Wind Power Uncertainty
An optimal preventive-corrective control model for static voltage stability under multiple $N-1$ contingencies considering the wind power uncertainty is established in this paper. The objective is to minimize the control variable adjustment cost including the load shedding cost of each contingency. The chance constraints of the static voltage stability margins (SVSMs) in the normal operation state and after each $N-1$ contingency are included. The approximate functions between the probability density functions (PDFs) of SVSMs and load shedding quantity with respect to preventive control variables are obtained to transform the expectation of load shedding quantity and the SVSM chance constraints into deterministic expressions. An approximate sequential convex quadratically constrained quadratic programming iteration method is proposed to solve the optimal control model. In each iteration, the approximate expressions and range are determined by the generated data samples. Moreover, a fast approximation calculation method of second-order matrices is proposed. By the naive Bayes classifier, the most severe $N-1$ contingencies are selected to replace all the contingencies to be added to the optimization model to improve the computational efficiency. Case studies on the IEEE-39 bus system and an actual provincial power grid demonstrate the effectiveness and efficiency of the proposed method.
期刊介绍:
The CSEE Journal of Power and Energy Systems (JPES) is an international bimonthly journal published by the Chinese Society for Electrical Engineering (CSEE) in collaboration with CEPRI (China Electric Power Research Institute) and IEEE (The Institute of Electrical and Electronics Engineers) Inc. Indexed by SCI, Scopus, INSPEC, CSAD (Chinese Science Abstracts Database), DOAJ, and ProQuest, it serves as a platform for reporting cutting-edge theories, methods, technologies, and applications shaping the development of power systems in energy transition. The journal offers authors an international platform to enhance the reach and impact of their contributions.