Shengwei Liu;Yuanzheng Li;Xuan Liu;Tianyang Zhao;Peng Wang
{"title":"利用海上风电场和云数据中心实现电力系统的弹性运行","authors":"Shengwei Liu;Yuanzheng Li;Xuan Liu;Tianyang Zhao;Peng Wang","doi":"10.17775/CSEEJPES.2022.01470","DOIUrl":null,"url":null,"abstract":"To enhance the resilience of power systems with offshore wind farms (OWFs), a proactive scheduling scheme is proposed to unlock the flexibility of cloud data centers (CDCs) responding to uncertain spatial and temporal impacts induced by hurricanes. The total life simulation (TLS) is adopted to project the local weather conditions at transmission lines and OWFs, before, during, and after the hurricane. The static power curve of wind turbines (WTs) is used to capture the output of OWFs, and the fragility analysis of transmission-line components is used to formulate the time-varying failure rates of transmission lines. A novel distributionally robust ambiguity set is constructed with a discrete support set, where the impacts of hurricanes are depicted by these supports. To minimize load sheddings and dropping workloads, the spatial and temporal demand response capabilities of CDCs according to task migration and delay tolerance are incorporated into resilient management. The flexibilities of CDC's power consumption are integrated into a two-stage distributionally robust optimization problem with conditional value at risk (CVaR). Based on Lagrange duality, this problem is reformulated into its deterministic counterpart and solved by a novel decomposition method with hybrid cuts, admitting fewer iterations and a faster convergence rate. The effectiveness of the proposed resilient management strategy is verified through case studies conducted on the modified IEEE-RTS 24 system, which includes 4 data centers and 5 offshore wind farms.","PeriodicalId":10729,"journal":{"name":"CSEE Journal of Power and Energy Systems","volume":null,"pages":null},"PeriodicalIF":6.9000,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10322691","citationCount":"0","resultStr":"{\"title\":\"Resilient Power Systems Operation with Offshore Wind Farms and Cloud Data Centers\",\"authors\":\"Shengwei Liu;Yuanzheng Li;Xuan Liu;Tianyang Zhao;Peng Wang\",\"doi\":\"10.17775/CSEEJPES.2022.01470\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To enhance the resilience of power systems with offshore wind farms (OWFs), a proactive scheduling scheme is proposed to unlock the flexibility of cloud data centers (CDCs) responding to uncertain spatial and temporal impacts induced by hurricanes. The total life simulation (TLS) is adopted to project the local weather conditions at transmission lines and OWFs, before, during, and after the hurricane. The static power curve of wind turbines (WTs) is used to capture the output of OWFs, and the fragility analysis of transmission-line components is used to formulate the time-varying failure rates of transmission lines. A novel distributionally robust ambiguity set is constructed with a discrete support set, where the impacts of hurricanes are depicted by these supports. To minimize load sheddings and dropping workloads, the spatial and temporal demand response capabilities of CDCs according to task migration and delay tolerance are incorporated into resilient management. The flexibilities of CDC's power consumption are integrated into a two-stage distributionally robust optimization problem with conditional value at risk (CVaR). Based on Lagrange duality, this problem is reformulated into its deterministic counterpart and solved by a novel decomposition method with hybrid cuts, admitting fewer iterations and a faster convergence rate. The effectiveness of the proposed resilient management strategy is verified through case studies conducted on the modified IEEE-RTS 24 system, which includes 4 data centers and 5 offshore wind farms.\",\"PeriodicalId\":10729,\"journal\":{\"name\":\"CSEE Journal of Power and Energy Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.9000,\"publicationDate\":\"2023-11-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10322691\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CSEE Journal of Power and Energy Systems\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10322691/\",\"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/10322691/","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}
Resilient Power Systems Operation with Offshore Wind Farms and Cloud Data Centers
To enhance the resilience of power systems with offshore wind farms (OWFs), a proactive scheduling scheme is proposed to unlock the flexibility of cloud data centers (CDCs) responding to uncertain spatial and temporal impacts induced by hurricanes. The total life simulation (TLS) is adopted to project the local weather conditions at transmission lines and OWFs, before, during, and after the hurricane. The static power curve of wind turbines (WTs) is used to capture the output of OWFs, and the fragility analysis of transmission-line components is used to formulate the time-varying failure rates of transmission lines. A novel distributionally robust ambiguity set is constructed with a discrete support set, where the impacts of hurricanes are depicted by these supports. To minimize load sheddings and dropping workloads, the spatial and temporal demand response capabilities of CDCs according to task migration and delay tolerance are incorporated into resilient management. The flexibilities of CDC's power consumption are integrated into a two-stage distributionally robust optimization problem with conditional value at risk (CVaR). Based on Lagrange duality, this problem is reformulated into its deterministic counterpart and solved by a novel decomposition method with hybrid cuts, admitting fewer iterations and a faster convergence rate. The effectiveness of the proposed resilient management strategy is verified through case studies conducted on the modified IEEE-RTS 24 system, which includes 4 data centers and 5 offshore wind farms.
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.