Resilient Power Systems Operation with Offshore Wind Farms and Cloud Data Centers  

作　　者：Shengwei Liu Yuanzheng Li Xuan Liu Tianyang Zhao Peng Wang 

机构地区：[1]Energy and Electricity Research Center,Jinan University,Zhuhai,519070,China [2]Huazhong University of Science and Technology,Wuhan,430074,China [3]North China Electric Power University,Beijing,102206,China [4]School of Electrical and Electronic Engineering,Nanyang Technological University,Singapore 639798,Singapore

出　　处：《CSEE Journal of Power and Energy Systems》2023年第6期1985-1998,共14页中国电机工程学会电力与能源系统学报（英文）

基　　金：the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources under Grant LAPS21002;the State Key Laboratory of Disaster Prevention and Reduction for Power Grid Transmission and Distribution Equipment under Grant SGHNFZ00FBYJJS2100047.

摘　　要：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 IEEERTS 24 system,which includes 4 data centers and 5 offshore wind farms.

关 键 词：Cloud computing data center decomposition HURRICANE offshore wind farm resilience enhancement total life simulation unit commitment 

分 类 号：TM614[电气工程—电力系统及自动化]