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Optimal operation of Internet Data Center with PV and energy storage type of UPS clusters
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作者 Man Chen Yuxin Zhao +2 位作者 Yuxuan Li Peng Peng Xisheng Tang 《Global Energy Interconnection》 EI CSCD 2024年第1期61-70,共10页
With the development of green data centers,a large number of Uninterruptible Power Supply(UPS)resources in Internet Data Center(IDC)are becoming idle assets owing to their low utilization rate.The revitalization of th... With the development of green data centers,a large number of Uninterruptible Power Supply(UPS)resources in Internet Data Center(IDC)are becoming idle assets owing to their low utilization rate.The revitalization of these idle UPS resources is an urgent problem that must be addressed.Based on the energy storage type of the UPS(EUPS)and using renewable sources,a solution for IDCs is proposed in this study.Subsequently,an EUPS cluster classification method based on the concept of shared mechanism niche(CSMN)was proposed to effectively solve the EUPS control problem.Accordingly,the classified EUPS aggregation unit was used to determine the optimal operation of the IDC.An IDC cost minimization optimization model was established,and the Quantum Particle Swarm Optimization(QPSO)algorithm was adopted.Finally,the economy and effectiveness of the three-tier optimization framework and model were verified through three case studies. 展开更多
关键词 Three-tier optimization framework Energy storage type of the UPS EUPS cluster classification method Quantum Particle Swarm Optimization
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Analytical Model and Topology Optimization of Doubly-fed Induction Generator
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作者 Lu Sun Haoyu Kang +4 位作者 Jin Wang Zequan Li Jianjun Liu Yiming Ma Libing Zhou 《CES Transactions on Electrical Machines and Systems》 EI CSCD 2024年第2期162-169,共8页
As the core component of energy conversion for large wind turbines,the output performance of doubly-fed induction generators (DFIGs) plays a decisive role in the power quality of wind turbines.To realize the fast and ... As the core component of energy conversion for large wind turbines,the output performance of doubly-fed induction generators (DFIGs) plays a decisive role in the power quality of wind turbines.To realize the fast and accurate design optimization of DFIGs,this paper proposes a novel hybriddriven surrogate-assisted optimization method.It firstly establishes an accurate subdomain model of DFIGs to analytically predict performance indexes.Furthermore,taking the inexpensive analytical dataset produced by the subdomain model as the source domain and the expensive finite element analysis dataset as the target domain,a high-precision surrogate model is trained in a transfer learning way and used for the subsequent multi-objective optimization process.Based on this model,taking the total harmonic distortion of electromotive force,cogging torque,and iron loss as objectives,and the slot and inner/outer diameters as parameters for optimizing the topology,achieve a rapid and accurate electromagnetic design for DFIGs.Finally,experiments are carried out on a 3MW DFIG to validate the effectiveness of the proposed method. 展开更多
关键词 Doubly-fed induction generators Accurate subdomain model Surrogate-assisted Transfer learning
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