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Data-driven Static Equivalence with Physics-informed Koopman Operators
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作者 Wei Lin Changhong Zhao +1 位作者 Maosheng Gao C.Y.Chung 《CSEE Journal of Power and Energy Systems》 SCIE EI CSCD 2024年第1期432-438,共7页
With deployment of measurement units,fitting static equivalent models of distribution networks(DNs)by linear regression has been recognized as an effective method in power flow analysis of a transmission network.Incre... With deployment of measurement units,fitting static equivalent models of distribution networks(DNs)by linear regression has been recognized as an effective method in power flow analysis of a transmission network.Increasing volatility of measurements caused by variable distributed renewable energy sources makes it more difficult to accurately fit such equivalent models.To tackle this challenge,this letter proposes a novel data-driven method to improve equivalency accuracy of DNs with distributed energy resources.This letter provides a new perspective that an equivalent model can be regarded as a mapping from internal conditions and border voltages to border power injections.Such mapping can be established through 1)Koopman operator theory,and 2)physical features of power flow equations at the root node of a DN.Performance of the proposed method is demonstrated on the IEEE 33-bus and IEEE 136-bus test systems connected to a 661-bus utility system. 展开更多
关键词 DATA-DRIVEN distribution network koopman operator theory static equivalent model
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