典型文献
Data-driven distribution network topology identification considering correlated generation power of distributed energy resource
文献摘要：
This paper proposes a data-driven topology identification method for distribution systems with dis-tributed energy resources(DERs).First,a neural network is trained to depict the relationship between nodal power injections and voltage magnitude measurements,and then it is used to generate synthetic measurements under independent nodal power injections,thus eliminating the influence of correlated nodal power injections on topology identification.Second,a maximal information coefficient-based maximum spanning tree algorithm is developed to obtain the network topology by evaluating the dependence among the synthetic measurements.The proposed method is tested on different distribution networks and the simulation results are compared with those of other methods to validate the effectiveness of the proposed method.
文献关键词：
中图分类号：
作者姓名：
Jialiang CHEN;Xiaoyuan XU;Zheng YAN;Han WANG
作者机构：
Key Laboratory of Control of Power Transmission and Conversion(Ministry of Education),Shanghai Jiao Tong University,Shanghai 200240,China
文献出处：
引用格式：
[1]Jialiang CHEN;Xiaoyuan XU;Zheng YAN;Han WANG-.Data-driven distribution network topology identification considering correlated generation power of distributed energy resource)[J].能源前沿,2022(01):121-129
A类：
B类：
Data,driven,distribution,topology,identification,considering,correlated,generation,power,distributed,energy,This,paper,proposes,data,systems,resources,DERs,First,neural,trained,depict,relationship,between,nodal,injections,voltage,magnitude,measurements,then,used,generate,synthetic,under,independent,thus,eliminating,influence,Second,maximal,information,coefficient,maximum,spanning,tree,algorithm,developed,obtain,by,evaluating,dependence,among,proposed,tested,different,networks,simulation,results,compared,those,other,methods,validate,effectiveness
AB值：
0.567451
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