TY - GEN
T1 - A Novel Discontinous Galerkin Method for the DC IR-Drop Analysis of Power Distribution Networks
AU - Yang, Anfa
AU - Tang, Min
AU - Mao, Junfa
AU - Li, Ping
AU - Bagci, Hakan
N1 - KAUST Repository Item: Exported on 2022-03-25
Acknowledgements: This work is supported by the National Key Research and Develop Program of China 2020YFA0709800. It’s also supported by NSFC
620712290
PY - 2021/7/28
Y1 - 2021/7/28
N2 - A Robin transmission condition (RTC) enhanced discontinuous Galerkin method (DGM) is proposed for direct current IR-Drop analysis of global PDN. Although DGM is one kind of domain decomposition method (DDM) naturally, it suffers much more number of unknowns compared with finite element method (FEM). To overcome this drawback, RTC is introduced to serve as a transmission condition apart from the numerical flux. As a result, the volume unknowns appeared in traditional DG method is elegantly transferred to the interface among neighboring subdomains. Thus, the DoFs are markedly reduced. To validate the proposed method, a representative numerical result is presented at the last of this paper.
AB - A Robin transmission condition (RTC) enhanced discontinuous Galerkin method (DGM) is proposed for direct current IR-Drop analysis of global PDN. Although DGM is one kind of domain decomposition method (DDM) naturally, it suffers much more number of unknowns compared with finite element method (FEM). To overcome this drawback, RTC is introduced to serve as a transmission condition apart from the numerical flux. As a result, the volume unknowns appeared in traditional DG method is elegantly transferred to the interface among neighboring subdomains. Thus, the DoFs are markedly reduced. To validate the proposed method, a representative numerical result is presented at the last of this paper.
UR - http://hdl.handle.net/10754/675940
UR - https://ieeexplore.ieee.org/document/9582082/
UR - http://www.scopus.com/inward/record.url?scp=85119331131&partnerID=8YFLogxK
U2 - 10.23919/ACES-China52398.2021.9582082
DO - 10.23919/ACES-China52398.2021.9582082
M3 - Conference contribution
SN - 9781733509619
BT - 2021 International Applied Computational Electromagnetics Society (ACES-China) Symposium
PB - IEEE
ER -