DC IR-Drop Analysis of Power Distribution Networks by a Robin Transmission Condition Enhanced Discontinuous Galerkin Method
KAUST DepartmentComputational Electromagnetics Laboratory
Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Electrical and Computer Engineering Program
Online Publication Date2021
Print Publication Date2022-01
Permanent link to this recordhttp://hdl.handle.net/10754/673849
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AbstractIn this work, a novel Robin transmission condition (RTC) enhanced discontinuous Galerkin (DG) method is proposed for the DC IR-Drop analysis of power distribution networks with Joule Heating effects included. Unlike the conventional DG method, the proposed DG method straightforwardly applied to discretize the second-order spatial partial differential governing equations for the electrostatic potential Φ and the steady-state temperature T, respectively. The numerical flux in DG used to facilitate the information exchange among neighboring subdomains introduces two additional variables: the current density J for the electrical potential equation and the thermal flux q for the thermal equation. To solve them, at the interface of neighboring subdomains a RTC is presented as the second equation to establish another connection for solutions in neighboring subdomains. With this strategy, the number of degrees of freedom (DoF) involved in the proposed RTC-DG method is dramatically reduced compared with the traditional DG method. The finalized matrix system is solved in a FETI-like procedure, namely, the unknowns are obtained in a subdomain-by-subdomain scheme. Finally, the accuracy and the efficiency of the proposed RTC-DG method is validated by serval representative examples.
CitationYang, A. F., Tang, M., Mao, J. F., Jiang, L. J., Bagci, H., & Li, P. (2021). DC IR-Drop Analysis of Power Distribution Networks by a Robin Transmission Condition Enhanced Discontinuous Galerkin Method. IEEE Transactions on Components, Packaging and Manufacturing Technology, 1–1. doi:10.1109/tcpmt.2021.3131513
SponsorsThis work was supported by the National Key Research and Development Program of China under Grant 2020YFA0709800, in part by Shanghai Committee of Science and Technology under Grant 20501130500, in part by NSFC under Grant 62071290.