Open AccessAffine arithmetic‐based power flow algorithm considering uncertainty for hybrid AC/DC grids incorporating VSCs
Author(s) -
Lu Fang,
Du Pingjing,
Liu Hongda,
Liu Fanming
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.6095
Subject(s) - affine arithmetic , converters , voltage source , grid , computer science , randomness , control theory (sociology) , affine transformation , algorithm , power (physics) , electric power system , power flow , voltage , mathematical optimization , mathematics , electrical engineering , engineering , control (management) , statistics , physics , geometry , quantum mechanics , artificial intelligence , pure mathematics
The randomness of new energy generation and variation in load demands bring uncertainty to large AC/DC grids. Traditional deterministic power flow equations have difficulty coping with the uncertainties of new energy generation and load. Here, an affine arithmetic (AA)‐based uncertainty power flow algorithm for hybrid AC/DC grids incorporating voltage source converters (VSCs) is presented. VSC station and DC grid models are established using AA. Diverse VSC control modes are considered in the power flow iterations. A comparison using the Monte–Carlo method shows that the proposed algorithm is able to obtain a feasible solution. The proposed method can be used by power system operators and planners to monitor and control AC/DC grids under various uncertainties.