Open AccessRobust optimisation for AC–DC power flow based on second‐order cone programming
Author(s) -
Zhou Ye,
Tian Yuan,
Wang Keyou,
Ghandhari Mehrdad
Publication year - 2017
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2017.0713
Subject(s) - power flow , realisation , control theory (sociology) , mathematical optimization , robust optimization , power (physics) , electric power system , computer science , renewable energy , point (geometry) , mathematics , engineering , control (management) , electrical engineering , physics , geometry , quantum mechanics , artificial intelligence
This study presents an adjustable robust optimisation method for AC–DC optimal power flow (OPF) considering the uncertainty of renewable energy source (RESs). The optimal power flow of AC–DC system is modelled as a second‐order cone (SOC) problem, and the affinely adjustable robust OPF (AAROPF) formulation is proposed. To apply AAROPF, the base‐point generation is calculated and determined to match the power with forecasted RES output before the realisation of the uncertainty. Also once the uncertainty is revealed, generators reschedule its output through participation factors responding to the uncertain fluctuation of RES output to ensure a feasible solution for all realisations of RES output within a prescribed uncertainty set. Numerical results are obtained on a modified AC–DC IEEE 30‐bus to minimise the expected operational cost. Results reveal a higher cost using AAROPF than the deterministic case, but it obtains a more robust solution with higher successful rates.