Robust optimisation for AC–DC power flow based on second‐order cone programming. Issue 13 (19th January 2018)

• Record Type: Journal Article
• Authors: Zhou, Ye; Tian, Yuan; Wang, Keyou; Ghandhari, Mehrdad
• Is Part Of: Journal of engineering. Volume 2017:Issue 13(2017)
• Page Start: 2164
• Page End: 2167
• Publication Date: 2018-01-19
• Subjects: load flow -- optimisation -- power generation scheduling -- AC generators -- power generation economics -- cost reduction; expected operational cost minimisation -- modified AC‐DC IEEE 30‐bus -- generator output rescheduling -- base‐point generation -- AAROPF formulation -- affinely adjustable robust OPF formulation -- SOC problem -- RES uncertainty -- renewable energy source -- AC‐DC OPF -- AC‐DC optimal power flow -- adjustable robust optimisation method -- second‐order cone programming -- robust optimisation; Engineering -- Periodicals; Engineering; Electronic journals; Periodicals; 620.005
• DOI: 10.1049/joe.2017.0713
• Languages: English
• ISSNs: 2051-3305

Abstract

Abstract : 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.