Three‐phase power flow calculation considering probability and interval uncertainties for power distribution systems. Issue 15 (15th July 2019)

• Record Type: Journal Article
• Authors: Wang, Chun; Ao, Xin; Fu, Wenbin
• Is Part Of: IET generation, transmission & distribution. Volume 13:Issue 15(2019)
• Page Start: 3334
• Page End: 3345
• Publication Date: 2019-07-15
• Subjects: load flow -- power distribution -- probability -- distribution networks -- Monte Carlo methods; interval uncertainties -- power distribution systems -- approximate method -- affine linear three‐phase power flow -- Latin hypercube sampling method -- affine node voltage -- affine inverse operation -- conservative estimation method -- interval variables -- probabilistic power flow -- LHS‐Monte‐Carlo simulation method -- phase power flow calculation -- probability -- stochastic nature -- weather condition -- interval properties; Electric power production -- Periodicals; Electric power transmission -- Periodicals; Electric power distribution -- Periodicals; 621.3105
• DOI: 10.1049/iet-gtd.2018.6777
• Languages: English
• ISSNs: 1751-8687

Abstract

Abstract : Factors such as the stochastic nature of weather condition and arbitrariness of loads make power flow have both probability and interval properties. In order to solve power flow considering probability and interval uncertainties for power distribution systems, an approximate method, which combines affine linear three‐phase power flow and Latin hypercube sampling (LHS) method, is proposed. The formulation of affine node voltage is derived based on affine inverse operation and conservative estimation method. Bound influences of interval variables (BIIVs) of affine node voltage are used to determine the upper bound and lower bound of the result of probabilistic power flow. Further decomposition of BIIVs, which contributes to reduce the conservation of results, is given. The effectiveness of the proposed method is verified using the modified IEEE 13‐bus system and IEEE 123‐bus system by comparing with LHS‐Monte‐Carlo simulation method.