Open AccessImproved affine arithmetic based optimisation model for interval power flow analysis
Author(s) -
Xu Chao,
Gu Wei,
Gao Fei,
Song Xiaohui,
Meng Xiaoli,
Fan Miao
Publication year - 2016
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.2016.0601
Subject(s) - affine arithmetic , benchmark (surveying) , interval arithmetic , mathematical optimization , affine transformation , interval (graph theory) , linear programming , computer science , monte carlo method , power flow , algorithm , electric power system , power (physics) , mathematics , mathematical analysis , physics , combinatorics , quantum mechanics , pure mathematics , bounded function , statistics , geodesy , geography
Power flow (PF) problem need to be further studied when confronted with uncertainties brought in by the increasing use of renewable energy. This study proposes a new solution method based on linear approximation of the affine arithmetic (AA) based PF model and optimal solution technique incorporated with boundary load flow framework under generation and load data uncertainties. In each iteration solution step, non‐linear interval PF problem is modelled by the approximation technique with AA. Boundaries of state variables are explored by solving linear programming models with constraints reformed at given operating points. After optimisation process, new operating point is obtained and updated for further iteration solution step. Application of the proposed methodology is implemented in several IEEE benchmark test systems and results are demonstrated in details. Comparisons between the previous interval method and Monte Carlo simulations verify the effectiveness and better performance of the proposed method.