@article{xuc-guw-gao-son-men-fan-16-aa-improv,
  author = {Xu, Chao and Gu, Wei and Gao, Fei and Song, Xiaohui and Meng, Xiaoli and Fan, Miao},
  title = {Improved Affine Arithmetic Based Optimisation Model for Interval Power Flow Analysis},
  journal = {IET Generation, Transmission {\&} Distribution},
  year = 2016,
  volume = {10},
  number = {15},
  pages = {3910-3918},
  doi = {10.1049/iet-gtd.2016.0601},
  abstract = {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.}
}