title: Automatic Learning of Fine Operating Rules for Online Power System Security Control.
abstract: Fine operating rules for security control and an automatic system for their online discovery were developed to adapt to the development of smart grids. The automatic system uses the real-time system state to determine critical flowgates, and then a continuation power flow-based security analysis is used to compute the initial transfer capability of critical flowgates. Next, the system applies the Monte Carlo simulations to expected short-term operating condition changes, feature selection, and a linear least squares fitting of the fine operating rules. The proposed system was validated both on an academic test system and on a provincial power system in China. The results indicated that the derived rules provide accuracy and good interpretability and are suitable for real-time power system security control. The use of high-performance computing systems enables these fine operating rules to be refreshed online every 15 min.
authors: Hongbin
authors: H
authors: Sun
authors: Feng
authors: F
authors: Zhao
authors: Hao
authors: H
authors: Wang
authors: Kang
authors: K
authors: Wang
authors: Weiyong
authors: W
authors: Jiang
authors: Qinglai
authors: Q
authors: Guo
authors: Boming
authors: B
authors: Zhang
authors: Louis
authors: L
authors: Wehenkel