An Improved Label Propagation Algorithm-Based Method to Develop Sectionalizing Strategies for Parallel Power System Restoration

The first task of parallel power system restoration is to sectionalize the blackout system into multiple subsystems. This paper applies the complex network community discovery theory into this sectionalizing problem and proposes an improved label propagation algorithm-based sectionalizing method considering the system topology and operation before blackouts. Firstly, each blackstart (BS) unit bus is marked with a different subsystem label. A label propagation matrix is calculated based on the active power of branches before the blackout. Then, to avoid the label oscillation, a novel label impact strategy considering the influence of the bus label itself is developed to improve the label propagation matrix. The buses' labels propagate to neighboring buses as the improved label propagation matrix until they do not change. The initial sectionalizing strategy is obtained through classifying the buses with the same label in the same subsystem. Finally, the sectionalizing constraints are used to evaluate the feasibility of the initial strategy. For the initial strategy that does not satisfy the constraints, a refining method to minimize the absolute value of active power exchange among subsystems is proposed to determine the final sectionalizing strategy based on it. Case studies on IEEE 39-bus and IEEE 118-bus test systems verify the effectiveness of the proposed method. The results indicate that the proposed method has advantages in creating strongly connected subsystems.