Fast Path-Oriented Strategy for Power System Restoration

An effective power system restoration strategy plays an important role in speeding up the recovery of electricity supply in cases of major blackouts. Determining the start-up sequences of non black-start units (NBSUs) is a major concern in power system restoration and is usually formulated as an optimization problem and solved by optimization algorithms including evolutionary algorithms which usually suffer from slow convergence. So far, analytical methods have not yet been widely adopted in formulating power system restoration strategies, and the majority of which are unit-oriented. However, the operation of a transmission network can hardly be integrated into the unit-oriented restoration strategies, thus the iterations between determining the start-up sequences of NBSUs and optimizing the structure of the transmission network concerned become inevitable. In this paper, a graph-theory-based path-oriented power system restoration strategy is proposed for fast, dynamic and highly adaptive power system restoration. A specified minimum spanning tree (SMST) is introduced to model the path-oriented restoration problem considering practical power system constraints, and a modified Prim's algorithm is proposed to generate the SMST. The optimality of the proposed SMST strategy and the performance of the modified Prim's result are also demonstrated. Finally, the feasibility and efficiency of the developed model and method are verified with a modified version of the New England 10-unit 39-bus power system and an actual power system in Guangdong, China.