Research On Network Reconstructing Sequences During The Early Period Of Black-start Restoration

Black-start restoration is an effective method for power system restoration after blackout. Resarch on black-start restoration is of great significance to speed up the restoration process, reduce the burden of restoration control work and the losses of power outage. As the most important stage of the black-start restoration, network reconstruction and its optimization strategy have great effects on the efficiency of power system restoration. The most important and difficult work of the study on network reconstructing strategy is the coordination of network reconfiguration, the unit start-up and load restoration. On the basis of analyzing the impact factors of unit start-up sequence, a mathematical model of network reconstruction is established with consideration of unit start-up sequence optimization. The shortest path method and crossed particle swarm optimization algorithm are combined to solve the network reconstruction problem. In this way, as much generating capacity as possible can be restored. For the balance problem of generating power and load, a load importance evaluation model and load recovery strategy are proposed in the thesis. On the one hand, the load importance evaluation model is established by integrating the node importance and load importance with transmission path cost, the DPSO algorithm is used to determine the prior restored load buses with the aim of the system active power balance. On the other hand, the available incremental power output in the current period is used to guide the load restoration, so the system load can be restored orderly and efficiently.