Title :
An optimization method of unit restoration based on NNIA for power system restoration
Author :
Shaoyan Li; Xueping Gu; Kai Li; Jinzhe Dong
Author_Institution :
School of Electric and Electronic Engineering, North China Electric Power University, Baoding, Hebei 071003, China
fDate :
7/1/2015 12:00:00 AM
Abstract :
A reasonable unit restoration plan is pivotal for the restoration of a power system after blackout. In this paper, the units to be restored are divided into two types: network-layer units and plant-layer units. By analyzing their interactions between each other and the respective contributions to the system restoration, an optimization method of unit restoration based on NNIA for power system restoration is proposed. The continuous unit restoration process is divided into a series of sequential time steps, and three optimization goals of each time step are designed. Nondominated Neighbor Immune Algorithm and the energizing path optimization algorithm proposed in this paper are employed to solve the multi-objective optimization problem. Then, the grey relation projection algorithm is applied to determine the best scheme for each time step. The effectiveness of the proposed method is validated by the optimization results on the New England 10-unit 39-bus power system.
Keywords :
"Artificial neural networks","Power systems","Network topology","Topology","Immune system","Nickel","Optimization"
Conference_Titel :
Power & Energy Society General Meeting, 2015 IEEE
DOI :
10.1109/PESGM.2015.7285762