The Transient Stability Preventive Control of Power System Based on RBF Neural Network

Abstract:

Article Preview

The transient stability preventive estimation and control is one of the most important tasks of the power system. The traditional time domain simulation method cannot meet the standard of on-line estimation because of its heavy computation burden. In this paper, we realize the on-line estimation of transient stability limits on critical lines of a power system using the favorable approximation ability of RBF network. We choose right samples by off-line count to train the RBF network in order to make the error satisfy demand. Preventive control direction and amount are determined based on first-order sensitivities of transient stability limits to generator outputs. The sensitivities are derived from partial derivatives of RBF network outputs to inputs. In the end, we take a practical power system for an example to demonstrate the efficiency of RBF network in estimation of the transient stability limit on critical lines and ability to provide preventive control strategy.

Info:

Periodical:

Advanced Materials Research (Volumes 121-122)

Edited by:

Donald C. Wunsch II, Honghua Tan, Dehuai Zeng, Qi Luo

Pages:

887-892

DOI:

10.4028/www.scientific.net/AMR.121-122.887

Citation:

L. L. Yu et al., "The Transient Stability Preventive Control of Power System Based on RBF Neural Network", Advanced Materials Research, Vols. 121-122, pp. 887-892, 2010

Online since:

June 2010

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.