Scheduled System Maintenance:
On May 6th, system maintenance will take place from 8:00 AM - 12:00 PM ET (12:00 - 16:00 UTC). During this time, there may be intermittent impact on performance. We apologize for the inconvenience.
By Topic

Voltage Stability Assessment Based on BP Neural Network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
4 Author(s)
Xiaoqing Han ; Coll. of Electr. & Power Eng., Taiyuan Univ. of Technol., Taiyuan ; Zhijing Zheng ; Nannan Tian ; Yuanyuan Hou

An assessment approach on power system voltage stability is provided using Back Propagation (BP) Neural Network, which takes the Voltage Collapse Proximity Indicator (VCPI) as assessment index. The key feature of the method is to establish static and dynamic assessment models on voltage stability. The training results of the static models based on load flow calculation can reflect the nonlinear mapping relationship correctly between power flows and voltages on load bus with given load increasing mode; Based on integrated load model, the dynamic model uses two three-layer BP networks to make classification and prediction on system, respectively. With two instances of WSCC-9 and 3 generator-12 bus power system, it is verified that the method is effective to voltage stability assessment on power system.

Published in:

Power and Energy Engineering Conference, 2009. APPEEC 2009. Asia-Pacific

Date of Conference:

27-31 March 2009