A novel approach for improving voltage stability margin by sensitivity analysis of Neural Network

• Published in: 2010 Conference Proceedings IPEC pp. 280 - 286
• Main Authors: Aghamohammadi, M R, Hashemi, S, Ghazizadeh, M S
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-10-2010
• Subjects: Artificial neural networks; Feature Extraction; Loading; Neural Networks; Power system stability; Reactive power; Sensitivity Analysis; Stability criteria; Training; Voltage security margin
• ISBN: 9781424473991; 1424473993
• ISSN: 1947-1262; 1947-1270
• DOI: 10.1109/IPECON.2010.5697145

This paper presents a new approach for estimating and improving voltage stability margin from phase and magnitude profiles of bus voltages using sensitivity analysis of Voltage Stability Assessment Neural Network (VSANN). Voltage profile contains useful information about system stability margin including the effect of load-generation pattern, line outage and reactive power compensation, so it is adopted as the input pattern of VSANN. In fact, VSANN approximates the functional relationship between VSM and the voltage profile. The sensitivity analysis of VSM with respect to reactive power compensation extracted from information stored in the weighting factor of VSANN is the most dominant feature of the proposed approach. Sensitivity of VSM helps one to select the most effective buses for reactive power compensation aimed to enhance VSM. The proposed approach has been implemented in IEEE 39-bus test system with promising results showing its effectiveness and applicability.