Power system disturbance identification from recorded dynamic data at the Northfield substation

For a power industry undergoing deregulation, the growing number of power marketers and independent power generators increases the variability of power flow patterns in an interconnected power system, thereby making the prediction of critical operating conditions and limits more demanding. Consequently, transmission system operators need new tools to understand the effects of disturbances. Among these needs are tools to classify and identify disturbances as they occur on the power system. In this paper, power system disturbance data from the Northfield substation dynamic recording device in the US New England power system are analyzed and their features extracted. Then a classification method is used to identify the disturbance. Events with multiple disturbances are also addressed. A MATLAB-based software, called 'Event Analyzer', has been developed for the disturbance identification. (C) 2003 Elsevier Ltd. All rights reserved.