Abstract
Fast methods for estimating voltage stability security limits are crucial in modern energy management systems. In this paper, a method to build a fuzzy inference system (FIS) is developed in order to estimate the loading margin. The main goal is to overcome the disadvantages of conventional methods and to apply this methodology in a real time operation environment. First, some voltage stability indices and variables are presented as candidate inputs to the FIS. Subtractive clustering is used to construct the initial FIS models, and adaptive neuro fuzzy inference systems allow tuning them so that it is possible to obtain better loading margin estimates. Extensive simulations were carried out in order to build data sets that take into account a quasi-random load direction, as well as information regarding base case and contingency situations, including branch, generator, and shunt single outages. Results are provided for the IEEE 30,118, and 300 bus test systems.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
