Abstract
A multilayer feedforward neural network is used to realize a moving-average model of an induction motor. This input-output representation generalizes earlier, widely-used static load models to include dynamic loads. The new model can easily be integrated in existing power flow and stability programs. The validity of the proposed methodology is demonstrated with the successful identification of small and large induction motors described by first-order and third-order differential models, respectively. The neural network-based models can accurately predict the machine real and reactive power consumptions under simultaneous or separate voltage and frequency disturbances.
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.
