Abstract
Artificial neural networks can be an intelligent controller to control non-linear, dynamic system through learning, which can easily accommodate the non-linearities and time dependencies. Most common neural networks have drawbacks such as large training time, large number of neurons and hidden layers required to deal with complex problems. To overcome these drawbacks and to develop a non-linear controller for a power system a generalized neuron (GN) has been developed. Combining the advantages of self-optimizing adaptive control strategy and the quick response of the GN, a new power system stabilizer is proposed. Results show that the proposed GN-based power system stabilizer (PSS) can provide good damping of the power system over a wide operating range and significantly improve the dynamic performance of the system.
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.
