Abstract
In this paper, the development of a Parallel Kalman Filter for a bilinear model in the presence of correlation between process and measurement noise is discussed. The developed theory is implemented for estimation of both states and parameters of power system networks using measurements from synchronized Phasor Measurement Units (PMUs). Dynamics of states and parameters of power system networks comprise system dynamics for the bilinear model representation, and measurements coming from PMUs are represented as observation for bilinear system model. Correlation between noise in voltage phasor dynamics and noise in measurements as well as correlation between noises in parameter dynamics and measurement noise are considered. The developed theory is implemented as a method to estimate voltage phasors and network parameters in parallel with each other. The developed theory is tested on various example power grids to show the effects of relevant correlation matrices on estimation of system states and network parameters of the power system network.
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 callMore From: International Journal of Renewable Energy Research
Disclaimer: 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.
