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Online Grid Support Inverter Parameters Identification Using Extended Kalman Filters | IEEE Conference Publication | IEEE Xplore

Online Grid Support Inverter Parameters Identification Using Extended Kalman Filters


Abstract:

Given the increasing integration of renewable energy sources into existing grids, power injection using Grid Supporting Inverters (GSIs) is gaining in popularity. This pa...Show More

Abstract:

Given the increasing integration of renewable energy sources into existing grids, power injection using Grid Supporting Inverters (GSIs) is gaining in popularity. This paper addresses the issue of dynamically identifying key parameters of a GSI used for power injection into a microgrid. It is shown that the dynamics of the system is based on two essential parts that can be assimilated to simple first-order filters: The DC-bus and AC-line filtering. A simple implementation of an Extended Kalman Filter (EKF) used for estimating in real-time both filter's output and key parameters in this noisy environment is proposed. The design was tested using a DSP-accurate implementation using the Matlab/Simulink environment and presented results show that predefined AC-line filter's parameters were successfully retrieved as the state of the system. The proposed design is suitable for progressive failure indication.
Date of Conference: 21-23 October 2018
Date Added to IEEE Xplore: 30 December 2018
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Conference Location: Washington, DC, USA

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