Broadband Methods in Stability Analysis of Multi-Parallel Grid-Connected Converters

Abstract

The share of power flowing through power electronics is increasing rapidly in modern power systems. Power-electronic converters have become essential in enabling efficient grid connection of renewable energy. Moreover, a simultaneous transformation is taking place in energy distribution and consumption, where converters are applied for high-performance power processing. The high power demands often require multi-parallel configurations of grid-connected converters, thereby modifying the dynamic characteristics of the power grid. Consequently, the power grid is threatened by adverse interactions between the grid and the parallel converters. The interactions may lead to dramatic power quality issues through harmonic resonance and they may even make the system prone to instability.

Previous studies have presented methods for assessing the stability of grid-connected systems through dynamic modeling or impedance-based stability criterion where the terminal impedance characteristics of a grid-connected converter are examined. A major advantage of the impedance-based approach is that the method does not require detailed information of the system parameter values. Assessing the stability of multi-parallel converters is typically challenging as the system configurations are complex and the dynamics change along with the system operation point. Consequently, broadband methods capable of fast measurements are required to minimize the measurement duration and to facilitate real-time analysis and adaptive control schemes.

This thesis presents online methods based on broadband pseudo-random sequences and Fourier techniques for the stability analysis of multi-parallel grid-connected converters. The broadband methods are capable of extracting the required impedance data from such systems rapidly by applying simultaneous multivariable measurements. The presented methods facilitate real-time stability analysis of the system and development of various adaptive controllers. Moreover, the stability assessment is shown to predict the stability of multi-parallel converter configurations, where the impedance-based analysis is enabled through the use of impedance aggregation. The presented methods are validated through a number of experimental measurements.